();\\n\\t\\tint fileCounter = 1;\\n\\t\\t// organize the files by experiments\\n\\t\\tfor (final Experiment experiment : experimentList.getExperiments()) {\\n\\n\\t\\t\\tfinal File prideXmlFile = experiment.getPrideXMLFile();\\n\\t\\t\\tif (prideXmlFile != null) {\\n\\t\\t\\t\\t// FILEMAPPINGS\\n\\t\\t\\t\\t// PRIDE XML\\n\\t\\t\\t\\tfinal int resultNum = fileCounter;\\n\\t\\t\\t\\tfinal PexFileMapping prideXMLFileMapping = new PexFileMapping(\\\"result\\\", fileCounter++,\\n\\t\\t\\t\\t\\t\\tprideXmlFile.getAbsolutePath(), null);\\n\\n\\t\\t\\t\\ttotalFileList.add(prideXMLFileMapping);\\n\\t\\t\\t\\tfileLocationsMapping.put(prideXMLFileMapping.getPath(), prideXMLFileMapping);\\n\\n\\t\\t\\t\\t// Iterate over replicates\\n\\t\\t\\t\\tfinal List<Replicate> replicates = experiment.getReplicates();\\n\\t\\t\\t\\tfor (final Replicate replicate : replicates) {\\n\\t\\t\\t\\t\\t// sample metadatas\\n\\t\\t\\t\\t\\taddSampleMetadatas(resultNum, replicate);\\n\\n\\t\\t\\t\\t\\t// PEak lists\\n\\t\\t\\t\\t\\tfinal List<PexFileMapping> peakListFileMappings = new ArrayList<PexFileMapping>();\\n\\t\\t\\t\\t\\t// raw files\\n\\t\\t\\t\\t\\tfinal List<PexFileMapping> rawFileMappings = new ArrayList<PexFileMapping>();\\n\\t\\t\\t\\t\\t// search engine output lists\\n\\t\\t\\t\\t\\tfinal List<PexFileMapping> outputSearchEngineFileMappings = new ArrayList<PexFileMapping>();\\n\\t\\t\\t\\t\\t// MIAPE MS and MSI reports\\n\\t\\t\\t\\t\\tfinal List<PexFileMapping> miapeReportFileMappings = new ArrayList<PexFileMapping>();\\n\\t\\t\\t\\t\\t// RAW FILES\\n\\t\\t\\t\\t\\tfinal List<PexFile> rawFiles = getReplicateRawFiles(replicate);\\n\\n\\t\\t\\t\\t\\tif (rawFiles != null) {\\n\\t\\t\\t\\t\\t\\tfor (final PexFile rawFile : rawFiles) {\\n\\t\\t\\t\\t\\t\\t\\tif (!fileLocationsMapping.containsKey(rawFile.getFileLocation())) {\\n\\t\\t\\t\\t\\t\\t\\t\\tfinal PexFileMapping rawFileMapping = new PexFileMapping(\\\"raw\\\", fileCounter++,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\trawFile.getFileLocation(), null);\\n\\t\\t\\t\\t\\t\\t\\t\\trawFileMappings.add(rawFileMapping);\\n\\t\\t\\t\\t\\t\\t\\t\\tfileLocationsMapping.put(rawFile.getFileLocation(), rawFileMapping);\\n\\n\\t\\t\\t\\t\\t\\t\\t\\t// PRIDE XML -> RAW file\\n\\t\\t\\t\\t\\t\\t\\t\\tprideXMLFileMapping.addRelationship(rawFileMapping.getId());\\n\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\t\\t// PEAK LISTS\\n\\t\\t\\t\\t\\tfinal List<PexFile> peakListFiles = getPeakListFiles(replicate);\\n\\t\\t\\t\\t\\tfinal List<PexFileMapping> replicatePeakListFileMappings = new ArrayList<PexFileMapping>();\\n\\t\\t\\t\\t\\tif (peakListFiles != null) {\\n\\t\\t\\t\\t\\t\\tfor (final PexFile peakList : peakListFiles) {\\n\\t\\t\\t\\t\\t\\t\\tif (!fileLocationsMapping.containsKey(peakList.getFileLocation())) {\\n\\t\\t\\t\\t\\t\\t\\t\\tfinal PexFileMapping peakListFileMapping = new PexFileMapping(\\\"peak\\\", fileCounter++,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tpeakList.getFileLocation(), null);\\n\\t\\t\\t\\t\\t\\t\\t\\tpeakListFileMappings.add(peakListFileMapping);\\n\\t\\t\\t\\t\\t\\t\\t\\treplicatePeakListFileMappings.add(peakListFileMapping);\\n\\t\\t\\t\\t\\t\\t\\t\\tfileLocationsMapping.put(peakList.getFileLocation(), peakListFileMapping);\\n\\n\\t\\t\\t\\t\\t\\t\\t\\t// PRIDE XML -> PEAK LIST file\\n\\t\\t\\t\\t\\t\\t\\t\\tprideXMLFileMapping.addRelationship(peakListFileMapping.getId());\\n\\t\\t\\t\\t\\t\\t\\t\\t// RAW file -> PEAK LIST file\\n\\t\\t\\t\\t\\t\\t\\t\\tfor (final PexFileMapping rawFileMapping : rawFileMappings) {\\n\\t\\t\\t\\t\\t\\t\\t\\t\\trawFileMapping.addRelationship(peakListFileMapping.getId());\\n\\t\\t\\t\\t\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\t\\t\\t\\t\\t// prideXMLFileMapping\\n\\t\\t\\t\\t\\t\\t\\t\\t// .addRelationship(peakListFileMapping\\n\\t\\t\\t\\t\\t\\t\\t\\t// .getId());\\n\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\t\\t// MIAPE MS REPORTS\\n\\t\\t\\t\\t\\tfinal List<PexFile> miapeMSReportFiles = getMiapeMSReportFiles(replicate);\\n\\t\\t\\t\\t\\tif (miapeMSReportFiles != null)\\n\\t\\t\\t\\t\\t\\tfor (final PexFile miapeMSReportFile : miapeMSReportFiles) {\\n\\t\\t\\t\\t\\t\\t\\tif (!fileLocationsMapping.containsKey(miapeMSReportFile.getFileLocation())) {\\n\\t\\t\\t\\t\\t\\t\\t\\tfinal PexFileMapping miapeReportFileMapping = new PexFileMapping(\\\"other\\\", fileCounter++,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tmiapeMSReportFile.getFileLocation(), null);\\n\\t\\t\\t\\t\\t\\t\\t\\tmiapeReportFileMappings.add(miapeReportFileMapping);\\n\\t\\t\\t\\t\\t\\t\\t\\tfileLocationsMapping.put(miapeMSReportFile.getFileLocation(), miapeReportFileMapping);\\n\\n\\t\\t\\t\\t\\t\\t\\t\\t// PRIDE XML -> MIAPE MS report\\n\\t\\t\\t\\t\\t\\t\\t\\tprideXMLFileMapping.addRelationship(miapeReportFileMapping.getId());\\n\\t\\t\\t\\t\\t\\t\\t\\t// RAW file -> MIAPE MS report\\n\\t\\t\\t\\t\\t\\t\\t\\tfor (final PexFileMapping rawFileMapping : rawFileMappings) {\\n\\t\\t\\t\\t\\t\\t\\t\\t\\trawFileMapping.addRelationship(miapeReportFileMapping.getId());\\n\\t\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\t\\t// PEAK LIST file -> MIAPE MS report\\n\\t\\t\\t\\t\\t\\t\\t\\tfor (final PexFileMapping peakListFileMapping : replicatePeakListFileMappings) {\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tpeakListFileMapping.addRelationship(miapeReportFileMapping.getId());\\n\\t\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\t\\t// SEARCH ENGINE OUTPUT FILES\\n\\t\\t\\t\\t\\tfinal List<PexFile> searchEngineOutputFiles = getSearchEngineOutputFiles(replicate);\\n\\t\\t\\t\\t\\tfinal List<PexFileMapping> replicatesearchEngineOutputFilesMappings = new ArrayList<PexFileMapping>();\\n\\t\\t\\t\\t\\tif (searchEngineOutputFiles != null) {\\n\\t\\t\\t\\t\\t\\tfor (final PexFile peakList : searchEngineOutputFiles) {\\n\\t\\t\\t\\t\\t\\t\\tif (!fileLocationsMapping.containsKey(peakList.getFileLocation())) {\\n\\t\\t\\t\\t\\t\\t\\t\\tfinal PexFileMapping searchEngineOutputFileMapping = new PexFileMapping(\\\"search\\\",\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tfileCounter++, peakList.getFileLocation(), null);\\n\\t\\t\\t\\t\\t\\t\\t\\toutputSearchEngineFileMappings.add(searchEngineOutputFileMapping);\\n\\t\\t\\t\\t\\t\\t\\t\\treplicatesearchEngineOutputFilesMappings.add(searchEngineOutputFileMapping);\\n\\t\\t\\t\\t\\t\\t\\t\\tfileLocationsMapping.put(peakList.getFileLocation(), searchEngineOutputFileMapping);\\n\\t\\t\\t\\t\\t\\t\\t\\t// PRIDE XML -> SEARCH ENGINE OUTPUT file\\n\\t\\t\\t\\t\\t\\t\\t\\tprideXMLFileMapping.addRelationship(searchEngineOutputFileMapping.getId());\\n\\t\\t\\t\\t\\t\\t\\t\\t// RAW file -> SEARCH ENGINE OUTPUT file\\n\\t\\t\\t\\t\\t\\t\\t\\tfor (final PexFileMapping rawFileMapping : rawFileMappings) {\\n\\t\\t\\t\\t\\t\\t\\t\\t\\trawFileMapping.addRelationship(searchEngineOutputFileMapping.getId());\\n\\t\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\t\\t// PEAK LIST FILE -> SEARCH ENGINE OUTPUT file\\n\\t\\t\\t\\t\\t\\t\\t\\tfor (final PexFileMapping peakListFileMapping : replicatePeakListFileMappings) {\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tpeakListFileMapping.addRelationship(searchEngineOutputFileMapping.getId());\\n\\t\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\t\\t// MIAPE MSI REPORTS\\n\\t\\t\\t\\t\\tfinal List<PexFile> miapeMSIReportFiles = getMiapeMSIReportFiles(replicate);\\n\\t\\t\\t\\t\\tif (miapeMSIReportFiles != null)\\n\\t\\t\\t\\t\\t\\tfor (final PexFile miapeMSIReportFile : miapeMSIReportFiles) {\\n\\t\\t\\t\\t\\t\\t\\tif (!fileLocationsMapping.containsKey(miapeMSIReportFile.getFileLocation())) {\\n\\t\\t\\t\\t\\t\\t\\t\\tfinal PexFileMapping miapeReportFileMapping = new PexFileMapping(\\\"other\\\", fileCounter++,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tmiapeMSIReportFile.getFileLocation(), null);\\n\\t\\t\\t\\t\\t\\t\\t\\tmiapeReportFileMappings.add(miapeReportFileMapping);\\n\\t\\t\\t\\t\\t\\t\\t\\tfileLocationsMapping.put(miapeMSIReportFile.getFileLocation(), miapeReportFileMapping);\\n\\n\\t\\t\\t\\t\\t\\t\\t\\t// PRIDE XML -> MIAPE MSI report\\n\\t\\t\\t\\t\\t\\t\\t\\tprideXMLFileMapping.addRelationship(miapeReportFileMapping.getId());\\n\\t\\t\\t\\t\\t\\t\\t\\t// RAW file -> MIAPE MSI report\\n\\t\\t\\t\\t\\t\\t\\t\\tfor (final PexFileMapping rawFileMapping : rawFileMappings) {\\n\\t\\t\\t\\t\\t\\t\\t\\t\\trawFileMapping.addRelationship(miapeReportFileMapping.getId());\\n\\t\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\t\\t// PEAK LIST FILE -> MIAPE MSI report\\n\\t\\t\\t\\t\\t\\t\\t\\tfor (final PexFileMapping peakListFileMapping : replicatePeakListFileMappings) {\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tpeakListFileMapping.addRelationship(miapeReportFileMapping.getId());\\n\\t\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\t\\t// SEARCH ENGINE OUTPUT file -> MIAPE MSI report\\n\\t\\t\\t\\t\\t\\t\\t\\tfor (final PexFileMapping searchEngineOutputFileMapping : replicatesearchEngineOutputFilesMappings) {\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tsearchEngineOutputFileMapping.addRelationship(miapeReportFileMapping.getId());\\n\\t\\t\\t\\t\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t// Add all to the same list and then sort by id\\n\\t\\t\\t\\t\\ttotalFileList.addAll(outputSearchEngineFileMappings);\\n\\t\\t\\t\\t\\ttotalFileList.addAll(miapeReportFileMappings);\\n\\t\\t\\t\\t\\ttotalFileList.addAll(peakListFileMappings);\\n\\t\\t\\t\\t\\ttotalFileList.addAll(rawFileMappings);\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t}\\n\\n\\t\\t// Sort the list of files\\n\\t\\tCollections.sort(totalFileList, new Comparator<PexFileMapping>() {\\n\\n\\t\\t\\t@Override\\n\\t\\t\\tpublic int compare(PexFileMapping o1, PexFileMapping o2) {\\n\\n\\t\\t\\t\\treturn Integer.valueOf(o1.getId()).compareTo(Integer.valueOf(o2.getId()));\\n\\n\\t\\t\\t}\\n\\n\\t\\t});\\n\\t\\tfor (final PexFileMapping pexFileMapping : totalFileList) {\\n\\t\\t\\tret.add(pexFileMapping.toString());\\n\\t\\t}\\n\\t\\treturn ret;\\n\\t}\",\n \"public void readDocument() throws FileNotFoundException{\\r\\n\\t\\t// Initialize 2 empty read document collections, one without duplicate words.\\r\\n\\t\\treadDocument = new LinkedBag<String>();\\r\\n\\t\\treadDocumentNoDuplicates = new LinkedSet<String>();\\r\\n\\t\\t\\r\\n\\t\\t// Prompt user for name of read document file.\\r\\n\\t\\tScanner input = new Scanner(System.in);\\r\\n\\t\\tSystem.out.print(\\\"Enter the file you would like checked with extension: \\\");\\r\\n\\t\\tString readDocFileName = input.nextLine();\\r\\n\\t\\t\\r\\n\\t\\t// If exists, open file specified by user. Then add words to both collections.\\r\\n\\t\\ttry {\\r\\n\\t\\t\\tFile file = new File(readDocFileName);\\r\\n\\t\\t\\tScanner scanner = new Scanner(file);\\r\\n\\t\\t\\twhile (scanner.hasNextLine()) {\\r\\n\\t\\t\\t\\tString word = scanner.next();\\r\\n\\t\\t\\t\\treadDocument.add(word.replaceFirst(\\\"^[^a-zA-Z]+\\\",\\\"\\\").replaceAll(\\\"[^a-zA-Z]+$\\\", \\\"\\\"));\\r\\n\\t\\t\\t\\treadDocumentNoDuplicates.add(word.replaceFirst(\\\"^[^a-zA-Z]+\\\",\\\"\\\").replaceAll(\\\"[^a-zA-Z]+$\\\", \\\"\\\"));\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\tscanner.close();\\r\\n\\t\\t\\tSystem.out.println(\\\"Document read\\\");\\r\\n\\r\\n\\t\\t\\t// Get initial list of incorrect words.\\r\\n\\t\\t\\tincorrectWords = readDocumentNoDuplicates.difference(dictionary);\\r\\n\\t\\t\\t\\r\\n\\t\\t\\t// Display message showing how many words were in the read document.\\r\\n\\t\\t\\tSystem.out.println(\\\"This document contains \\\" + readDocument.size() + \\\" words.\\\");\\r\\n\\t\\t}\\r\\n\\t\\tcatch (FileNotFoundException e) {\\r\\n\\t\\t\\treadDocument = null;\\r\\n\\t\\t\\treadDocumentNoDuplicates = null;\\r\\n\\t\\t\\tSystem.out.println(\\\"Error: File '\\\" + readDocFileName + \\\"' not found. Please try again.\\\");\\r\\n\\t\\t}\\r\\n\\t}\",\n \"private static void loadFiles(String[] files) throws IOException {\\n\\t\\tfor(String file : files){\\n\\n\\t\\t\\t//Create reader for the file\\n\\t\\t\\tBufferedReader fileReader = new BufferedReader(new FileReader(file));\\n\\n\\t\\t\\t//Create HashMap to store words and counts\\n\\t\\t\\tHashMap<String,WordCount> fileWordCounts = new HashMap<String,WordCount>();\\n\\t\\t\\tArrayList<String> sentences = new ArrayList<String>();\\n\\n\\t\\t\\t//While the file still has more lines to be read from\\n\\t\\t\\twhile(fileReader.ready()){\\n\\n\\t\\t\\t\\t//Read a line from the file\\n\\t\\t\\t\\tString fileLine = fileReader.readLine();\\n\\t\\t\\t\\t//Add the line to file sentences\\n\\t\\t\\t\\tsentences.add(fileLine);\\n\\t\\t\\t\\t//Split the file and remove punctuation from words\\n\\t\\t\\t\\tString[] fileWords = fileLine.replaceAll(\\\"[^a-zA-Z ]\\\", \\\"\\\").toLowerCase().split(\\\"\\\\\\\\s+\\\");\\n\\n\\t\\t\\t\\t//iterate through all words in each line\\n\\t\\t\\t\\tfor (String word : fileWords)\\n\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\tWordCount count = fileWordCounts.get(word);\\n\\t\\t\\t\\t\\t//If word is not in file, add it \\n\\t\\t\\t\\t\\tif (count == null) {\\n\\t\\t\\t\\t\\t\\tfileWordCounts.put(word,new WordCount(word));\\n\\t\\t\\t\\t\\t} else {\\n\\t\\t\\t\\t\\t\\tcount.inc(); //If not, increment it\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t} \\n\\t\\t\\t}\\n\\n\\t\\t\\t//Add file to fileDatabase \\n\\t\\t\\tfileDatabase.map.put(file, new FileObject(file, fileWordCounts, sentences));\\n\\n\\t\\t\\tfileReader.close(); // Close File\\n\\n\\t\\t}//End of For Loop reading from all files\\n\\t}\",\n \"public Map<String, String> NextDocument() throws IOException {\\n\\t\\tMap<String, String> map = new HashMap<>();\\n\\t\\tStringBuffer content = new StringBuffer();\\n\\t\\tString line = inputStream.readLine();\\n\\t\\tif(line==null) {\\n\\t\\t\\tinputStream.close();\\n\\t\\t\\treturn null;\\n\\t\\t} else {\\n\\t\\t\\tmap.put(\\\"DOCNO\\\", line);\\n\\t\\t\\tmap.put(\\\"CONTENT\\\", inputStream.readLine());\\n\\t\\t\\treturn map;\\n\\t\\t}\\n\\t}\",\n \"private void processMetadataFromLoader() {\\n\\n int recordCount = mdi.readInt();\\n\\n long currentTime = System.currentTimeMillis();\\n synchronized (entities) {\\n clearOldTempIndexes(currentTime);\\n\\n for (int i = 0; i < recordCount; i++) {\\n int tempIndex = mdi.readInt();\\n assert DirectProtocol.isValidTempIndex(tempIndex);\\n String symbol = mdi.readCharSequence().toString().intern();\\n\\n ConstantIdentityKey key;\\n int entityIndex = entities.get(symbol, NOT_FOUND_VALUE);\\n if (entityIndex == NOT_FOUND_VALUE) {\\n entityIndex = entities.size();\\n key = new ConstantIdentityKey(symbol);\\n entities.put(key, entityIndex);\\n } else {\\n key = entities.getKeyObject(symbol);\\n }\\n\\n // Note: key is guarantied to be same object as in \\\"entities\\\" field\\n tempIndexes.put(tempIndex, key);\\n\\n sendMetadata(symbol, entityIndex);\\n }\\n if (recordCount > 0) {\\n lastTempIndexAdded = currentTime;\\n }\\n }\\n }\",\n \"@android.annotation.SuppressLint({\\\"NewApi\\\"})\\n private void listRoots() {\\n /*\\n r23 = this;\\n r21 = 0;\\n r0 = r21;\\n r1 = r23;\\n r1.currentDir = r0;\\n r0 = r23;\\n r0 = r0.items;\\n r21 = r0;\\n r21.clear();\\n r17 = new java.util.HashSet;\\n r17.<init>();\\n r21 = android.os.Environment.getExternalStorageDirectory();\\n r5 = r21.getPath();\\n r12 = android.os.Environment.isExternalStorageRemovable();\\n r6 = android.os.Environment.getExternalStorageState();\\n r21 = \\\"mounted\\\";\\n r0 = r21;\\n r21 = r6.equals(r0);\\n if (r21 != 0) goto L_0x003c;\\n L_0x0031:\\n r21 = \\\"mounted_ro\\\";\\n r0 = r21;\\n r21 = r6.equals(r0);\\n if (r21 == 0) goto L_0x0084;\\n L_0x003c:\\n r8 = new org.telegram.ui.DocumentSelectActivity$ListItem;\\n r21 = 0;\\n r0 = r23;\\n r1 = r21;\\n r8.<init>();\\n r21 = android.os.Environment.isExternalStorageRemovable();\\n if (r21 == 0) goto L_0x02ae;\\n L_0x004d:\\n r21 = \\\"SdCard\\\";\\n r22 = 2131494825; // 0x7f0c07a9 float:1.861317E38 double:1.0530983673E-314;\\n r21 = org.telegram.messenger.LocaleController.getString(r21, r22);\\n r0 = r21;\\n r8.title = r0;\\n r21 = 2131165433; // 0x7f0700f9 float:1.7945083E38 double:1.052935626E-314;\\n r0 = r21;\\n r8.icon = r0;\\n L_0x0062:\\n r0 = r23;\\n r21 = r0.getRootSubtitle(r5);\\n r0 = r21;\\n r8.subtitle = r0;\\n r21 = android.os.Environment.getExternalStorageDirectory();\\n r0 = r21;\\n r8.file = r0;\\n r0 = r23;\\n r0 = r0.items;\\n r21 = r0;\\n r0 = r21;\\n r0.add(r8);\\n r0 = r17;\\n r0.add(r5);\\n L_0x0084:\\n r3 = 0;\\n r4 = new java.io.BufferedReader;\\t Catch:{ Exception -> 0x0302 }\\n r21 = new java.io.FileReader;\\t Catch:{ Exception -> 0x0302 }\\n r22 = \\\"/proc/mounts\\\";\\n r21.<init>(r22);\\t Catch:{ Exception -> 0x0302 }\\n r0 = r21;\\n r4.<init>(r0);\\t Catch:{ Exception -> 0x0302 }\\n L_0x0094:\\n r14 = r4.readLine();\\t Catch:{ Exception -> 0x01c3, all -> 0x02d5 }\\n if (r14 == 0) goto L_0x02dd;\\n L_0x009a:\\n r21 = \\\"vfat\\\";\\n r0 = r21;\\n r21 = r14.contains(r0);\\t Catch:{ Exception -> 0x01c3, all -> 0x02d5 }\\n if (r21 != 0) goto L_0x00b0;\\n L_0x00a5:\\n r21 = \\\"/mnt\\\";\\n r0 = r21;\\n r21 = r14.contains(r0);\\t Catch:{ Exception -> 0x01c3, all -> 0x02d5 }\\n if (r21 == 0) goto L_0x0094;\\n L_0x00b0:\\n r21 = org.telegram.messenger.BuildVars.LOGS_ENABLED;\\t Catch:{ Exception -> 0x01c3, all -> 0x02d5 }\\n if (r21 == 0) goto L_0x00b7;\\n L_0x00b4:\\n org.telegram.messenger.FileLog.d(r14);\\t Catch:{ Exception -> 0x01c3, all -> 0x02d5 }\\n L_0x00b7:\\n r19 = new java.util.StringTokenizer;\\t Catch:{ Exception -> 0x01c3, all -> 0x02d5 }\\n r21 = \\\" \\\";\\n r0 = r19;\\n r1 = r21;\\n r0.<init>(r14, r1);\\t Catch:{ Exception -> 0x01c3, all -> 0x02d5 }\\n r20 = r19.nextToken();\\t Catch:{ Exception -> 0x01c3, all -> 0x02d5 }\\n r16 = r19.nextToken();\\t Catch:{ Exception -> 0x01c3, all -> 0x02d5 }\\n r0 = r17;\\n r1 = r16;\\n r21 = r0.contains(r1);\\t Catch:{ Exception -> 0x01c3, all -> 0x02d5 }\\n if (r21 != 0) goto L_0x0094;\\n L_0x00d5:\\n r21 = \\\"/dev/block/vold\\\";\\n r0 = r21;\\n r21 = r14.contains(r0);\\t Catch:{ Exception -> 0x01c3, all -> 0x02d5 }\\n if (r21 == 0) goto L_0x0094;\\n L_0x00e0:\\n r21 = \\\"/mnt/secure\\\";\\n r0 = r21;\\n r21 = r14.contains(r0);\\t Catch:{ Exception -> 0x01c3, all -> 0x02d5 }\\n if (r21 != 0) goto L_0x0094;\\n L_0x00eb:\\n r21 = \\\"/mnt/asec\\\";\\n r0 = r21;\\n r21 = r14.contains(r0);\\t Catch:{ Exception -> 0x01c3, all -> 0x02d5 }\\n if (r21 != 0) goto L_0x0094;\\n L_0x00f6:\\n r21 = \\\"/mnt/obb\\\";\\n r0 = r21;\\n r21 = r14.contains(r0);\\t Catch:{ Exception -> 0x01c3, all -> 0x02d5 }\\n if (r21 != 0) goto L_0x0094;\\n L_0x0101:\\n r21 = \\\"/dev/mapper\\\";\\n r0 = r21;\\n r21 = r14.contains(r0);\\t Catch:{ Exception -> 0x01c3, all -> 0x02d5 }\\n if (r21 != 0) goto L_0x0094;\\n L_0x010c:\\n r21 = \\\"tmpfs\\\";\\n r0 = r21;\\n r21 = r14.contains(r0);\\t Catch:{ Exception -> 0x01c3, all -> 0x02d5 }\\n if (r21 != 0) goto L_0x0094;\\n L_0x0117:\\n r21 = new java.io.File;\\t Catch:{ Exception -> 0x01c3, all -> 0x02d5 }\\n r0 = r21;\\n r1 = r16;\\n r0.<init>(r1);\\t Catch:{ Exception -> 0x01c3, all -> 0x02d5 }\\n r21 = r21.isDirectory();\\t Catch:{ Exception -> 0x01c3, all -> 0x02d5 }\\n if (r21 != 0) goto L_0x0163;\\n L_0x0126:\\n r21 = 47;\\n r0 = r16;\\n r1 = r21;\\n r11 = r0.lastIndexOf(r1);\\t Catch:{ Exception -> 0x01c3, all -> 0x02d5 }\\n r21 = -1;\\n r0 = r21;\\n if (r11 == r0) goto L_0x0163;\\n L_0x0136:\\n r21 = new java.lang.StringBuilder;\\t Catch:{ Exception -> 0x01c3, all -> 0x02d5 }\\n r21.<init>();\\t Catch:{ Exception -> 0x01c3, all -> 0x02d5 }\\n r22 = \\\"/storage/\\\";\\n r21 = r21.append(r22);\\t Catch:{ Exception -> 0x01c3, all -> 0x02d5 }\\n r22 = r11 + 1;\\n r0 = r16;\\n r1 = r22;\\n r22 = r0.substring(r1);\\t Catch:{ Exception -> 0x01c3, all -> 0x02d5 }\\n r21 = r21.append(r22);\\t Catch:{ Exception -> 0x01c3, all -> 0x02d5 }\\n r15 = r21.toString();\\t Catch:{ Exception -> 0x01c3, all -> 0x02d5 }\\n r21 = new java.io.File;\\t Catch:{ Exception -> 0x01c3, all -> 0x02d5 }\\n r0 = r21;\\n r0.<init>(r15);\\t Catch:{ Exception -> 0x01c3, all -> 0x02d5 }\\n r21 = r21.isDirectory();\\t Catch:{ Exception -> 0x01c3, all -> 0x02d5 }\\n if (r21 == 0) goto L_0x0163;\\n L_0x0161:\\n r16 = r15;\\n L_0x0163:\\n r0 = r17;\\n r1 = r16;\\n r0.add(r1);\\t Catch:{ Exception -> 0x01c3, all -> 0x02d5 }\\n r13 = new org.telegram.ui.DocumentSelectActivity$ListItem;\\t Catch:{ Exception -> 0x01bd, all -> 0x02d5 }\\n r21 = 0;\\n r0 = r23;\\n r1 = r21;\\n r13.<init>();\\t Catch:{ Exception -> 0x01bd, all -> 0x02d5 }\\n r21 = r16.toLowerCase();\\t Catch:{ Exception -> 0x01bd, all -> 0x02d5 }\\n r22 = \\\"sd\\\";\\n r21 = r21.contains(r22);\\t Catch:{ Exception -> 0x01bd, all -> 0x02d5 }\\n if (r21 == 0) goto L_0x02c5;\\n L_0x0182:\\n r21 = \\\"SdCard\\\";\\n r22 = 2131494825; // 0x7f0c07a9 float:1.861317E38 double:1.0530983673E-314;\\n r21 = org.telegram.messenger.LocaleController.getString(r21, r22);\\t Catch:{ Exception -> 0x01bd, all -> 0x02d5 }\\n r0 = r21;\\n r13.title = r0;\\t Catch:{ Exception -> 0x01bd, all -> 0x02d5 }\\n L_0x0190:\\n r21 = 2131165433; // 0x7f0700f9 float:1.7945083E38 double:1.052935626E-314;\\n r0 = r21;\\n r13.icon = r0;\\t Catch:{ Exception -> 0x01bd, all -> 0x02d5 }\\n r0 = r23;\\n r1 = r16;\\n r21 = r0.getRootSubtitle(r1);\\t Catch:{ Exception -> 0x01bd, all -> 0x02d5 }\\n r0 = r21;\\n r13.subtitle = r0;\\t Catch:{ Exception -> 0x01bd, all -> 0x02d5 }\\n r21 = new java.io.File;\\t Catch:{ Exception -> 0x01bd, all -> 0x02d5 }\\n r0 = r21;\\n r1 = r16;\\n r0.<init>(r1);\\t Catch:{ Exception -> 0x01bd, all -> 0x02d5 }\\n r0 = r21;\\n r13.file = r0;\\t Catch:{ Exception -> 0x01bd, all -> 0x02d5 }\\n r0 = r23;\\n r0 = r0.items;\\t Catch:{ Exception -> 0x01bd, all -> 0x02d5 }\\n r21 = r0;\\n r0 = r21;\\n r0.add(r13);\\t Catch:{ Exception -> 0x01bd, all -> 0x02d5 }\\n goto L_0x0094;\\n L_0x01bd:\\n r7 = move-exception;\\n org.telegram.messenger.FileLog.e(r7);\\t Catch:{ Exception -> 0x01c3, all -> 0x02d5 }\\n goto L_0x0094;\\n L_0x01c3:\\n r7 = move-exception;\\n r3 = r4;\\n L_0x01c5:\\n org.telegram.messenger.FileLog.e(r7);\\t Catch:{ all -> 0x0300 }\\n if (r3 == 0) goto L_0x01cd;\\n L_0x01ca:\\n r3.close();\\t Catch:{ Exception -> 0x02ec }\\n L_0x01cd:\\n r9 = new org.telegram.ui.DocumentSelectActivity$ListItem;\\n r21 = 0;\\n r0 = r23;\\n r1 = r21;\\n r9.<init>();\\n r21 = \\\"/\\\";\\n r0 = r21;\\n r9.title = r0;\\n r21 = \\\"SystemRoot\\\";\\n r22 = 2131495071; // 0x7f0c089f float:1.8613668E38 double:1.053098489E-314;\\n r21 = org.telegram.messenger.LocaleController.getString(r21, r22);\\n r0 = r21;\\n r9.subtitle = r0;\\n r21 = 2131165426; // 0x7f0700f2 float:1.7945069E38 double:1.0529356226E-314;\\n r0 = r21;\\n r9.icon = r0;\\n r21 = new java.io.File;\\n r22 = \\\"/\\\";\\n r21.<init>(r22);\\n r0 = r21;\\n r9.file = r0;\\n r0 = r23;\\n r0 = r0.items;\\n r21 = r0;\\n r0 = r21;\\n r0.add(r9);\\n r18 = new java.io.File;\\t Catch:{ Exception -> 0x02f7 }\\n r21 = android.os.Environment.getExternalStorageDirectory();\\t Catch:{ Exception -> 0x02f7 }\\n r22 = \\\"Telegram\\\";\\n r0 = r18;\\n r1 = r21;\\n r2 = r22;\\n r0.<init>(r1, r2);\\t Catch:{ Exception -> 0x02f7 }\\n r21 = r18.exists();\\t Catch:{ Exception -> 0x02f7 }\\n if (r21 == 0) goto L_0x0254;\\n L_0x0223:\\n r10 = new org.telegram.ui.DocumentSelectActivity$ListItem;\\t Catch:{ Exception -> 0x02f7 }\\n r21 = 0;\\n r0 = r23;\\n r1 = r21;\\n r10.<init>();\\t Catch:{ Exception -> 0x02f7 }\\n r21 = \\\"Telegram\\\";\\n r0 = r21;\\n r10.title = r0;\\t Catch:{ Exception -> 0x02fd }\\n r21 = r18.toString();\\t Catch:{ Exception -> 0x02fd }\\n r0 = r21;\\n r10.subtitle = r0;\\t Catch:{ Exception -> 0x02fd }\\n r21 = 2131165426; // 0x7f0700f2 float:1.7945069E38 double:1.0529356226E-314;\\n r0 = r21;\\n r10.icon = r0;\\t Catch:{ Exception -> 0x02fd }\\n r0 = r18;\\n r10.file = r0;\\t Catch:{ Exception -> 0x02fd }\\n r0 = r23;\\n r0 = r0.items;\\t Catch:{ Exception -> 0x02fd }\\n r21 = r0;\\n r0 = r21;\\n r0.add(r10);\\t Catch:{ Exception -> 0x02fd }\\n r9 = r10;\\n L_0x0254:\\n r9 = new org.telegram.ui.DocumentSelectActivity$ListItem;\\n r21 = 0;\\n r0 = r23;\\n r1 = r21;\\n r9.<init>();\\n r21 = \\\"Gallery\\\";\\n r22 = 2131493847; // 0x7f0c03d7 float:1.8611186E38 double:1.053097884E-314;\\n r21 = org.telegram.messenger.LocaleController.getString(r21, r22);\\n r0 = r21;\\n r9.title = r0;\\n r21 = \\\"GalleryInfo\\\";\\n r22 = 2131493848; // 0x7f0c03d8 float:1.8611188E38 double:1.0530978846E-314;\\n r21 = org.telegram.messenger.LocaleController.getString(r21, r22);\\n r0 = r21;\\n r9.subtitle = r0;\\n r21 = 2131165529; // 0x7f070159 float:1.7945278E38 double:1.0529356735E-314;\\n r0 = r21;\\n r9.icon = r0;\\n r21 = 0;\\n r0 = r21;\\n r9.file = r0;\\n r0 = r23;\\n r0 = r0.items;\\n r21 = r0;\\n r0 = r21;\\n r0.add(r9);\\n r0 = r23;\\n r0 = r0.listView;\\n r21 = r0;\\n org.telegram.messenger.AndroidUtilities.clearDrawableAnimation(r21);\\n r21 = 1;\\n r0 = r21;\\n r1 = r23;\\n r1.scrolling = r0;\\n r0 = r23;\\n r0 = r0.listAdapter;\\n r21 = r0;\\n r21.notifyDataSetChanged();\\n return;\\n L_0x02ae:\\n r21 = \\\"InternalStorage\\\";\\n r22 = 2131493929; // 0x7f0c0429 float:1.8611352E38 double:1.0530979246E-314;\\n r21 = org.telegram.messenger.LocaleController.getString(r21, r22);\\n r0 = r21;\\n r8.title = r0;\\n r21 = 2131165528; // 0x7f070158 float:1.7945276E38 double:1.052935673E-314;\\n r0 = r21;\\n r8.icon = r0;\\n goto L_0x0062;\\n L_0x02c5:\\n r21 = \\\"ExternalStorage\\\";\\n r22 = 2131493730; // 0x7f0c0362 float:1.8610948E38 double:1.0530978263E-314;\\n r21 = org.telegram.messenger.LocaleController.getString(r21, r22);\\t Catch:{ Exception -> 0x01bd, all -> 0x02d5 }\\n r0 = r21;\\n r13.title = r0;\\t Catch:{ Exception -> 0x01bd, all -> 0x02d5 }\\n goto L_0x0190;\\n L_0x02d5:\\n r21 = move-exception;\\n r3 = r4;\\n L_0x02d7:\\n if (r3 == 0) goto L_0x02dc;\\n L_0x02d9:\\n r3.close();\\t Catch:{ Exception -> 0x02f2 }\\n L_0x02dc:\\n throw r21;\\n L_0x02dd:\\n if (r4 == 0) goto L_0x0305;\\n L_0x02df:\\n r4.close();\\t Catch:{ Exception -> 0x02e5 }\\n r3 = r4;\\n goto L_0x01cd;\\n L_0x02e5:\\n r7 = move-exception;\\n org.telegram.messenger.FileLog.e(r7);\\n r3 = r4;\\n goto L_0x01cd;\\n L_0x02ec:\\n r7 = move-exception;\\n org.telegram.messenger.FileLog.e(r7);\\n goto L_0x01cd;\\n L_0x02f2:\\n r7 = move-exception;\\n org.telegram.messenger.FileLog.e(r7);\\n goto L_0x02dc;\\n L_0x02f7:\\n r7 = move-exception;\\n L_0x02f8:\\n org.telegram.messenger.FileLog.e(r7);\\n goto L_0x0254;\\n L_0x02fd:\\n r7 = move-exception;\\n r9 = r10;\\n goto L_0x02f8;\\n L_0x0300:\\n r21 = move-exception;\\n goto L_0x02d7;\\n L_0x0302:\\n r7 = move-exception;\\n goto L_0x01c5;\\n L_0x0305:\\n r3 = r4;\\n goto L_0x01cd;\\n */\\n throw new UnsupportedOperationException(\\\"Method not decompiled: org.telegram.ui.DocumentSelectActivity.listRoots():void\\\");\\n }\",\n \"public static void startup() {\\n\\t\\tString thisLine;\\n\\t\\tString currentName = \\\"\\\";\\n\\t\\tboolean next = true;\\n\\n\\t\\t// DEBUG\\n\\t\\t// System.out.println(\\\"entered here\\\");\\n\\n\\t\\t// Loop across the arguments\\n\\n\\t\\t// Open the file for reading\\n\\t\\ttry {\\n\\t\\t\\tBufferedReader br = new BufferedReader(new FileReader(GIGA_WORD));\\n\\t\\t\\twhile ((thisLine = br.readLine()) != null) {\\n\\t\\t\\t\\tString str = thisLine.trim();// .replaceAll(\\\"(\\\\\\\\r|\\\\\\\\n)\\\", \\\"\\\");\\n\\t\\t\\t\\tString[] wordNumber = str.split(\\\"[ ]{2,}\\\");\\n\\t\\t\\t\\tString word = wordNumber[0].toLowerCase();\\n\\t\\t\\t\\tint cnt = Integer.parseInt(wordNumber[1]);\\n\\t\\t\\t\\tgigaMap.put(word, cnt);\\n\\t\\t\\t}\\n\\t\\t\\tbr.close();\\n\\t\\t\\tbr = null;\\n\\t\\t\\tbr = new BufferedReader(new FileReader(FILE_NAME));\\n\\t\\t\\twhile ((thisLine = br.readLine()) != null) {\\n\\t\\t\\t\\tString str = thisLine.trim();// replaceAll(\\\"(\\\\\\\\r|\\\\\\\\n)\\\", \\\"\\\");\\n\\t\\t\\t\\tif (str.equals(\\\"[Term]\\\")) {\\n\\t\\t\\t\\t\\tnext = true;\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\tif (str.startsWith(\\\"name:\\\")) {\\n\\t\\t\\t\\t\\tif (next) {\\n\\t\\t\\t\\t\\t\\tcurrentName = str.replaceAll(\\\"name: \\\", \\\"\\\");\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\tif (str.startsWith(\\\"synonym:\\\")) {\\n\\t\\t\\t\\t\\tif (str.contains(\\\"EXACT\\\") || str.contains(\\\"NARROW\\\")) {\\n\\t\\t\\t\\t\\t\\t// synonym..\\n\\t\\t\\t\\t\\t\\tPattern pattern = Pattern\\n\\t\\t\\t\\t\\t\\t\\t\\t.compile(\\\"synonym:.*\\\\\\\"(.*)\\\\\\\".*\\\");\\n\\t\\t\\t\\t\\t\\tMatcher matcher = pattern.matcher(str);\\n\\t\\t\\t\\t\\t\\t// DEBUG\\n\\t\\t\\t\\t\\t\\t// System.err.println(str);\\n\\t\\t\\t\\t\\t\\tif (matcher.find()) {\\n\\t\\t\\t\\t\\t\\t\\tString syno = matcher.group(1);\\n\\t\\t\\t\\t\\t\\t\\tif (!currentName.equals(\\\"\\\")) {\\n\\t\\t\\t\\t\\t\\t\\t\\t// System.err.format(\\\"%s:%s.\\\\n\\\", currentName,\\n\\t\\t\\t\\t\\t\\t\\t\\t// syno);\\n\\n\\t\\t\\t\\t\\t\\t\\t\\tadd(currentName, syno);\\n\\t\\t\\t\\t\\t\\t\\t\\tadd(syno, currentName);\\n\\t\\t\\t\\t\\t\\t\\t\\trecursiveAddSyno(currentName, syno);\\n\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t\\tbr.close();\\n\\t\\t\\tbr = null;\\n\\t\\t} catch (IOException e) {\\n\\t\\t\\tSystem.err.println(\\\"Error: \\\" + e);\\n\\t\\t}\\n\\t}\",\n \"public void start(){\\n\\t\\tboolean readFromFile = readFromIndex();\\r\\n\\t\\tif (!readFromFile){\\t\\r\\n\\t\\t\\tfor (int i = 0;i<1000;++i){\\r\\n\\t\\t\\t\\tString file = \\\"../crawler/pages/page\\\"+i+\\\".html\\\";\\r\\n\\t\\t\\t\\taddFile(file);\\r\\n\\t\\t\\t}\\r\\n\\t\\t}\\r\\n\\t}\",\n \"public static void testDictionary() throws IOException {\\n String wnhome=\\\"c:\\\\\\\\Users\\\\\\\\Katherine\\\\\\\\Documents\\\\\\\\2nd sem\\\\\\\\IR\\\\\\\\project\\\\\\\\WordNet_3.1\\\";\\n String path = wnhome + File.separator + \\\"dict\\\";\\n\\n\\n URL url = new URL(\\\"file\\\", null, path);\\n\\n IDictionary dictionary = new Dictionary(url);\\n dictionary.open();\\n // /Users/Ward/Downloads\\n IIndexWord indexWord = dictionary.getIndexWord(\\\"use\\\", POS.VERB);\\n\\n for (IWordID wordID : indexWord.getWordIDs()) {\\n\\n IWord word = dictionary.getWord(wordID);\\n for (IWord word1 : word.getSynset().getWords()) {\\n System.out.println(word1.getLemma());\\n }\\n// System.out.println(\\\"Id = \\\" + wordID);\\n// System.out.println(\\\" Lemma = \\\" + word.getLemma());\\n// System.out.println(\\\" Gloss = \\\" + word.getSynset().getGloss());\\n\\n List<ISynsetID> hypernyms =\\n word.getSynset().getRelatedSynsets(Pointer.HYPERNYM);\\n // print out each h y p e r n y m s id and synonyms\\n List<IWord> words;\\n for (ISynsetID sid : hypernyms) {\\n words = dictionary.getSynset(sid).getWords();\\n System.out.print(sid + \\\" {\\\");\\n for (Iterator<IWord> i = words.iterator(); i.hasNext(); ) {\\n System.out.print(i.next().getLemma());\\n if (i.hasNext())\\n System.out.print(\\\", \\\");\\n }\\n System.out.println(\\\"}\\\");\\n }\\n }\\n }\",\n \"@SuppressWarnings(\\\"unchecked\\\")\\r\\n private void newMap() throws IOException, ClassNotFoundException {\\r\\n this.music_map.clear();\\r\\n if (needNewMap()) {\\r\\n if (!save_file.exists()) {\\r\\n System.out.println(\\\"DIZIONARIO NON PRESENTE\\\");\\r\\n System.out.println(\\\"CREAZIONE NUOVO DIZIONARIO IN CORSO...\\\");\\r\\n\\r\\n this.setTarget();\\r\\n\\r\\n this.recoursiveMapCreation(this.music_root);\\r\\n this.saveMap();\\r\\n } else {\\r\\n System.out.println(\\\"DIZIONARIO NON AGGIORNATO\\\");\\r\\n if (!UtilFunctions.newDictionaryRequest(this.save_file, this.music_root)) {\\r\\n System.out.println(\\\"AGGIORNAMENTO DIZIONARIO RIFIUTATO\\\");\\r\\n FileInputStream f = new FileInputStream(this.save_file);\\r\\n ObjectInputStream o = new ObjectInputStream(f);\\r\\n this.music_map.putAll((Map<String, String[]>) o.readObject());\\r\\n current.set(ProgressDialog.TOTAL.get());\\r\\n } else {\\r\\n System.out.println(\\\"CREAZIONE NUOVO DIZIONARIO IN CORSO...\\\");\\r\\n this.setTarget();\\r\\n this.recoursiveMapCreation(this.music_root);\\r\\n this.saveMap();\\r\\n }\\r\\n }\\r\\n } else {\\r\\n System.out.println(\\\"DIZIONARIO GIA' PRESENTE\\\");\\r\\n FileInputStream f = new FileInputStream(this.save_file);\\r\\n ObjectInputStream o = new ObjectInputStream(f);\\r\\n this.music_map.putAll((Map<String, String[]>) o.readObject());\\r\\n current.set(ProgressDialog.TOTAL.get());\\r\\n }\\r\\n }\",\n \"private static void searchMemo() {\\n\\t\\t\\n\\t}\",\n \"private static Positional_inverted_index posindexCorpus(DocumentCorpus corpus) throws ClassNotFoundException, InstantiationException, IllegalAccessException, FileNotFoundException, IOException {\\n\\n NewTokenProcessor processor = new NewTokenProcessor();\\n Iterable<Document> docs = corpus.getDocuments(); //call registerFileDocumentFactory first?\\n\\n List<Double> Doc_length = new ArrayList<>();\\n Positional_inverted_index index = new Positional_inverted_index();\\n\\n double token_count = 0;\\n\\n // Iterate through the documents, and:\\n for (Document d : docs) {\\n //File f = new File(path + \\\"\\\\\\\\\\\" + d.getTitle());\\n File f = new File(path + \\\"\\\\\\\\\\\" + d.getFileName().toString());\\n double Filesize = f.length();\\n //edited by bhavya\\n double doc_weight = 0; //first entry in docweights.bin\\n double doc_tokens = 0;\\n double doc_length = 0;\\n HashMap<String, Integer> tftd = new HashMap<>();\\n // Tokenize the document's content by constructing an EnglishTokenStream around the document's content.\\n Reader reader = d.getContent();\\n EnglishTokenStream stream = new EnglishTokenStream(reader); //can access tokens through this stream\\n N++;\\n // Iterate through the tokens in the document, processing them using a BasicTokenProcessor,\\n //\\t\\tand adding them to the HashSet vocabulary.\\n Iterable<String> tokens = stream.getTokens();\\n int i = 0;\\n\\n for (String token : tokens) {\\n\\n //adding token in index\\n List<String> word = new ArrayList<String>();\\n word = processor.processToken(token);\\n //System.out.println(word.get(0));\\n if (word.get(0).matches(\\\"\\\")) {\\n continue;\\n } else {\\n\\n index.addTerm(word.get(0), i, d.getId());\\n\\n }\\n i = i + 1;\\n\\n //we check if token already exists in hashmap or not. \\n //if it exists, increase its freq by 1 else make a new entry.\\n if (tftd.containsKey(word.get(0))) {\\n doc_tokens++;\\n int count = tftd.get(word.get(0));\\n tftd.replace(word.get(0), count + 1);\\n } else {\\n doc_tokens++;\\n// token_count++; //gives total number of tokens.\\n tftd.put(word.get(0), 1);\\n }\\n\\n }\\n double length = 0;\\n double wdt = 0;\\n\\n double total_tftd = 0;\\n for (Map.Entry<String, Integer> entry : tftd.entrySet()) {\\n\\n wdt = 1 + log(entry.getValue());\\n\\n length = length + pow(wdt, 2);\\n total_tftd = total_tftd + entry.getValue();\\n }\\n token_count = token_count + doc_tokens;\\n doc_weight = pow(length, 0.5);\\n double avg_tftd = total_tftd / (double) tftd.size();\\n\\n Doc_length.add(doc_weight);\\n Doc_length.add(avg_tftd);\\n Doc_length.add(doc_tokens);\\n Doc_length.add(Filesize);\\n }\\n Doc_length.add(token_count / N);\\n\\n DiskIndexWriter d = new DiskIndexWriter();\\n d.write_doc(path, Doc_length);\\n\\n return index;\\n }\",\n \"@Override\\n public void processCas(CAS aCas) throws ResourceProcessException {\\nSystem.out.println(\\\"Retrival evaluator...\\\");\\n JCas jcas;\\n try {\\n jcas = aCas.getJCas();\\n } catch (CASException e) {\\n throw new ResourceProcessException(e);\\n }\\n\\n FSIterator it = jcas.getAnnotationIndex(Document.type).iterator();\\n \\n// if (it.hasNext()) {\\n// Document doc = (Document) it.next();\\n// cnt++;\\n// }\\n// log(cnt);\\n it = jcas.getAnnotationIndex(Document.type).iterator();\\n\\n if (it.hasNext()) {\\n Document doc = (Document) it.next();\\n int queryid = doc.getQueryID();\\n int rel = doc.getRelevanceValue();\\n // Make sure that your previous annotators have populated this in CAS\\n FSList fsTokenList = doc.getTokenList();\\n ArrayList<Token> tokenList = Utils.fromFSListToCollection(fsTokenList, Token.class);\\n Map<String, Integer> queryVector = new HashMap<String, Integer>();\\n Map<String, Integer> docVector = new HashMap<String, Integer>();\\n if (rel == 99) {\\n for (Token t : tokenList) {\\n queryVector.put(t.getText(), t.getFrequency());\\n }\\n queryVectorlist.add(queryVector);\\n } else {\\n for (Token t : tokenList) {\\n docVector.put(t.getText(), t.getFrequency());\\n }\\n double cos = computeCosineSimilarity(queryVectorlist.get(queryid - 1), docVector);\\n coslist.add(cos);\\n\\n if (rel == 1) {\\n gold = lines;\\n goldcos = cos;\\n System.out.println(\\\"goldcos\\\"+goldcos);\\n }\\n }\\n \\n if (qIdList.size() >= 1 && qIdList.get(qIdList.size() - 1) != queryid) {\\n// System.out.println(\\\"lines:\\\"+lines);\\n sortSimilarity(coslist);\\n log(coslist);\\n int rank=findRank(coslist,goldcos);\\n rankList.add(rank);\\n coslist = new ArrayList<Double>();\\n }\\n\\n qIdList.add(doc.getQueryID());// 有啥用？？？\\n relList.add(doc.getRelevanceValue());\\n\\n // Do something useful here\\n lines++;\\n }\\n //log(coslist);\\n\\n }\",\n \"public IndexDatabase(String index_path, String genomes_path_file, int K_size, SequenceDatabase genomeDb) {\\n int cores = Runtime.getRuntime().availableProcessors() / 2 + 1;\\n int k;\\n long p;\\n IndexPointer null_pointer = new IndexPointer();\\n try {\\n Files.createDirectory(Paths.get(index_path));\\n System.out.println(\\\"Running KMC2... \\\");\\n executeCommand(\\\"kmc -r -k\\\" + K_size + \\\" -t\\\" + cores + \\\" -m\\\" + \\n (Runtime.getRuntime().maxMemory() / 1073741824L) + \\\" -ci1 -fm \\\" + \\n (genomeDb.num_genomes > 1 ? \\\"@\\\" + genomes_path_file.trim() : genomeDb.genome_names[1]) + \\\" \\\" + index_path + \\\"/kmers \\\" + index_path);\\n String output = executeCommand(\\\"kmc_tools sort \\\" + index_path + \\\"/kmers \\\" + index_path + \\\"/sorted\\\");\\n if (output.startsWith(\\\"This database contains sorted k-mers already!\\\")) {\\n new File(index_path + \\\"/kmers.kmc_pre\\\").renameTo(new File(index_path + \\\"/sorted.kmc_pre\\\"));\\n new File(index_path + \\\"/kmers.kmc_suf\\\").renameTo(new File(index_path + \\\"/sorted.kmc_suf\\\"));\\n //Files.copy(Paths.get(path+\\\"/kmers.kmc_pre\\\"), Paths.get(path+\\\"/sorted.kmc_pre\\\"));\\n //Files.copy(Paths.get(path+\\\"/kmers.kmc_suf\\\"), Paths.get(path+\\\"/sorted.kmc_suf\\\"));\\n } else {\\n new File(index_path + \\\"/kmers.kmc_pre\\\").delete();\\n new File(index_path + \\\"/kmers.kmc_suf\\\").delete();\\n }\\n pre_file = new RandomAccessFile(index_path + \\\"/sorted.kmc_pre\\\", \\\"r\\\");\\n pre_file.seek(pre_file.length() - 8);\\n header_pos = read_int(pre_file);\\n pre_file.seek(pre_file.length() - 8 - header_pos);\\n // read the index properties \\n K = read_int(pre_file);\\n mode = read_int(pre_file);\\n ctr_size = read_int(pre_file);\\n pre_len = read_int(pre_file);\\n min_count = read_int(pre_file);\\n max_count = read_int(pre_file);\\n kmers_num = read_long(pre_file);\\n suf_len = K - pre_len;\\n key = new kmer(K, pre_len, suf_len);\\n System.out.println(\\\"Indexing \\\" + kmers_num + \\\" kmers... \\\");\\n // load the prefix file into the memory \\n pre_file.seek(4);\\n int q, len = 1 << (2 * pre_len);\\n prefix_ptr = new long[len];\\n MappedByteBuffer pre_buff;\\n for (q = 0, p = 0; p < 8; ++p) {\\n pre_buff = pre_file.getChannel().map(FileChannel.MapMode.READ_ONLY, 4 + p * len, len);\\n for (k = 0; k < len / 8; ++k, ++q) {\\n prefix_ptr[q] = read_long(pre_buff);\\n }\\n pre_buff = null;\\n }\\n pre_file.close();\\n\\n // mapping suffix file into the memory\\n suf_rec_size = ctr_size + suf_len / 4;\\n MAX_BYTE_COUNT = MAX_BYTE_COUNT / suf_rec_size * suf_rec_size;\\n suf_parts_num = (int) ((kmers_num * suf_rec_size) % MAX_BYTE_COUNT == 0 ? (kmers_num * suf_rec_size) / MAX_BYTE_COUNT : (kmers_num * suf_rec_size) / MAX_BYTE_COUNT + 1);\\n suf_parts_size = new long[suf_parts_num];\\n suf_file = new RandomAccessFile(index_path + \\\"/sorted.kmc_suf\\\", \\\"r\\\");\\n suf_buff = new MappedByteBuffer[suf_parts_num];\\n for (k = 0; k < suf_parts_num; ++k) {\\n suf_parts_size[k] = (int) (k == suf_parts_num - 1 ? (kmers_num * suf_rec_size) % MAX_BYTE_COUNT : MAX_BYTE_COUNT);\\n suf_buff[k] = suf_file.getChannel().map(FileChannel.MapMode.READ_ONLY, 4 + k * suf_parts_size[0], suf_parts_size[k]);\\n }\\n // mapping pointers file into the memory\\n MAX_BYTE_COUNT = MAX_BYTE_COUNT / POINTER_LENGTH * POINTER_LENGTH;\\n ptr_parts_num = (int) ((kmers_num * POINTER_LENGTH) % MAX_BYTE_COUNT == 0 ? (kmers_num * POINTER_LENGTH) / MAX_BYTE_COUNT : (kmers_num * POINTER_LENGTH) / MAX_BYTE_COUNT + 1);\\n ptr_parts_size = new long[ptr_parts_num];\\n ptr_file = new RandomAccessFile(index_path + \\\"/pointers.db\\\", \\\"rw\\\");\\n ptr_buff = new MappedByteBuffer[ptr_parts_num];\\n for (k = 0; k < ptr_parts_num; ++k) {\\n ptr_parts_size[k] = (int) (k == ptr_parts_num - 1 ? (kmers_num * POINTER_LENGTH) % MAX_BYTE_COUNT : MAX_BYTE_COUNT);\\n ptr_buff[k] = ptr_file.getChannel().map(FileChannel.MapMode.READ_WRITE, k * ptr_parts_size[0], ptr_parts_size[k]);\\n }\\n for (p = 0; p < kmers_num; ++p) {\\n put_pointer(null_pointer, p);\\n }\\n } catch (IOException e) {\\n System.out.println(e.getMessage());\\n System.exit(1);\\n }\\n }\",\n \"String prepareLegalDocuments();\",\n \"public void map(Object key, Text value, Context context\\n\\t\\t ) throws IOException, InterruptedException {\\n\\n\\t\\t\\t\\n\\t\\t\\t\\n\\t\\t\\t \\n\\t\\t\\t String curr_string=value.toString();\\n\\t\\t\\t /// splitting based on \\\"*\\\" as a delimiter...\\n\\t\\t\\t String [] parts=curr_string.split(\\\"\\\\\\\\*\\\");\\n\\t\\t\\t String curr_key=parts[0];\\n\\t\\t\\t // Removing spaces from both left and right part of the string..\\n\\t\\t\\t String curr_value=parts[1].trim();\\n\\t\\t\\t String [] small_parts=curr_value.split(\\\",\\\");\\n\\t\\t\\t // Taking the count of unique files which are present in the input given to tfidf\\n\\t\\t\\t int no_of_unique_files=Integer.parseInt(small_parts[small_parts.length-1]);\\n\\t\\t\\t /// The formula to compute idf is log((1+no_of_files)/no_of_unique_files))....\\n\\t\\t\\t Configuration conf=context.getConfiguration();\\n\\t\\t\\t String value_count=conf.get(\\\"test\\\");\\n\\t\\t\\t if(!value_count.isEmpty())\\n\\t\\t\\t {\\n\\t\\t\\t int total_no_files=Integer.parseInt(value_count);\\n\\t\\t\\t double x=(total_no_files/no_of_unique_files);\\n\\t\\t\\t // Formula fo rcomputing the idf value....\\n\\t\\t\\t double idf_value=Math.log10(1+x);\\n\\t\\t\\t for(int i=0;i<small_parts.length-1;i++)\\n\\t\\t\\t {\\n\\t\\t\\t\\t String [] waste=small_parts[i].split(\\\"=\\\");\\n\\t\\t\\t\\t String file_name=waste[0];\\n\\t\\t\\t\\t // Computing the tfidf on the fly...\\n\\t\\t\\t\\t double tf_idf=idf_value*Double.parseDouble(waste[1]);\\n\\t\\t\\t\\t Text word3 = new Text();\\n\\t\\t\\t\\t Text word4 = new Text();\\n\\t\\t\\t\\t word3.set(curr_key+\\\"#####\\\"+file_name+\\\",\\\");\\n\\t\\t\\t\\t word4.set(tf_idf+\\\"\\\");\\n\\t\\t\\t\\t context.write(word3,word4);\\n\\t\\t\\t\\t \\n\\t\\t\\t }\\n\\t\\t\\t //word1.set(curr_key);\\n\\t\\t\\t //word2.set(idf_value+\\\"\\\");\\n\\t\\t\\t //context.write(word1,word2); \\n\\t\\t\\t} \\n\\t\\t}\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.5995485","0.5839277","0.57960045","0.55711436","0.5396472","0.5236064","0.52118707","0.51939565","0.5157785","0.5112572","0.51100713","0.5089438","0.5079131","0.50780505","0.50760406","0.5066933","0.5057492","0.50543725","0.50523096","0.5043695","0.5038304","0.5009075","0.49719515","0.49581295","0.4944205","0.49276507","0.4907697","0.4902209","0.4896648","0.48889354","0.48823825","0.488056","0.48662427","0.48614132","0.4850053","0.4849248","0.48469514","0.48429763","0.48417798","0.48406094","0.4815679","0.48137245","0.48038596","0.48017445","0.4800362","0.47947884","0.47921696","0.47903392","0.478264","0.4780683","0.47727266","0.4762182","0.4758358","0.4754589","0.4750219","0.47501132","0.47488496","0.47466916","0.47464988","0.4745162","0.47450745","0.47446653","0.47435054","0.47360802","0.4730707","0.47282305","0.4725884","0.47255173","0.47235167","0.47208193","0.46977526","0.46950242","0.4693711","0.46840605","0.46834663","0.46818656","0.46722725","0.4670596","0.4668984","0.46638846","0.46635565","0.46605822","0.46480033","0.4647653","0.46438873","0.46427816","0.46359292","0.46263427","0.46230012","0.4621833","0.46208137","0.46171245","0.4617014","0.461547","0.46154234","0.46147498","0.46142325","0.46139985","0.46132553","0.46095335","0.46063212"],"string":"[\n \"0.5995485\",\n \"0.5839277\",\n \"0.57960045\",\n \"0.55711436\",\n \"0.5396472\",\n \"0.5236064\",\n \"0.52118707\",\n \"0.51939565\",\n \"0.5157785\",\n \"0.5112572\",\n \"0.51100713\",\n \"0.5089438\",\n \"0.5079131\",\n \"0.50780505\",\n \"0.50760406\",\n \"0.5066933\",\n \"0.5057492\",\n \"0.50543725\",\n \"0.50523096\",\n \"0.5043695\",\n \"0.5038304\",\n \"0.5009075\",\n \"0.49719515\",\n \"0.49581295\",\n \"0.4944205\",\n \"0.49276507\",\n \"0.4907697\",\n \"0.4902209\",\n \"0.4896648\",\n \"0.48889354\",\n \"0.48823825\",\n \"0.488056\",\n \"0.48662427\",\n \"0.48614132\",\n \"0.4850053\",\n \"0.4849248\",\n \"0.48469514\",\n \"0.48429763\",\n \"0.48417798\",\n \"0.48406094\",\n \"0.4815679\",\n \"0.48137245\",\n \"0.48038596\",\n \"0.48017445\",\n \"0.4800362\",\n \"0.47947884\",\n \"0.47921696\",\n \"0.47903392\",\n \"0.478264\",\n \"0.4780683\",\n \"0.47727266\",\n \"0.4762182\",\n \"0.4758358\",\n \"0.4754589\",\n \"0.4750219\",\n \"0.47501132\",\n \"0.47488496\",\n \"0.47466916\",\n \"0.47464988\",\n \"0.4745162\",\n \"0.47450745\",\n \"0.47446653\",\n \"0.47435054\",\n \"0.47360802\",\n \"0.4730707\",\n \"0.47282305\",\n \"0.4725884\",\n \"0.47255173\",\n \"0.47235167\",\n \"0.47208193\",\n \"0.46977526\",\n \"0.46950242\",\n \"0.4693711\",\n \"0.46840605\",\n \"0.46834663\",\n \"0.46818656\",\n \"0.46722725\",\n \"0.4670596\",\n \"0.4668984\",\n \"0.46638846\",\n \"0.46635565\",\n \"0.46605822\",\n \"0.46480033\",\n \"0.4647653\",\n \"0.46438873\",\n \"0.46427816\",\n \"0.46359292\",\n \"0.46263427\",\n \"0.46230012\",\n \"0.4621833\",\n \"0.46208137\",\n \"0.46171245\",\n \"0.4617014\",\n \"0.461547\",\n \"0.46154234\",\n \"0.46147498\",\n \"0.46142325\",\n \"0.46139985\",\n \"0.46132553\",\n \"0.46095335\",\n \"0.46063212\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}},{"rowIdx":13883,"cells":{"query":{"kind":"string","value":"[NEW] Saves the tokentermIDs map and list with document names"},"document":{"kind":"string","value":"public void saveAll(){\n // Store postings\n for (Map.Entry<String, PostingsList> entry : this.index.entrySet()) {\n saveJSON(\"postings/t\"+hash(entry.getKey())+\".json\", entry.getValue());\n System.err.println(\"postings/t\"+hash(entry.getKey())+\".json\");\n count++;\n if (count%1000==0)\n System.err.println(\"storing \"+ count);\n }\n // Store mapping ID<->document names mapping\n this.saveJSON(\"postings/docIDs.json\", this.docIDs);\n this.saveJSON(\"postings/docLengths.json\", this.docLengths);\n }"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["private void saveToken() throws IOException {\n\t\t\n\t\tFileWriter termIdx = new FileWriter(StoragePath+Path.termIdxDir);\n\t\t\n\t\tfor(Entry<String, Integer> term: termDic.entrySet()){\n\t\t\ttermIdx.append(term.getKey() + \"\\n\" + term.getValue() + \"\\n\");\n\t\t}\n\t\t\n\t\ttermIdx.close();\n\t\t\n\t}","public static void generateInvertedIndex(Map<String, List<Posting>> stemMap, List<String> documentIds)\n {\n long lineCounter = 0;\n int documentCounter = -1;\n String currentDocId = \"\";\n String currentDocTitle = \"\";\n Scanner scanner = new Scanner(System.in);\n\n while (scanner.hasNext())\n {\n String line = scanner.nextLine();\n lineCounter++;\n \n if (line.startsWith(\"$DOC\"))\n {\n String[] wordStems = line.split(\" \");\n currentDocId = wordStems[1];\n documentCounter++;\n }\n else if (line.startsWith(\"$TITLE\"))\n {\n /* Save document titles for documentId list */\n long docLineNumber = lineCounter - 1;\n currentDocTitle = \"\";\n \n while (scanner.hasNext())\n {\n String nextTitleLine = scanner.nextLine();\n if (nextTitleLine.startsWith(\"$TEXT\"))\n {\n lineCounter++;\n documentIds.add(String.format(\"%s %d %s\\n\", currentDocId, docLineNumber, currentDocTitle));\n break;\n }\n else\n {\n lineCounter++;\n currentDocTitle += nextTitleLine;\n currentDocTitle += \" \";\n }\n }\n }\n else\n {\n String[] wordStems = line.split(\" \");\n for (String wordStem: wordStems)\n {\n if (stemMap.containsKey(wordStem))\n {\n List<Posting> currentStemPostings = stemMap.get(wordStem);\n int lastElementIndex = currentStemPostings.size() - 1;\n Posting lastPosting = currentStemPostings.get(lastElementIndex);\n \n if (lastPosting.documentId == documentCounter)\n {\n lastPosting.termFrequency += 1;\n }\n else\n {\n Posting posting = new Posting(documentCounter, 1);\n currentStemPostings.add(posting);\n }\n }\n else\n {\n List<Posting> postings = new ArrayList<>();\n Posting posting = new Posting(documentCounter, 1);\n postings.add(posting);\n stemMap.put(wordStem, postings);\n }\n }\n }\n }\n scanner.close();\n }","public void writeIDs() {\n try {\n FileOutputStream fileOut = new FileOutputStream(\"temp/ids.ser\");\n ObjectOutputStream out = new ObjectOutputStream(fileOut);\n out.writeObject(ids);\n out.close();\n fileOut.close();\n } catch (IOException e) {\n e.printStackTrace();\n }\n\n }","private void scanDocuments()\n{\n document_counts = new HashMap<>();\n kgram_counts = new HashMap<>();\n for (File f : root_files) {\n addDocuments(f);\n }\n}","public static void printInvertedIndexToFile(Map<String, List<Posting>> stemMap, List<String> documentIds)\n {\n try\n {\n PrintWriter dictionaryPW = new PrintWriter(DICTIONARY_OUTPUT_FILE_PATH, \"UTF-8\");\n PrintWriter postingsPW = new PrintWriter(POSTINGS_OUTPUT_FILE_PATH, \"UTF-8\");\n PrintWriter docIdsPW = new PrintWriter(DOCUMENT_ID_OUTPUT_FILE_PATH, \"UTF-8\");\n\n int numStems = stemMap.size();\n int numPostingEntries = 0;\n int numDocuments = documentIds.size();\n \n for (List<Posting> posting: stemMap.values())\n {\n numPostingEntries += posting.size();\n }\n\n dictionaryPW.println(numStems);\n postingsPW.println(numPostingEntries);\n docIdsPW.println(numDocuments);\n\n for (Entry<String, List<Posting>> entrySet: stemMap.entrySet())\n {\n String stem = entrySet.getKey();\n List<Posting> postings = entrySet.getValue();\n\n dictionaryPW.println(String.format(\"%s %d\", stem, postings.size()));\n for (Posting posting: postings)\n {\n postingsPW.println(String.format(\"%d %d\", posting.documentId, posting.termFrequency));\n numPostingEntries++;\n }\n }\n\n for (String docId: documentIds)\n {\n docIdsPW.print(docId);\n }\n\n dictionaryPW.close();\n postingsPW.close();\n docIdsPW.close();\n }\n catch (Exception e)\n {\n System.out.println(e.getMessage());\n }\n }","private void saveIds(ArrayList<String> idList) {\n\n\t\ttry {\n\t\t\tFileOutputStream fileOutputStream = context.openFileOutput(\n\t\t\t\t\tSAVE_FILE, Context.MODE_PRIVATE);\n\t\t\tOutputStreamWriter outputStreamWriter = new OutputStreamWriter(\n\t\t\t\t\tfileOutputStream);\n\t\t\tGsonBuilder builder = new GsonBuilder();\n\t\t\tGson gson = builder.create();\n\t\t\tgson.toJson(idList, outputStreamWriter); // Serialize to Json\n\t\t\toutputStreamWriter.flush();\n\t\t\toutputStreamWriter.close();\n\t\t} catch (IOException e) {\n\t\t\te.printStackTrace();\n\t\t}\n\t}","public static void save(String indexFileName) throws FileNotFoundException, UnsupportedEncodingException{\n\t\tHashMap<String, String> sCurrentHashMap = globalHash.get(indexFileName);\n\t\t\n\t\tPrintWriter writer = new PrintWriter(indexFileName+\".txt\", \"UTF-8\");\n\n\t\tIterator it = sCurrentHashMap.entrySet().iterator();\n\t\twhile(it.hasNext()){\n\t\t\tHashMap.Entry<String, String> entry = (HashMap.Entry<String, String>) it.next();\n\t\t\t//if this term appear more than one doc\n\t\t\tif(entry.getValue().length()>1) {\n\t\t\t\tStringTokenizer stDocID = new StringTokenizer(entry.getValue(),\",\");\n\t\t\t\twriter.println(entry.getKey()+\",\"+stDocID.countTokens()+\":<\"+entry.getValue()+\">\");\n\t\t\t} else{\n\t\t\t\twriter.println(entry.getKey()+\",1:<\"+entry.getValue()+\">\");\n\t\t\t}\n\t\t}\n\t\twriter.close();\n\t}","public void IndexADocument(String docno, String content) throws IOException {\n\t\tdocid++;\n\t\tdoc2docid.put(docno, docid);\n\t\tdocid2doc.put(docid, docno);\n\n\t\t// Insert every term in this doc into docid2map\n\t\tString[] terms = content.trim().split(\" \");\n\t\tMap<Integer, Integer> docTerm = new HashMap<>();\n\t\tint thisTermid;\n\t\tfor(String term: terms){\n\t\t\t// get termid\n\t\t\tif(term2termid.get(term)!=null) thisTermid = term2termid.get(term);\n\t\t\telse{\n\t\t\t\tthisTermid = ++termid;\n\t\t\t\tterm2termid.put(term, thisTermid);\n\t\t\t}\n\t\t\tdocTerm.put(thisTermid, docTerm.getOrDefault(thisTermid, 0)+1);\n\t\t\t// Merge this term's information into termid2map\n\t\t\tMap<Integer, Integer> temp = termid2map.getOrDefault(thisTermid, new HashMap());\n\t\t\ttemp.put(docid, temp.getOrDefault(docid, 0)+1);\n\t\t\ttermid2map.put(thisTermid, temp);\n\t\t\ttermid2fre.put(thisTermid, termid2fre.getOrDefault(thisTermid, 0)+1);\n\t\t}\n\t\tdocid2map.put(docid, docTerm);\n\n//\t\t// Merge all the terms' information into termid2map\n//\t\tfor(Long tid: docTerm.keySet()){\n//\t\t\tMap<Long, Long> temp = termid2map.getOrDefault(tid, new HashMap());\n//\t\t\ttemp.put(docid,docTerm.get(tid));\n//\t\t\ttermid2map.put(tid, temp);\n//\t\t\t// update this term's frequency\n//\t\t\ttermid2fre.put(tid, termid2fre.getOrDefault(tid,0L)+docTerm.get(tid));\n//\t\t}\n\n\t\t// When termid2map and docid2map is big enough, put it into disk\n\t\tif(docid%blockSize==0){\n\t\t\tWritePostingFile();\n\t\t\tWriteDocFile();\n\t\t}\n\t}","static private void saveSentenceTokens( final String outputDirPath,\n final String documentId, final Iterable<String> tokenizedSentences ) {\n // Be prepared for documentId that contains directory segments, some of which may not exist\n final File outputFile = new File( outputDirPath + File.pathSeparator + documentId );\n if ( !outputFile.getParentFile().exists() && !outputFile.getParentFile().mkdirs() ) {\n LOGGER.error( outputFile.getPath() + \" is an invalid output file path\" );\n return;\n }\n try ( final BufferedWriter writer = new BufferedWriter( new FileWriter( outputFile ) ) ) {\n for ( String tokenizedSentence : tokenizedSentences ) {\n writer.write( tokenizedSentence );\n writer.newLine();\n }\n } catch ( IOException ioE ) {\n LOGGER.error( ioE.getMessage() );\n }\n }","private void writeVocabPost(FlIndexer fi) throws IOException{\n this.docNormPow = new HashMap<>();\n \n LinkedList<Integer> tf;\n LinkedList<String> files;\n String token;\n int position=0;\n File file = new File(\"CollectionIndex/VocabularyFile.txt\");\n File Postingfile = new File(\"CollectionIndex/PostingFile.txt\");\n \n\tFileWriter fw = new FileWriter(file.getAbsoluteFile());\n FileWriter fw_posting = new FileWriter(Postingfile.getAbsolutePath());\n try (BufferedWriter bw = new BufferedWriter(fw)) {\n try (BufferedWriter bw_posting = new BufferedWriter(fw_posting)){\n for (Map.Entry<String, TermNode> entry : fi.mapTerms.entrySet()){\n double idf = ((double)this.docMap.size())/entry.getValue().getDf();\n //idf=log2(idf, 2);\n bw.write(entry.getValue().getTerm()+\" \"+entry.getValue().getDf()+\" \"+idf+\" \"+position+\"\\n\");\n \n tf=entry.getValue().getTfList();\n files=entry.getValue().getFileList();\n int i=tf.size();\n for (int j=0; j<i; j++){\n double tfidf=idf*((double)tf.get(j)/fi.getMaxTF(files.get(j)));\n double tfidfpow=Math.pow(tfidf, 2);\n\n \n if(this.docNormPow.containsKey(files.get(j))){\n //this.docNorm.put(files.get(j), this.docNorm.get(files.get(j))+tfidf);\n this.docNormPow.put(files.get(j), this.docNormPow.get(files.get(j))+tfidfpow);\n }\n else{\n //this.docNorm.put(files.get(j), tfidf);\n this.docNormPow.put(files.get(j), tfidfpow);\n }\n \n token=this.docMap.get(files.get(j))+\" \"+tf.get(j)+\" \"\n +entry.getValue().multiMap.get(files.get(j))+\" \"+tfidf+\"\\n\";\n position= position + token.length();\n \n bw_posting.write(token);\n }\n }\n }\n }\n \n System.out.println(\"Done creating VocabularyFile.txt\");\n System.out.println(\"Done creating PostingFile.txt\");\n }","public Vector mapDocument(MultiSet<String> bow) {\n //logger.info(\"lsm.mapDocument\");\n SparseVector vector = new SparseVector();\n\n Iterator<String> it = bow.iterator();\n String term = null;\n int index = 0;\n int tf = 0;\n float tfIdf;\n for (int i = 0; it.hasNext(); i++) {\n //logger.info(i + \" \" + t[i]);\n term = it.next();\n index = termIndex.get(term);\n\n if (index != -1) {\n tf = bow.getFrequency(term);\n tfIdf = (float) (log2(tf)) * Iidf[index];\n\n //logger.info(term + \" ==> \" + index + \", tf.idf = \" + tf + \"(\" + (log2(tf)) + \") * \" + Iidf[index] + \" = \" + tfIdf);\n vector.add(index, tfIdf);\n\n }\n } // end for\n\n return vector;\n }","public static void main(String[] args) throws IOException{\n\t\tint termIndex = 1;\n\t\t\n\t\t// startOffset holds the start offset for each term in\n\t\t// the corpus.\n\t\tlong startOffset = 0;\n\t\t\t\n\t\t// unique_terms is true if there are atleast one more\n\t\t// unique term in corpus.\n\t\tboolean unique_terms = true;\n\t\t\n\t\t\n\t\t//load the stopwords from the HDD\n\t\tString stopwords = getStopWords();\n\t\t\n\t\t// allTokenHash contains all the terms and its termid\n\t\tHashMap<String, Integer> allTermHash = new HashMap<String, Integer>();\n\t\t\n\t\t// catalogHash contains the term and its position in\n\t\t// the inverted list present in the HDD.\n\t\tHashMap<Integer, Multimap> catalogHash = new HashMap<Integer, Multimap>();\n\t\t\n\t\t// finalCatalogHash contains the catalogHash for the invertedIndexHash\n\t\t// present in the HDD.\n\t\tHashMap<Integer, String> finalCatalogHash = new HashMap<Integer, String>();\n\t\t\n\t\t// token1000Hash contains the term and Dblocks for the first 1000\n\t\tHashMap<Integer, Multimap> token1000DocHash = new HashMap<Integer, Multimap>();\n\t\t\n\t\t// documentHash contains the doclength of all the documents in the corpus\n\t\tHashMap<String, String> documentHash = new HashMap<String, String>();\t\n\t\t\n\t\t// id holds the document id corresponding to the docNumber.\n\t\tint id = 1;\n\t\t\n\t\t// until all unique terms are exhausted\n\t\t// pass through the documents and index the terms.\n\t\t//while(unique_terms){\n\t\t\t\n\t\t\tFile folder = new File(\"C:/Naveen/CCS/IR/AP89_DATA/AP_DATA/ap89_collection\");\n\t\t\t//File folder = new File(\"C:/Users/Naveen/Desktop/TestFolder\");\n\t\t\tFile[] listOfFiles = folder.listFiles();\n\t\t\t\n\t\t\t//for each file in the folder \n\t\t\tfor (File file : listOfFiles) {\n\t\t\t if (file.isFile()) {\n\t\t\t \t\n\t\t\t \tString str = file.getPath().replace(\"\\\\\",\"//\");\n\t\t\t \t\n\t\t\t \t\n\t\t\t\t\t//Document doc = new Document();\n\t\t\t //System.out.println(\"\"+str);\n\t\t\t\t\t//variables to keep parse document.\n\t\t\t\t\tint docCount = 0;\n\t\t\t\t\tint docNumber = 0;\n\t\t\t\t\tint endDoc = 0;\n\t\t\t\t\tint textCount = 0;\n\t\t\t\t\tint noText = 0;\n\t\t\t\t\tPath path = Paths.get(str);\n\t\t\t\t\t\n\t\t\t\t\t//Document id and text\n\t\t\t\t\tString docID = null;\n\t\t\t\t\tString docTEXT = null;\n\t\t\t\t\t\n\t\t\t\t\t//Stringbuffer to hold the text of each document\n\t\t\t\t\tStringBuffer text = new StringBuffer();\n\t\t\t\t\t\n\t\t\t\t\tScanner scanner = new Scanner(path);\n\t\t\t\t\twhile(scanner.hasNext()){\n\t\t\t\t\t\tString line = scanner.nextLine();\n\t\t\t\t\t\tif(line.contains(\"<DOC>\")){\n\t\t\t\t\t\t\t++docCount;\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t}\n\t\t\t\t\t\telse if(line.contains(\"</DOC>\")){\n\t\t\t\t\t\t\t++endDoc;\n\t\t\t\t\t\t\tdocTEXT = text.toString();\n\t\t\t\t\t\t\t//docTEXT = docTEXT.replaceAll(\"[\\\\n]\",\" \");\n\t\t\t\t\t\t\tSystem.out.println(\"ID: \"+id);\n\t\t\t\t\t\t\t//System.out.println(\"TEXT: \"+docTEXT);\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t// text with stop words removed\n\t\t\t\t\t\t\tPattern pattern1 = Pattern.compile(\"\\\\b(?:\"+stopwords+\")\\\\b\\\\s*\", Pattern.CASE_INSENSITIVE);\n\t\t\t\t\t\t\tMatcher matcher1 = pattern1.matcher(docTEXT);\n\t\t\t\t\t\t\tdocTEXT = matcher1.replaceAll(\"\");\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t// text with stemming\n\t\t\t\t\t\t\t//docTEXT = stemmer(docTEXT);\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\tint docLength = 1;\n\t\t\t\t\t\t\t// regex to build the tokens from the document text\n\t\t\t\t\t\t\tPattern pattern = Pattern.compile(\"\\\\w+(\\\\.?\\\\w+)*\");\n\t\t\t\t\t\t\tMatcher matcher = pattern.matcher(docTEXT.toLowerCase());\n\t\t\t\t\t\t\twhile (matcher.find()) {\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tfor (int i = 0; i < matcher.groupCount(); i++) {\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t// alltermHash contains term and term id\n\t\t\t\t\t\t\t\t\t// if term is present in the alltermHash\n\t\t\t\t\t\t\t\t\tif(allTermHash.containsKey(matcher.group(i))){\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\tint termId = allTermHash.get(matcher.group(i));\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t//if term is present in the token1000Hash\n\t\t\t\t\t\t\t\t\t\t//then update the dblock of the term.\n\t\t\t\t\t\t\t\t\t\tif(token1000DocHash.containsKey(termId)){\n\t\t\t\t\t\t\t\t\t\t\tMultimap<String, String> dBlockUpdate = token1000DocHash.get(termId);\n\t\t\t\t\t\t\t\t\t\t\t//Multimap<Integer, Integer> dBlockUpdate = token1000DocHash.get(matcher.group(i));\n\t\t\t\t\t\t\t\t\t\t\tif(dBlockUpdate.containsKey(id)){\n\t\t\t\t\t\t\t\t\t\t\t\tdBlockUpdate.put(String.valueOf(id), String.valueOf(matcher.start()));\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\telse{\n\t\t\t\t\t\t\t\t\t\t\t\tdBlockUpdate.put(String.valueOf(id), String.valueOf(matcher.start()));\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t//if term is not present in the token1000hash\n\t\t\t\t\t\t\t\t\t\t//then add the token with its dBlock\n\t\t\t\t\t\t\t\t\t\telse{\n\t\t\t\t\t\t\t\t\t\t\tMultimap<String, String> dBlockInsert = ArrayListMultimap.create();\n\t\t\t\t\t\t\t\t\t\t\tdBlockInsert.put(String.valueOf(id), String.valueOf(matcher.start()));\n\t\t\t\t\t\t\t\t\t\t\ttoken1000DocHash.put(termId, dBlockInsert);\t\n\t\t\t\t\t\t\t\t\t\t}\t\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// if the term is not present I will put the term into allTermHash\n\t\t\t\t\t\t\t\t\t// put corresponding value into the token1000DocHash and increment\n\t\t\t\t\t\t\t\t\t// termIndex\n\t\t\t\t\t\t\t\t\telse{\n\t\t\t\t\t\t\t\t\t\tallTermHash.put(matcher.group(i),termIndex);\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\tMultimap<String, String> dBlockInsert = ArrayListMultimap.create();\n\t\t\t\t\t\t\t\t\t\tdBlockInsert.put(String.valueOf(id), String.valueOf(matcher.start()));\n\t\t\t\t\t\t\t\t\t\ttoken1000DocHash.put(termIndex, dBlockInsert);\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\ttermIndex++;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tdocLength++;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tif(id%1000 == 0){\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t// then dump index file to HDD\n\t\t\t\t\t\t\t\t\twriteInvertedIndex(token1000DocHash,\"token1000DocHash\");\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t// update catalog file\n\t\t\t\t\t\t\t\t\t// to populate catalogHash with the offset\n\t\t\t\t\t\t\t\t\tfor(Entry<Integer, Multimap> entry : token1000DocHash.entrySet()){\n\t\t\t\t\t\t\t\t\t\tif(catalogHash.containsKey(entry.getKey())){\n\t\t\t\t\t\t\t\t\t\t\tint len = (entry.getKey()+\":\"+entry.getValue()).length();\n\t\t\t\t\t\t\t\t\t\t\t//String offset = String.valueOf(startOffset)+\":\"+String.valueOf(len);\n\t\t\t\t\t\t\t\t\t\t\tMultimap<String, String> catUpdate = catalogHash.get(entry.getKey());\n\t\t\t\t\t\t\t\t\t\t\tcatUpdate.put(String.valueOf(startOffset), String.valueOf(len));\n\t\t\t\t\t\t\t\t\t\t\tcatalogHash.put(entry.getKey(), catUpdate);\n\t\t\t\t\t\t\t\t\t\t\tstartOffset += len+2;\n\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\telse{\n\t\t\t\t\t\t\t\t\t\t\tint len = (entry.getKey()+\":\"+entry.getValue()).length();\n\t\t\t\t\t\t\t\t\t\t\t//String offset = String.valueOf(startOffset)+\":\"+String.valueOf(len);\n\t\t\t\t\t\t\t\t\t\t\tMultimap<String, String> catInsert = ArrayListMultimap.create();\n\t\t\t\t\t\t\t\t\t\t\tcatInsert.put(String.valueOf(startOffset), String.valueOf(len));\n\t\t\t\t\t\t\t\t\t\t\tcatalogHash.put(entry.getKey(), catInsert);//entry.getValue());\n\t\t\t\t\t\t\t\t\t\t\tstartOffset += len+2;\n\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t}\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t//clear the token1000DocHash\n\t\t\t\t\t\t\t\t\ttoken1000DocHash.clear();\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\tdocumentHash.put(docID, \"\"+id+\":\"+docLength);\n\t\t\t\t\t\t\tid++;\n\t\t\t\t\t\t\ttext = new StringBuffer();\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t}\n\t\t\t\t\t\telse if(line.contains(\"<DOCNO>\")){\n\t\t\t\t\t\t\t++docNumber;\n\t\t\t\t\t\t\tdocID = line.substring(8, 21);\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t}\n\t\t\t\t\t\telse if(line.contains(\"<TEXT>\")){\n\t\t\t\t\t\t\t++textCount;\n\t\t\t\t\t\t}\n\t\t\t\t\t\telse if((line.contains(\"<DOC>\"))||\n\t\t\t\t\t\t\t\t(line.contains(\"</DOC>\"))||\n\t\t\t\t\t\t\t\t(line.contains(\"<DOCNO>\"))||\n\t\t\t\t\t\t\t\t(line.contains(\"<FILEID>\"))||\n\t\t\t\t\t\t\t\t(line.contains(\"<FIRST>\"))||\n\t\t\t\t\t\t\t\t(line.contains(\"<SECOND>\"))||\n\t\t\t\t\t\t\t\t(line.contains(\"<HEAD>\"))||\n\t\t\t\t\t\t\t\t(line.contains(\"</HEAD>\"))||\n\t\t\t\t\t\t\t\t(line.contains(\"<BYLINE>\"))||\n\t\t\t\t\t\t\t\t(line.contains(\"</BYLINE>\"))||\n\t\t\t\t\t\t\t\t(line.contains(\"<UNK>\"))||\n\t\t\t\t\t\t\t\t(line.contains(\"</UNK>\"))||\n\t\t\t\t\t\t\t\t(line.contains(\"<DATELINE>\"))||\n\t\t\t\t\t\t\t\t(line.contains(\"<NOTE>\"))||\n\t\t\t\t\t\t\t\t(line.contains(\"</NOTE>\"))||\n\t\t\t\t\t\t\t\t(line.contains(\"</TEXT>\"))||\n\t\t\t\t\t\t\t\t(line.contains(\"<TEXT>\"))){\n\t\t\t\t\t\t\t ++noText;\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t}\n\t\t\t\t\t\telse if(endDoc == docCount - 1){\n\t\t\t\t\t\t\ttext.append(line);\n\t\t\t\t\t\t\ttext.append(\" \");\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t \t\n\t\t\t }//end of if - to check if this is a file and parse.\n\t\t\t \n\t\t\t}//end of for loop to load each file\n\t\t\t\n\t\t//}//end of while loop \n\t\t\n\t// write catalogfile to the hdd to check.\n\t\t\t\n\t\t\t// then dump index file to HDD\n\t\t\twriteInvertedIndex(token1000DocHash,\"token1000DocHash\");\n\t\t\t\n\t\t\t// update catalog file\n\t\t\t// to populate catalogHash with the offset\n\t\t\tfor(Entry<Integer, Multimap> entry : token1000DocHash.entrySet()){\n\t\t\t\tif(catalogHash.containsKey(entry.getKey())){\n\t\t\t\t\tint len = (entry.getKey()+\":\"+entry.getValue()).length();\n\t\t\t\t\t//String offset = String.valueOf(startOffset)+\":\"+String.valueOf(len);\n\t\t\t\t\tMultimap<String, String> catUpdate = catalogHash.get(entry.getKey());\n\t\t\t\t\tcatUpdate.put(String.valueOf(startOffset), String.valueOf(len));\n\t\t\t\t\tcatalogHash.put(entry.getKey(), catUpdate);\n\t\t\t\t\tstartOffset += len+2;\n\t\t\t\t\t\n\t\t\t\t}\n\t\t\t\telse{\n\t\t\t\t\tint len = (entry.getKey()+\":\"+entry.getValue()).length();\n\t\t\t\t\t//String offset = String.valueOf(startOffset)+\":\"+String.valueOf(len);\n\t\t\t\t\tMultimap<String, String> catInsert = ArrayListMultimap.create();\n\t\t\t\t\tcatInsert.put(String.valueOf(startOffset), String.valueOf(len));\n\t\t\t\t\tcatalogHash.put(entry.getKey(), catInsert);//entry.getValue());\n\t\t\t\t\tstartOffset += len+2;\n\t\t\t\t\t\n\t\t\t\t}\t\t\t\t\t\t\t\t\t\t\n\t\t\t}\n\t\t\t\n\t\t\t\n\t\t\t\n\t\t\twriteInvertedIndex(catalogHash,\"catalogHash\");\n\t\t\tprintHashMapSI(allTermHash);\n\t\t\tprintHashMapSS(documentHash);\n\t\t\t\n\t\t\tlong InvIndstartOffset = 0;\n\t\t\t\n\t\t\t//write it to file\n \n\t\t\t//change the finalcatalogHash to the form termid:startoffset:length\n\t\t\tfor (Integer name: catalogHash.keySet()){\n\t String key = name.toString();\n\t String value = catalogHash.get(name).toString(); \n\t //System.out.println(key + \" \" + value); \n\t String finalTermIndex = genInvertedIndex(key, value);\n\t finalTermIndex = key+\":\"+finalTermIndex;\n\t int indexLength = finalTermIndex.length();\n\t \n\t \n\t PrintWriter writer = new PrintWriter(new BufferedWriter\n\t \t\t(new FileWriter(\"C:/Users/Naveen/Desktop/TestRuns/LastRun/InvertedIndex\", true)));\n\t writer.println(finalTermIndex);\n\t writer.close();\n\t \n\t //update the finalcatalogHash\n\t //Multimap<String, String> catInsert = ArrayListMultimap.create();\n\t\t\t\t//catInsert.put(String.valueOf(InvIndstartOffset), String.valueOf(indexLength));\n\t\t\t\tfinalCatalogHash.put(name, String.valueOf(InvIndstartOffset)+\":\"+String.valueOf(indexLength));//entry.getValue());\n\t\t\t\tInvIndstartOffset += indexLength+2;\n\t \n\t\t\t}\n\t\t\t\n\t\t\t\n\t\t\t\n\t\t\tprintHashMapIS(finalCatalogHash);\n\t\t\t\n\t}","public static TreeMap<Integer,String> calc_tf_idf( String \tbaseFolder,\n\t\t\t\t\t\t\t\t\t\t\t\t\t String baseFolder_out,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tString \tinputFile, \n\t\t\t\t\t\t\t\t\t\t\t\t\t\tString delimiter_for_inputFile,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tint \ttoken_index_having_text,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tString \toutFile,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tboolean is_do_stemming_on_word,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tboolean is_ignore_stop_words_all_together,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tboolean isSOPprint\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t){\n\t\tTreeMap<Integer,String> mapOut=new TreeMap<Integer, String>();\n\t\ttry{\n\t\t\tString line=\"\";\n\t\t\tBufferedReader reader = new BufferedReader(new InputStreamReader(new FileInputStream( inputFile) ));\n\t\t\t//boolean is_do_stemming_on_word=true;\n\t\t\tStemmer stemmer=new Stemmer(); String token=\"\";\n\t\t TreeMap<String, Integer> mapVoc_Freq=new TreeMap<String, Integer>();\n\t\t TreeMap<String, List<Integer>> map_Word_UniqueDocumentIdHavingIT=new TreeMap<String, List<Integer>>();\n\t\t TreeMap<Integer, TreeMap<String, Integer > > map_DocID_wordFrequency=new TreeMap<Integer, TreeMap<String,Integer>>();\n\t\t\t\tint lineNumber=0; int last_doc_id=-1;\n\t\t\t\n\t\t\tFileWriter writer_voc=new FileWriter(new File(baseFolder_out+\"unique_word_vocabulary.txt\"));\n\t\t\t\t\n\t\t\tFileWriter writer=new FileWriter(new File(outFile));\n\t\t\t// files for docID wordID tf-idf output\n\t\t\tFileWriter writer_no_stopword=new FileWriter(new File(outFile+\"_noStopWord.txt\"));\t\t\t\n\t\t\tFileWriter writer_wordID=new FileWriter(new File(outFile+\"_WORD_ID.txt\"));\n\t\t\tFileWriter writer_wordID_no_stopword=new FileWriter(new File(outFile+\"_noStopWord_WORD_ID.txt\"));\n\t\t\tFileWriter writer_word_stemmedWord=new FileWriter(new File(outFile+\"_Word_stemmedWord.txt\"));\n\t\t\t\n\t\t\t// files for docID wordID frequency output\n\t\t\tFileWriter writer2=new FileWriter(new File(outFile+\"_docWordID_freq2.txt\"));\n\t\t\tFileWriter writer2_no_stopword=new FileWriter(new File(outFile+\"_noStopWord2.txt\"));\n\t\t\tFileWriter writer2_wordID=new FileWriter(new File(outFile+\"_WORD_ID2.txt\"));\n\t\t\tFileWriter writer2_wordID_no_stopword=new FileWriter(new File(outFile+\"_noStopWord_WORD_ID2.txt\"));\n\t\t\tFileWriter writer2_word_stemmedWord=new FileWriter(new File(outFile+\"_Word_stemmedWord2.txt\"));\n\t\t\t\n\n\t\t\t\n\t\t\tFileWriter writer_debug=new FileWriter(new File(outFile+\"_DEBUG.txt\"));\n\t\t\tFileWriter writer_debug_2=new FileWriter(new File(outFile+\"_DEBUG_2.txt\"));\n\t\t\t\n\t\t\tTreeMap<String,Integer> map_already_wrote=new TreeMap<String, Integer>();\n\t\t\t//\n\t\t\twhile ((line = reader.readLine()) != null) {\n\t\t\t\tlineNumber++;\n\t\t\t\tSystem.out.println(\"lineNumber:\"+lineNumber);\n\t\t\t\t\n\t\t\t\t//DEBUG BREAK\n//\t\t\t\tif(lineNumber>100) break;\n\t\t\t\t\n\t\t\t\t//mapVoc_Freq=new TreeMap<String, Integer>();\n\t\t\t\tint curr_doc_id=lineNumber;\n\t\t\t\tString [] token_= line.split(delimiter_for_inputFile);\n\t\t\t\t\n\t\t\t\t //clean\n\t\t\t\t token=token_[token_index_having_text-1].replace(\"\\\"\", \" \").replace(\"'\", \" \").replace(\",\", \" \").replace(\";\",\" \").replace(\".\", \" \")\n\t\t\t\t\t\t\t\t .replace(\"‘\", \" \").replace(\"“\", \" \").replace(\"–\", \" \").replace(\")\", \" \").replace(\"(\", \" \")\n\t\t\t\t\t\t\t\t .replace(\"-\", \" \").replace(\":\", \" \").replace(\"’\", \" \").replace(\"”\", \" \").replace(\"—\", \" \")\n\t\t\t\t\t\t\t\t .replace(\"#\", \" \").replace(\"%\", \" \")//.replace(\"$\", \" \")\n\t\t\t\t\t\t\t\t .replace(\"/\",\" \")\n\t\t\t\t\t\t\t\t .replace(\" \", \" \");\n\t\t\t\t \n\t\t\t\t token=token.toLowerCase();\n\n\t\t\t\t \n\t\t\t\t // \n\t\t\t\t String [] arr_token=token.split(\" \");\n\t\t\t\t int cnt=0;\n\t\t\t\t // \n\t\t\t\t while(cnt < arr_token.length){\n\t\t\t\t\t String temp= Ltrim.ltrim( arr_token[cnt]);\n\t\t\t\t\t \n\t\t\t\t\t // ignore stop words all together\n\t\t\t\t\t if(is_ignore_stop_words_all_together==true && Stopwords.is_stopword(temp)){\n\t\t\t\t\t\t cnt++;\n\t\t\t\t\t\t continue;\n\t\t\t\t\t }\n\t\t\t\t\t \n\t\t\t\t\t // do stemming\n\t\t\t\t\t if(is_do_stemming_on_word){\n\t\t\t\t\t\t String orig_temp=temp;\n\t\t\t\t\t\t //ltrim.ltrim(\n\t\t\t\t\t\t temp= stemmer.stem(temp);\n\t\t\t\t\t\t \n\t\t\t\t\t\t if(!map_already_wrote.containsKey(orig_temp)){\n\t\t\t\t\t\t\t writer_word_stemmedWord.append(orig_temp+\"!!!\"+temp +\"\\n\");\n\t\t\t\t\t\t\t writer_word_stemmedWord.flush();\n\t\t\t\t\t\t }\n\t\t\t\t\t\t \n\t\t\t\t\t\t map_already_wrote.put(orig_temp, -1);\n\t\t\t\t\t\t \n\t\t\t\t\t }\n\t\t\t\t\t else \n\t\t\t\t\t\t temp=temp;\n\n\t\t\t\t\t\t // \n\t\t\t\t\t\t if(!mapVoc_Freq.containsKey(temp)){\n\t\t\t\t\t\t\t //vocabulary term-freq\n\t\t\t\t\t\t\t mapVoc_Freq.put(temp, 1);\t\t\t\t\t\t\t\t\t\t\t\t \n\t\t\t\t\t\t\t //word-document freq- unique number of documents this word occurs.\n\t\t\t\t\t\t\t List l=new ArrayList<Integer>();\n\t\t\t\t\t\t\t l.add(curr_doc_id);\n\t\t\t\t\t\t\t map_Word_UniqueDocumentIdHavingIT.put(temp, l);\n\t\t\t\t\t\t\t \n\t\t\t\t\t\t\t //doc-wise frequency\n\t\t\t\t\t\t\t if(!map_DocID_wordFrequency.containsKey(curr_doc_id)){\n\t\t\t\t\t\t\t\t TreeMap<String,Integer> t2=new TreeMap<String, Integer>();\n\t\t\t\t\t\t\t\t t2.put( temp, 1 ) ;\n\t\t\t\t\t\t\t\t map_DocID_wordFrequency.put(curr_doc_id, t2);\n\t\t\t\t\t\t\t }\n\t\t\t\t\t\t\t else{\n\t\t\t\t\t\t\t\t TreeMap<String,Integer> t2=map_DocID_wordFrequency.get(curr_doc_id);\n\t\t\t\t\t\t\t\t \n\t\t\t\t\t\t\t\t if(!t2.containsKey(temp)){\n\t\t\t\t\t\t\t\t\t TreeMap<String,Integer> t2_2=map_DocID_wordFrequency.get(curr_doc_id);\n\t\t\t\t\t\t\t\t\t t2_2.put( temp, 1 ) ;\n\t\t\t\t\t\t\t\t\t map_DocID_wordFrequency.put(curr_doc_id, t2_2);\n\t\t\t\t\t\t\t\t }\n\t\t\t\t\t\t\t\t else{\n\t\t\t\t\t\t\t\t\t TreeMap<String,Integer> t2_2=map_DocID_wordFrequency.get(curr_doc_id);\n\t\t\t\t\t\t\t\t\t int sz=t2.get(temp)+1;\n\t\t\t\t\t\t\t\t\t t2_2.put( temp, sz ) ;\n\t\t\t\t\t\t\t\t\t map_DocID_wordFrequency.put(curr_doc_id, t2_2);\n\t\t\t\t\t\t\t\t }\n\t\t\t\t\t\t\t }\n\t\t\t\t\t\t\t \n\t\t\t\t\t\t }\n\t\t\t\t\t\t else{\n\t\t\t\t\t\t\t int freq=mapVoc_Freq.get(temp)+1;\n\t\t\t\t\t\t\t //System.out.println(\"last_doc_id!=curr_doc_id->\"+last_doc_id+\"<-->\"+curr_doc_id );\n\t\t\t\t\t\t\t //vocabulary term-freq\n\t\t\t\t\t\t\t mapVoc_Freq.put(temp, freq);\n\t\t\t\t\t\t\t // word-document freq- unique number of documents this word occurs.\n\t\t\t\t\t\t\t \n\t\t\t\t\t\t\t\t List<Integer> uniq_doc=map_Word_UniqueDocumentIdHavingIT.get(temp);\n\t\t\t\t\t\t\t\t // if this docID not contained before in list\n\t\t\t\t\t\t\t\t if(!uniq_doc.contains(curr_doc_id)){\n\t\t\t\t\t\t\t\t\t uniq_doc.add(curr_doc_id );\n\t\t\t\t\t\t\t\t\t map_Word_UniqueDocumentIdHavingIT.put(temp, uniq_doc);\n\t\t\t\t\t\t\t\t }\n\t\t\t\t\t\t\t\t \n\t\t\t\t\t\t\t\t //doc-wise frequency\n\t\t\t\t\t\t\t\t if(!map_DocID_wordFrequency.containsKey(curr_doc_id)){\n\t\t\t\t\t\t\t\t\t TreeMap<String,Integer> t2=new TreeMap<String, Integer>();\n\t\t\t\t\t\t\t\t\t t2.put( temp, 1 ) ;\n\t\t\t\t\t\t\t\t\t map_DocID_wordFrequency.put(curr_doc_id, t2);\n\t\t\t\t\t\t\t\t }\n\t\t\t\t\t\t\t\t else{\n\t\t\t\t\t\t\t\t\t TreeMap<String,Integer> t2=map_DocID_wordFrequency.get(curr_doc_id);\n\t\t\t\t\t\t\t\t\t \n\t\t\t\t\t\t\t\t\t if(!t2.containsKey(temp)){\n\t\t\t\t\t\t\t\t\t\t TreeMap<String,Integer> t2_2=map_DocID_wordFrequency.get(curr_doc_id);\n\t\t\t\t\t\t\t\t\t\t t2_2.put( temp, 1 ) ;\n\t\t\t\t\t\t\t\t\t\t map_DocID_wordFrequency.put(curr_doc_id, t2_2);\n\t\t\t\t\t\t\t\t\t }\n\t\t\t\t\t\t\t\t\t else{\n\t\t\t\t\t\t\t\t\t\t TreeMap<String,Integer> t2_2=map_DocID_wordFrequency.get(curr_doc_id);\n\t\t\t\t\t\t\t\t\t\t int sz=t2.get(temp)+1;\n\t\t\t\t\t\t\t\t\t\t t2_2.put( temp, sz ) ;\n\t\t\t\t\t\t\t\t\t\t map_DocID_wordFrequency.put(curr_doc_id, t2_2);\n\t\t\t\t\t\t\t\t\t }\n\t\t\t\t\t\t\t\t\t \n\t\t\t\t\t\t\t\t }\n\t\t\t\t\t\t\t\t \n\t\t\t\t\t\t }\n\t\t\t\t\tcnt++;\n\t\t\t\t }\n\t\t\t\t \n\t\t\t\t if(isSOPprint){\n\t\t\t\t\t System.out.println(\"doc:\"+curr_doc_id+\" token-freq:\"+mapVoc_Freq.size()+\" token-doc.freq:\"+map_Word_UniqueDocumentIdHavingIT.size());\n\t\t\t\t }\n\t\t\t\t //\n\t\t\t\t last_doc_id=curr_doc_id;\n\t\t\t}\n\t\t\tSystem.out.println(\" token-freq:\"+mapVoc_Freq.size()+\" token-doc.freq:\"+map_Word_UniqueDocumentIdHavingIT.size());\n\t\t\tint uniq_word_id=1;\n\t\t\tTreeMap<String, Integer> mapVocabulary_word_wordID= new TreeMap<String, Integer>();\n\t\t\t// create uniq_word_id for each word in vocabulary\n\t\t\tfor(String word:mapVoc_Freq.keySet()){\n\t\t\t\tmapVocabulary_word_wordID.put(word, uniq_word_id);\n\t\t\t\t\n\t\t\t\twriter_voc.append(word+\"!!!\"+uniq_word_id+\"\\n\");\n\t\t\t\twriter_voc.flush();\n\t\t\t\t \n\t\t\t\tuniq_word_id++;\n\t\t\t}\n\t\t\tSystem.out.println(\"step 1: running docid-wordid-tf-IDF\");\n\t\t\t//step 1: calculate tf-idf (DONT COMMENT BELOW)\n\t\t\tfor(int docID:map_DocID_wordFrequency.keySet()){\n\t\t\t\t//System.out.println(\"docID:\"+docID+ \" size:\" +map_DocID_wordFrequency.get(docID).size()); //\t+\" word-freq:\"+map_DocID_wordFrequency.get(docID));\n\t\t\t\twriter_debug.append(\"docID:\"+docID+ \" size:\" +map_DocID_wordFrequency.get(docID).size()+\" word-freq:\"+map_DocID_wordFrequency.get(docID)+\"\\n\");\n\t\t\t\twriter_debug.flush();\n\t\t\t\tdouble tf_idf=0.0;\n\t\t\t\t//Iterate each word in current document\n\t\t\t\tfor(String word:map_DocID_wordFrequency.get(docID).keySet() ){\n\t\t\t\t\t//\n\t\t\t\t\tif(mapVoc_Freq.containsKey(word )){\n\t\t\t\t\t\t\n\t\t\t\t\t\t//System.out.println(\"param1,2:\"+map_DocID_wordFrequency.get(docID).get(word) +\" \"+map_Word_UniqueDocumentIdHavingIT.get(word).size() );\n\t\t\t\t\t\t// tf-idf\n\t\t\t\t\t\ttf_idf=map_DocID_wordFrequency.get(docID).get(word) * Math.log10( map_DocID_wordFrequency.size() / map_Word_UniqueDocumentIdHavingIT.get(word).size() );\n\t\t\t\t\t\t//System.out.println();\n\t\t\t\t\t\twriter.append( docID+\"!!!\"+word+\"!!!\"+tf_idf+\"\\n\");\n\t\t\t\t\t\twriter.flush();\n\t\t\t\t\t\t\n\t\t\t\t\t\twriter_wordID.append( docID+\"!!!\"+mapVocabulary_word_wordID.get(word)+\"!!!\"+tf_idf+\"\\n\");\n\t\t\t\t\t\twriter_wordID.flush();\n\t\t\t\t\t\t\n\t\t\t\t\t\t// \n\t\t\t\t\t\tif(!Stopwords.is_stopword(word.toLowerCase())){\n\t\t\t\t\t\t\twriter_no_stopword.append(docID+\"!!!\"+word+\"!!!\"+tf_idf+\"\\n\");\n\t\t\t\t\t\t\twriter_no_stopword.flush();\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\twriter_wordID_no_stopword.append(docID+\"!!!\"+ mapVocabulary_word_wordID.get(word) +\"!!!\"+tf_idf+\"\\n\");\n\t\t\t\t\t\t\twriter_wordID_no_stopword.flush();\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t\telse{\n\t\t\t\t\t\twriter_debug_2.append( \"(not exist in vocab) word->\"+word+\" for doc_id->\"+docID+\"\\n\");\n\t\t\t\t\t\twriter_debug_2.flush();\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t} //for(int docID:map_DocID_wordFrequency.keySet()){\n\t\t\t\n\t\t\tSystem.out.println(\"step 2: running docid-wordid-frquency\");\n\t\t\t//step 2: (DOC-WORDID AND FREQUENCY)another output - writing <docID!!!wordID!!!frequency>\n\t\t\tfor(int docID:map_DocID_wordFrequency.keySet()){\n\t\t\t\t\n\t\t\t\tSystem.out.println(\"2.docID:\"+docID+ \" size:\" +map_DocID_wordFrequency.get(docID).size()); //\t+\" word-freq:\"+map_DocID_wordFrequency.get(docID));\n\t\t\t\t//writer_debug.append(\"docID:\"+docID+ \" size:\" +map_DocID_wordFrequency.get(docID).size()+\" word-freq:\"+map_DocID_wordFrequency.get(docID)+\"\\n\");\n\t\t\t\t//writer_debug.flush();\n\t\t\t\tint frequency=0;\n\t\t\t\t//Iterate each word in current document\n\t\t\t\tfor(String word:map_DocID_wordFrequency.get(docID).keySet() ){\n\t\t\t\t\t//\n\t\t\t\t\tif(mapVoc_Freq.containsKey(word )){\n\t\t\t\t\t\t\n\t\t\t\t\t\t// System.out.println(\"param1,2:\"+map_DocID_wordFrequency.get(docID).get(word) +\" \"+map_Word_UniqueDocumentIdHavingIT.get(word).size() );\n\t\t\t\t\t\t// frequency\n\t\t\t\t\t\tfrequency=map_DocID_wordFrequency.get(docID).get(word);\n\t\t\t\t\t\t//System.out.println();\n\t\t\t\t\t\twriter2.append( docID+\"!!!\"+word+\"!!!\"+frequency+\"\\n\");\n\t\t\t\t\t\twriter2.flush();\n\t\t\t\t\t\t\n\t\t\t\t\t\twriter2_wordID.append( docID+\"!!!\"+mapVocabulary_word_wordID.get(word)+\"!!!\"+frequency+\"\\n\");\n\t\t\t\t\t\twriter2_wordID.flush();\n\t\t\t\t\t\t \n\t\t\t\t\t\t// \n\t\t\t\t\t\tif(!Stopwords.is_stopword(word.toLowerCase())){\n\t\t\t\t\t\t\twriter2_no_stopword.append(docID+\"!!!\"+word+\"!!!\"+frequency+\"\\n\");\n\t\t\t\t\t\t\twriter2_no_stopword.flush();\n\t\t\t\t\t\t\t//\n\t\t\t\t\t\t\twriter2_wordID_no_stopword.append(docID+\"!!!\"+ mapVocabulary_word_wordID.get(word) +\"!!!\"+frequency+\"\\n\");\n\t\t\t\t\t\t\twriter2_wordID_no_stopword.flush();\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t\telse{\n\t\t\t\t\t\twriter_debug_2.append( \"(not exist in vocab) word->\"+word+\" for doc_id->\"+docID+\"\\n\");\n\t\t\t\t\t\twriter_debug_2.flush();\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t} //for(int docID:map_DocID_wordFrequency.keySet()){\n\n\t\t\tSystem.out.println(\"********************************************\");\n\t\t\tSystem.out.println(\"File holding the not found words in vocabulary: \"+\"outFile+\\\"_DEBUG_2.txt\\\"\");\n\t\t\tSystem.out.println(\"Doc-wise word freq: \"+\"outFile+\\\"_DEBUG.txt\\\"\");\n\t\t\tSystem.out.println(\"******Below files are docId-wordID-tfIDF\");\n\t\t\tSystem.out.println(\"with Word->\"+outFile);\n\t\t\tSystem.out.println(\"with Word(no stopword)->\"+outFile+\"_noStopWord.txt\");\n\t\t\tSystem.out.println(\"with WordID->\"+outFile+\"_WORD_ID.txt\");\n\t\t\tSystem.out.println(\"with WordID(no stopword)->\"+outFile+\"_noStopWord_WORD_ID.txt\");\n\t\t\tSystem.out.println(\"VOC FILE ->\"+baseFolder+\"unique_word_vocabulary.txt\");\n\t\t\t//**********/\n\t\t\tSystem.out.println(\"***********Below files are docId-wordID-frequency (file ends with \\\"format2.txt\\\"\");\n\t\t\tSystem.out.println( \"\"+outFile+\"_docWordID_freq2.txt\");\n\t\t\tSystem.out.println( \"\"+outFile+\"_noStopWord2.txt\");\n\t\t\tSystem.out.println( \"\"+outFile+\"_WORD_ID2.txt\");\n\t\t\tSystem.out.println( \"\"+outFile+\"_noStopWord_WORD_ID2.txt\");\n\t\t\tSystem.out.println( \"\"+outFile+\"_Word_stemmedWord2.txt\");\n\t\t\t \n\t\t\tmapOut.put(-99, outFile+\"_noStopWord_WORD_ID.txt\");\n\t\t\t//maximum word id\n\t\t\tmapOut.put(1, String.valueOf( uniq_word_id) );\n\t\t}\n\t\tcatch(Exception e){\n\t\t\te.printStackTrace();\n\t\t}\n\t\treturn mapOut;\n\t}","public static void DocumentFrequencies() throws FileNotFoundException {\n for (Entry<String, List<Integer>> entry : dictionary.entrySet()) {\n List<Integer> termfrequency = new ArrayList<>();\n\n termfrequency = entry.getValue();\t// getting each word's termfrequency list\n int i = 0;\n termfrequency.add(0); \t\t\t//maintaining documentfrequency at the 57th index\n Integer documentFrequency = termfrequency.get(totaldocument+1);\n while(i<56) { //iterate 0 to 55 all speeches term frequency\n if(termfrequency.get(i)>0) {\t\t//increment document frequency of that word if termfrequency is greater than 0.0\n documentFrequency++;\t\t\t//increment document frequency\n }\n i++;\t\t//increment index\n }\n termfrequency.set(57, documentFrequency);\t//re-set the documentfrequency and save the current maintained document frequency from 0 to calculated value\n dictionary.put(entry.getKey(), termfrequency);\t\t// place the incremented final value of that word back to the same list in dictionary hashmap\n }\n //save();\n }","public void createIDMap()\n {\n IDMap = new HashMap<>();\n idFile.open(\"idpassword.txt\");\n String line = idFile.getNextLine();\n\n\n\n while(line!=null) {\n String[] fields = line.split(\",\");\n IDMap.put(fields[0], fields[1]);\n\n line = idFile.getNextLine();\n\n }\n\n }","public void indexDocument(String documentName, ArrayList<String> documentTokens) {\n for (String token : documentTokens) {\n if (!this.index.containsKey(token)) {\n // Create a key with that token\n this.index.put(token, new HashMap<>());\n }\n\n // Get the HashMap associated with that term\n HashMap<String, Integer> term = this.index.get(token);\n\n // Check if term has a posting for the document\n if (term.containsKey(documentName)) {\n // Increase its occurrence by 1\n int occurrences = term.get(documentName);\n term.put(documentName, ++occurrences);\n } else {\n // Create a new posting for the term\n term.put(documentName, 1);\n }\n }\n }","public void buildWordFileMap(){\n hashWords.clear();\n DirectoryResource dr = new DirectoryResource();\n for (File f : dr.selectedFiles()){ //for all the files selected make the hashWords hashmap\n addWordsFromFile(f);\n }\n \n }","private void createTokenIndex(){\n\t\tLinkedList<String> tokens = new LinkedList<>(tokenDict.keySet());\n\t\tArrayList<ArrayList<Integer>> vals = new ArrayList<>(tokenDict.values());\n\t\tint k = 8;\n\n\t\tKFront kf = new KFront(true);\n\t\tkf.createKFront(k, tokens);\n\n\t\tTokensIndex tIdx = new TokensIndex(k, this.dir);\n\t\ttIdx.insertData(kf.getTable(), vals, kf.getConcatString());\n\n\t\tsaveToDir(TOKEN_INDEX_FILE, tIdx);\n\t}","private static Positional_inverted_index posindexCorpus(DocumentCorpus corpus) throws ClassNotFoundException, InstantiationException, IllegalAccessException, FileNotFoundException, IOException {\n\n NewTokenProcessor processor = new NewTokenProcessor();\n Iterable<Document> docs = corpus.getDocuments(); //call registerFileDocumentFactory first?\n\n List<Double> Doc_length = new ArrayList<>();\n Positional_inverted_index index = new Positional_inverted_index();\n\n double token_count = 0;\n\n // Iterate through the documents, and:\n for (Document d : docs) {\n //File f = new File(path + \"\\\\\" + d.getTitle());\n File f = new File(path + \"\\\\\" + d.getFileName().toString());\n double Filesize = f.length();\n //edited by bhavya\n double doc_weight = 0; //first entry in docweights.bin\n double doc_tokens = 0;\n double doc_length = 0;\n HashMap<String, Integer> tftd = new HashMap<>();\n // Tokenize the document's content by constructing an EnglishTokenStream around the document's content.\n Reader reader = d.getContent();\n EnglishTokenStream stream = new EnglishTokenStream(reader); //can access tokens through this stream\n N++;\n // Iterate through the tokens in the document, processing them using a BasicTokenProcessor,\n //\t\tand adding them to the HashSet vocabulary.\n Iterable<String> tokens = stream.getTokens();\n int i = 0;\n\n for (String token : tokens) {\n\n //adding token in index\n List<String> word = new ArrayList<String>();\n word = processor.processToken(token);\n //System.out.println(word.get(0));\n if (word.get(0).matches(\"\")) {\n continue;\n } else {\n\n index.addTerm(word.get(0), i, d.getId());\n\n }\n i = i + 1;\n\n //we check if token already exists in hashmap or not. \n //if it exists, increase its freq by 1 else make a new entry.\n if (tftd.containsKey(word.get(0))) {\n doc_tokens++;\n int count = tftd.get(word.get(0));\n tftd.replace(word.get(0), count + 1);\n } else {\n doc_tokens++;\n// token_count++; //gives total number of tokens.\n tftd.put(word.get(0), 1);\n }\n\n }\n double length = 0;\n double wdt = 0;\n\n double total_tftd = 0;\n for (Map.Entry<String, Integer> entry : tftd.entrySet()) {\n\n wdt = 1 + log(entry.getValue());\n\n length = length + pow(wdt, 2);\n total_tftd = total_tftd + entry.getValue();\n }\n token_count = token_count + doc_tokens;\n doc_weight = pow(length, 0.5);\n double avg_tftd = total_tftd / (double) tftd.size();\n\n Doc_length.add(doc_weight);\n Doc_length.add(avg_tftd);\n Doc_length.add(doc_tokens);\n Doc_length.add(Filesize);\n }\n Doc_length.add(token_count / N);\n\n DiskIndexWriter d = new DiskIndexWriter();\n d.write_doc(path, Doc_length);\n\n return index;\n }","static void idlize() throws IOException {\r\n\t\t/**give mid who has name a id, for other mid, keep using mid to identify them*/\r\n\t\t//\t\tHashMap<String, Integer> namedmid2name = new HashMap<String, Integer>(20000000);\r\n\t\t//\t\tHashMap<String, Integer> relationname2id = new HashMap<String, Integer>(1000000);\r\n\t\t//\t\tDelimitedWriter dw = new DelimitedWriter(Main.dir + \"/visible_idize\");\r\n\t\t//\t\tDelimitedWriter dw_debug = new DelimitedWriter(Main.dir + \"/visible_debug\");\r\n\t\t//\t\t{\r\n\t\t//\t\t\tDelimitedReader dr = new DelimitedReader(Main.file_fbenglishname);\r\n\t\t//\t\t\tString[] l;\r\n\t\t//\t\t\twhile ((l = dr.read()) != null) {\r\n\t\t//\t\t\t\tnamedmid2name.put(l[0], namedmid2name.size());\r\n\t\t//\t\t\t}\r\n\t\t//\t\t\tD.p(\"load mid2name finished\");\r\n\t\t//\t\t\tdr.close();\r\n\t\t//\t\t}\r\n\t\t//\t\t{\r\n\t\t//\t\t\tDelimitedReader dr = new DelimitedReader(Main.file_visible_str);\r\n\t\t//\t\t\tString[] l;\r\n\t\t//\t\t\twhile ((l = dr.read()) != null) {\r\n\t\t//\t\t\t\tString mid = l[0];\r\n\t\t//\t\t\t\tInteger gid = namedmid2name.get(mid);\r\n\t\t//\t\t\t\tif (gid == null) {\r\n\t\t//\t\t\t\t\tdw_debug.write(l);\r\n\t\t//\t\t\t\t\tcontinue;\r\n\t\t//\t\t\t\t}\r\n\t\t//\t\t\t\tString relationname = l[2];\r\n\t\t//\t\t\t\tif (!relationname2id.containsKey(relationname)) {\r\n\t\t//\t\t\t\t\trelationname2id.put(relationname, relationname2id.size());\r\n\t\t//\t\t\t\t}\r\n\t\t//\t\t\t\tint relid = relationname2id.get(relationname);\r\n\t\t//\t\t\t\tdw.write(l[1], gid, relid, l[3]);\r\n\t\t//\t\t\t}\r\n\t\t//\t\t\tdr.close();\r\n\t\t//\t\t}\r\n\t\t//\t\t{\r\n\t\t//\t\t\tDelimitedReader dr = new DelimitedReader(Main.file_visible_str);\r\n\t\t//\t\t\tString[] l;\r\n\t\t//\t\t\twhile ((l = dr.read()) != null) {\r\n\t\t//\t\t\t\tString mid1 = l[0];\r\n\t\t//\t\t\t\tString mid2 = l[3];\r\n\t\t//\t\t\t\tInteger gid1 = namedmid2name.get(mid1);\r\n\t\t//\t\t\t\tInteger gid2 = namedmid2name.get(mid2);\r\n\t\t//\t\t\t\tif (gid1 == null || gid2 == null) {\r\n\t\t//\t\t\t\t\tdw_debug.write(l);\r\n\t\t//\t\t\t\t\tcontinue;\r\n\t\t//\t\t\t\t}\r\n\t\t//\t\t\t\tString relationname = l[2];\r\n\t\t//\t\t\t\tif (!relationname2id.containsKey(relationname)) {\r\n\t\t//\t\t\t\t\trelationname2id.put(relationname, relationname2id.size());\r\n\t\t//\t\t\t\t}\r\n\t\t//\t\t\t\tint relid = relationname2id.get(relationname);\r\n\t\t//\t\t\t\tdw.write(l[1], gid1, relid, gid2, l[3]);\r\n\t\t//\t\t\t}\r\n\t\t//\t\t\tdr.close();\r\n\t\t//\t\t}\r\n\t\t//\t\tdw.close();\r\n\t\t//\t\t{\r\n\t\t//\t\t\tDelimitedWriter dwrel = new DelimitedWriter(Main.dir + \"/visible_relations.temp\");\r\n\t\t//\t\t\tfor (Entry<String, Integer> e : relationname2id.entrySet()) {\r\n\t\t//\t\t\t\tdwrel.write(e.getValue(), e.getKey());\r\n\t\t//\t\t\t}\r\n\t\t//\t\t\tdwrel.close();\r\n\t\t//\t\t\tSort.sort(Main.dir + \"/visible_relations.temp\", Main.dir + \"/visible_relations\", Main.dir,\r\n\t\t//\t\t\t\t\tnew Comparator<String[]>() {\r\n\t\t//\t\t\t\t\t\t@Override\r\n\t\t//\t\t\t\t\t\tpublic int compare(String[] o1, String[] o2) {\r\n\t\t//\t\t\t\t\t\t\t// TODO Auto-generated method stub\r\n\t\t//\t\t\t\t\t\t\treturn Integer.parseInt(o1[0]) - Integer.parseInt(o2[0]);\r\n\t\t//\t\t\t\t\t\t}\r\n\t\t//\r\n\t\t//\t\t\t\t\t});\r\n\t\t//\t\t}\r\n\t\t//\t\t{\r\n\t\t//\t\t\tDelimitedWriter dwmid = new DelimitedWriter(Main.dir + \"/visible_mid2gid.temp\");\r\n\t\t//\t\t\tfor (Entry<String, Integer> e : namedmid2name.entrySet()) {\r\n\t\t//\t\t\t\tdwmid.write(e.getValue(), e.getKey());\r\n\t\t//\t\t\t}\r\n\t\t//\t\t\tdwmid.close();\r\n\t\t//\t\t\tSort.sort(Main.dir + \"/visible_mid2gid.temp\", Main.dir + \"/visible_mid2gid\", Main.dir,\r\n\t\t//\t\t\t\t\tnew Comparator<String[]>() {\r\n\t\t//\t\t\t\t\t\t@Override\r\n\t\t//\t\t\t\t\t\tpublic int compare(String[] o1, String[] o2) {\r\n\t\t//\t\t\t\t\t\t\t// TODO Auto-generated method stub\r\n\t\t//\t\t\t\t\t\t\treturn Integer.parseInt(o1[0]) - Integer.parseInt(o2[0]);\r\n\t\t//\t\t\t\t\t\t}\r\n\t\t//\r\n\t\t//\t\t\t\t\t});\r\n\t\t//\t\t}\r\n\t}","public void map()\n\t{\n\t // key is the documentId\n\t\t// value is the url\n\t\t//fetch the document using the documentId\n\t\t\n\t}","private void saveMap() {\r\n new Thread(() -> {\r\n try {\r\n FileOutputStream f = new FileOutputStream(this.save_file);\r\n ObjectOutputStream S = new ObjectOutputStream(f);\r\n S.writeObject(this.music_map);\r\n S.close();\r\n f.close();\r\n if (!this.save_file.setLastModified(this.music_root.lastModified())) {\r\n throw new IllegalStateException(\"Impossibile aggiornare il file dizionario\");\r\n }\r\n } catch (IOException e) {\r\n e.printStackTrace();\r\n }\r\n }).start();\r\n }","private static void collectVariables(Document document){\n //collecting all the nodes inside a list\n nodeList = document.selectNodes(NOTES);\n\n //initialising the lists\n entriesList = new ArrayList<>();\n locationsList = new ArrayList<>();\n attachmentList = new ArrayList<>();\n tagsForEntryList = new ArrayList<>();\n\n //hashSet for handling the duplicate fileNames\n fileNameSet = new LinkedHashSet<>();\n\n //linkedHashMap for storing the uid for each tag\n uidForEachTag = new LinkedHashMap<>();\n uidForEachLocation = new LinkedHashMap<>();\n\n //id set for storing unique location id\n locationsIdSet = new LinkedHashSet<>();\n\n Tags tags;\n Location location;\n Entry entry;\n Attachment attachment;\n\n byte[] decoded = null;\n\n //looping through the list\n for(Node node : nodeList){\n\n String title = \"\";\n String parsedHtml = \"\";\n String formattedDate = \"\";\n String location_uid = \"\";\n String mime = \"\";\n String fileName = \"\";\n String attachment_uid = null;\n String entry_uid = \"\";\n String type = \"photo\";\n String baseEncoding;\n String tag_uid = \"\";\n\n //get all tags including duplicates\n if( node.selectSingleNode(TAG) !=null) {\n List<Node> evernote_tags = node.selectNodes(TAG);\n for (Node evenote_tag : evernote_tags) {\n //generate unique id for the tag and map it.\n //if the name id pair does not exist\n if(!uidForEachTag.containsKey(evenote_tag.getText())) {\n uidForEachTag.put(evenote_tag.getText(), Entry.generateRandomUid());\n }\n //create new diaro.Tags Object\n tags = new Tags(uidForEachTag.get(evenote_tag.getText()),evenote_tag.getText());\n tagsForEntryList.add(tags);\n }\n }\n\n //get all Locations\n // using diaro.Entry.concatLatLng to add title as {<Latitude></Latitude>,<Longitude></Longitude>}\n if( node.selectSingleNode(LATITUDE) != null && node.selectSingleNode(LONGITUDE) != null) {\n String latitude = String.format(\"%.5f\",Double.parseDouble(node.selectSingleNode(LATITUDE).getText()));\n String longitude = String.format(\"%.5f\",Double.parseDouble(node.selectSingleNode(LONGITUDE).getText()));\n String location_title = (ImportUtils.concatLatLng(latitude, longitude));\n\n //mapping every uid to the address\n if(!uidForEachLocation.containsKey(location_title)) {\n uidForEachLocation.put(location_title, Entry.generateRandomUid());\n }\n location_uid = uidForEachLocation.get(location_title);\n location = new Location(location_uid,latitude,longitude,location_title, location_title, DEFAULT_ZOOM);\n if (!locationsIdSet.contains(location.location_uid)) {\n locationsList.add(location);\n locationsIdSet.add(location.location_uid);\n }\n }\n\n //get all Entries\n if(node.selectSingleNode(TITLE) != null ){\n title = node.selectSingleNode(TITLE).getText();\n }\n if(node.selectSingleNode(CONTENT) != null ){\n String text = node.selectSingleNode(CONTENT).getText();\n // using Jsoup to parseXml HTML inside Content\n parsedHtml = Jsoup.parse(text).text();\n }\n if(node.selectSingleNode(CREATED) != null){\n String date = node.selectSingleNode(CREATED).getText().substring(0, 8);\n String month = date.substring(4, 6);\n String day = date.substring(6, 8);\n String year = date.substring(2, 4);\n formattedDate = String.format(\"%s/%s/%s\", month, day, year);\n }\n\n //get all the tags\n //append all the string stringBuilder\n if(tagsForEntryList.size() != 0){\n for(Tags tag : tagsForEntryList) {\n tag_uid = tag_uid + (\",\") + (String.join(\",\", tag.tagsId));\n }\n tag_uid = tag_uid + (\",\");\n System.out.println(tag_uid);\n\n }\n entry = new Entry();\n entry.setUid(Entry.generateRandomUid());\n entry.setTz_offset(OFFSET);\n entry.setDate(formattedDate);\n entry.setText(parsedHtml);\n entry.setTitle(title);\n entry.setFolder_uid(FOLDER_UID);\n entry.setLocation_uid(location_uid);\n entry.setTags(tag_uid);\n //clear the list\n //clear the tag_uid variable for next loop\n tagsForEntryList.clear();\n tag_uid = \"\";\n //add entry in the list\n entriesList.add(entry);\n\n //get all the attachments\n if (node.selectSingleNode(RESOURCE) != null) {\n List<Node> attachmentsForEachEntry = node.selectNodes(RESOURCE);\n //loop through all the attachments for a single note/entry\n for (Node attachmentForeach : attachmentsForEachEntry) {\n try {\n mime = attachmentForeach.selectSingleNode(MIME).getText();\n\n }catch( NullPointerException e){\n e.printStackTrace();\n }\n // check for a valid attachment\n if(checkForImageMime(mime)) {\n try {\n fileName = attachmentForeach.selectSingleNode(RESOURCE_ATTRIBUTE_FILENAME).getText();\n attachment_uid = Entry.generateRandomUid();\n entry_uid = entry.uid;\n baseEncoding = attachmentForeach.selectSingleNode(DATA).getText();\n //----- please do a check for valid Base64--\n decoded = Base64.getMimeDecoder().decode(baseEncoding);\n // assign primary_photo uid to entry\n entry.primary_photo_uid = attachment_uid;\n }catch(IllegalArgumentException | NullPointerException e){\n e.printStackTrace();\n }\n // check if the fileName already exists\n // if true generate a new fileName to prevent duplicates\n if(fileNameSet.add(fileName)){\n fileNameSet.add(fileName);\n attachment = new Attachment(attachment_uid, entry_uid, type,fileName,decoded);\n }else{\n String newFileName = ImportUtils.generateNewFileName(fileName);\n fileNameSet.add(newFileName);\n attachment = new Attachment(attachment_uid, entry_uid, type,newFileName,decoded);\n }\n attachmentList.add(attachment);\n }\n }\n }\n }\n\n }","private HashMap<String, HashSet<String>> convertIndexToMap(IndexReader reader) throws IOException{\n\t\t HashMap<String, HashSet<String>> hmap = new HashMap<String, HashSet<String>>();\n\t\t HashSet<String> docIdSet;\n\t\t \n\t\t for(int i=0; i<reader.numDocs(); i++){\n\t\t\t Fields termVect = reader.getTermVectors(i);\n\n\t\t\t if(termVect == null)\n\t\t\t\t continue;\n\t\t\t \n\t for (String field : termVect) {\n\t \t \n\t Terms terms = termVect.terms(field);\n\t TermsEnum termsEnum = terms.iterator();\n\t Document doc = reader.document(i);\n\t \n\t while(termsEnum.next() != null){\n\t \t BytesRef term = termsEnum.term();\n\t \t String strTerm = term.utf8ToString();\n\t \t \n\t \t if (hmap.containsKey(strTerm)){\n\t \t\t docIdSet = hmap.get(strTerm);\n\t \t\t docIdSet.add(doc.get(\"url\"));\n\t \t } else{\n\t \t\t docIdSet = new HashSet<String>();\n\t \t\t docIdSet.add(doc.get(\"url\"));\n\t \t\t hmap.put(strTerm, docIdSet);\n\t \t }\n\t }\n\t }\n\t\t }\n\t\t \n\t\t return hmap;\n\t}","public void IndexADocument(String docno, String content) throws IOException {\n\t\tthis.idWriter.write(docID+\":\"+docno);\n\t\tthis.idWriter.newLine();\n\t\tthis.idWriter.flush();\n\t\tString[] words = content.split(\" \");\n\t\tHashMap<String,Integer> count = new HashMap<>();\n\t\tfor(String s:words){\n\t\t\tcount.put(s,count.getOrDefault(s,0)+1);\n\t\t}\n\t\tfor(String key: count.keySet()){\n\t\t\tif(this.map.containsKey(key)){\n\t\t\t\tthis.map.get(key).append(docID).append(\":\").append(count.get(key)).append(\",\");\n\t\t\t}else {\n\t\t\t\tStringBuilder sb = new StringBuilder();\n\t\t\t\tthis.map.put(key, sb.append(docID).append(\":\").append(count.get(key)).append(\",\"));\n\t\t\t}\n\t\t}\n\t\tdocID++;\n\t}","public void writeDocumentForA(String filename, String path) throws Exception\r\n\t{\n\t\tFile folder = new File(path);\r\n\t\tFile[] listOfFiles = folder.listFiles();\r\n\t \r\n\t \r\n\t \tFileWriter fwText;\r\n\t\tBufferedWriter bwText;\r\n\t\t\r\n\t\tfwText = new FileWriter(\"C:/Users/jipeng/Desktop/Qiang/updateSum/TAC2008/Parag/\"+ filename+\"/\" +\"A.txt\");\r\n\t\tbwText = new BufferedWriter(fwText);\r\n\t\t\r\n\t \tfor ( int i=0; i<listOfFiles.length; i++) {\r\n\t \t\t//String name = listOfFiles[i].getName();\r\n\t\t\t\r\n\t\t\t\r\n\t\t\tString text = readText(listOfFiles[i].getAbsolutePath());\r\n\t\t\t\r\n\t\t\tFileWriter fwWI = new FileWriter(\"C:/pun.txt\");\r\n\t\t\tBufferedWriter bwWI = new BufferedWriter(fwWI);\r\n\t\t\t\r\n\t\t\tbwWI.write(text);\r\n\t\t\t\r\n\t\t\tbwWI.close();\r\n\t\t\tfwWI.close();\r\n\t\t\t\r\n\t\t\t\r\n\t\t\tList<List<HasWord>> sentences = MaxentTagger.tokenizeText(new BufferedReader(new FileReader(\"C:/pun.txt\")));\r\n\t\t\t\r\n\t\t\t//System.out.println(text);\r\n\t\t\tArrayList<Integer> textList = new ArrayList<Integer>();\r\n\t\t\t\r\n\t\t\tfor (List<HasWord> sentence : sentences)\r\n\t\t\t {\r\n\t\t\t ArrayList<TaggedWord> tSentence = tagger.tagSentence(sentence);\r\n\t\t\t \r\n\t\t\t for(int j=0; j<tSentence.size(); j++)\r\n\t\t\t {\r\n\t\t\t \t \tString word = tSentence.get(j).value();\r\n\t\t\t \t \t\r\n\t\t\t \t \tString token = word.toLowerCase();\r\n\t\t\t \t \r\n\t\t\t \t \tif(token.length()>2 )\r\n\t\t\t\t \t{\r\n\t\t\t \t\t\t if (!m_EnStopwords.isStopword(token)) \r\n\t\t\t \t\t\t {\r\n\t\t\t \t\t\t\t\r\n\t\t\t\t\t\t\t\t if (word2IdHash.get(token)==null)\r\n\t\t\t\t\t\t\t\t {\r\n\t\t\t\t\t\t\t\t\t textList.add(id);\r\n\t\t\t\t\t\t\t\t\t // bwText.write(String.valueOf(id)+ \" \");\r\n\t\t\t\t\t\t\t\t\t\r\n\t\t\t\t\t\t\t\t\t word2IdHash.put(token, id);\r\n\t\t\t\t\t\t\t\t\t \r\n\t\t\t\t\t\t\t\t\t allWordsArr.add(token);\r\n\t\t\t\t\t\t\t\t\t \r\n\t\t\t\t\t\t\t\t\t id++;\r\n\t\t\t\t\t\t\t\t } else\r\n\t\t\t\t\t\t\t\t {\r\n\t\t\t\t\t\t\t\t \tint wid=(Integer)word2IdHash.get(token);\r\n\t\t\t\t\t\t\t\t \tif(!textList.contains(wid))\r\n\t\t\t\t\t\t\t\t \t\ttextList.add(wid);\r\n\t\t\t\t\t\t\t\t \t//bwText.write(String.valueOf(wid)+ \" \");\r\n\t\t\t\t\t\t\t\t }\r\n\t\t\t\t\t\t\t\t \t\r\n\t\t\t\t\t\t\t\t }\r\n\t\t\t\t\t\t\t\t \r\n\t\t\t\t\t \t}\r\n\t\t\t \t }\r\n\t\t\t }\r\n\t\t\tCollections.sort(textList);\r\n\t\t \r\n\t\t\tString text2 = valueFromList(textList);\r\n\t\t bwText.write(text2);\r\n\t\t //System.out.println(text2);\r\n\t\t bwText.newLine();\r\n\t\t textList.clear();\r\n\t\t \r\n\t \t}\r\n\t \tbwText.close();\r\n\t fwText.close();\r\n\t}","public static void pageRankmain() {\n\t\t\t\n\t\t\tstopWordStore();\n\t\t\t//File[] file_read= dir.listFiles();\n\t\t\t//textProcessor(file_read);// Will be called from LinkCrawler\n\t\t\t//queryProcess();\n\t\t\t//System.out.println(\"docsave \"+ docsave);\n\t\t\t/*for ( Map.Entry<String, ArrayList<String>> entry : docsave.entrySet()) {\n\t\t\t String key = entry.getKey();\n\t\t\t List<String> values = entry.getValue();\n\t\t\t System.out.print(\"Key = \" + key);\n\t\t\t System.out.println(\" , Values = \"+ values);\n\t\t\t}*/\n\t\t\t//########## RESPOINSIBLE FOR CREATING INVERTED INDEX OF TERMS ##########\n\t\t\tfor(int i=0;i<vocabulary.size();i++) {\n\t\t\t\tint count=1;\n\t\t\t\tMap<String, Integer> nestMap = new HashMap<String, Integer>();\n\t\t\t\tfor ( Map.Entry<String, ArrayList<String>> entry : docsave.entrySet()) {\n\t\t\t\t String keyMain = entry.getKey();\n\t\t\t\t List<String> values = entry.getValue();\n\t\t\t\t if(values.contains(vocabulary.get(i)))\n\t\t\t\t \t{\n\t\t\t\t \tentryDf.put(vocabulary.get(i), count);//entryDf stores documents frequency of vocabulary word \\\\it increase the count value for specific key\n\t\t\t\t \tcount++;\n\t\t\t\t \t}\n\t\t\t\t \n\t\t\t\t nestMap.put(keyMain, Collections.frequency(values,vocabulary.get(i)));\n\t\t\t \t\n\t\t\t \t//System.out.println(\"VOC \"+ vocabulary.get(i)+ \" KeyMain \" +keyMain+ \" \"+ Collections.frequency(values,vocabulary.get(i)));\n\t\t\t\t\t}\n\t\t\t\t\ttfList.put(vocabulary.get(i), nestMap);\n\t\t\t}\n\t\t\t//########## RESPOINSIBLE FOR CREATING A MAP \"storeIdf\" TO STORE IDF VALUES OF TERMS ##########\n\t\t\tfor ( Map.Entry<String, Integer> endf : entryDf.entrySet()) {\n\t\t\t\tString keydf = endf.getKey();\n\t\t\t\tint valdf = endf.getValue();\n\t\t\t\t//System.out.print(\"Key = \" + \"'\"+keydf+ \"'\");\n\t\t\t //System.out.print(\" , Values = \"+ valdf);\n\t\t\t double Hudai = (double) (docsave.size())/valdf;\n\t\t\t //System.out.println(\"docsave size \"+docsave.size()+ \" valdf \"+ valdf + \" Hudai \"+ Hudai+ \" log Value1 \"+ Math.log(Hudai)+ \" log Value2 \"+ Math.log(2));\n\t\t\t double idf= Math.log(Hudai)/Math.log(2);\n\t\t\t storeIdf.put(keydf, idf);\n\t\t\t //System.out.print(\" idf-> \"+ idf);\n\t\t\t //System.out.println();\n\t\t\t} \n\t\t\t\n\t\t\t//############ Just for Printing ##########NO WORK HERE########\n\t\t\tfor (Map.Entry<String, Map<String, Integer>> tokTf : tfList.entrySet()) {\n\t\t\t\tString keyTf = tokTf.getKey();\n\t\t\t\tMap<String, Integer> valTF = tokTf.getValue();\n\t\t\t\tSystem.out.println(\"Inverted Indexing by Key Word = \" + \"'\"+keyTf+ \"'\");\n\t\t\t\tfor (Map.Entry<String, Integer> nesTf : valTF.entrySet()) {\n\t\t\t\t\tString keyTF = nesTf.getKey();\n\t\t\t\t\tInteger valTf = nesTf.getValue();\n\t\t\t\t\tSystem.out.print(\" Document Consists This Key Word = \" + \"'\"+ keyTF+ \"'\");\n\t\t\t\t\tSystem.out.println(\" , Term Frequencies in This Doc = \"+ valTf);\n\t\t\t\t} \n\t\t\t}\n\t\t\t//########### FOR CALCULATING DOCUMENT LENTH #############//\n\t\t\tfor ( Map.Entry<String, ArrayList<String>> entry_new : docsave.entrySet()) // Iterating Number of Documents\n\t\t\t{\n\t\t\t\tString keyMain_new = entry_new.getKey();\n\t\t\t\t//int countStop=0;\n\t\t\t\tdouble sum=0;\n\t\t\t\t for(Map.Entry<String, Map<String, Integer>> tokTf_new : tfList.entrySet()) // Iterating through the vocabulary\n\t\t\t\t { \n\t\t\t\t\t Map<String, Integer> valTF_new = tokTf_new.getValue();\n\t\t\t\t\t for (Map.Entry<String, Integer> nesTf_new : valTF_new.entrySet()) // Iterating Through the Documents\n\t\t\t\t\t {\n\t\t\t\t\t\t if(keyMain_new.equals(nesTf_new.getKey())) // Only doc name EQUAL with docsave name can enter here\n\t\t\t\t\t\t {\n\t\t\t\t\t\t\t double val = nesTf_new.getValue()* (Double) storeIdf.get(tokTf_new.getKey());\n\t\t\t\t\t\t\t sum = sum+ Math.pow(val, 2);\n\t\t\t\t\t\t }\n\t\t\t\t\t }\n\t\t\t\t\t \n\t\t\t\t\t //countStop++;\n\t\t\t\t }\n\t\t\t\t docLength.put(keyMain_new, Math.sqrt(sum));\n\t\t\t\t sum=0;\n\t\t\t}\n\t\t\t\n\t\t\t\n\t\t\tSystem.out.println(\"Document Length \"+ docLength);\n\t\t\t//System.out.println(\"tfList \"+tfList);\n\t\t\t\n\t\t\t //########### FOR CALCULATING QUERY LENTH #############///\n\t\t\t\tdouble qrySum=0;\n\t\t\t\t for(String qryTerm: queryList) // Iterating through the vocabulary\n\t\t\t\t {\n\t\t\t\t\t//entryQf.put(qryTerm, Collections.frequency(queryList,qryTerm));// VUl ase\n\t\t\t\t\t \n\t\t\t\t\t\t if(storeIdf.get(qryTerm) != null) \n\t\t\t\t\t\t {\n\t\t\t\t\t\t\t entryQf.put(qryTerm, Collections.frequency(queryList,qryTerm));\n\t\t\t\t\t\t\t double val = entryQf.get(qryTerm)* (Double) storeIdf.get(qryTerm);\n\t\t\t\t\t\t\t qrySum = qrySum+ Math.pow(val, 2);\n\t\t\t\t\t\t }\n\t\t\t\t\t System.out.println(qryTerm+\" \"+entryQf.get(qryTerm)+ \" \"+ (Double) storeIdf.get(qryTerm));\n\t\t\t\t }\n\t\t\t\t qrySum=Math.sqrt(qrySum);\n\t\t\t\t System.out.println(\"qrySum \" + qrySum);\n\t\t\t\t \n\t\t\t\t//########### FOR CALCULATING COSINE SIMILARITY #############///\n\t\t\t\t for ( Map.Entry<String, ArrayList<String>> entry_dotP : docsave.entrySet()) // Iterating Number of Documents\n\t\t\t\t\t{\n\t\t\t\t\t\tdouble sumProduct=0;\n\t\t\t\t\t\tdouble productTfIdf=0;\n\t\t\t\t\t\tString keyMain_new = entry_dotP.getKey(); //Geting Doc Name\n\t\t\t\t\t\t for(Map.Entry<String, Integer> qryTermItr : entryQf.entrySet()) // Iterating through the vocabulary\n\t\t\t\t\t\t {\n\t\t\t\t\t\t\t \n\t\t\t\t\t\t\t Map<String, Integer> matchTerm = tfList.get(qryTermItr.getKey()); // Getting a map of doc Names by a Query Term as value of tfList\n\n\t\t\t\t\t\t\t\t if(matchTerm.containsKey(keyMain_new)) // Only doc name EQUAL with docsave name can enter here\n\t\t\t\t\t\t\t\t {\n\t\t\t\t\t\t\t\t\t //System.out.println(\"Test \"+ matchTerm.get(keyMain_new) +\" keyMain_new \" + keyMain_new);\n\t\t\t\t\t\t\t\t\t double docTfIdf= matchTerm.get(keyMain_new) * storeIdf.get(qryTermItr.getKey());\n\t\t\t\t\t\t\t\t\t double qryTfIdf= qryTermItr.getValue() * storeIdf.get(qryTermItr.getKey());\n\t\t\t\t\t\t\t\t\t productTfIdf = docTfIdf * qryTfIdf;\n\t\t\t\t\t\t\t\t }\n\t\t\t\t\t\t\t \n\t\t\t\t\t\t\t sumProduct= sumProduct+productTfIdf;\n\t\t\t\t\t\t\t //System.out.println(\"productTfIdf \"+productTfIdf+\" sumProduct \"+ sumProduct);\n\t\t\t\t\t\t\t productTfIdf=0;\n\t\t\t\t\t\t }\n\t\t\t\t\t\t cosineProd.put(entry_dotP.getKey(), sumProduct/(docLength.get(entry_dotP.getKey())*qrySum));\n\t\t\t\t\t\t sumProduct=0;\n\t\t\t\t\t\t //System.out.println(entry_dotP.getKey()+ \" \" + docLength.get(entry_dotP.getKey()));\n\t\t\t\t\t}\n\t\t\t\t System.out.println(\"cosineProd \"+ cosineProd);\n\t\t\t\t \n\t\t\t\t System.out.println(\"Number of Top Pages you want to see\");\n\t\t\t\t int topRank = Integer.parseInt(scan.nextLine());\n\t\t\t\t Map<String, Double> result = cosineProd.entrySet().stream()\n\t\t\t .sorted(Map.Entry.comparingByValue(Comparator.reverseOrder())).limit(topRank)\n\t\t\t .collect(Collectors.toMap(Map.Entry::getKey, Map.Entry::getValue,\n\t\t\t (oldValue, newValue) -> oldValue, LinkedHashMap::new));\n\n\t\t\t\t scan.close();\n\t\t\t //Alternative way\n\t\t\t //Map<String, Double> result2 = new LinkedHashMap<>();\n\t\t\t //cosineProd.entrySet().stream().sorted(Map.Entry.<String, Double>comparingByValue().reversed()).limit(2).forEachOrdered(x -> result2.put(x.getKey(), x.getValue()));\n\n\t\t\t System.out.println(\"Sorted...\");\n\t\t\t System.out.println(result);\n\t\t\t //System.out.println(result2);\n\t}","private ArrayList<String> loadIds() {\n\n\t\tArrayList<String> idArray = new ArrayList<String>();\n\t\ttry {\n\t\t\tFileInputStream fileInputStream = context.openFileInput(SAVE_FILE);\n\t\t\tInputStreamReader inputStreamReader = new InputStreamReader(\n\t\t\t\t\tfileInputStream);\n\t\t\tType listType = new TypeToken<ArrayList<String>>() {\n\t\t\t}.getType();\n\t\t\tGsonBuilder builder = new GsonBuilder();\n\t\t\tGson gson = builder.create();\n\t\t\tArrayList<String> list = gson.fromJson(inputStreamReader, listType);\n\t\t\tidArray = list;\n\t\t} catch (IOException e) {\n\t\t\te.printStackTrace();\n\t\t}\n\t\treturn idArray;\n\t}","public List<K> getSavedIds() {\n if (dbObjects.length > 0 && dbObjects[0] instanceof JacksonDBObject) {\n throw new UnsupportedOperationException(\n \"Generated _id retrieval not supported when using stream serialization\");\n }\n\n List<K> ids = new ArrayList<K>();\n for (DBObject dbObject : dbObjects) {\n ids.add(jacksonDBCollection.convertFromDbId(dbObject.get(\"_id\")));\n }\n\n return ids;\n }","private synchronized void saveInternal() {\n if (relatedDocumentsCounter == 0) {\r\n return;\r\n }\r\n\r\n final TrigramIndexJsonModel model = new TrigramIndexJsonModel( relatedDocuments, indexGeneration, trigram );\r\n final TrigramDocumentCountJsonModel count = new TrigramDocumentCountJsonModel( trigram, globalRelatedDocumentsCounter );\r\n\r\n indexGeneration++;\r\n relatedDocuments = new TreeSet<>();\r\n relatedDocumentsCounter = 0;\r\n\r\n // put that save action and all unnecessary path calculations into a thread pool, \r\n // no need that other word can't be indexed, because of someone's save action... \r\n\r\n Runnable runnable = new Runnable() {\r\n @Override\r\n public void run() {\r\n Path trigramsPath = TrigramSubPathCalculator.getPathForTrigram( trigramsBasePath, trigram,\r\n \".\" + model.getIndexGeneration() + TRIGRAM_REFERENCE_SUFFIX );\r\n createTargetDirectoryIfNotExist( trigramsPath.getParent() );\r\n\r\n // write content of one part of the index\r\n try (BufferedWriter writer = Files.newBufferedWriter( trigramsPath, StandardCharsets.UTF_8 )) {\r\n Gson gson = new Gson();\r\n writer.write( gson.toJson( model ) );\r\n }\r\n catch (IOException e) {\r\n System.out.println( String.format( \"saving file: '%s' caused this error...\", trigramsPath ) );\r\n e.printStackTrace();\r\n }\r\n\r\n // write+overwrite the global documents counter as well\r\n Path trigramCountPath = TrigramSubPathCalculator.getPathForTrigram( trigramsBasePath, trigram, TRIGRAM_COUNT_SUFFIX );\r\n\r\n try (BufferedWriter writer = Files.newBufferedWriter( trigramCountPath, StandardCharsets.UTF_8 )) {\r\n Gson gson = new Gson();\r\n writer.write( gson.toJson( count ) );\r\n }\r\n catch (IOException e) {\r\n System.out.println( String.format( \"saving file: '%s' caused this error...\", trigramCountPath ) );\r\n e.printStackTrace();\r\n }\r\n\r\n }\r\n };\r\n\r\n // TODO: put into task thread-pool (deque) for really saving indexing time.\r\n runnable.run();\r\n }","private void saveGenres(){\n\t\tFile genreList = new File(Paths.get(\"genres.txt\").toString());\n\t\ttry{\n\t\t\tBufferedWriter writer = new BufferedWriter(new FileWriter(genreList));\n\t\t\tfor (String s : genres){\n\t\t\t\twriter.write(s);\n\t\t\t\twriter.newLine();\n\t\t\t}\n\t\t\twriter.close();\n\t\t} catch(IOException ex){\n\t\t\t\n\t\t}\n\t}","public static Map<String, AuthorMod> indexEmails(String fileName)\n\t{\n\t\tMap<String, AuthorMod> authBank= new HashMap<String, AuthorMod>();\t\t \n\t\tAuthorMod curAuth;\n\t\t//vars for for loop - one loop per email\n\t\tString curTok;\n\t\tString lastTok;\n\t\t\n\t\ttry \n\t\t{\n\t\t\tScanner scanner = new Scanner(new FileInputStream(fileName));\n\t\t try \n\t\t {\n\t\t while (scanner.hasNextLine())\n\t\t {\n\t\t \n\t\t \t String[] emailToks= SimpleTokenizer.INSTANCE.tokenize(scanner.nextLine());\n\t\t \t\n\t\t \t lastTok = \"<s>\";\n\t\t \t curTok = emailToks[3]; //maybe 2, check output\n\t\t \t Pair<String, String> firstBg = new Pair<String, String>(lastTok, curTok);\t\t \t \n\t\t \t //author check, possible set\n\t\t \t String authID = emailToks[0] + emailToks[1] + emailToks[2]; //check output from the tokenizer\t \t\n\t\t \t if (authBank.containsKey(authID)){\n\t\t \t\t curAuth = authBank.get(authID);\n\t\t \t\t curAuth.trainSize = curAuth.trainSize + (emailToks.length-2);\n\t\t \t\t curAuth.ug.updateSeen(lastTok);\n\t\t \t } else {\n\t\t \t\t curAuth = new AuthorMod();\n\t\t \t\t curAuth.id = authID;\n\t\t \t\t curAuth.trainSize = emailToks.length - 2;\n\t\t\t \t curAuth.ug.addNew(lastTok);\n\t\t \t }\n\t\t \t \n\t\t \t //initalize loop\n\t\t \t if(curAuth.ug.contains(curTok)) {\n\t\t \t\t curAuth.ug.updateSeen(curTok);\n\t\t \t } \n\t\t \t else {\t\t \n\t\t \t\t curAuth.ug.addNew(curTok);\n\t\t \t }\n\n\t\t \t if(curAuth.bg.containsBg(firstBg)) {\n\t\t \t\t curAuth.bg.updateSeen(firstBg);\n\t\t \t } else {\n\t\t \t\t curAuth.bg.addNew(firstBg);\n\t\t \t }\n\t\t \t \t \n\t\t \t //index for that author, code very similar to bigram/unigram\n\t\t \t for(int i = 4; i < emailToks.length; i++)\t\t \n\t\t \t\t {\n\t\t \t\t\t curTok= emailToks[i];\n\t\t \t\t\t Pair<String, String> loopBg = new Pair<String, String>(lastTok, curTok);\n\t\t \t\t\t \n\t\t \t\t\t //three cases. \n\t\t \t\t\t //1) bigram has been seen\n\t\t \t\t\t if (curAuth.bg.containsBg(loopBg))\n\t\t \t\t\t {\n\t\t \t\t\t\t curAuth.bg.updateSeen(loopBg);\n\t\t \t\t\t\t curAuth.ug.updateSeen(curTok);\n\t\t \t\t\t } \n\t\t \t\t\t //2) word seen, but not bigram\n\t\t \t\t\t else\n\t\t \t\t\t { \n\t\t \t\t\t\t if (curAuth.ug.contains(curTok))\n\t\t \t\t\t \t\t{\n\t\t \t\t\t\t\t curAuth.bg.addNew(loopBg);\n\t\t \t\t\t\t\t curAuth.ug.updateSeen(curTok);\n\t\t \t\t\t\t\t} \n\t\t \t\t\t\t //3) new word entirely\n\t\t \t\t\t\t else\n\t\t \t\t\t\t {\n\t\t \t\t\t\t\t curAuth.ug.addNew(curTok);\n\t\t \t\t\t\t\t curAuth.bg.addNew(loopBg); \n\t\t \t\t\t\t } \n\t\t \t\t\t }\t \n\t\t \t\t\t lastTok = curTok;\n\t\t \t\t\t} //end inner loop\n\t\t \tauthBank.put(curAuth.id, curAuth); \n\t\t \t\t} //end outer loop \n\t\t }\t\n\t\t finally\n\t\t {\n\t\t scanner.close();\n\t\t }\n\t\t}\n\t\tcatch(Exception e)\n\t\t{\n\t\t\tSystem.err.println(\"Error: \" + e.getMessage());\n\t\t}\n\t\treturn authBank;\n\t}","Map<String, String> getTokens();","private Map<String,Map<String,List<String>>> buildDictionary(Document doc){\n\t\t\n\t\tElement root = doc.getDocumentElement();\n\t\t\n\t\t\n\t\tMap<String,Map<String,List<String>>> dictionary = new HashMap<String,Map<String,List<String>>>();\n\t\tthis.termSet = new TreeSet<String>();\n\t\t\n\t\tNodeList termList = doc.getElementsByTagName(\"term\");\n\t\tfor(int i = 0; i < termList.getLength(); i++){\n\t\t\tElement termElement = (Element) termList.item(i);\n\t\t\tElement nameElement = (Element) termElement.getElementsByTagName(\"name\").item(0);\n\t\t\tString name = nameElement.getTextContent();\n\t\t\tthis.termSet.add(name);\n\n\t\t\tMap<String,List<String>> synonymGroup = new HashMap<String,List<String>>();\n\t\t\tsynonymGroup.put(\"exact\", new ArrayList<String>());\n\t\t\tsynonymGroup.put(\"related\", new ArrayList<String>());\n\t\t\tsynonymGroup.put(\"broad\", new ArrayList<String>());\n\t\t\tsynonymGroup.put(\"narrow\", new ArrayList<String>());\n\t\t\t\n\t\t\tNodeList synonyms = termElement.getElementsByTagName(\"synonym\");\n\t\t\tfor(int j=0; j<synonyms.getLength(); j++){\n\t\t\t\tElement synonymElement = (Element) synonyms.item(j);\n\t\t\t\tString synonym = synonymElement.getTextContent();\n\t\t\t\tString scope = synonymElement.getAttribute(\"scope\");\n\t\t\t\t//System.out.println(scope);\n\t\t\t\tList<String> synonymList = (List<String>) synonymGroup.get(scope);\n\t\t\t\t\n\t\t\t\t//System.out.println(synonym);\n\t\t\t\t\n\t\t\t\tsynonymList.add(synonym);\n\t\t\t}\n\t\t\t\n\t\t\tdictionary.put(name,synonymGroup);\t\t\n\t\t\t\n\t\t}\n\t\t\n\t\treturn dictionary;\n\t}","public synchronized List<Integer> getDocIdsTodosDocumentos() throws Exception{\r\n\t\tList<Integer> lista = new ArrayList<Integer>();\r\n\t\t\r\n\t\tMTDIterator<MTDDocument> iterator = iterator();\r\n\t\twhile(iterator.hasNext()){\r\n\t\t\tMTDDocument doc = iterator.next();\r\n\t\t\tlista.add(doc.getDocId());\r\n\t\t}\r\n\t\titerator.close();\r\n\t\t\r\n\t\treturn lista;\r\n\t}","private static Map<String, List<List<String>>>[] splitYagoDataIntoDocumentSets(File yagoInputFile) {\r\n\t\tMap<String, List<List<String>>> trainData = new HashMap<String, List<List<String>>>();\r\n\t\tMap<String, List<List<String>>> testaData = new HashMap<String, List<List<String>>>();\r\n\t\tMap<String, List<List<String>>> testbData = new HashMap<String, List<List<String>>>();\r\n\t\t\r\n\t\tBufferedReader reader = FileUtil.getFileReader(yagoInputFile.getAbsolutePath());\r\n\t\ttry {\r\n\t\t\tString documentName = null;\r\n\t\t\tString documentSet = null;\r\n\t\t\tList<List<String>> documentLines = null;\r\n\t\t\tList<String> sentenceLines = null;\r\n\t\t\tString line = null;\r\n\t\t\twhile ((line = reader.readLine()) != null) {\r\n\t\t\t\tif (line.startsWith(\"-DOCSTART-\")) {\r\n\t\t\t\t\tif (documentSet != null) {\r\n\t\t\t\t\t\tif (documentSet.equals(\"train\"))\r\n\t\t\t\t\t\t\ttrainData.put(documentName, documentLines);\r\n\t\t\t\t\t\telse if (documentSet.equals(\"testa\"))\r\n\t\t\t\t\t\t\ttestaData.put(documentName, documentLines);\r\n\t\t\t\t\t\telse if (documentSet.equals(\"testb\"))\r\n\t\t\t\t\t\t\ttestbData.put(documentName, documentLines);\r\n\t\t\t\t\t}\r\n\t\t\t\t\t\r\n\t\t\t\t\tString docId = line.substring(\"-DOCSTART- (\".length(), line.length() - 1);\r\n\t\t\t\t\tString[] docIdParts = docId.split(\" \");\r\n\t\t\t\t\tdocumentName = docIdParts[0] + \"_\" + docIdParts[1];\r\n\t\t\t\t\t\r\n\t\t\t\t\tif (docIdParts[0].endsWith(\"testa\"))\r\n\t\t\t\t\t\tdocumentSet = \"testa\";\r\n\t\t\t\t\telse if (docIdParts[0].endsWith(\"testb\"))\r\n\t\t\t\t\t\tdocumentSet = \"testb\";\r\n\t\t\t\t\telse\r\n\t\t\t\t\t\tdocumentSet = \"train\";\r\n\t\t\t\t\t\r\n\t\t\t\t\tdocumentLines = new ArrayList<List<String>>();\r\n\t\t\t\t\tsentenceLines = new ArrayList<String>();\r\n\t\t\t\t} else if (line.trim().length() == 0) {\r\n\t\t\t\t\tdocumentLines.add(sentenceLines);\r\n\t\t\t\t\tsentenceLines = new ArrayList<String>();\r\n\t\t\t\t} else {\r\n\t\t\t\t\tsentenceLines.add(line);\r\n\t\t\t\t}\r\n\t\t\t}\r\n\t\t\t\r\n\t\t\tif (documentSet.equals(\"train\"))\r\n\t\t\t\ttrainData.put(documentName, documentLines);\r\n\t\t\telse if (documentSet.equals(\"testa\"))\r\n\t\t\t\ttestaData.put(documentName, documentLines);\r\n\t\t\telse if (documentSet.equals(\"testb\"))\r\n\t\t\t\ttestbData.put(documentName, documentLines);\r\n\t\t} catch (IOException e) {\r\n\t\t\treturn null;\r\n\t\t}\r\n\r\n\t\t@SuppressWarnings(\"unchecked\")\r\n\t\tMap<String, List<List<String>>>[] returnData = new HashMap[3];\r\n\t\treturnData[0] = trainData;\r\n\t\treturnData[1] = testaData;\r\n\t\treturnData[2] = testbData;\r\n\t\t\r\n\t\treturn returnData;\r\n\t}","private static void writeToCoordinateFile(String idNames, String[] id_to_coord_list, String outputFileName){\n String[] stringToWrite = getStringBasedOnCoordinate( idNames, id_to_coord_list); //list of id we found, ignore the first 0th index\n writeToFile(stringToWrite, outputFileName);\n }","public void allartongs() throws IOException{\r\n writefiles data=new writefiles(\"d:\\\\documents\\\\textfiles\\\\AllArtSongs.txt\",true);\r\n Map<String,String> ArrangerNamesLineMap=new HashMap<>();\r\n for(int songid:ArrangerLinesMap.keySet()){\r\n int arrangerid=ArrangerLinesMap.get(songid);\r\n ArrangersMap.get((songid));\r\n ArrangerNamesLineMap.put(test.getsongName(songid), ArrangersMap.get(arrangerid));\r\n }\r\n for(String songname:ArrangerNamesLineMap.keySet()){\r\n System.out.println(\"The artist is:\"+ArrangerNamesLineMap.get(songname)+\" The song is:\"+songname);\r\n data.writeToFile(\"The artist is:\"+ArrangerNamesLineMap.get(songname)+\" The song is:\"+songname);\r\n }\r\n System.out.println(ArrangerNamesLineMap.size());\r\n }","public synchronized List<MTDDocument> getDocumentos(Collection<Integer> ids){\r\n\t\tArrayList<MTDDocument> listaRetorno = new ArrayList<MTDDocument>();\r\n\t\tDirectoryReader reader;\r\n\t\ttry {\r\n\t\t\treader = DirectoryReader.open(getCopiaDiretorioMemoria());\r\n\t\tIndexSearcher searcher = new IndexSearcher(reader);\t\t\r\n\t for(Integer docId: ids){\r\n \t\tDocument documento = searcher.doc(docId.intValue());\r\n \t\tif(documento != null){\r\n \t\tMTDDocument doc = new MTDDocumentBuilder().buildDocument(documento).build();\r\n \t\tdoc.setDocId(docId.intValue());\r\n \t\tlistaRetorno.add(doc);\r\n \t\t}else\r\n \t\t{System.out.println(\"Document with docId \"+docId.intValue()+\" not found.\");}\r\n\t }\r\n\t\t} catch (IOException e) {\r\n\t\t\t// TODO Auto-generated catch block\r\n\t\t\te.printStackTrace();\r\n\t\t}\r\n\t\treturn listaRetorno;\r\n\t}","private static void writeMappingsToFile(String releaseNumber, List<List<Object>> stableIdsToOldIdsMappings, Set<String> currentStableIdentifiers) throws IOException {\n\t\tPath oldStableIdsMappingFilePath = Paths.get(releaseNumber, \"reactome_stable_ids.txt\");\n\t\tString header = \"# Reactome stable IDs for release \" + releaseNumber + \"\\n\" + \"Stable_ID\\told_identifier(s)\\n\";\n\t\tFiles.write(oldStableIdsMappingFilePath, header.getBytes(), StandardOpenOption.CREATE, StandardOpenOption.TRUNCATE_EXISTING);\n\t\tfor (List<Object> stableIdsArray : stableIdsToOldIdsMappings)\n\t\t{\n\t\t\tString primaryId = (String) stableIdsArray.get(0);\n\t\t\t@SuppressWarnings(\"unchecked\")\n\t\t\tList<String> secondaryIds = (ArrayList<String>) stableIdsArray.get(1);\n\t\t\tif (currentStableIdentifierWithMapping(currentStableIdentifiers, primaryId, secondaryIds)) {\n\t\t\t\tString line = primaryId + \"\\t\" + String.join(\",\", secondaryIds) + \"\\n\";\n\t\t\t\tFiles.write(oldStableIdsMappingFilePath, line.getBytes(), StandardOpenOption.APPEND);\n\t\t\t}\n\t\t}\n\t}","private void savePoSTag(PoSTag poSTag){\n Long num;\n num = poSTagPerWordMap.get(poSTag.getWord());\n poSTagPerWordMap.put(poSTag.getWord(), (num == null) ? (long)1 : num+1);\n\n num = poSTagMap.get(poSTag);\n poSTagMap.put(poSTag, (num == null) ? (long)1 : num+1);\n\n\n }","public void getVector() throws IOException {\n\t\tint i=1;\r\n\t\tfor(String key:keyword){\r\n\t\t\tWord w=new Word();\r\n\t\t\tdouble tf=calTF(key);\r\n\t\t\tdouble idf=calIDF(key);\r\n\t\t\tdouble tfidf=tf*idf;\r\n\t\t\tw.setId(i);\r\n\t\t\ti++;\r\n\t\t\tw.setName(key);\r\n\t\t\tw.setTfidf(tfidf);\r\n\t\t\tif(word.containsKey(key)){\r\n\t\t\t\tw.setCount((Integer) word.get(key));\r\n\t\t\t}\r\n\t\t\tkeymap.add(w);\r\n\t\t}\r\n\t\tFileHelper.writeTrainFile(keymap);\r\n\t\tFileHelper.writeTestFile(keymap);\r\n\t}","public void saveToReadID(ArrayList<String> idList) {\n\n\t\tSAVE_FILE = TO_READ_FILE;\n\t\tsaveIds(idList);\n\t}","private void saveMarkerPrefs(){\n String latLngsList = new Gson().toJson(latLngs);\n String namesList = new Gson().toJson(locationNames);\n dataStorage.setLatLngList(latLngsList);\n dataStorage.setLocNameList(namesList);\n }","private void outputResults()\n{\n try {\n PrintWriter pw = new PrintWriter(new FileWriter(output_file));\n pw.println(total_documents);\n for (Map.Entry<String,Integer> ent : document_counts.entrySet()) {\n String wd = ent.getKey();\n int ct = ent.getValue();\n pw.println(ct + \" \" + wd);\n }\n pw.println(START_KGRAMS);\n pw.println(total_kdocuments);\n for (Map.Entry<String,Integer> ent : kgram_counts.entrySet()) {\n String wd = ent.getKey();\n int ct = ent.getValue();\n pw.println(ct + \" \" + wd);\n } \n pw.close();\n }\n catch (IOException e) {\n IvyLog.logE(\"SWIFT\",\"Problem generating output\",e);\n }\n}","public static void docWtgArray() {\n int docCount = 0;\n\n while(docCount<totaldocument) {\n List<Double> pass = new ArrayList();\n for(Entry<String,List<Double>> entry : wtgMap.entrySet()) {\n List<Double> docList = new ArrayList();\n docList = entry.getValue();\n double temp = docList.get(docCount);\n pass.add(temp);\n }\n\n double answer = CosineSimilarity(pass,query);\n if(answer >= alpha) {\n DocID.put(docCount,answer);\n }\n docCount++;\n }\n }","static private void printSentenceTokens( final String documentId, final Iterable<String> tokenizedSentences ) {\n System.out.println( \"=========================== \" + documentId + \" ===========================\" );\n for ( String tokenizedSentence : tokenizedSentences ) {\n System.out.println( tokenizedSentence );\n }\n }","public VSM(String[] docs) {\n\t\tmyDocs = docs;\n\t\ttermList = new ArrayList<String>();\n\t\tdocLists = new ArrayList<ArrayList<Doc>>();\n\t\tArrayList<Doc> docList;\n\t\t// parse the documents to construct the index and collect the raw\n\t\t// frequencies.\n\t\tfor (int i = 0; i < myDocs.length; i++) {\n\t\t\tString[] tokens = myDocs[i].split(\" \");\n\t\t\tString token;\n\t\t\tfor (int j = 0; j < tokens.length; j++) {\n\t\t\t\ttoken = tokens[j];\n\t\t\t\tif (!termList.contains(token)) {\n\t\t\t\t\ttermList.add(token);\n\t\t\t\t\tdocList = new ArrayList<Doc>();\n\t\t\t\t\tDoc doc = new Doc(i, 1); // initial raw frequency is 1\n\t\t\t\t\tdocList.add(doc);\n\t\t\t\t\tdocLists.add(docList);\n\t\t\t\t} else {\n\t\t\t\t\tint index = termList.indexOf(token);\n\t\t\t\t\tdocList = docLists.get(index);\n\t\t\t\t\tint k = 0;\n\t\t\t\t\tboolean match = false;\n\n\t\t\t\t\t// search the postings list for a document id, if match,\n\t\t\t\t\t// insert a new position number to the document id\n\t\t\t\t\tfor (Doc doc : docList) {\n\t\t\t\t\t\tif (doc.docId == i) {\n\t\t\t\t\t\t\tdoc.tw++; // increase word count\n\t\t\t\t\t\t\tmatch = true;\n\t\t\t\t\t\t\tbreak;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tk++;\n\t\t\t\t\t}\n\t\t\t\t\t// if no match, add a new document id along with the\n\t\t\t\t\t// position number\n\t\t\t\t\tif (!match) {\n\t\t\t\t\t\tDoc doc = new Doc(i, 1);\n\t\t\t\t\t\tdocList.add(doc);\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}//\n\t\t}// end with parsing\n\n\t\t// compute the tf-idf term weights and the doc lengths\n\t\tint N = myDocs.length;\n\t\tdocLength = new double[N];\n\t\tfor (int i = 0; i < termList.size(); i++) {\n\t\t\tdocList = docLists.get(i);\n\t\t\tint df = docList.size();\n\t\t\tDoc doc;\n\t\t\tfor (int j = 0; j < docList.size(); j++) {\n\t\t\t\tdoc = docList.get(j);\n\t\t\t\tdouble tfidf = (1 + Math.log(doc.tw))\n\t\t\t\t\t\t* Math.log(N / (df * 1.0));\n\t\t\t\tdocLength[doc.docId] += Math.pow(tfidf, 2);\n\t\t\t\tdoc.tw = tfidf;\n\t\t\t\tdocList.set(j, doc);\n\t\t\t}\n\t\t}\n\t\t// update the length\n\t\tfor (int i = 0; i < N; i++) {\n\t\t\tdocLength[i] = Math.sqrt(docLength[i]);\n\t\t}\n\n\t}","public static void saveAsMultipleFiles(Map<Atto, List<ITerm>> atti, String path)\n\t{\n\t\tFile dir = new File(path);\n\t\tif (!dir.exists() || !dir.isDirectory())\n\t\t\tthrow new IllegalArgumentException(\"!dir.exists() || !dir.isDirectory()\");\n\t\t\n\t\tFileUtils.clearDirectory(dir);\n\t\t\n\t\ttry\n\t\t{\n\t\t\tint counter = 0;\n\t\t\tfor (Entry<Atto, List<ITerm>> entry : atti.entrySet())\n\t\t\t{\n\t\n\t\t\t\tString filename = path + File.separator + attoTermsPrefix + counter + jsonExtension;\n\t\t\t\tJSONActDescriptorSaver saver = new JSONActDescriptorSaver(WritersFactory.newUTF8FileWriter(filename));\n\t\t\t\tsaver.save(entry);\n\t\t\t\t\n\t\t\t\tcounter++;\n\t\t\t}\n\t\t}\n\t\tcatch (IOException e)\n\t\t{\n\t\t\tSystem.err.println(e);\n\t\t}\n\t}","public void insert( String token, int docID, int offset ) {\n // Add to map of postingslist\n //if (docID % 100 == 0)\n //System.err.println(\"Trying to insert ''\" + token + \"'' found in doc \"+docID);\n if (this.index.containsKey(token)){\n //System.err.println(token+\" already in memory\");\n this.index.get(token).insert(docID, offset);\n }\n else{\n //System.err.println(\"new token: \" +token+\" stored\");\n PostingsList postingslist = new PostingsList();\n postingslist.insert(docID, offset);\n this.index.put(token, postingslist);\n }\n\n // Add to matrix of tf\n if (!this.tfMap.containsKey(docID)){\n HashMap<String, Integer> m = new HashMap<String, Integer>();\n m.put(token, 1);\n this.tfMap.put(docID, m);\n\n if (this.idfMap.containsKey(token))\n this.idfMap.put(token, this.idfMap.get(token)+1);\n else\n this.idfMap.put(token, 1);\n }\n\n else if (!this.tfMap.get(docID).containsKey(token)){\n this.tfMap.get(docID).put(token, 1);\n\n if (this.idfMap.containsKey(token))\n this.idfMap.put(token, this.idfMap.get(token)+1);\n else\n this.idfMap.put(token, 1);\n }\n\n else{\n int v = this.tfMap.get(docID).get(token) + 1;\n this.tfMap.get(docID).put(token, v);\n }\n }","public long getDocumentName();","public abstract Set<String> getTerms(Document doc);","public String addStudent (String name,String admin){\n Document doc = new Document(\"name\", name);\n doc.put(\"skills\",Arrays.asList());\n studentSkills.insertOne(doc);\n this.createNewToken(doc.get(\"_id\").toString(),admin);\n return doc.get(\"_id\").toString();\n}","public void saveBooks(){\n\t\ttry{\t\n\t\t\tPrintWriter pw = new PrintWriter(new FileWriter(\"../bin/books.csv\"));\t\n\t\t\tIterator bookIterator = bookMap.keySet().iterator();\n\t\t\twhile(bookIterator.hasNext() != false){\n\t\t\t\tString current = bookIterator.next().toString();\n\t\t\t\tfor(int i=0;i<bookMap.get(current).size();i++){\t\n\t\t\t\t\tpw.write(bookMap.get(current).get(i).getTitle() \n\t\t\t\t\t\t+ \",\" + bookMap.get(current).get(i).getAuthor()\n\t\t\t\t\t\t+ \",\" + bookMap.get(current).get(i).getYear()\n\t\t\t\t\t\t+ \",\" + bookMap.get(current).get(i).getType()\n\t\t\t\t\t\t+ \",\" + bookMap.get(current).get(i).getId());\n\t\t\t\t\tpw.write(\"\\n\");\n\t\t\t\t}\n\t\t\t}\t\n\t\t\tpw.close();\n\t\t\tSystem.out.println(\"\\tDone!\");\n\t\t}catch(IOException e){\n\t\t\tSystem.out.println(e.toString());\n\t\t}\n\n\t}","public void readIDs() {\n try {\n FileInputStream fileIn = new FileInputStream(\"temp/ids.ser\");\n ObjectInputStream in = new ObjectInputStream(fileIn);\n ids = (HashMap<String, Member>) in.readObject();\n in.close();\n fileIn.close();\n } catch (IOException e) {\n ids = new HashMap<>();\n } catch (ClassNotFoundException c) {\n System.out.println(\"Class HashMap not found\");\n c.printStackTrace();\n return;\n }\n\n }","@Override\n public void run() {\n final Location location = getLastBestLocation();\n\n\n location.getLatitude();\n location.getLongitude();\n\n\n\n\n\n // Create a new user with a first and last name\n Map<String, Object> user = new HashMap<>();\n user.put(\"lat\", location.getLatitude());\n user.put(\"long\", location.getLongitude());\n\n// Add a new document with a generated ID\n\n db.collection(\"gps\").document(\"QvFfCM86QQJRAIk68MQv\").update(user)\n .addOnSuccessListener(new OnSuccessListener<Void>() {\n @Override\n public void onSuccess(Void aVoid) {\nString locs= location.getLatitude()+\",\"+location.getLongitude();\n loc.setText(locs);\n Log.w(TAG, \"onSuccess\"+count);\n count = count+1;\n }\n })\n .addOnFailureListener(new OnFailureListener() {\n @Override\n public void onFailure(@NonNull Exception e) {\n Log.w(TAG, \"Error adding document\", e);\n }\n });\n\n // Repeat every 2 seconds\n handler.postDelayed(runnable, 500);\n }","private void createDocWords() {\n\t\tArrayList<DocWords> docList=new ArrayList<>();\n\t\ttry {\n\t\t\tBufferedReader in = new BufferedReader(new FileReader(\"E:\\\\graduate\\\\cloud\\\\project\\\\data\\\\docWords.txt\"));\n\t\t\tString line = \"\";\n\t\t\twhile ((line = in.readLine()) != null) {\n\t\t\t\tString parts[] = line.split(\" \");\n\t\t\t\tDocWords docWords=new DocWords();\n\t\t\t\tdocWords.setDocName(parts[0].replace(\".txt\", \"\"));\n\t\t\t\tdocWords.setCount(Float.parseFloat(parts[1]));\n\t\t\t\tdocList.add(docWords);\n\t\t\t}\n\t\t\tin.close();\n\t\t} catch (IOException e) {\n\t\t\te.printStackTrace();\n\t\t}\n\t\tDBUtil.insertDocWords(docList);\n\t}","private void createDicts(String inputFile){\n\t\tproductIds = new TreeMap<>();\n\t\ttokenDict = new TreeMap<>();\n\t\treviewIds = new TreeMap<>();\n\n\t\tDataParser dataParser = null;\n\t\ttry {\n\t\t\tdataParser = new DataParser(inputFile);\n\t\t} catch (IOException e) {\n\t\t\tSystem.out.println(\"Error occurred while reading the reviews input file.\");\n\t\t\tSystem.exit(1);\n\t\t}\n\n\t\tfor (int i = 0; i < dataParser.allReviews.size(); i++) {\n\t\t\taddProductId(dataParser.allReviews.get(i).get(\"productId\"), i + 1);\n\t\t\tint length = addReviewText(dataParser.allReviews.get(i).get(\"text\"), i + 1);\n\t\t\taddReviewId(dataParser.allReviews.get(i), i, length);\n\t\t}\n\t}","@SuppressWarnings(\"empty-statement\")\n public ArrayList process(String input){\n //public static void main(String[] args) throws SQLException {\n\n //Scanner in = new Scanner(System.in);\n //String InputStr = in.nextLine(); // to read user input;\n String InputStr = input;\n \n System.out.println(input);\n \n boolean quotated = false; // to know input with quotation or not;\n try {\n ConnectToDB();\n int TotalnumDoc = GetNumDocs();\n\n if (InputStr.startsWith(\"\\\"\") && InputStr.endsWith(\"\\\"\")) {\n System.out.println(\"quotation\");\n quotated = true;\n GetDoc_Word(InputStr, TotalnumDoc);\n System.out.println(\"total number of doc =\" + TotalnumDoc);\n Postions();\n } else {\n GetDoc_StemWord(InputStr, TotalnumDoc);\n quotated = false;\n }\n\n for (Map.Entry<String, SrchWord> entry1 : WordList.entrySet()) /// for\n /// printing\n {\n System.out.println(entry1.getKey() + \"\tIDF: \" + entry1.getValue().IDf);\n\n SrchWord w1 = entry1.getValue();\n w1.PrintSrchWord();\n System.out.println(\"___________________________\");\n\n }\n System.out.println(\"================================================================\");\n Ranker();\n \n for (Map.Entry<Integer, DocRank> entry1 : pages.entrySet()) \n {\n entry1.getValue().ID = entry1.getKey();\n }\n \n List<DocRank> sortedRank = new ArrayList<>(pages.values());\n \n if (!quotated)\n { \n sortedRank.sort( new SortByPageRank());\n }\n else\n {\n sortedRank.sort( new SortByValidFlag());\n }\n //*****************************************************************\n // sortedRank now contains objects DocRank containing the pageRank and the DocID(choose ascendingly or descendingly\n // from SortByPageRank.java compare function)\n // the ID should enable the retrieval of the URL and title from the table Docs_URL\n //****************************************************************\n \n ArrayList sortedIds = new ArrayList();\n \n for (int i=0; i<sortedRank.size(); i++)\n {\n System.out.println(\"DocID : \" +sortedRank.get(i).ID);\n System.out.println(\"pageRank: \" + sortedRank.get(i).rank);\n \n sortedIds.add(sortedRank.get(i).ID); // dont forget to change the comparator to descending\n //System.out.println(sortedRank.get(i).ID);\n }\n \n pages.clear();\n return sortedIds;\n \n } catch (Exception e) {\n\n e.printStackTrace();\n return null;\n\n } finally {\n\n WordList.clear(); // clearing map after searching\n if (con != null) {\n try {\n con.close();\n } catch (Exception e) {\n }\n }\n }\n\n }","public void getThesaurusMap (String wordTofind) {\r\n\t \tfor (Entry<String, List> entry : tMap.entrySet()) {\r\n\t \t\tList singleListofSynonims = entry.getValue();\r\n\t \t\tif (singleListofSynonims.contains(wordTofind)){\r\n\t \t\t\t\r\n\t \t\t\tmappedList.add(singleListofSynonims);\r\n\t \t\t\tGoogleToThesarus.put(wordTofind,singleListofSynonims);\r\n\t \t\t}\r\n\t \t\telse {\r\n\t \t\t\t//System.out.println(\"value not in map\");\r\n\t \t}\r\n\t \t}\r\n\t }","void genIDFData(String vocabFile, String outFile) throws Exception {\n List<String> lines = FileUtils.readLines(new File(vocabFile), Charset.defaultCharset());\n BufferedWriter bw = new BufferedWriter(new FileWriter(outFile));\n int N = reader.numDocs();\n for (String line: lines) {\n String word = TrecDocIndexer.analyze(indexer.getAnalyzer(), line).trim();\n int df = reader.docFreq(new Term(TrecDocIndexer.FIELD_ANALYZED_CONTENT, word));\n bw.write(line.trim() + \"\\t\");\n bw.write(String.valueOf(Math.log(N/(double)df)));\n bw.newLine();\n }\n bw.close();\n }","public void saveReadID(ArrayList<String> idList) {\n\n\t\tSAVE_FILE = READ_FILE;\n\t\tsaveIds(idList);\n\t}","public static void loadTargetTerm2IdMapping(File input) throws IOException {\n\t\t\tm_namesMap = new SimpleBidirectionalMap<String, Integer>();\n\t\t\tString encoding = FileUtils.getFileEncoding(input);\n\t\t\tBufferedReader reader = new BufferedReader(new InputStreamReader(new FileInputStream(input), encoding));\n\t\t\tString line = reader.readLine();\n\t\t\tint lineNum = 1;\n\t\t\tboolean testFormat = false;\n\t\t\tif(StringUtils.checkIfNumber(line.split(\"\\t\")[0]))\n\t\t\t\ttestFormat = true;\n\t\t\twhile(line!= null) {\n\t\t\t\tif(line.equals(\"@@@\"))\n\t\t\t\t\tbreak;\n\t\t\t\tif(testFormat) {\n\t\t\t\t\tString num = line.split(\"\\t\")[0];\n\t\t\t\t\tSystem.out.println(\"key: \"+line.trim().substring(num.length()+1) + \" value: \" + Integer.parseInt(num));\n\t\t\t\t\tm_namesMap.put(line.trim().substring(num.length()+1), Integer.parseInt(num));\n\t\t\t\t}\n\t\t\t\telse {\n\t\t\t\t\tSystem.out.println(\"key????\" + lineNum + \"instead of \" + line.split(\"\\t\")[0]);\n\t\t\t\t\tm_namesMap.put(line.trim(), lineNum);\n\t\t\t\t}\n\t\t\t\tline = reader.readLine();\n\t\t\t\tlineNum ++;\n\t\t\t}\n\t\t}","public static void main(String[] args) throws FileNotFoundException, IOException {\n \n \n File textBank = new File(\"textbank/\");\n Hashtable<Integer,Integer> frequency;\n Hashtable<Integer, String> table;\n table = new Hashtable<>();\n frequency = new Hashtable<>();\n Scanner input = new Scanner(new File(\"stoplist.txt\"));\n int max=0;\n while (input.hasNext()) {\n String next;\n next = input.next();\n if(next.length()>max)\n max=next.length();\n table.put(next.hashCode(), next); //to set up the hashmap with the wordsd\n \n }\n \n System.out.println(max);\n \n Pattern p0=Pattern.compile(\"[\\\\,\\\\=\\\\{\\\\}\\\\\\\\\\\\\\\"\\\\_\\\\+\\\\*\\\\#\\\\<\\\\>\\\\!\\\\`\\\\-\\\\?\\\\'\\\\:\\\\;\\\\~\\\\^\\\\&\\\\%\\\\$\\\\(\\\\)\\\\]\\\\[]\") \n ,p1=Pattern.compile(\"[\\\\.\\\\,\\\\@\\\\d]+(?=(?:\\\\s+|$))\");\n \n \n \n wor = new ConcurrentSkipListMap<>();\n \n ConcurrentMap<String , Map<String,Integer>> wordToDoc = new ConcurrentMap<String, Map<String, Integer>>() {\n @Override\n public Map<String, Integer> putIfAbsent(String key, Map<String, Integer> value) {\n throw new UnsupportedOperationException(\"Not supported yet.\"); //To change body of generated methods, choose Tools | Templates.\n }\n\n @Override\n public boolean remove(Object key, Object value) {\n throw new UnsupportedOperationException(\"Not supported yet.\"); //To change body of generated methods, choose Tools | Templates.\n }\n\n @Override\n public boolean replace(String key, Map<String, Integer> oldValue, Map<String, Integer> newValue) {\n throw new UnsupportedOperationException(\"Not supported yet.\"); //To change body of generated methods, choose Tools | Templates.\n }\n\n @Override\n public Map<String, Integer> replace(String key, Map<String, Integer> value) {\n throw new UnsupportedOperationException(\"Not supported yet.\"); //To change body of generated methods, choose Tools | Templates.\n }\n\n @Override\n public int size() {\n throw new UnsupportedOperationException(\"Not supported yet.\"); //To change body of generated methods, choose Tools | Templates.\n }\n\n @Override\n public boolean isEmpty() {\n throw new UnsupportedOperationException(\"Not supported yet.\"); //To change body of generated methods, choose Tools | Templates.\n }\n\n @Override\n public boolean containsKey(Object key) {\n throw new UnsupportedOperationException(\"Not supported yet.\"); //To change body of generated methods, choose Tools | Templates.\n }\n\n @Override\n public boolean containsValue(Object value) {\n throw new UnsupportedOperationException(\"Not supported yet.\"); //To change body of generated methods, choose Tools | Templates.\n }\n\n @Override\n public Map<String, Integer> get(Object key) {\n return wor.get((String)key);//To change body of generated methods, choose Tools | Templates.\n }\n\n @Override\n public Map<String, Integer> put(String key, Map<String, Integer> value) {\n wor.put(key, value); // this saving me n \n //if(frequency.get(key.hashCode())== null)\n \n //frequency.put(key.hashCode(), )\n return null;\n }\n\n @Override\n public Map<String, Integer> remove(Object key) {\n throw new UnsupportedOperationException(\"Not supported yet.\"); //To change body of generated methods, choose Tools | Templates.\n }\n\n @Override\n public void putAll(Map<? extends String, ? extends Map<String, Integer>> m) {\n throw new UnsupportedOperationException(\"Not supported yet.\"); //To change body of generated methods, choose Tools | Templates.\n }\n\n @Override\n public void clear() {\n throw new UnsupportedOperationException(\"Not supported yet.\"); //To change body of generated methods, choose Tools | Templates.\n }\n\n @Override\n public Set<String> keySet() {\n throw new UnsupportedOperationException(\"Not supported yet.\"); //To change body of generated methods, choose Tools | Templates.\n }\n\n @Override\n public Collection<Map<String, Integer>> values() {\n throw new UnsupportedOperationException(\"Not supported yet.\"); //To change body of generated methods, choose Tools | Templates.\n }\n\n @Override\n public Set<Map.Entry<String, Map<String, Integer>>> entrySet() {\n throw new UnsupportedOperationException(\"Not supported yet.\"); //To change body of generated methods, choose Tools | Templates.\n }\n };\n totalFiles = textBank.listFiles().length;\n for (File textFile : textBank.listFiles()) {\n totalReadFiles++;\n //checking whether file has txt extension and file size is higher than 0\n if(textFile.getName().contains(\".txt\") && textFile.length() > 0){\n docName.add(textFile.getName().replace(\".txt\", \".stp\"));\n StopListHandler sp = new StopListHandler(textFile, table,System.currentTimeMillis(),p0,p1,wordToDoc);\n sp.setFinished(() -> {\n \n tmp++;\n \n if(tmp==counter)\n //printTable(counter);\n \n if(totalReadFiles == totalFiles)\n {\n printTable(counter);\n }\n \n });\n \n sp.start();\n counter ++;}\n \n \n }\n System.out.println(counter);\n //while(true){if(tmp==counter-1) break;}\n System.out.println(\"s\");\n \n }","private void initIDFMap(List<List<Map<String,List<Double>>>> tfMap){\n\t\tfor (int i = 0; i < tfMap.size(); i++) {\n\t\t\tList<Map<String,List<Double>>> gestureDocument = tfMap.get(i);\n\t\t\tfor (int j = 0; j < gestureDocument.size(); j++) {\n\t\t\t\tMap<String,List<Double>> tempMap = gestureDocument.get(j);\n\t\t\t\tIterator<Entry<String, List<Double>>> it = tempMap.entrySet().iterator();\n\t\t\t\t while (it.hasNext()) {\n\t\t\t\t Map.Entry<String,Integer> pairs = (Map.Entry)it.next(); \n\t\t\t\t if(getTfIDFMapGlobal().containsKey(pairs.getKey()))\n\t\t\t\t \tgetTfIDFMapGlobal().put(pairs.getKey(), getTfIDFMapGlobal().get(pairs.getKey())+1);\n\t\t\t\t else\n\t\t\t\t \tgetTfIDFMapGlobal().put(pairs.getKey(), 1);\n\t\t\t\t }\n\t\t\t}\n\t\t}\n\t}","private static void saveMapToFile(HashMap<String, Integer> posCounts, String fileName) throws FileNotFoundException, IOException {\n\t\tProperties properties = new Properties();\r\n\r\n\t for (Map.Entry<String,Integer> entry : posCounts.entrySet()) {\r\n\t properties.put(entry.getKey(), entry.getValue().toString());\r\n\t }\r\n\t \r\n\t properties.store(new FileOutputStream(fileName), null);\r\n\t}","public static void save(String fname, ArrayList<Tweet> tw) {\n\ttry {\n\t FileOutputStream fout = new FileOutputStream(fname);\n\t ObjectOutputStream oos = new ObjectOutputStream(fout);\n\t oos.writeObject(tw);\n\t oos.close();\n\t} catch (FileNotFoundException ex) {\n\t ex.printStackTrace();\n\t} catch (IOException ioex) {\n\t ioex.printStackTrace();\n\t}\n }","public static void printHashMapSS(Map<String, String> map) throws IOException{\n\t\tPrintWriter writer = new PrintWriter(\"C:/Users/Naveen/Desktop/TestRuns/LastRun/documentHash\");\n\t\tfor (Entry<String, String> entry : map.entrySet())\n\t {\t \t\t\n\t \t\twriter.println(entry.getKey()+\":\"+entry.getValue());\n\t }\n\t writer.close();\n\t}","public void writeFile() {\n\t\ttry {\n\t\t\tFile dir = Environment.getExternalStorageDirectory();\n\t\t\tFile myFile = new File(dir.toString() + File.separator + FILENAME);\n\t\t\tLog.i(\"MyMovies\", \"SeSus write : \" + myFile.toString());\n\t\t\tmyFile.createNewFile();\n\t\t\tFileOutputStream fOut = new FileOutputStream(myFile);\n\t\t\tOutputStreamWriter myOutWriter = \n\t\t\t\t\tnew OutputStreamWriter(fOut);\n\t\t\tfor (Map.Entry<String, ValueElement> me : hm.entrySet()) {\n\t\t\t\tString refs = (me.getValue().cRefMovies>0? \"MOVIE\" : \"\");\n\t\t\t\trefs += (me.getValue().cRefBooks>0? \"BOOK\" : \"\");\n\t\t\t\tString line = me.getKey() + DELIMITER + me.getValue().zweiteZeile \n\t\t\t\t\t\t //+ DELIMITER\n\t\t\t\t\t\t //+ me.getValue().count\n\t\t\t\t\t \t+ DELIMITER\n\t\t\t\t\t \t+ refs\n\t\t\t\t\t \t + System.getProperty(\"line.separator\");\n\t\t\t\t//Log.i(\"MyMovies\", \"SeSus extracted : \" + line);\n\t\t\t\tmyOutWriter.write(line);\n\t\t\t}\n\t\t\tmyOutWriter.close();\n\t\t\tfOut.close();\n\t\t} catch (IOException e) {\n\t\t\t//\n\t\t\tLog.i(\"MyMovies\", \"SeSus write Exception : \");\n\t\t\te.printStackTrace();\n\t\t}\n\t}","void addWordsToDoc(int doc,List<VocabWord> words);","public void saveUsers() {\n FileWriter fileWriter = null;\n PrintWriter printWriter = null;\n try {\n fileWriter = new FileWriter(pathData);\n printWriter = new PrintWriter(fileWriter);\n if (users != null) {\n \n for (Map.Entry m : users.entrySet()) {\n printWriter.println(m.getKey() + spChar + m.getValue() + \"\\n\");\n }\n }\n printWriter.close();\n } catch (IOException e) {\n }\n }","public void map(LongWritable docID, Text value, OutputCollector<Text, Text> output, Reporter reporter) throws IOException {\n FileSplit fileSplit = (FileSplit) reporter.getInputSplit();\n String filename = \"\" + fileSplit.getPath().getName();\n\n int argc = Integer.parseInt(conf.get(\"argc\"));\n java.util.Map<String, Integer> keywords = new HashMap<String, Integer>();\n\n for (int i = 0; i < argc; i++) {\n String inputString = conf.get(\"keyword\" + i);\n\n keywords.put(inputString, 0);\n\n\n }\n\n String line = value.toString();\n StringTokenizer tokenizer = new StringTokenizer(line);\n while (tokenizer.hasMoreTokens()) {\n\n String token = tokenizer.nextToken();\n for (java.util.Map.Entry<String, Integer> me : keywords.entrySet()) {\n if (token.equalsIgnoreCase(me.getKey())) {\n\n keywords.put(me.getKey(), me.getValue() + 1);\n\n }\n }\n }\n\n for (java.util.Map.Entry<String, Integer> me : keywords.entrySet()) {\n\n keyword.set(me.getKey());\n filenameCount.set(filename + \"_\" + me.getValue());\n\n output.collect(keyword, filenameCount);\n }\n }","private void saveToStorage() {\n FileOutputStream fos = null;\n try {\n fos = context.openFileOutput(\"GeoFences\", Context.MODE_PRIVATE);\n ObjectOutputStream oos = new ObjectOutputStream(fos);\n oos.writeObject(currentList);\n oos.close();\n } catch (IOException e) {\n e.printStackTrace();\n }\n }","private void reLoadIndexesFromFileToIndexMap(File file) throws IOException {\n BufferedReader reader = new BufferedReader(new FileReader(file));\n for (String line = reader.readLine(); line != null; line = reader\n .readLine()) {\n String[] termIndex = line.split(\" \");\n String key = termIndex[0];\n LinkedList<TermPositions> value = new LinkedList<>();\n String postingList = termIndex[1];\n // split the posting lists 1:1,2,4;2:4\n String[] subPostings = postingList.split(\";\");\n for (String posting : subPostings) {\n String[] docPosting = posting.split(\":\");\n int docId = Integer.parseInt(docPosting[0]);\n String[] positions = docPosting[1].split(\",\");\n LinkedList<Integer> positionsList = new LinkedList<>();\n for (String position : positions) {\n positionsList.add(Integer.parseInt(position));\n }\n TermPositions termPositions = new TermPositions(docId, positionsList);\n value.add(termPositions);\n }\n indexMap.put(key, value);\n\n }\n\n }","public static void update(String indexFileName, String listOfDoc) throws IOException{\n\t\tHashMap<String, String> sCurrentHashMap = null;\n\t\tboolean hasFile = true;\n\t\t\n\t\tif(globalHash.containsKey(indexFileName)){\n\t\t\t//ถ้ามีใน global แล้ว เอาออกมาแล้วเอามารวมกับที่เพิ่งอ่านไฟล์ได้เลย\n\t\t\tsCurrentHashMap = globalHash.get(indexFileName);\n\t\t\n\t\t}else{ \n\t\t\t//if no hashmap in globalHash, then check if there's this fileName.txt in directory\n\t\t\t\n\t\t\tif(!new File(indexFileName+\".txt\").isFile()){\n\t\t\t\t\tSystem.out.println(\"ERROR: The inverted file is not found.\");\n\t\t\t\t\thasFile = false;\n\t\t\t}else{\n\t \t sCurrentHashMap = genHashMapFromInvertedIndexFile(indexFileName);\n\t\t\t \n\t\t\t}\n\t\t}\n\t\t\n\t\tif(hasFile){\n\t\t\tArrayList<Term> newTermList = extractDoc(listOfDoc);\n\t\t\t//if the new term list has value (not doc not found)\n\t\t\tif(newTermList.size()>0){\n\t\t\t\t\n\t\t\t\t\n\t\t\t\tsCurrentHashMap = addListToHashMap(sCurrentHashMap, newTermList);\n\t\t\t\t\n\t\t\t\t/*เพิ่มเงื่อนไขกรณี ลบคำออกจากไฟล์ \n\t\t\t\t * 1.ทำ list เป็น hashMap อีกอันไว้เซิชไวไว\n\t\t\t\t * loop amount of doc\n\t\t\t\t * 2.ไล่ iterative ของ hashMap ว่ามี value อันไหน contain ชื่อไฟล์บ้าง ถ้าcontain ให้เช็คกลับว่า key นั้น มีในแฮชอีกอันหรือเปล่า\n\t\t\t\t*/\n\t\t\t\t\n\t\t\t\t/* // Convert new word (from file) list to HashMap\n\t\t\t\tHashMap<String, String> newWordHashMap = new HashMap<String, String>();\n\t\t\t\tfor(Term i: newTermList){\n\t\t\t\t\tnewWordHashMap.put(i.getTerm(), i.getDocNumber()+\"\");\n\t\t\t\t}\n\t\t\t\t\n\t\t\t\t\n\t\t\t\tIterator it = sCurrentHashMap.entrySet().iterator();\n\t\t\t\twhile(it.hasNext()){\n\t\t\t\t\tHashMap.Entry<String, String> entry = (HashMap.Entry<String, String>) it.next();\n\t\t\t\t\t//if its value contains the doc number, then check if its key is in the newTermHash or note\n\t\t\t\t\t// if not --> this term was removed --> remove this key out from sCurrentHashMap\n\t\t\t\t\tif(entry.getValue().contains(s)) {\n\t\t\t\t\t\t\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t\t*/\n\t\t\t\t\n\t\t\t\tglobalHash.put(indexFileName, sCurrentHashMap);\n\n\t\t\t\t\n\t\t\t}\n\t\t\t\n\t\t}\n\t\t\n\t\t\n\t\t\n\t\t\n\t}","public static void getAllDocumentIds(ArrayList idList, String collectionName) {\n idList.clear();\n MainActivity.db.collection(collectionName).get().addOnCompleteListener(new OnCompleteListener<QuerySnapshot>() {\n @Override\n public void onComplete(@NonNull Task<QuerySnapshot> task) {\n if (task.isSuccessful()) {\n for (QueryDocumentSnapshot document : task.getResult()) {\n idList.add(document.getId());\n Log.d(TAG, document.getId() + \" => \" + document.getData());\n }\n } else {\n Log.w(TAG, \"Error getting documents.\", task.getException());\n }\n }\n });\n }","private void invertedToDatabase(){\r\n cleFreq = new HashMap<>();\r\n System.out.println(\"Strat collecting\");\r\n Map<String,List<Invertedindex>> collects = collecting();\r\n System.out.println(\"Ending collecting\");\r\n Database.getInstance().invertedIndex(collects);\r\n Database.getInstance().addPoids(cleFreq);\r\n }","private void storeData() {\r\n final File tweetsFile = new File(tweetsStorePath);\r\n final File usersFile = new File(usersStorePath);\r\n final Set<TweetEntity> tweetEntities = new HashSet();\r\n final Set<UserEntity> userEntities = new HashSet();\r\n \r\n tweets.entrySet().stream().forEach(entry -> {\r\n entry.getValue().stream().forEach(\r\n status -> {\r\n try {\r\n tweetEntities.add(\r\n new TweetEntity(status,\r\n entry.getKey()));\r\n userEntities.add(\r\n new UserEntity(status.getUser()));\r\n } catch (UnsupportedEncodingException ex) {\r\n \r\n }\r\n });\r\n });\r\n\r\n try {\r\n try (PrintWriter tweetWriter = new PrintWriter(tweetsFile)) {\r\n tweetEntities.stream().forEach(entity -> {\r\n tweetWriter.println(entity.toString());\r\n });\r\n }\r\n try (PrintWriter userWriter = new PrintWriter(usersFile)) {\r\n userEntities.stream().forEach(entity -> {\r\n userWriter.println(entity.toString());\r\n });\r\n }\r\n } catch (IOException ex) {\r\n System.out.println(\"DBLIS - storeData() - error storing data\" + ex);\r\n }\r\n }","public void parseThesaurus() throws IOException {\r\n\t\t\t//We create an object below to read the thesaurus file\r\n\t\t\tFileInputStream fis = new FileInputStream(\"src//ie//gmit//dip//resources//MobyThesaurus3.txt\");\r\n\t\t\tBufferedReader br=new BufferedReader(new InputStreamReader(fis));\r\n\t\t\t List <List<String>> listOflist= new ArrayList<>();\r\n\t\t\t// HashMap<String,List> tMap = new HashMap<>();\t\t\r\n\t\t\t List <String> individualListOfSynonyms= new ArrayList <String>();\r\n\r\n\t\t\t \r\n\t\t\t //we create a hashmap with the first word being the key value and the rest a list of synonims we will use\r\n\t\t\twhile(br.readLine()!=null) {\r\n\t\t\t\t\r\n\t\t\t\tString somestring = br.readLine();\r\n\t\t\t\tString[] testsplit= somestring.split(\",\");\r\n\t\t\t\tindividualListOfSynonyms=Arrays.asList(testsplit);\r\n\t\t\t\tString indexvalue=individualListOfSynonyms.get(0).toString();\r\n\t\t\t tMap.put(indexvalue, individualListOfSynonyms);\r\n\t\t\t //br.close();\r\n\t\t\t //System.out.println(tMap);\r\n\t\t\t }\r\n\t\t\t}","public void setDocsInfo(String path) {\n BufferedReader br = null;\n try {\n br = new BufferedReader(new FileReader(new File(path)));\n String line = \"\";\n while ((line = (br.readLine())) != null) {\n String [] splitLineByDelimiter = line.split(\", \");\n String docId = splitLineByDelimiter[0].substring(0, splitLineByDelimiter[0].indexOf(\":\"));\n String docLength = splitLineByDelimiter[1];\n docsInfo.put(docId, Integer.parseInt(docLength));\n }\n br.close();\n } catch (IOException e) {\n e.printStackTrace();\n }\n\n }","private void createDocs() {\n\t\t\n\t\tArrayList<Document> docs=new ArrayList<>();\n\t\tString foldername=\"E:\\\\graduate\\\\cloud\\\\project\\\\data\\\\input\";\n\t\tFile folder=new File(foldername);\n\t\tFile[] listOfFiles = folder.listFiles();\n\t\tfor (File file : listOfFiles) {\n\t\t\ttry {\n\t\t\t\tFileInputStream fisTargetFile = new FileInputStream(new File(foldername+\"\\\\\"+file.getName()));\n\t\t\t\tString fileContents = IOUtils.toString(fisTargetFile, \"UTF-8\");\n\t\t\t\tString[] text=fileContents.split(\"ParseText::\");\n\t\t\t\tif(text.length>1){\n\t\t\t\t\tString snippet=text[1].trim().length()>100 ? text[1].trim().substring(0, 100): text[1].trim();\n\t\t\t\t\tDocument doc=new Document();\n\t\t\t\t\tdoc.setFileName(file.getName().replace(\".txt\", \"\"));\n\t\t\t\t\tdoc.setUrl(text[0].split(\"URL::\")[1].trim());\n\t\t\t\t\tdoc.setText(snippet+\"...\");\n\t\t\t\t\tdocs.add(doc);\n\t\t\t\t}\n\t\t\t}catch(IOException e){\n\t\t\t\te.printStackTrace();\n\t\t\t}\t\n\t\t}\t\n\t\tDBUtil.insertDocs(docs);\n\t}","private void setUpPlaces(){\n db.collection(\"Tokens\").get()\n .addOnCompleteListener(new OnCompleteListener<QuerySnapshot>() {\n @Override\n public void onComplete(@NonNull Task<QuerySnapshot> task) {\n if (task.isSuccessful()) {\n for (QueryDocumentSnapshot document : task.getResult()) {\n String id = document.getId();\n String name = document.get(\"name\").toString();\n String desc = document.get(\"description\").toString();\n String[] latLng = document.get(\"latlng\").toString().split(\",\");\n double latitude = Double.parseDouble(latLng[0]);\n double longitude = Double.parseDouble(latLng[1]);\n places.add(new PlaceToken(id, name, desc, new LatLng(latitude, longitude)));\n }\n }\n }\n });\n }","public void map(Object key, Text value, Context context\n\t\t ) throws IOException, InterruptedException {\n\n\t\t\t\n\t\t\t\n\t\t\t \n\t\t\t String curr_string=value.toString();\n\t\t\t /// splitting based on \"*\" as a delimiter...\n\t\t\t String [] parts=curr_string.split(\"\\\\*\");\n\t\t\t String curr_key=parts[0];\n\t\t\t // Removing spaces from both left and right part of the string..\n\t\t\t String curr_value=parts[1].trim();\n\t\t\t String [] small_parts=curr_value.split(\",\");\n\t\t\t // Taking the count of unique files which are present in the input given to tfidf\n\t\t\t int no_of_unique_files=Integer.parseInt(small_parts[small_parts.length-1]);\n\t\t\t /// The formula to compute idf is log((1+no_of_files)/no_of_unique_files))....\n\t\t\t Configuration conf=context.getConfiguration();\n\t\t\t String value_count=conf.get(\"test\");\n\t\t\t if(!value_count.isEmpty())\n\t\t\t {\n\t\t\t int total_no_files=Integer.parseInt(value_count);\n\t\t\t double x=(total_no_files/no_of_unique_files);\n\t\t\t // Formula fo rcomputing the idf value....\n\t\t\t double idf_value=Math.log10(1+x);\n\t\t\t for(int i=0;i<small_parts.length-1;i++)\n\t\t\t {\n\t\t\t\t String [] waste=small_parts[i].split(\"=\");\n\t\t\t\t String file_name=waste[0];\n\t\t\t\t // Computing the tfidf on the fly...\n\t\t\t\t double tf_idf=idf_value*Double.parseDouble(waste[1]);\n\t\t\t\t Text word3 = new Text();\n\t\t\t\t Text word4 = new Text();\n\t\t\t\t word3.set(curr_key+\"#####\"+file_name+\",\");\n\t\t\t\t word4.set(tf_idf+\"\");\n\t\t\t\t context.write(word3,word4);\n\t\t\t\t \n\t\t\t }\n\t\t\t //word1.set(curr_key);\n\t\t\t //word2.set(idf_value+\"\");\n\t\t\t //context.write(word1,word2); \n\t\t\t} \n\t\t}","public static void DumpLocationCoordinatestoKMLRevised(Places places) throws IOException{\n\n String filen = folder_path+\"loc2kmlRevised.txt\";\n File file = new File(filen);\n if (!file.exists()) {\n file.createNewFile();\n }\n BufferedWriter output = new BufferedWriter(new FileWriter(file));\n\n for(int i=0;i<places.places.size();i++){\n LocationCluster locationcls=places.places.get(i);\n output.write(locationcls.placeID+\"~\");\n\n List<UserPhoto> sublist=locationcls.getIdenticalsubLocations();\n if(sublist.size()>2){\n\n for(int j=0;j<sublist.size()-1;j++){\n\n output.write(sublist.get(j).geotag.lat+\",\"+sublist.get(j).geotag.lng);\n if(j<sublist.size()-2){\n output.write(\"|\");\n }\n }\n\n }\n else{\n\n GeoTag center =locationcls.GetCentriod();\n output.write(center.lat+\",\"+center.lng);\n }\n\n\n output.write(\"\\n\");\n\n\n\n\n }\noutput.flush();\n\n }","private void loadLoreEntries() {\n entryIDMap = new ConcurrentHashMap<>();\n entryIDThreads = new ThreadGroup(\"entryIDThreads\");\n\n for (int i = 0; i < bookSelectionData.size(); i++) {\n\n final String entryName = bookSelectionData.get(i).getBookName();\n final long entryID = bookSelectionData.get(i).getBookID();\n\n new Thread(entryIDThreads, new Runnable() {\n @Override\n public void run() {\n try {\n ArrayList<Long> arraylist = new ArrayList<>();\n arraylist.add(entryID);\n DataAccessObject_LoreBookSelectionDefinition node = database.getDao().getPresentationNodeById(arraylist).get(0);\n JsonObject json = node.getJson();\n JsonArray entryNodes = json.getAsJsonObject(\"children\").getAsJsonArray(\"records\");\n\n long[] ID = new long[entryNodes.size()];\n for (int j = 0; j < entryNodes.size(); j++) {\n JsonObject entry = (JsonObject) entryNodes.get(j);\n long hash = Long.parseLong(entry.get(\"recordHash\").getAsString());\n ID[j] = convertHash(hash);\n }\n entryIDMap.put(entryName, ID);\n } catch (Exception ignored) {\n }\n }\n }).start();\n }\n }","private void saveInFile() {\n\t\tthis.deleteFile();\n\t\tfor (CounterModel obj : counterListModel.getCounterList()) {\n\t\t\ttry {\n\t\t\t\tGson gson = new Gson();\n\t\t\t\tif (obj.getCounterName().equals(counterModel.getCounterName())) {\n\t\t\t\t\tobj = counterModel;\n\t\t\t\t}\n\t\t\t\tString json = gson.toJson(obj) +'\\n';\n\t\t\t\tFileOutputStream fos = openFileOutput(FILENAME,\n\t\t\t\t\t\tContext.MODE_APPEND);\n\t\t\t\tfos.write(json.getBytes());\n\t\t\t\tfos.close();\n\t\t\t} catch (FileNotFoundException e) {\n\t\t\t\t// TODO Auto-generated catch block\n\t\t\t\te.printStackTrace();\n\t\t\t} catch (IOException e) {\n\t\t\t\t// TODO Auto-generated catch block\n\t\t\t\te.printStackTrace();\n\t\t\t}\n\t\t}\n\t}","public void allartistsongs() throws IOException{\r\n List<String> ArrangersAndTheirSongs=new ArrayList<>();\r\n String allsongs=\"\";\r\n int counter=0;\r\n for(int id: ArrangersMap.keySet()){\r\n String ArrangerName=ArrangersMap.get(id);\r\n for(String song:ArrangerLinesList){\r\n String perform[];\r\n perform=song.split(\"/\");\r\n int arrangeid=Integer.parseInt(perform[1]);\r\n if(id==arrangeid){\r\n int songid= Integer.parseInt(perform[0]);\r\n String songname=test.getsongName(songid);\r\n allsongs+=songname+\" \";\r\n counter++;\r\n } \r\n }\r\n ArrangersAndTheirSongs.add(\"The Arranger's Name is:\"+ArrangerName+\" The number of songs is:\"+counter+ \" Their songs are:\"+allsongs);\r\n allsongs=\"\";\r\n counter=0;\r\n }\r\n writeListToTextFile(\"d:\\\\documents\\\\textfiles\\\\ArrangersAndTheirSongs.txt\",ArrangersAndTheirSongs);\r\n // test.writeSongs(\"d:\\\\documents\\\\textfiles\\\\ArrangersAndTheirSongs.txt\");\r\n // Path path=Paths.get()\r\n for(String line:ArrangersAndTheirSongs){\r\n System.out.println(line);\r\n }\r\n System.out.println(ArrangersAndTheirSongs.size());\r\n \r\n System.out.println(\"The size of ArrangersMap is:\"+ArrangersMap.size());\r\n System.out.println(\"The counter is:\"+counter);\r\n }","private static void readAndWriteNodes(String name) throws IOException {\n System.out.println(name);\n Map<Long, Long> nodeMap = new HashMap<>();\n boolean firstLine = true;\n fileReader = new BufferedReader(new FileReader(PATH + name));\n fileWriter = new BufferedWriter(new FileWriter(PATH + \"/uid/\" + name));\n String line;\n while ((line = fileReader.readLine()) != null) {\n if (!firstLine) {\n long globalId = getGlobalId();\n String[] lineTokens = LINE_TOKEN_SEPARATOR.split(line);\n long ID = Long.parseLong(lineTokens[0]);\n nodeMap.put(ID, globalId);\n String writeLine = \"\";\n for (int i = 0; i < lineTokens.length; i++) {\n if (i == 0) {\n writeLine += globalId;\n } else {\n writeLine += lineTokens[i];\n }\n writeLine += \"|\";\n }\n fileWriter.write(writeLine);\n fileWriter.newLine();\n vertexCount++;\n globalVertexCount++;\n } else {\n fileWriter.write(line);\n fileWriter.newLine();\n firstLine = false;\n }\n }\n fileWriter.close();\n fileReader.close();\n counterMapNodes.put(name, vertexCount);\n vertexCount = 0;\n vertexList.add(nodeMap);\n }","BsonToken getCurrentToken();","public void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException\n {\n String line = value.toString().toLowerCase();\n\n // Splitting into doc number and its text\n String document_split[] = line.split(\"\\t\",2);\n Text document_number = new Text(document_split[0]);\n\n // Replace all non alphabetic characters and non spaces with a space\n String document_content=document_split[1].replaceAll(\"[^ a-z]+\", \" \");\n\n String bigram_word_1=null;\n String bigram_word_2=null;\n // Tokenize into words\n StringTokenizer tokenizer = new StringTokenizer(document_content);\n int x=0;\n while(tokenizer.hasMoreTokens())\n {\n x+=1;\n if(x==1)\n {\n bigram_word_1=tokenizer.nextToken();\n }\n else\n {\n bigram_word_2=tokenizer.nextToken();\n String bigram_pair_string=bigram_word_1+\" \"+bigram_word_2;\n bigram_pair.set(bigram_pair_string);\n context.write(bigram_pair, document_number);\n break;\n }\n }\n while(tokenizer.hasMoreTokens())\n {\n bigram_word_1=bigram_word_2;\n bigram_word_2=tokenizer.nextToken();\n String bigram_pair_string=bigram_word_1+\" \"+bigram_word_2;\n bigram_pair.set(bigram_pair_string);\n context.write(bigram_pair, document_number);\n }\n }","public void indexCreate()\n {\n try{\n Directory dir = FSDirectory.open(Paths.get(\"indice/\"));\n Analyzer analyzer = new StandardAnalyzer();\n IndexWriterConfig iwc = new IndexWriterConfig(analyzer);\n iwc.setOpenMode(OpenMode.CREATE);\n IndexWriter writer = new IndexWriter(dir,iwc);\n MongoConnection mongo = MongoConnection.getMongo();\n mongo.OpenMongoClient();\n DBCursor cursor = mongo.getTweets();\n Document doc = null;\n\n while (cursor.hasNext()) {\n DBObject cur = cursor.next();\n if (cur.get(\"retweet\").toString().equals(\"false\")) {\n doc = new Document();\n doc.add(new StringField(\"id\", cur.get(\"_id\").toString(), Field.Store.YES));\n doc.add(new TextField(\"text\", cur.get(\"text\").toString(), Field.Store.YES));\n doc.add(new StringField(\"analysis\", cur.get(\"analysis\").toString(), Field.Store.YES));\n //doc.add(new StringField(\"finalCountry\",cur.get(\"finalCountry\").toString(),Field.Store.YES));\n doc.add(new StringField(\"userScreenName\", cur.get(\"userScreenName\").toString(), Field.Store.YES));\n doc.add(new StringField(\"userFollowersCount\", cur.get(\"userFollowersCount\").toString(), Field.Store.YES));\n doc.add(new StringField(\"favoriteCount\", cur.get(\"favoriteCount\").toString(), Field.Store.YES));\n\n if (writer.getConfig().getOpenMode() == OpenMode.CREATE) {\n System.out.println(\"Indexando el tweet: \" + doc.get(\"text\") + \"\\n\");\n writer.addDocument(doc);\n System.out.println(doc);\n } else {\n System.out.println(\"Actualizando el tweet: \" + doc.get(\"text\") + \"\\n\");\n writer.updateDocument(new Term(\"text\" + cur.get(\"text\")), doc);\n System.out.println(doc);\n }\n }\n }\n cursor.close();\n writer.close();\n }\n catch(IOException ioe){\n System.out.println(\" Error en \"+ ioe.getClass() + \"\\n mensaje: \" + ioe.getMessage());\n }\n }","private void indexDocumentHelper(HashMap<String, StringBuilder> fm)\n\t\t\tthrows IOException {\n\n\t\tIndexWriter writer = getIndexWriter();\n\n\t\tDocument doc = new Document();\n\n\t\tfor (int i = 0; i < fieldNames.length; i++) {\n\n\t\t\tif (fieldNames[i].equals(\"DOCNO\")) {\n\n\t\t\t\tdoc.add(new StringField(fieldNames[i], fm.get(fieldNames[i])\n\t\t\t\t\t\t.toString(), Field.Store.YES));\n\t\t\t}\n\n\t\t\telse {\n\t\t\t\tdoc.add(new TextField(fieldNames[i], fm.get(fieldNames[i])\n\t\t\t\t\t\t.toString(), Field.Store.YES));\n\t\t\t}\n\t\t}\n\n\t\twriter.addDocument(doc);\n\n\t}","java.lang.String getDocumentId();","@Override\n\tpublic String getDocumentKey() {\n\t\treturn uid.toString();\n\t}","public void updateMapsRecords(){\n\n // The file to save the maps records\n File file= new File(MAPS_FILE_PATH);\n Document document = DocumentHelper.createDocument();\n Element rootElement = document.addElement(\"xml\");\n if(mapsList==null)\n return;\n for(GridMap themap:mapsList){\n rootElement.add(themap.encode());\n }\n FileOperator.fileWriter(file,document);\n }","@Override\n public void run() {\n FirebaseFirestore.getInstance().collection(\"users/\" + companyID + \"/trips\")\n .addSnapshotListener(new EventListener<QuerySnapshot>() {\n @Override\n public void onEvent(@Nullable QuerySnapshot value, @Nullable FirebaseFirestoreException e) {\n if (e != null) {\n Log.w(TAG, \"Listen failed.\", e);\n return;\n }\n tripList.clear();//clear the ArrayList, because this method get all the document id instead of\n //the one that just created\n for (QueryDocumentSnapshot doc : value) {\n if (doc.getId() != null) {\n tripList.add(doc.getId());//store the document IDs to ArrayList\n\n Log.d(TAG, \"Retrieved data: \" + doc.getId());\n }\n }\n showTripList();//show trip name to listView\n }\n });\n }","@RequestMapping(\"/showUpload\")\n\tpublic String showDocument(ModelMap map){\n\t\t//get all DB records and send to UI\n\t\tList<Object[]> ob=service.getFileIdAndNames();\n\t\tmap.addAttribute(\"listOb\", ob);\n\t\treturn \"UploadFile\";\n\t}","public static void main(String[] args) throws Exception \n\t{\n\t\tList<String> stopWords = new ArrayList<String>();\n\t\tstopWords = stopWordsCreation();\n\n\n\t\t\n\t\tHashMap<Integer, String> hmap = new HashMap<Integer, String>();\t//Used in tittle, all terms are unique, and any dups become \" \"\n\t\n\t\t\n\t\tList<String> uniqueTerms = new ArrayList<String>();\n\t\tList<String> allTerms = new ArrayList<String>();\n\t\t\t\t\n\t\t\n\t\tHashMap<Integer, String> hmap2 = new HashMap<Integer, String>();\n\t\tHashMap<Integer, String> allValues = new HashMap<Integer, String>();\n\t\tHashMap<Integer, Double> docNorms = new HashMap<Integer, Double>();\n\t\t\n\t\t\n\t\t\n\t\t\n\t\tMap<Integer, List<String>> postingsFileListAllWords = new HashMap<>();\t\t\n\t\tMap<Integer, List<String>> postingsFileList = new HashMap<>();\n\t\t\n\t\tMap<Integer, List<StringBuilder>> docAndTitles = new HashMap<>();\n\t\tMap<Integer, List<StringBuilder>> docAndAbstract = new HashMap<>();\n\t\tMap<Integer, List<StringBuilder>> docAndAuthors = new HashMap<>();\n\t\t\n\t\t\n\t\tMap<Integer, List<Double>> termWeights = new HashMap<>();\n\t\t\n\t\tList<Integer> docTermCountList = new ArrayList<Integer>();\n\t\t\n\t\tBufferedReader br = null;\n\t\tFileReader fr = null;\n\t\tString sCurrentLine;\n\n\t\tint documentCount = 0;\n\t\tint documentFound = 0;\n\t\tint articleNew = 0;\n\t\tint docTermCount = 0;\n\t\t\n\t\t\n\t\tboolean abstractReached = false;\n\n\t\ttry {\n\t\t\tfr = new FileReader(FILENAME);\n\t\t\tbr = new BufferedReader(fr);\n\n\t\t\t// Continues to get 1 line from document until it reaches the end of EVERY doc\n\t\t\twhile ((sCurrentLine = br.readLine()) != null) \n\t\t\t{\n\t\t\t\t// sCurrentLine now contains the 1 line from the document\n\n\t\t\t\t// Take line and split each word and place them into array\n\t\t\t\tString[] arr = sCurrentLine.split(\" \");\n\n\n\t\t\t\t//Go through the entire array\n\t\t\t\tfor (String ss : arr) \n\t\t\t\t{\n\t\t\t\t\t\n\t\t\t\t\t/*\n\t\t\t\t\t * This section takes the array and checks to see if it has reached a new\n\t\t\t\t\t * document or not. If the current line begins with an .I, then it knows that a\n\t\t\t\t\t * document has just started. If it incounters another .I, then it knows that a\n\t\t\t\t\t * new document has started.\n\t\t\t\t\t */\n\t\t\t\t\t//System.out.println(\"Before anything: \"+sCurrentLine);\n\t\t\t\t\tif (arr[0].equals(\".I\")) \n\t\t\t\t\t{\t\t\t\t\t\t\n\t\t\t\t\t\tif (articleNew == 0) \n\t\t\t\t\t\t{\n\t\t\t\t\t\t\tarticleNew = 1;\n\t\t\t\t\t\t\tdocumentFound = Integer.parseInt(arr[1]);\n\t\t\t\t\t\t} \n\t\t\t\t\t\telse if (articleNew == 1) \n\t\t\t\t\t\t{\n\t\t\t\t\t\t\tarticleNew = 0;\n\t\t\t\t\t\t\tdocumentFound = Integer.parseInt(arr[1]);\n\t\t\t\t\t\t}\t\t\t\n\t\t\t\t\t\t//System.out.println(documentFound);\n\t\t\t\t\t\t//count++;\n\t\t\t\t\t\tbreak;\n\t\t\t\t\t}\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t/* This section detects that after a document has entered,\n\t\t\t\t\t * it has to gather all the words contained in the title \n\t\t\t\t\t * section.\n\t\t\t\t\t */\n\t\t\t\t\tif (arr[0].equals(\".T\") ) \n\t\t\t\t\t{\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t// Go to line UNDER .T since that is where tittle is located\n\t\t\t\t\t\t//sCurrentLine = br.readLine();\n\t\t\t\t\t\tdocAndTitles.put(documentFound, new ArrayList<StringBuilder>());\n\t\t\t\t\t\t//System.out.println(\"docAndTitles.get(documentCount+1): \" +docAndTitles.get(documentFound));\n\t\t\t\t\t\t//System.out.println(\"Docs and titles: \"+docAndTitles);\n\t\t\t\t\t\tStringBuilder title = new StringBuilder();\n\t\t\t\t\t\t\n\t\t\t\t\t\twhile ( !(sCurrentLine = br.readLine()).matches(\".B|.A|.N|.X|.K|.C\") )\n\t\t\t\t\t\t{\t\t\t\t\n\t\t\t\t\t\t\t/* In this section, there are 2 lists being made. One list\n\t\t\t\t\t\t\t * is for all the unique words in every title in the document (hmap).\n\t\t\t\t\t\t\t * Hmap contains all unique words, and anytime a duplicate word is \n\t\t\t\t\t\t\t * found, it is replaced with an empty space in the map.\n\t\t\t\t\t\t\t * All Values \n\t\t\t\t\t\t\t * \n\t\t\t\t\t\t\t */\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t//postingsFileList.put(documentFound - 1, new ArrayList<String>());\n\t\t\t\t\t\t\t//postingsFileList.get(documentFound - 1).add(term2);\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t//System.out.println(\"current line: \"+sCurrentLine);\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\tString[] tittle = sCurrentLine.split(\" \");\n\t\t\t\t\t\t\tif (tittle[0].equals(\".W\") )\n\t\t\t\t\t\t\t{\t\t\n\t\t\t\t\t\t\t\tabstractReached = true;\n\t\t\t\t\t\t\t\tbreak;\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\ttitle.append(sCurrentLine);\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\tfor (String tittleWords : tittle)\n\t\t\t\t\t\t\t{\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\ttittleWords = tittleWords.toLowerCase();\n\t\t\t\t\t\t\t\ttittleWords = tittleWords.replaceAll(\"[-&^%'{}*|$+\\\\/\\\\?!<>=.,;_:()\\\\[\\\\]\\\"\\\\d]\", \"\");\n\t\t\t\t\t\t\t\ttittleWords = tittleWords.replaceAll(\"[-&^%'*{}|$+\\\\/\\\\?!<>=.,;_:()\\\\[\\\\]\\\"\\\\d]\", \"\");\n\t\t\t\t\t\t\t\ttittleWords = tittleWords.replaceAll(\"[-&^%'{}*|$+\\\\/\\\\?!<>=.,;_:()\\\\[\\\\]\\\"\\\\d]\", \"\");\n\t\t\t\t\t\t\t\t//System.out.println(tittleWords);\n\t\t\t\t\t\t\t\tif (hmap.containsValue(tittleWords)) \n\t\t\t\t\t\t\t\t{\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\thmap.put(documentCount, \" \");\n\t\t\t\t\t\t\t\t\tallValues.put(documentCount, tittleWords);\n\t\t\t\t\t\t\t\t\tallTerms.add(tittleWords);\n\t\t\t\t\t\t\t\t\tdocumentCount++;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\telse \n\t\t\t\t\t\t\t\t{\n\t\t\t\t\t\t\t\t\tallTerms.add(tittleWords);\n\t\t\t\t\t\t\t\t\tallValues.put(documentCount, tittleWords);\n\t\t\t\t\t\t\t\t\thmap.put(documentCount, tittleWords);\n\t\t\t\t\t\t\t\t\tif (!(uniqueTerms.contains(tittleWords)))\n\t\t\t\t\t\t\t\t\t{\n\t\t\t\t\t\t\t\t\t\tif ((stopWordsSetting && !(stopWords.contains(tittleWords))))\n\t\t\t\t\t\t\t\t\t\t\tuniqueTerms.add(tittleWords);\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tdocumentCount++;\n\t\t\t\t\t\t\t\t}\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t//docAndTitles.get(documentCount).add(\" \");\n\t\t\t\t\t\t\ttitle.append(\"\\n\");\n\t\t\t\t\t\t}\n\t\t\t\t\t\t//System.out.println(\"Title: \"+title);\n\t\t\t\t\t\t//System.out.println(\"docAndTitles.get(documentCount+1): \" +docAndTitles.get(documentFound));\n\t\t\t\t\t\tdocAndTitles.get(documentFound).add(title);\n\t\t\t\t\t\t//System.out.println(\"Done!: \"+ docAndTitles);\n\t\t\t\t\t}\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\tif (arr[0].equals(\".A\") ) \n\t\t\t\t\t{\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t// Go to line UNDER .T since that is where tittle is located\n\t\t\t\t\t\t//sCurrentLine = br.readLine();\n\t\t\t\t\t\tdocAndAuthors.put(documentFound, new ArrayList<StringBuilder>());\n\t\t\t\t\t\t//System.out.println(\"docAndTitles.get(documentCount+1): \" +docAndTitles.get(documentFound));\n\t\t\t\t\t\t//System.out.println(\"Docs and titles: \"+docAndTitles);\n\t\t\t\t\t\tStringBuilder author = new StringBuilder();\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\twhile ( !(sCurrentLine = br.readLine()).matches(\".N|.X|.K|.C\") )\n\t\t\t\t\t\t{\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t/* In this section, there are 2 lists being made. One list\n\t\t\t\t\t\t\t * is for all the unique words in every title in the document (hmap).\n\t\t\t\t\t\t\t * Hmap contains all unique words, and anytime a duplicate word is \n\t\t\t\t\t\t\t * found, it is replaced with an empty space in the map.\n\t\t\t\t\t\t\t * All Values \n\t\t\t\t\t\t\t * \n\t\t\t\t\t\t\t */\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t//postingsFileList.put(documentFound - 1, new ArrayList<String>());\n\t\t\t\t\t\t\t//postingsFileList.get(documentFound - 1).add(term2);\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t//System.out.println(\"current line: \"+sCurrentLine);\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\tString[] tittle = sCurrentLine.split(\" \");\n\t\t\t\t\t\t\tif (tittle[0].equals(\".W\") )\n\t\t\t\t\t\t\t{\t\t\n\t\t\t\t\t\t\t\tabstractReached = true;\n\t\t\t\t\t\t\t\tbreak;\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\tauthor.append(sCurrentLine);\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t//docAndTitles.get(documentCount).add(\" \");\n\t\t\t\t\t\t\tauthor.append(\"\\n\");\n\t\t\t\t\t\t}\n\t\t\t\t\t\t//System.out.println(\"Title: \"+title);\n\t\t\t\t\t\t//System.out.println(\"docAndTitles.get(documentCount+1): \" +docAndTitles.get(documentFound));\n\t\t\t\t\t\tdocAndAuthors.get(documentFound).add(author);\n\t\t\t\t\t\t//System.out.println(\"Done!: \"+ docAndTitles);\n\t\t\t\t\t}\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t/* Since there may or may not be an asbtract after\n\t\t\t\t\t * the title, we need to check what the next section\n\t\t\t\t\t * is. We know that every doc has a publication date,\n\t\t\t\t\t * so it can end there, but if there is no abstract,\n\t\t\t\t\t * then it will keep scanning until it reaches the publication\n\t\t\t\t\t * date. If abstract is empty (in tests), it will also finish instantly\n\t\t\t\t\t * since it's blank and goes straight to .B (the publishing date).\n\t\t\t\t\t * Works EXACTLY like Title \t\t \n\t\t\t\t\t */\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\tif (abstractReached) \n\t\t\t\t\t{\t\n\t\t\t\t\t\t//System.out.println(\"\\n\");\n\t\t\t\t\t\t//System.out.println(\"REACHED ABSTRACT and current line is: \" +sCurrentLine);\n\t\t\t\t\t\tdocAndAbstract.put(documentFound, new ArrayList<StringBuilder>());\n\t\t\t\t\t\tStringBuilder totalAbstract = new StringBuilder();\n\t\t\t\t\t\t\n\t\t\t\t\t\twhile ( !(sCurrentLine = br.readLine()).matches(\".T|.I|.A|.N|.X|.K|.C\") )\n\t\t\t\t\t\t{\t\n\t\t\t\t\t\t\tString[] abstaract = sCurrentLine.split(\" \");\n\t\t\t\t\t\t\tif (abstaract[0].equals(\".B\") )\n\t\t\t\t\t\t\t{\t\t\t\n\t\t\t\t\t\t\t\tabstractReached = false;\n\t\t\t\t\t\t\t\tbreak;\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\ttotalAbstract.append(sCurrentLine);\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\tString[] misc = sCurrentLine.split(\" \");\n\t\t\t\t\t\t\tfor (String miscWords : misc) \n\t\t\t\t\t\t\t{\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tmiscWords = miscWords.toLowerCase(); \n\t\t\t\t\t\t\t\tmiscWords = miscWords.replaceAll(\"[-&^%'*$+|{}?!\\\\/<\\\\>=.,;_:()\\\\[\\\\]\\\"\\\\d]\", \"\");\n\t\t\t\t\t\t\t\tmiscWords = miscWords.replaceAll(\"[-&^%'*$+|?{}!\\\\/<\\\\>=.,;_:()\\\\[\\\\]\\\"\\\\d]\", \"\");\t\t\n\t\t\t\t\t\t\t\tmiscWords = miscWords.replaceAll(\"[-&^%'*$+|{}?!\\\\/<\\\\>=.,;_:()\\\\[\\\\]\\\"\\\\d]\", \"\");\t\t\n\t\t\t\t\t\t\t\t//System.out.println(miscWords);\n\t\t\t\t\t\t\t\tif (hmap.containsValue(miscWords)) \n\t\t\t\t\t\t\t\t{\n\t\t\t\t\t\t\t\t\thmap.put(documentCount, \" \");\n\t\t\t\t\t\t\t\t\tallValues.put(documentCount, miscWords);\n\t\t\t\t\t\t\t\t\tallTerms.add(miscWords);\n\t\t\t\t\t\t\t\t\tdocumentCount++;\n\t\n\t\t\t\t\t\t\t\t} \n\t\t\t\t\t\t\t\telse \n\t\t\t\t\t\t\t\t{\n\t\t\t\t\t\t\t\t\tallTerms.add(miscWords);\n\t\t\t\t\t\t\t\t\thmap.put(documentCount, miscWords);\n\t\t\t\t\t\t\t\t\tallValues.put(documentCount, miscWords);\n\t\t\t\t\t\t\t\t\tif (!(uniqueTerms.contains(miscWords)))\n\t\t\t\t\t\t\t\t\t{\n\t\t\t\t\t\t\t\t\t\tif ((stopWordsSetting && !(stopWords.contains(miscWords))))\n\t\t\t\t\t\t\t\t\t\t\tuniqueTerms.add(miscWords);\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tdocumentCount++;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\t\n\t\t\t\t\t\t\ttotalAbstract.append(\"\\n\");\n\t\t\t\t\t\t}\n\t\t\t\t\t\tdocAndAbstract.get(documentFound).add(totalAbstract);\n\t\t\t\t\t}\n\t\t\t\t\t\n\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t}\t\n\t\t\t\t\n\t\t\t\t//Once article is found, we enter all of of it's title and abstract terms \n\t\t\t\tif (articleNew == 0) \n\t\t\t\t{\n\t\t\t\t\t\n\t\t\t\t\tdocumentFound = documentFound - 1;\n\t\t\t\t\t//System.out.println(\"Words found in Doc: \" + documentFound);\n\t\t\t\t\t//System.out.println(\"Map is\" +allValues);\n\t\t\t\t\tSet set = hmap.entrySet();\n\t\t\t\t\tIterator iterator = set.iterator();\n\n\t\t\t\t\tSet set2 = allValues.entrySet();\n\t\t\t\t\tIterator iterator2 = set2.iterator();\n\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\tpostingsFileList.put(documentFound - 1, new ArrayList<String>());\n\t\t\t\t\tpostingsFileListAllWords.put(documentFound - 1, new ArrayList<String>());\n\t\t\t\t\twhile (iterator.hasNext()) {\n\t\t\t\t\t\tMap.Entry mentry = (Map.Entry) iterator.next();\n\t\t\t\t\t\t// (\"key is: \"+ mentry.getKey() + \" & Value is: \" + mentry.getValue());\n\t\t\t\t\t\t// (\"Value is: \" + mentry.getValue());\n\t\t\t\t\t\t// );\n\t\t\t\t\t\tString term = mentry.getValue().toString();\n\t\t\t\t\t\t// //\"This is going to be put in doc3: \"+ (documentFound-1));\n\t\t\t\t\t\tpostingsFileList.get(documentFound - 1).add(term);\n\t\t\t\t\t\t// if ( !((mentry.getValue()).equals(\" \")) )\n\t\t\t\t\t\tdocTermCount++;\n\t\t\t\t\t}\n\t\t\t\t\t// \"BEFORE its put in, this is what it looks like\" + hmap);\n\t\t\t\t\thmap2.putAll(hmap);\n\t\t\t\t\thmap.clear();\n\t\t\t\t\tarticleNew = 1;\n\n\t\t\t\t\tdocTermCountList.add(docTermCount);\n\t\t\t\t\tdocTermCount = 0;\n\n\t\t\t\t\twhile (iterator2.hasNext()) {\n\t\t\t\t\t\tMap.Entry mentry2 = (Map.Entry) iterator2.next();\n\t\t\t\t\t\t// (\"key is: \"+ mentry.getKey() + \" & Value is: \" + mentry.getValue());\n\t\t\t\t\t\t// (\"Value2 is: \" + mentry2.getValue());\n\t\t\t\t\t\t// );\n\t\t\t\t\t\tString term = mentry2.getValue().toString();\n\t\t\t\t\t\t// //\"This is going to be put in doc3: \"+ (documentFound-1));\n\t\t\t\t\t\tpostingsFileListAllWords.get(documentFound - 1).add(term);\n\t\t\t\t\t\t// if ( !((mentry.getValue()).equals(\" \")) )\n\t\t\t\t\t\t// docTermCount++;\n\t\t\t\t\t}\n\n\t\t\t\t\tallValues.clear();\t\t\t\t\t\n\t\t\t\t\tdocumentFound = Integer.parseInt(arr[1]);\n\n\t\t\t\t\t// \"MEANWHILE THESE ARE ALL VALUES\" + postingsFileListAllWords);\n\n\t\t\t\t}\t\t\t\t\t\t\t\n\t\t\t}\n\t\t\t\n\t\t\t\n\t\t\t\n\t\t\t//System.out.println(\"Looking at final doc!\");\n\t\t\t//Final loop for last sets\n\t\t\tSet set = hmap.entrySet();\n\t\t\tIterator iterator = set.iterator();\n\n\t\t\tSet setA = allValues.entrySet();\n\t\t\tIterator iteratorA = setA.iterator();\n\t\t\tpostingsFileList.put(documentFound - 1, new ArrayList<String>());\n\t\t\tpostingsFileListAllWords.put(documentFound - 1, new ArrayList<String>());\n\t\t\twhile (iterator.hasNext()) {\n\t\t\t\tMap.Entry mentry = (Map.Entry) iterator.next();\n\t\t\t\t// (\"key is: \"+ mentry.getKey() + \" & Value is: \" + mentry.getValue());\n\t\t\t\t// (\"Value is: \" + mentry.getValue());\n\t\t\t\t// //);\n\t\t\t\t// if ( !((mentry.getValue()).equals(\" \")) )\n\t\t\t\tString term2 = mentry.getValue().toString();\n\t\t\t\tpostingsFileList.get(documentFound - 1).add(term2);\n\n\t\t\t\tdocTermCount++;\n\t\t\t}\n\t\t\t//System.out.println(\"Done looking at final doc!\");\n\t\t\t\n\t\t\t\n\t\t\t//System.out.println(\"Sorting time!\");\n\t\t\twhile (iteratorA.hasNext()) {\n\t\t\t\tMap.Entry mentry2 = (Map.Entry) iteratorA.next();\n\t\t\t\t// (\"key is: \"+ mentry.getKey() + \" & Value is: \" + mentry.getValue());\n\t\t\t\t// (\"Value2 is: \" + mentry2.getValue());\n\t\t\t\t// //);\n\t\t\t\tString term = mentry2.getValue().toString();\n\t\t\t\t// //\"This is going to be put in doc3: \"+ (documentFound-1));\n\t\t\t\tpostingsFileListAllWords.get(documentFound - 1).add(term);\n\t\t\t\t// if ( !((mentry.getValue()).equals(\" \")) )\n\t\t\t\t// docTermCount++;\n\t\t\t}\n\n\t\t\thmap2.putAll(hmap);\n\t\t\thmap.clear();\n\t\t\tdocTermCountList.add(docTermCount);\n\t\t\tdocTermCount = 0;\n\n\n\t\t\t\n\t\t\n\t\t\t// END OF LOOKING AT ALL DOCS\n\t\t\t\n\t\t\t//System.out.println(\"Docs and titles: \"+docAndTitles);\n\t\t\t\n\t\t\t//System.out.println(\"All terms\" +allTerms);\n\t\t\tString[] sortedArray = allTerms.toArray(new String[0]);\n\t\t\tString[] sortedArrayUnique = uniqueTerms.toArray(new String[0]);\n\t\t\t//System.out.println(Arrays.toString(sortedArray));\n\t\t\t\n\t\t\tArrays.sort(sortedArray);\n\t\t\tArrays.sort(sortedArrayUnique);\n\t\t\t\n\t\t\t\n\t\t\t\n\t\t\t//Sortings \n\t\t\tSet set3 = hmap2.entrySet();\n\t\t\tIterator iterator3 = set3.iterator();\n\n\t\t\t// Sorting the map\n\t\t\t//System.out.println(\"Before sorting \" +hmap2);\t\t\t\n\t\t\tMap<Integer, String> map = sortByValues(hmap2);\n\t\t\t//System.out.println(\"after sorting \" +map);\n\t\t\t// //\"After Sorting:\");\n\t\t\tSet set2 = map.entrySet();\n\t\t\tIterator iterator2 = set2.iterator();\n\t\t\tint docCount = 1;\n\t\t\twhile (iterator2.hasNext()) {\n\t\t\t\tMap.Entry me2 = (Map.Entry) iterator2.next();\n\t\t\t\t// (me2.getKey() + \": \");\n\t\t\t\t// //me2.getValue());\n\t\t\t}\n\t\t\t\n\t\t\t//System.out.println(\"Done sorting!\");\n\t\t\n\t\t\t\n\t\t\t\n\t\t\t\n\t\t\t//System.out.println(\"Posting starts \");\n\t\t\t//\"THIS IS START OF DICTIONARTY\" \n\t\t\tBufferedWriter bw = null;\n\t\t\tFileWriter fw = null;\n\t\t\t\n\t\t\t\n\t\t\t//System.out.println(\"Start making an array thats big as every doc total \");\n\t\t\tfor (int z = 1; z < documentFound+1; z++)\n\t\t\t{\n\t\t\t\ttermWeights.put(z, new ArrayList<Double>());\n\t\t\t}\n\t\t\t//System.out.println(\"Done making that large array Doc \");\n\t\t\t\n\t\t\t//System.out.println(\"Current Weights: \"+termWeights);\n\t\t\t\n\t\t\t//System.out.println(\"All terms\" +allTerms)\n\t\t\t//System.out.println(Arrays.toString(sortedArray));\n\t\t\t//System.out.println(Arrays.toString(sortedArrayUnique));\n\t\t\t//System.out.println(uniqueTerms);\n\t\t\t\n\t\t\t\n\t\t\t\n\t\t\t//\tSystem.out.println(\"Posting starts \");\n\t\t\t// \tPOSTING FILE STARTS \n\t\t\ttry {\n\t\t\t\t// Posting File\n\t\t\t\t//System.out.println(\"postingsFileListAllWords: \"+postingsFileListAllWords); //Contains every word including Dups, seperated per doc\n\t\t\t\t//System.out.println(\"postingsFileList: \"+postingsFileList); \t\t //Contains unique words, dups are \" \", seperated per doc\n\t\t\t\t//System.out.println(\"postingsFileListAllWords.size(): \" +postingsFileListAllWords.size()); //Total # of docs \n\t\t\t\t//System.out.println(\"Array size: \"+sortedArrayUnique.length);\n\n\t\t\t\tfw = new FileWriter(POSTING);\n\t\t\t\tbw = new BufferedWriter(fw);\n\t\t\t\tString temp = \" \";\n\t\t\t\tDouble termFreq = 0.0;\n\t\t\t\t// //postingsFileListAllWords);\n\t\t\t\tList<String> finalTermList = new ArrayList<String>();\n\t\t\t\t\n\t\t\t\t\n\t\t\t\n\t\t\t\t\t// //postingsFileList.get(i).size());\n\t\t\t\t\tfor (int j = 0; j < sortedArrayUnique.length; ++j)\t\t\t\t\t // go thru each word, CURRENT TERM\n\t\t\t\t\t{\n\t\t\t\t\t\t//System.out.println(\"Term is: \" + sortedArrayUnique[j]);\n\t\t\t\t\t\ttemp = sortedArrayUnique[j];\t\t\t\t\t\n\t\t\t\t\t\tif ((stopWordsSetting && stopWords.contains(temp))) \n\t\t\t\t\t\t{\t\t\t\t\t\t\n\t\t\t\t\t\t\tcontinue;\n\t\t\t\t\t\t}\n\n\t\t\t\t\t\tif (!(finalTermList.contains(temp))) \n\t\t\t\t\t\t{\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t//PART TO FIND DOCUMENT FREQ\t\t\t\t\t\t\t\n\t\t\t\t\t\t\tint docCountIDF = 0;\n\t\t\t\t\t\t\t//Start here for dictionary \n\t\t\t\t\t\t\tfor (int totalWords = 0; totalWords < sortedArray.length; totalWords++) \t\t\n\t\t\t\t\t\t\t{\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tif (temp.compareTo(\" \") == 0 || (stopWordsSetting && stopWords.contains(temp))) \n\t\t\t\t\t\t\t\t{\n\t\t\t\t\t\t\t\t\t//EITHER BLANK OR STOPWORD \n\t\t\t\t\t\t\t\t\t//System.out.println(\"fOUND STOP WORD\");\n\t\t\t\t\t\t\t\t\tcontinue;\n\t\t\t\t\t\t\t\t}\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tString temp2 = sortedArray[totalWords];\n\t\t\t\t\t\t\t\t\t//System.out.println(\"Compare: \"+temp+ \" with \" +temp2);\n\t\t\t\t\t\t\t\t\tif (temp.compareTo(temp2) == 0) {\n\t\t\t\t\t\t\t\t\t\t// (temp2+\" \");\t\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\tdocCountIDF++;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t//System.out.println(\"Total Number: \" +docCountIDF);\n\t\t\t\t\t\t\t//System.out.println(\"documentFound: \" +documentFound);\n\t\t\t\t\t\t\t//System.out.println(\"So its \" + documentFound + \" dividied by \" +docCountIDF);\n\t\t\t\t\t\t\t//docCountIDF = 1;\t\t\t\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\tdouble idf = (Math.log10(((double)documentFound/(double)docCountIDF)));\n\t\t\t\t\t\t\t//System.out.println(\"Calculated IDF: \"+idf);\n\t\t\t\t\t\t\tif (idf < 0.0)\n\t\t\t\t\t\t\t{\n\t\t\t\t\t\t\t\tidf = 0.0;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t//System.out.println(\"IDF is: \" +idf);\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t//System.out.println(\"Size of doc words: \" + postingsFileListAllWords.size());\n\t\t\t\t\t\t\tfor (int k = 0; k < postingsFileListAllWords.size(); k++) \t\t//Go thru each doc. Since only looking at 1 term, it does it once per doc\n\t\t\t\t\t\t\t{\n\t\t\t\t\t\t\t\t//System.out.println(\"Current Doc: \" +(k+1));\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\ttermFreq = 1 + (Math.log10(Collections.frequency(postingsFileListAllWords.get(k), temp)));\t\t\t\n\t\t\t\t\t\t\t\t\t//System.out.println(\"Freq is: \" +Collections.frequency(postingsFileListAllWords.get(k), temp));\n\t\t\t\t\t\t\t\t\t//System.out.println(termFreq + \": \" + termFreq.isInfinite());\n\t\t\t\t\t\t\t\t\tif (termFreq.isInfinite() || termFreq <= 0)\n\t\t\t\t\t\t\t\t\t{\n\t\t\t\t\t\t\t\t\t\ttermFreq = 0.0;\n\t\t\t\t\t\t\t\t\t}\t\t\t\t\n\t\t\t\t\t\t\t\t\t//System.out.println(\"termFreq :\" +termFreq); \n\t\t\t\t\t\t\t\t\t//System.out.println(\"idf: \" +idf);\n\t\t\t\t\t\t\t\t\ttermWeights.get(k+1).add( (idf*termFreq) );\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t//System.out.println(\"\");\n\t\t\t\t\t\t\tfinalTermList.add(temp);\t\t\t\t\t\t\t\n\t\t\t\t\t\t}\t\n\t\t\t\t\t\t//System.out.println(\"Current Weights: \"+termWeights);\n\t\t\t\t\t\t\n\t\t\t\t\t\t//FINALCOUNTER\n\t\t\t\t\t\t//System.out.println(\"Done looking at word: \" +j);\n\t\t\t\t\t\t//System.out.println(\"\");\n\t\t\t\t\t}\n\t\t\t\t\t\n\t\t\t\t\t//System.out.println(\"Current Weights: \"+termWeights);\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\twhile (true)\n\t\t\t\t {\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\tSystem.out.println(\"Enter a query: \");\n\t\t\t\t\t\n\t \tScanner scanner = new Scanner(System.in);\n\t \tString enterQuery = scanner.nextLine();\n\t \t\n\t \t\n\t\t\t\t\tList<Double> queryWeights = new ArrayList<Double>();\n\t\t\t\t\t\n\t\t\t\t\t// Query turn\t\t\t\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\tenterQuery = enterQuery.toLowerCase();\t\t\n\t\t\t\t\tenterQuery = enterQuery.replaceAll(\"[-&^%'*$+|{}?!\\\\/<\\\\>=.,;_:()\\\\[\\\\]\\\"]\", \"\");\n\t\t\t\t\t//System.out.println(\"Query is: \" + enterQuery);\n\t\t\t\t\t\n\t\t\t\t\tif (enterQuery.equals(\"exit\"))\n\t\t\t\t\t{\n\t\t\t\t\t\tbreak;\n\t\t\t\t\t}\n\t\t\t\t\tString[] queryArray = enterQuery.split(\" \");\n\t\t\t\t\tArrays.sort(queryArray);\n\t\t\t\t\t\n\t\t\t\t\t//Find the query weights for each term in vocab\n\t\t\t\t\tfor (int j = 0; j < sortedArrayUnique.length; ++j)\t\t\t\t\t // go thru each word, CURRENT TERM\n\t\t\t\t\t{\n\t\t\t\t\t\t//System.out.println(\"Term is: \" + sortedArrayUnique[j]);\n\t\t\t\t\t\ttemp = sortedArrayUnique[j];\t\t\t\t\t\n\t\t\t\t\t\tif ((stopWordsSetting && stopWords.contains(temp))) \n\t\t\t\t\t\t{\t\t\t\t\t\t\n\t\t\t\t\t\t\tcontinue;\n\t\t\t\t\t\t}\n\t\t\t\t\t\n\t\t\t\t\t\tint docCountDF = 0;\n\t\t\t\t\t\t//Start here for dictionary \n\t\t\t\t\t\tfor (int totalWords = 0; totalWords < queryArray.length; totalWords++) \t\t\n\t\t\t\t\t\t{\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\tif (temp.compareTo(\" \") == 0 || (stopWordsSetting && stopWords.contains(temp))) \n\t\t\t\t\t\t\t{\n\t\t\t\t\t\t\t\t//EITHER BLANK OR STOPWORD\n\t\t\t\t\t\t\t\tcontinue;\n\t\t\t\t\t\t\t}\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tString temp2 = queryArray[totalWords];\n\t\t\t\t\t\t\t\t//System.out.println(\"Compare: \"+temp+ \" with \" +temp2);\n\t\t\t\t\t\t\t\tif (temp.compareTo(temp2) == 0) {\n\t\t\t\t\t\t\t\t\t// (temp2+\" \");\t\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tdocCountDF++;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t\tDouble queryWeight = 1 + (Math.log10(docCountDF));\n\t\t\t\t\t\tif (queryWeight.isInfinite())\n\t\t\t\t\t\t{\n\t\t\t\t\t\t\tqueryWeight = 0.0;\n\t\t\t\t\t\t}\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\tqueryWeights.add(queryWeight);\n\t\t\t\t\t}\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t//System.out.println(\"Query WEights is: \"+queryWeights);\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t// Finding the norms for DOCS\t\t\t\t\t\n\t\t\t\t\tfor (int norms = 1; norms < documentFound+1; norms++)\n\t\t\t\t\t{\n\t\t\t\t\t\tdouble currentTotal = 0.0;\n\t\t\t\t\t\t\n\t\t\t\t\t\tfor (int weightsPerDoc = 0; weightsPerDoc < termWeights.get(norms).size(); weightsPerDoc++)\n\t\t\t\t\t\t{\t\t\t\t\t\t\n\t\t\t\t\t\t\tdouble square = Math.pow(termWeights.get(norms).get(weightsPerDoc), 2);\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t//System.out.println(\"Current square: \" + termWeights.get(norms).get(weightsPerDoc));\n\t\t\t\t\t\t\tcurrentTotal = currentTotal + square;\n\t\t\t\t\t\t\t//System.out.println(\"Current total: \" + currentTotal);\n\t\t\t\t\t\t}\n\t\t\t\t\t\t//System.out.println(\"About to square root this: \" +currentTotal);\n\t\t\t\t\t\tdouble root = Math.sqrt(currentTotal);\n\t\t\t\t\t\tdocNorms.put(norms, root);\n\t\t\t\t\t}\n\t\t\t\t\t//System.out.println(\"All of the docs norms: \"+docNorms);\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t//Finding the norm for the query\n\t\t\t\t\tdouble currentTotal = 0.0;\t\t\t\t\t\n\t\t\t\t\tfor (int weightsPerDoc = 0; weightsPerDoc < queryWeights.size(); weightsPerDoc++)\n\t\t\t\t\t{\t\t\t\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\tdouble square = Math.pow(queryWeights.get(weightsPerDoc), 2);\n\t\t\t\t\t\tcurrentTotal = currentTotal + square;\t\t\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t}\n\t\t\t\t\tdouble root = Math.sqrt(currentTotal);\n\t\t\t\t\tdouble queryNorm = root; \t\t\t\t\t\t\n\t\t\t\t\t//System.out.println(\"Query norm \" + queryNorm);\n\t\t\t\t\t\n\t\t\t\t\t//Finding the cosine sim\n\t\t\t\t\t//System.out.println(\"Term Weights \" + termWeights);\n\t\t\t\t\tHashMap<Integer, Double> cosineScore = new HashMap<Integer, Double>();\n\t\t\t\t\tfor (int cosineSim = 1; cosineSim < documentFound+1; cosineSim++)\n\t\t\t\t\t{\n\t\t\t\t\t\tdouble total = 0.0;\n\t\t\t\t\t\tfor (int docTerms = 0; docTerms < termWeights.get(cosineSim).size(); docTerms++)\n\t\t\t\t\t\t{\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\tdouble docTermWeight = termWeights.get(cosineSim).get(docTerms);\n\t\t\t\t\t\t\tdouble queryTermWeight = queryWeights.get(docTerms);\n\t\t\t\t\t\t\t//System.out.println(\"queryTermWeight \" + queryTermWeight);\n\t\t\t\t\t\t\t//System.out.println(\"docTermWeight \" + docTermWeight);\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\ttotal = total + (docTermWeight*queryTermWeight);\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t}\n\t\t\t\t\t\tdouble cosineSimScore = 0.0;\n\t\t\t\t\t\tif (!(total == 0.0 || (docNorms.get(cosineSim) * queryNorm) == 0))\n\t\t\t\t\t\t{\n\t\t\t\t\t\t\tcosineSimScore = total / (docNorms.get(cosineSim) * queryNorm);\n\t\t\t\t\t\t}\n\t\t\t\t\t\telse\n\t\t\t\t\t\t{\n\t\t\t\t\t\t\tcosineSimScore = 0.0;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t\n\t\t\t\t\t\tcosineScore.put(cosineSim, cosineSimScore);\n\t\t\t\t\t}\n\t\t\t\t\tcosineScore = sortByValues2(cosineScore);\t\t\t\t\t\n\t\t\t\t\t//System.out.println(\"This is the cosineScores: \" +cosineScore);\n\t\t\t\t\t\n\t\t\t\t\t//System.out.println(\"docAndTitles: \"+ docAndTitles);\n\t\t\t\t\tint topK = 0;\n\t\t\t\t\tint noValue = 0;\n\t\t\t\t\tfor (Integer name: cosineScore.keySet())\n\t\t\t\t\t{\n\t\t\t\t\t\tif (topK < 50)\n\t\t\t\t\t\t{\t\n\t\t\t\t\t\t\t\n\t\t\t\t String key =name.toString();\n\t\t\t\t //String value = cosineScore.get(name).toString(); \n\t\t\t\t if (!(cosineScore.get(name) <= 0))\n\t\t\t\t {\n\t\t\t\t \tSystem.out.println(\"Doc: \"+key);\t\t\t\t \t\t\t\t\t \t\t\t\t\t \t\n\t\t\t\t \t\n\t\t\t\t \tStringBuilder builder = new StringBuilder();\n\t\t\t\t \tfor (StringBuilder value : docAndTitles.get(name)) {\n\t\t\t\t \t builder.append(value);\n\t\t\t\t \t}\n\t\t\t\t \tString text = builder.toString();\t\t\t\t \t\n\t\t\t\t \t//System.out.println(\"Title:\\n\" +docAndTitles.get(name));\n\t\t\t\t \tSystem.out.println(\"Title: \" +text);\n\t\t\t\t \t\n\t\t\t\t \t\n\t\t\t\t \t\n\t\t\t\t \t\n\t\t\t\t \t\n\t\t\t\t \t//System.out.println(\"Authors:\\n\" +docAndAuthors.get(name));\n\t\t\t\t \t\n\t\t\t\t \tif (docAndAuthors.get(name) == null || docAndAuthors.get(name).toString().equals(\"\"))\n\t\t\t\t \t{\n\t\t\t\t \t\tSystem.out.println(\"Authors: N\\\\A\\n\");\n\t\t\t\t \t}\n\t\t\t\t \telse \n\t\t\t\t \t{\t\t\t\t \t\t\t\t\t\t \t\n\t\t\t\t\t \tStringBuilder builder2 = new StringBuilder();\n\t\t\t\t\t \tfor (StringBuilder value : docAndAuthors.get(name)) {\n\t\t\t\t\t \t builder2.append(value);\n\t\t\t\t\t \t}\n\t\t\t\t\t \tString text2 = builder2.toString();\t\t\t\t \t\n\t\t\t\t\t \t\n\t\t\t\t\t \tSystem.out.println(\"Authors found: \" +text2);\n\t\t\t\t \t}\t\n\t\t\t\t \t\n\t\t\t\t \t\n\t\t\t\t \t/* ABSTRACT \n\t\t\t\t \tif (docAndAbstract.get(name) == null)\n\t\t\t\t \t{\n\t\t\t\t \t\tSystem.out.println(\"Abstract: N\\\\A\\n\");\n\t\t\t\t \t}\n\t\t\t\t \telse \n\t\t\t\t \t{\t\t\t\t \t\t\t\t\t\t \t\n\t\t\t\t\t \tStringBuilder builder2 = new StringBuilder();\n\t\t\t\t\t \tfor (StringBuilder value : docAndAbstract.get(name)) {\n\t\t\t\t\t \t builder2.append(value);\n\t\t\t\t\t \t}\n\t\t\t\t\t \tString text2 = builder2.toString();\t\t\t\t \t\n\t\t\t\t\t \t\n\t\t\t\t\t \tSystem.out.println(\"Abstract: \" +text2);\n\t\t\t\t \t}\t\n\t\t\t\t \t*/\n\t\t\t\t \t\n\t\t\t\t \tSystem.out.println(\"\");\n\t\t\t\t }\n\t\t\t\t else {\n\t\t\t\t \tnoValue++;\n\t\t\t\t }\n\t\t\t\t topK++;\n\t\t\t\t \n\t\t\t\t\t\t}\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\tif (noValue == documentFound)\n\t\t\t\t\t\t{\n\t\t\t\t\t\t\tSystem.out.println(\"No documents contain query!\");\n\t\t\t\t\t\t}\n\t\t\t\t\t} \n\t\t\t\t\ttopK=0;\n\t\t\t\t\tnoValue = 0;\n\t\t\t\t }\n\t\t\t\t\n\t\t\t} finally {\n\t\t\t\ttry {\n\t\t\t\t\tif (bw != null)\n\t\t\t\t\t\tbw.close();\n\n\t\t\t\t\tif (fw != null)\n\t\t\t\t\t\tfw.close();\n\n\t\t\t\t} catch (IOException ex) {\n\n\t\t\t\t\tex.printStackTrace();\n\n\t\t\t\t}\n\n\t\t\t}\n\t\t\t\n\n\t\t} catch (IOException e) {\n\t\t\te.printStackTrace();\n\t\t} finally {\n\t\t\ttry {\n\t\t\t\tif (br != null)\n\t\t\t\t\tbr.close();\n\n\t\t\t\tif (fr != null)\n\t\t\t\t\tfr.close();\n\n\t\t\t} catch (IOException ex) {\n\n\t\t\t\tex.printStackTrace();\n\n\t\t\t}\n\n\t\t}\n\t\t\t\n\t\t\t\n\t\t\t\n\t\t\t\n\t\t\t\n\n\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\tint itemCount = uniqueTerms.size();\n\t\t\t//System.out.println(allValues);\n\t\t\tSystem.out.println(\"Total Terms BEFORE STEMING: \" +itemCount);\n\t\t\tSystem.out.println(\"Total Documents \" + documentFound);\n\t\t\t\t\t\t\n\t\t \n\t\t\t \n\t\t\t \n\t\t\t//END OF MAIN\n\t\t}","public static Map<Object, Object> processDocuments(\n\t\t\tString trainingSetFolderPath,boolean removeStopWords, boolean doSmoothing) {\n\t\tint numTokens = 0; \n\n\t\t// Map to store the processed results.\n\t\tMap<Object, Object> result = new HashMap<Object, Object>(); \n\n\t\t// Map to keep track of words and its frequency\n\n\t\tMap<String, Integer> tokenCntMap = new HashMap<String, Integer>(); \n\n\t\tFile trainingSetFolder = new File(trainingSetFolderPath);\n\t\tFile[] documents = trainingSetFolder.listFiles();\n\t\tfor (File doc : documents) {\n\t\t\ttry {\n\t\t\t\t\n\t\t\t\tBufferedReader bufferedReader = new BufferedReader(\n\t\t\t\t\t\tnew FileReader(doc));\n\t\t\t\tString line;\n\t\t\t\twhile ((line = bufferedReader.readLine()) != null) {\n\t\t\t\t\tString[] tokens = line.split(\"\\\\s+\");\n\t\t\t\t\tnumTokens += tokens.length;\n\t\t\t\t\tif(removeStopWords == false){\n\t\t\t\t\t\tfor (String token : tokens) {\n\t\t\t\t\t\t\ttoken = token.replaceAll(\"[^a-zA-Z]\", \"\");\n\t\t\t\t\t\t\ttoken = token.toLowerCase();\n\t\t\t\t\t\t\tif(!token.isEmpty()){\n\t\t\t\t\t\t\t\tif (tokenCntMap.containsKey(token)) {\n\t\t\t\t\t\t\t\t\ttokenCntMap.put(token, tokenCntMap.get(token)\n\t\t\t\t\t\t\t\t\t\t\t.intValue() + 1);\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ttokenCntMap.put(token, 1);\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t\telse{\n\t\t\t\t\t\tfor (String token : tokens) {\n\t\t\t\t\t\t\ttoken = token.replaceAll(\"[^a-zA-Z]\", \"\");\n\t\t\t\t\t\t\ttoken = token.toLowerCase();\n\t\t\t\t\t\t\tif(!token.isEmpty() && !stopWords.contains(token)){\n\t\t\t\t\t\t\t\tif (tokenCntMap.containsKey(token)) {\n\t\t\t\t\t\t\t\t\ttokenCntMap.put(token, tokenCntMap.get(token)\n\t\t\t\t\t\t\t\t\t\t\t.intValue() + 1);\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ttokenCntMap.put(token, 1);\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t\tbufferedReader.close();\n\t\t\t} catch (Exception e) {\n\t\t\t\te.printStackTrace();\n\t\t\t}\n\t\t}\n\t\tresult.put(\"NumTokens\", numTokens);\n\t\tresult.put(\"NumDocuments\", documents.length);\n\t\tresult.put(\"TokenCntMap\", tokenCntMap);\n\t\treturn result;\n\n\t}","public void fileSaved(OpenDefinitionsDocument doc) { }"],"string":"[\n \"private void saveToken() throws IOException {\\n\\t\\t\\n\\t\\tFileWriter termIdx = new FileWriter(StoragePath+Path.termIdxDir);\\n\\t\\t\\n\\t\\tfor(Entry<String, Integer> term: termDic.entrySet()){\\n\\t\\t\\ttermIdx.append(term.getKey() + \\\"\\\\n\\\" + term.getValue() + \\\"\\\\n\\\");\\n\\t\\t}\\n\\t\\t\\n\\t\\ttermIdx.close();\\n\\t\\t\\n\\t}\",\n \"public static void generateInvertedIndex(Map<String, List<Posting>> stemMap, List<String> documentIds)\\n {\\n long lineCounter = 0;\\n int documentCounter = -1;\\n String currentDocId = \\\"\\\";\\n String currentDocTitle = \\\"\\\";\\n Scanner scanner = new Scanner(System.in);\\n\\n while (scanner.hasNext())\\n {\\n String line = scanner.nextLine();\\n lineCounter++;\\n \\n if (line.startsWith(\\\"$DOC\\\"))\\n {\\n String[] wordStems = line.split(\\\" \\\");\\n currentDocId = wordStems[1];\\n documentCounter++;\\n }\\n else if (line.startsWith(\\\"$TITLE\\\"))\\n {\\n /* Save document titles for documentId list */\\n long docLineNumber = lineCounter - 1;\\n currentDocTitle = \\\"\\\";\\n \\n while (scanner.hasNext())\\n {\\n String nextTitleLine = scanner.nextLine();\\n if (nextTitleLine.startsWith(\\\"$TEXT\\\"))\\n {\\n lineCounter++;\\n documentIds.add(String.format(\\\"%s %d %s\\\\n\\\", currentDocId, docLineNumber, currentDocTitle));\\n break;\\n }\\n else\\n {\\n lineCounter++;\\n currentDocTitle += nextTitleLine;\\n currentDocTitle += \\\" \\\";\\n }\\n }\\n }\\n else\\n {\\n String[] wordStems = line.split(\\\" \\\");\\n for (String wordStem: wordStems)\\n {\\n if (stemMap.containsKey(wordStem))\\n {\\n List<Posting> currentStemPostings = stemMap.get(wordStem);\\n int lastElementIndex = currentStemPostings.size() - 1;\\n Posting lastPosting = currentStemPostings.get(lastElementIndex);\\n \\n if (lastPosting.documentId == documentCounter)\\n {\\n lastPosting.termFrequency += 1;\\n }\\n else\\n {\\n Posting posting = new Posting(documentCounter, 1);\\n currentStemPostings.add(posting);\\n }\\n }\\n else\\n {\\n List<Posting> postings = new ArrayList<>();\\n Posting posting = new Posting(documentCounter, 1);\\n postings.add(posting);\\n stemMap.put(wordStem, postings);\\n }\\n }\\n }\\n }\\n scanner.close();\\n }\",\n \"public void writeIDs() {\\n try {\\n FileOutputStream fileOut = new FileOutputStream(\\\"temp/ids.ser\\\");\\n ObjectOutputStream out = new ObjectOutputStream(fileOut);\\n out.writeObject(ids);\\n out.close();\\n fileOut.close();\\n } catch (IOException e) {\\n e.printStackTrace();\\n }\\n\\n }\",\n \"private void scanDocuments()\\n{\\n document_counts = new HashMap<>();\\n kgram_counts = new HashMap<>();\\n for (File f : root_files) {\\n addDocuments(f);\\n }\\n}\",\n \"public static void printInvertedIndexToFile(Map<String, List<Posting>> stemMap, List<String> documentIds)\\n {\\n try\\n {\\n PrintWriter dictionaryPW = new PrintWriter(DICTIONARY_OUTPUT_FILE_PATH, \\\"UTF-8\\\");\\n PrintWriter postingsPW = new PrintWriter(POSTINGS_OUTPUT_FILE_PATH, \\\"UTF-8\\\");\\n PrintWriter docIdsPW = new PrintWriter(DOCUMENT_ID_OUTPUT_FILE_PATH, \\\"UTF-8\\\");\\n\\n int numStems = stemMap.size();\\n int numPostingEntries = 0;\\n int numDocuments = documentIds.size();\\n \\n for (List<Posting> posting: stemMap.values())\\n {\\n numPostingEntries += posting.size();\\n }\\n\\n dictionaryPW.println(numStems);\\n postingsPW.println(numPostingEntries);\\n docIdsPW.println(numDocuments);\\n\\n for (Entry<String, List<Posting>> entrySet: stemMap.entrySet())\\n {\\n String stem = entrySet.getKey();\\n List<Posting> postings = entrySet.getValue();\\n\\n dictionaryPW.println(String.format(\\\"%s %d\\\", stem, postings.size()));\\n for (Posting posting: postings)\\n {\\n postingsPW.println(String.format(\\\"%d %d\\\", posting.documentId, posting.termFrequency));\\n numPostingEntries++;\\n }\\n }\\n\\n for (String docId: documentIds)\\n {\\n docIdsPW.print(docId);\\n }\\n\\n dictionaryPW.close();\\n postingsPW.close();\\n docIdsPW.close();\\n }\\n catch (Exception e)\\n {\\n System.out.println(e.getMessage());\\n }\\n }\",\n \"private void saveIds(ArrayList<String> idList) {\\n\\n\\t\\ttry {\\n\\t\\t\\tFileOutputStream fileOutputStream = context.openFileOutput(\\n\\t\\t\\t\\t\\tSAVE_FILE, Context.MODE_PRIVATE);\\n\\t\\t\\tOutputStreamWriter outputStreamWriter = new OutputStreamWriter(\\n\\t\\t\\t\\t\\tfileOutputStream);\\n\\t\\t\\tGsonBuilder builder = new GsonBuilder();\\n\\t\\t\\tGson gson = builder.create();\\n\\t\\t\\tgson.toJson(idList, outputStreamWriter); // Serialize to Json\\n\\t\\t\\toutputStreamWriter.flush();\\n\\t\\t\\toutputStreamWriter.close();\\n\\t\\t} catch (IOException e) {\\n\\t\\t\\te.printStackTrace();\\n\\t\\t}\\n\\t}\",\n \"public static void save(String indexFileName) throws FileNotFoundException, UnsupportedEncodingException{\\n\\t\\tHashMap<String, String> sCurrentHashMap = globalHash.get(indexFileName);\\n\\t\\t\\n\\t\\tPrintWriter writer = new PrintWriter(indexFileName+\\\".txt\\\", \\\"UTF-8\\\");\\n\\n\\t\\tIterator it = sCurrentHashMap.entrySet().iterator();\\n\\t\\twhile(it.hasNext()){\\n\\t\\t\\tHashMap.Entry<String, String> entry = (HashMap.Entry<String, String>) it.next();\\n\\t\\t\\t//if this term appear more than one doc\\n\\t\\t\\tif(entry.getValue().length()>1) {\\n\\t\\t\\t\\tStringTokenizer stDocID = new StringTokenizer(entry.getValue(),\\\",\\\");\\n\\t\\t\\t\\twriter.println(entry.getKey()+\\\",\\\"+stDocID.countTokens()+\\\":<\\\"+entry.getValue()+\\\">\\\");\\n\\t\\t\\t} else{\\n\\t\\t\\t\\twriter.println(entry.getKey()+\\\",1:<\\\"+entry.getValue()+\\\">\\\");\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\twriter.close();\\n\\t}\",\n \"public void IndexADocument(String docno, String content) throws IOException {\\n\\t\\tdocid++;\\n\\t\\tdoc2docid.put(docno, docid);\\n\\t\\tdocid2doc.put(docid, docno);\\n\\n\\t\\t// Insert every term in this doc into docid2map\\n\\t\\tString[] terms = content.trim().split(\\\" \\\");\\n\\t\\tMap<Integer, Integer> docTerm = new HashMap<>();\\n\\t\\tint thisTermid;\\n\\t\\tfor(String term: terms){\\n\\t\\t\\t// get termid\\n\\t\\t\\tif(term2termid.get(term)!=null) thisTermid = term2termid.get(term);\\n\\t\\t\\telse{\\n\\t\\t\\t\\tthisTermid = ++termid;\\n\\t\\t\\t\\tterm2termid.put(term, thisTermid);\\n\\t\\t\\t}\\n\\t\\t\\tdocTerm.put(thisTermid, docTerm.getOrDefault(thisTermid, 0)+1);\\n\\t\\t\\t// Merge this term's information into termid2map\\n\\t\\t\\tMap<Integer, Integer> temp = termid2map.getOrDefault(thisTermid, new HashMap());\\n\\t\\t\\ttemp.put(docid, temp.getOrDefault(docid, 0)+1);\\n\\t\\t\\ttermid2map.put(thisTermid, temp);\\n\\t\\t\\ttermid2fre.put(thisTermid, termid2fre.getOrDefault(thisTermid, 0)+1);\\n\\t\\t}\\n\\t\\tdocid2map.put(docid, docTerm);\\n\\n//\\t\\t// Merge all the terms' information into termid2map\\n//\\t\\tfor(Long tid: docTerm.keySet()){\\n//\\t\\t\\tMap<Long, Long> temp = termid2map.getOrDefault(tid, new HashMap());\\n//\\t\\t\\ttemp.put(docid,docTerm.get(tid));\\n//\\t\\t\\ttermid2map.put(tid, temp);\\n//\\t\\t\\t// update this term's frequency\\n//\\t\\t\\ttermid2fre.put(tid, termid2fre.getOrDefault(tid,0L)+docTerm.get(tid));\\n//\\t\\t}\\n\\n\\t\\t// When termid2map and docid2map is big enough, put it into disk\\n\\t\\tif(docid%blockSize==0){\\n\\t\\t\\tWritePostingFile();\\n\\t\\t\\tWriteDocFile();\\n\\t\\t}\\n\\t}\",\n \"static private void saveSentenceTokens( final String outputDirPath,\\n final String documentId, final Iterable<String> tokenizedSentences ) {\\n // Be prepared for documentId that contains directory segments, some of which may not exist\\n final File outputFile = new File( outputDirPath + File.pathSeparator + documentId );\\n if ( !outputFile.getParentFile().exists() && !outputFile.getParentFile().mkdirs() ) {\\n LOGGER.error( outputFile.getPath() + \\\" is an invalid output file path\\\" );\\n return;\\n }\\n try ( final BufferedWriter writer = new BufferedWriter( new FileWriter( outputFile ) ) ) {\\n for ( String tokenizedSentence : tokenizedSentences ) {\\n writer.write( tokenizedSentence );\\n writer.newLine();\\n }\\n } catch ( IOException ioE ) {\\n LOGGER.error( ioE.getMessage() );\\n }\\n }\",\n \"private void writeVocabPost(FlIndexer fi) throws IOException{\\n this.docNormPow = new HashMap<>();\\n \\n LinkedList<Integer> tf;\\n LinkedList<String> files;\\n String token;\\n int position=0;\\n File file = new File(\\\"CollectionIndex/VocabularyFile.txt\\\");\\n File Postingfile = new File(\\\"CollectionIndex/PostingFile.txt\\\");\\n \\n\\tFileWriter fw = new FileWriter(file.getAbsoluteFile());\\n FileWriter fw_posting = new FileWriter(Postingfile.getAbsolutePath());\\n try (BufferedWriter bw = new BufferedWriter(fw)) {\\n try (BufferedWriter bw_posting = new BufferedWriter(fw_posting)){\\n for (Map.Entry<String, TermNode> entry : fi.mapTerms.entrySet()){\\n double idf = ((double)this.docMap.size())/entry.getValue().getDf();\\n //idf=log2(idf, 2);\\n bw.write(entry.getValue().getTerm()+\\\" \\\"+entry.getValue().getDf()+\\\" \\\"+idf+\\\" \\\"+position+\\\"\\\\n\\\");\\n \\n tf=entry.getValue().getTfList();\\n files=entry.getValue().getFileList();\\n int i=tf.size();\\n for (int j=0; j<i; j++){\\n double tfidf=idf*((double)tf.get(j)/fi.getMaxTF(files.get(j)));\\n double tfidfpow=Math.pow(tfidf, 2);\\n\\n \\n if(this.docNormPow.containsKey(files.get(j))){\\n //this.docNorm.put(files.get(j), this.docNorm.get(files.get(j))+tfidf);\\n this.docNormPow.put(files.get(j), this.docNormPow.get(files.get(j))+tfidfpow);\\n }\\n else{\\n //this.docNorm.put(files.get(j), tfidf);\\n this.docNormPow.put(files.get(j), tfidfpow);\\n }\\n \\n token=this.docMap.get(files.get(j))+\\\" \\\"+tf.get(j)+\\\" \\\"\\n +entry.getValue().multiMap.get(files.get(j))+\\\" \\\"+tfidf+\\\"\\\\n\\\";\\n position= position + token.length();\\n \\n bw_posting.write(token);\\n }\\n }\\n }\\n }\\n \\n System.out.println(\\\"Done creating VocabularyFile.txt\\\");\\n System.out.println(\\\"Done creating PostingFile.txt\\\");\\n }\",\n \"public Vector mapDocument(MultiSet<String> bow) {\\n //logger.info(\\\"lsm.mapDocument\\\");\\n SparseVector vector = new SparseVector();\\n\\n Iterator<String> it = bow.iterator();\\n String term = null;\\n int index = 0;\\n int tf = 0;\\n float tfIdf;\\n for (int i = 0; it.hasNext(); i++) {\\n //logger.info(i + \\\" \\\" + t[i]);\\n term = it.next();\\n index = termIndex.get(term);\\n\\n if (index != -1) {\\n tf = bow.getFrequency(term);\\n tfIdf = (float) (log2(tf)) * Iidf[index];\\n\\n //logger.info(term + \\\" ==> \\\" + index + \\\", tf.idf = \\\" + tf + \\\"(\\\" + (log2(tf)) + \\\") * \\\" + Iidf[index] + \\\" = \\\" + tfIdf);\\n vector.add(index, tfIdf);\\n\\n }\\n } // end for\\n\\n return vector;\\n }\",\n \"public static void main(String[] args) throws IOException{\\n\\t\\tint termIndex = 1;\\n\\t\\t\\n\\t\\t// startOffset holds the start offset for each term in\\n\\t\\t// the corpus.\\n\\t\\tlong startOffset = 0;\\n\\t\\t\\t\\n\\t\\t// unique_terms is true if there are atleast one more\\n\\t\\t// unique term in corpus.\\n\\t\\tboolean unique_terms = true;\\n\\t\\t\\n\\t\\t\\n\\t\\t//load the stopwords from the HDD\\n\\t\\tString stopwords = getStopWords();\\n\\t\\t\\n\\t\\t// allTokenHash contains all the terms and its termid\\n\\t\\tHashMap<String, Integer> allTermHash = new HashMap<String, Integer>();\\n\\t\\t\\n\\t\\t// catalogHash contains the term and its position in\\n\\t\\t// the inverted list present in the HDD.\\n\\t\\tHashMap<Integer, Multimap> catalogHash = new HashMap<Integer, Multimap>();\\n\\t\\t\\n\\t\\t// finalCatalogHash contains the catalogHash for the invertedIndexHash\\n\\t\\t// present in the HDD.\\n\\t\\tHashMap<Integer, String> finalCatalogHash = new HashMap<Integer, String>();\\n\\t\\t\\n\\t\\t// token1000Hash contains the term and Dblocks for the first 1000\\n\\t\\tHashMap<Integer, Multimap> token1000DocHash = new HashMap<Integer, Multimap>();\\n\\t\\t\\n\\t\\t// documentHash contains the doclength of all the documents in the corpus\\n\\t\\tHashMap<String, String> documentHash = new HashMap<String, String>();\\t\\n\\t\\t\\n\\t\\t// id holds the document id corresponding to the docNumber.\\n\\t\\tint id = 1;\\n\\t\\t\\n\\t\\t// until all unique terms are exhausted\\n\\t\\t// pass through the documents and index the terms.\\n\\t\\t//while(unique_terms){\\n\\t\\t\\t\\n\\t\\t\\tFile folder = new File(\\\"C:/Naveen/CCS/IR/AP89_DATA/AP_DATA/ap89_collection\\\");\\n\\t\\t\\t//File folder = new File(\\\"C:/Users/Naveen/Desktop/TestFolder\\\");\\n\\t\\t\\tFile[] listOfFiles = folder.listFiles();\\n\\t\\t\\t\\n\\t\\t\\t//for each file in the folder \\n\\t\\t\\tfor (File file : listOfFiles) {\\n\\t\\t\\t if (file.isFile()) {\\n\\t\\t\\t \\t\\n\\t\\t\\t \\tString str = file.getPath().replace(\\\"\\\\\\\\\\\",\\\"//\\\");\\n\\t\\t\\t \\t\\n\\t\\t\\t \\t\\n\\t\\t\\t\\t\\t//Document doc = new Document();\\n\\t\\t\\t //System.out.println(\\\"\\\"+str);\\n\\t\\t\\t\\t\\t//variables to keep parse document.\\n\\t\\t\\t\\t\\tint docCount = 0;\\n\\t\\t\\t\\t\\tint docNumber = 0;\\n\\t\\t\\t\\t\\tint endDoc = 0;\\n\\t\\t\\t\\t\\tint textCount = 0;\\n\\t\\t\\t\\t\\tint noText = 0;\\n\\t\\t\\t\\t\\tPath path = Paths.get(str);\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t//Document id and text\\n\\t\\t\\t\\t\\tString docID = null;\\n\\t\\t\\t\\t\\tString docTEXT = null;\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t//Stringbuffer to hold the text of each document\\n\\t\\t\\t\\t\\tStringBuffer text = new StringBuffer();\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\tScanner scanner = new Scanner(path);\\n\\t\\t\\t\\t\\twhile(scanner.hasNext()){\\n\\t\\t\\t\\t\\t\\tString line = scanner.nextLine();\\n\\t\\t\\t\\t\\t\\tif(line.contains(\\\"<DOC>\\\")){\\n\\t\\t\\t\\t\\t\\t\\t++docCount;\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\telse if(line.contains(\\\"</DOC>\\\")){\\n\\t\\t\\t\\t\\t\\t\\t++endDoc;\\n\\t\\t\\t\\t\\t\\t\\tdocTEXT = text.toString();\\n\\t\\t\\t\\t\\t\\t\\t//docTEXT = docTEXT.replaceAll(\\\"[\\\\\\\\n]\\\",\\\" \\\");\\n\\t\\t\\t\\t\\t\\t\\tSystem.out.println(\\\"ID: \\\"+id);\\n\\t\\t\\t\\t\\t\\t\\t//System.out.println(\\\"TEXT: \\\"+docTEXT);\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t// text with stop words removed\\n\\t\\t\\t\\t\\t\\t\\tPattern pattern1 = Pattern.compile(\\\"\\\\\\\\b(?:\\\"+stopwords+\\\")\\\\\\\\b\\\\\\\\s*\\\", Pattern.CASE_INSENSITIVE);\\n\\t\\t\\t\\t\\t\\t\\tMatcher matcher1 = pattern1.matcher(docTEXT);\\n\\t\\t\\t\\t\\t\\t\\tdocTEXT = matcher1.replaceAll(\\\"\\\");\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t// text with stemming\\n\\t\\t\\t\\t\\t\\t\\t//docTEXT = stemmer(docTEXT);\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\tint docLength = 1;\\n\\t\\t\\t\\t\\t\\t\\t// regex to build the tokens from the document text\\n\\t\\t\\t\\t\\t\\t\\tPattern pattern = Pattern.compile(\\\"\\\\\\\\w+(\\\\\\\\.?\\\\\\\\w+)*\\\");\\n\\t\\t\\t\\t\\t\\t\\tMatcher matcher = pattern.matcher(docTEXT.toLowerCase());\\n\\t\\t\\t\\t\\t\\t\\twhile (matcher.find()) {\\n\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\tfor (int i = 0; i < matcher.groupCount(); i++) {\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t// alltermHash contains term and term id\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t// if term is present in the alltermHash\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tif(allTermHash.containsKey(matcher.group(i))){\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tint termId = allTermHash.get(matcher.group(i));\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t//if term is present in the token1000Hash\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t//then update the dblock of the term.\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tif(token1000DocHash.containsKey(termId)){\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tMultimap<String, String> dBlockUpdate = token1000DocHash.get(termId);\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t//Multimap<Integer, Integer> dBlockUpdate = token1000DocHash.get(matcher.group(i));\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tif(dBlockUpdate.containsKey(id)){\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tdBlockUpdate.put(String.valueOf(id), String.valueOf(matcher.start()));\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\telse{\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tdBlockUpdate.put(String.valueOf(id), String.valueOf(matcher.start()));\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t//if term is not present in the token1000hash\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t//then add the token with its dBlock\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\telse{\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tMultimap<String, String> dBlockInsert = ArrayListMultimap.create();\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tdBlockInsert.put(String.valueOf(id), String.valueOf(matcher.start()));\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\ttoken1000DocHash.put(termId, dBlockInsert);\\t\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t}\\t\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t// if the term is not present I will put the term into allTermHash\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t// put corresponding value into the token1000DocHash and increment\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t// termIndex\\n\\t\\t\\t\\t\\t\\t\\t\\t\\telse{\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tallTermHash.put(matcher.group(i),termIndex);\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tMultimap<String, String> dBlockInsert = ArrayListMultimap.create();\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tdBlockInsert.put(String.valueOf(id), String.valueOf(matcher.start()));\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\ttoken1000DocHash.put(termIndex, dBlockInsert);\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\ttermIndex++;\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tdocLength++;\\n\\t\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\tif(id%1000 == 0){\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t// then dump index file to HDD\\n\\t\\t\\t\\t\\t\\t\\t\\t\\twriteInvertedIndex(token1000DocHash,\\\"token1000DocHash\\\");\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t// update catalog file\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t// to populate catalogHash with the offset\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tfor(Entry<Integer, Multimap> entry : token1000DocHash.entrySet()){\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tif(catalogHash.containsKey(entry.getKey())){\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tint len = (entry.getKey()+\\\":\\\"+entry.getValue()).length();\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t//String offset = String.valueOf(startOffset)+\\\":\\\"+String.valueOf(len);\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tMultimap<String, String> catUpdate = catalogHash.get(entry.getKey());\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tcatUpdate.put(String.valueOf(startOffset), String.valueOf(len));\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tcatalogHash.put(entry.getKey(), catUpdate);\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tstartOffset += len+2;\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\telse{\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tint len = (entry.getKey()+\\\":\\\"+entry.getValue()).length();\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t//String offset = String.valueOf(startOffset)+\\\":\\\"+String.valueOf(len);\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tMultimap<String, String> catInsert = ArrayListMultimap.create();\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tcatInsert.put(String.valueOf(startOffset), String.valueOf(len));\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tcatalogHash.put(entry.getKey(), catInsert);//entry.getValue());\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tstartOffset += len+2;\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t}\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t//clear the token1000DocHash\\n\\t\\t\\t\\t\\t\\t\\t\\t\\ttoken1000DocHash.clear();\\n\\t\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\tdocumentHash.put(docID, \\\"\\\"+id+\\\":\\\"+docLength);\\n\\t\\t\\t\\t\\t\\t\\tid++;\\n\\t\\t\\t\\t\\t\\t\\ttext = new StringBuffer();\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\telse if(line.contains(\\\"<DOCNO>\\\")){\\n\\t\\t\\t\\t\\t\\t\\t++docNumber;\\n\\t\\t\\t\\t\\t\\t\\tdocID = line.substring(8, 21);\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\telse if(line.contains(\\\"<TEXT>\\\")){\\n\\t\\t\\t\\t\\t\\t\\t++textCount;\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\telse if((line.contains(\\\"<DOC>\\\"))||\\n\\t\\t\\t\\t\\t\\t\\t\\t(line.contains(\\\"</DOC>\\\"))||\\n\\t\\t\\t\\t\\t\\t\\t\\t(line.contains(\\\"<DOCNO>\\\"))||\\n\\t\\t\\t\\t\\t\\t\\t\\t(line.contains(\\\"<FILEID>\\\"))||\\n\\t\\t\\t\\t\\t\\t\\t\\t(line.contains(\\\"<FIRST>\\\"))||\\n\\t\\t\\t\\t\\t\\t\\t\\t(line.contains(\\\"<SECOND>\\\"))||\\n\\t\\t\\t\\t\\t\\t\\t\\t(line.contains(\\\"<HEAD>\\\"))||\\n\\t\\t\\t\\t\\t\\t\\t\\t(line.contains(\\\"</HEAD>\\\"))||\\n\\t\\t\\t\\t\\t\\t\\t\\t(line.contains(\\\"<BYLINE>\\\"))||\\n\\t\\t\\t\\t\\t\\t\\t\\t(line.contains(\\\"</BYLINE>\\\"))||\\n\\t\\t\\t\\t\\t\\t\\t\\t(line.contains(\\\"<UNK>\\\"))||\\n\\t\\t\\t\\t\\t\\t\\t\\t(line.contains(\\\"</UNK>\\\"))||\\n\\t\\t\\t\\t\\t\\t\\t\\t(line.contains(\\\"<DATELINE>\\\"))||\\n\\t\\t\\t\\t\\t\\t\\t\\t(line.contains(\\\"<NOTE>\\\"))||\\n\\t\\t\\t\\t\\t\\t\\t\\t(line.contains(\\\"</NOTE>\\\"))||\\n\\t\\t\\t\\t\\t\\t\\t\\t(line.contains(\\\"</TEXT>\\\"))||\\n\\t\\t\\t\\t\\t\\t\\t\\t(line.contains(\\\"<TEXT>\\\"))){\\n\\t\\t\\t\\t\\t\\t\\t ++noText;\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\telse if(endDoc == docCount - 1){\\n\\t\\t\\t\\t\\t\\t\\ttext.append(line);\\n\\t\\t\\t\\t\\t\\t\\ttext.append(\\\" \\\");\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t \\t\\n\\t\\t\\t }//end of if - to check if this is a file and parse.\\n\\t\\t\\t \\n\\t\\t\\t}//end of for loop to load each file\\n\\t\\t\\t\\n\\t\\t//}//end of while loop \\n\\t\\t\\n\\t// write catalogfile to the hdd to check.\\n\\t\\t\\t\\n\\t\\t\\t// then dump index file to HDD\\n\\t\\t\\twriteInvertedIndex(token1000DocHash,\\\"token1000DocHash\\\");\\n\\t\\t\\t\\n\\t\\t\\t// update catalog file\\n\\t\\t\\t// to populate catalogHash with the offset\\n\\t\\t\\tfor(Entry<Integer, Multimap> entry : token1000DocHash.entrySet()){\\n\\t\\t\\t\\tif(catalogHash.containsKey(entry.getKey())){\\n\\t\\t\\t\\t\\tint len = (entry.getKey()+\\\":\\\"+entry.getValue()).length();\\n\\t\\t\\t\\t\\t//String offset = String.valueOf(startOffset)+\\\":\\\"+String.valueOf(len);\\n\\t\\t\\t\\t\\tMultimap<String, String> catUpdate = catalogHash.get(entry.getKey());\\n\\t\\t\\t\\t\\tcatUpdate.put(String.valueOf(startOffset), String.valueOf(len));\\n\\t\\t\\t\\t\\tcatalogHash.put(entry.getKey(), catUpdate);\\n\\t\\t\\t\\t\\tstartOffset += len+2;\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\telse{\\n\\t\\t\\t\\t\\tint len = (entry.getKey()+\\\":\\\"+entry.getValue()).length();\\n\\t\\t\\t\\t\\t//String offset = String.valueOf(startOffset)+\\\":\\\"+String.valueOf(len);\\n\\t\\t\\t\\t\\tMultimap<String, String> catInsert = ArrayListMultimap.create();\\n\\t\\t\\t\\t\\tcatInsert.put(String.valueOf(startOffset), String.valueOf(len));\\n\\t\\t\\t\\t\\tcatalogHash.put(entry.getKey(), catInsert);//entry.getValue());\\n\\t\\t\\t\\t\\tstartOffset += len+2;\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t}\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t}\\n\\t\\t\\t\\n\\t\\t\\t\\n\\t\\t\\t\\n\\t\\t\\twriteInvertedIndex(catalogHash,\\\"catalogHash\\\");\\n\\t\\t\\tprintHashMapSI(allTermHash);\\n\\t\\t\\tprintHashMapSS(documentHash);\\n\\t\\t\\t\\n\\t\\t\\tlong InvIndstartOffset = 0;\\n\\t\\t\\t\\n\\t\\t\\t//write it to file\\n \\n\\t\\t\\t//change the finalcatalogHash to the form termid:startoffset:length\\n\\t\\t\\tfor (Integer name: catalogHash.keySet()){\\n\\t String key = name.toString();\\n\\t String value = catalogHash.get(name).toString(); \\n\\t //System.out.println(key + \\\" \\\" + value); \\n\\t String finalTermIndex = genInvertedIndex(key, value);\\n\\t finalTermIndex = key+\\\":\\\"+finalTermIndex;\\n\\t int indexLength = finalTermIndex.length();\\n\\t \\n\\t \\n\\t PrintWriter writer = new PrintWriter(new BufferedWriter\\n\\t \\t\\t(new FileWriter(\\\"C:/Users/Naveen/Desktop/TestRuns/LastRun/InvertedIndex\\\", true)));\\n\\t writer.println(finalTermIndex);\\n\\t writer.close();\\n\\t \\n\\t //update the finalcatalogHash\\n\\t //Multimap<String, String> catInsert = ArrayListMultimap.create();\\n\\t\\t\\t\\t//catInsert.put(String.valueOf(InvIndstartOffset), String.valueOf(indexLength));\\n\\t\\t\\t\\tfinalCatalogHash.put(name, String.valueOf(InvIndstartOffset)+\\\":\\\"+String.valueOf(indexLength));//entry.getValue());\\n\\t\\t\\t\\tInvIndstartOffset += indexLength+2;\\n\\t \\n\\t\\t\\t}\\n\\t\\t\\t\\n\\t\\t\\t\\n\\t\\t\\t\\n\\t\\t\\tprintHashMapIS(finalCatalogHash);\\n\\t\\t\\t\\n\\t}\",\n \"public static TreeMap<Integer,String> calc_tf_idf( String \\tbaseFolder,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t String baseFolder_out,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tString \\tinputFile, \\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tString delimiter_for_inputFile,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tint \\ttoken_index_having_text,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tString \\toutFile,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tboolean is_do_stemming_on_word,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tboolean is_ignore_stop_words_all_together,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tboolean isSOPprint\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t){\\n\\t\\tTreeMap<Integer,String> mapOut=new TreeMap<Integer, String>();\\n\\t\\ttry{\\n\\t\\t\\tString line=\\\"\\\";\\n\\t\\t\\tBufferedReader reader = new BufferedReader(new InputStreamReader(new FileInputStream( inputFile) ));\\n\\t\\t\\t//boolean is_do_stemming_on_word=true;\\n\\t\\t\\tStemmer stemmer=new Stemmer(); String token=\\\"\\\";\\n\\t\\t TreeMap<String, Integer> mapVoc_Freq=new TreeMap<String, Integer>();\\n\\t\\t TreeMap<String, List<Integer>> map_Word_UniqueDocumentIdHavingIT=new TreeMap<String, List<Integer>>();\\n\\t\\t TreeMap<Integer, TreeMap<String, Integer > > map_DocID_wordFrequency=new TreeMap<Integer, TreeMap<String,Integer>>();\\n\\t\\t\\t\\tint lineNumber=0; int last_doc_id=-1;\\n\\t\\t\\t\\n\\t\\t\\tFileWriter writer_voc=new FileWriter(new File(baseFolder_out+\\\"unique_word_vocabulary.txt\\\"));\\n\\t\\t\\t\\t\\n\\t\\t\\tFileWriter writer=new FileWriter(new File(outFile));\\n\\t\\t\\t// files for docID wordID tf-idf output\\n\\t\\t\\tFileWriter writer_no_stopword=new FileWriter(new File(outFile+\\\"_noStopWord.txt\\\"));\\t\\t\\t\\n\\t\\t\\tFileWriter writer_wordID=new FileWriter(new File(outFile+\\\"_WORD_ID.txt\\\"));\\n\\t\\t\\tFileWriter writer_wordID_no_stopword=new FileWriter(new File(outFile+\\\"_noStopWord_WORD_ID.txt\\\"));\\n\\t\\t\\tFileWriter writer_word_stemmedWord=new FileWriter(new File(outFile+\\\"_Word_stemmedWord.txt\\\"));\\n\\t\\t\\t\\n\\t\\t\\t// files for docID wordID frequency output\\n\\t\\t\\tFileWriter writer2=new FileWriter(new File(outFile+\\\"_docWordID_freq2.txt\\\"));\\n\\t\\t\\tFileWriter writer2_no_stopword=new FileWriter(new File(outFile+\\\"_noStopWord2.txt\\\"));\\n\\t\\t\\tFileWriter writer2_wordID=new FileWriter(new File(outFile+\\\"_WORD_ID2.txt\\\"));\\n\\t\\t\\tFileWriter writer2_wordID_no_stopword=new FileWriter(new File(outFile+\\\"_noStopWord_WORD_ID2.txt\\\"));\\n\\t\\t\\tFileWriter writer2_word_stemmedWord=new FileWriter(new File(outFile+\\\"_Word_stemmedWord2.txt\\\"));\\n\\t\\t\\t\\n\\n\\t\\t\\t\\n\\t\\t\\tFileWriter writer_debug=new FileWriter(new File(outFile+\\\"_DEBUG.txt\\\"));\\n\\t\\t\\tFileWriter writer_debug_2=new FileWriter(new File(outFile+\\\"_DEBUG_2.txt\\\"));\\n\\t\\t\\t\\n\\t\\t\\tTreeMap<String,Integer> map_already_wrote=new TreeMap<String, Integer>();\\n\\t\\t\\t//\\n\\t\\t\\twhile ((line = reader.readLine()) != null) {\\n\\t\\t\\t\\tlineNumber++;\\n\\t\\t\\t\\tSystem.out.println(\\\"lineNumber:\\\"+lineNumber);\\n\\t\\t\\t\\t\\n\\t\\t\\t\\t//DEBUG BREAK\\n//\\t\\t\\t\\tif(lineNumber>100) break;\\n\\t\\t\\t\\t\\n\\t\\t\\t\\t//mapVoc_Freq=new TreeMap<String, Integer>();\\n\\t\\t\\t\\tint curr_doc_id=lineNumber;\\n\\t\\t\\t\\tString [] token_= line.split(delimiter_for_inputFile);\\n\\t\\t\\t\\t\\n\\t\\t\\t\\t //clean\\n\\t\\t\\t\\t token=token_[token_index_having_text-1].replace(\\\"\\\\\\\"\\\", \\\" \\\").replace(\\\"'\\\", \\\" \\\").replace(\\\",\\\", \\\" \\\").replace(\\\";\\\",\\\" \\\").replace(\\\".\\\", \\\" \\\")\\n\\t\\t\\t\\t\\t\\t\\t\\t .replace(\\\"‘\\\", \\\" \\\").replace(\\\"“\\\", \\\" \\\").replace(\\\"–\\\", \\\" \\\").replace(\\\")\\\", \\\" \\\").replace(\\\"(\\\", \\\" \\\")\\n\\t\\t\\t\\t\\t\\t\\t\\t .replace(\\\"-\\\", \\\" \\\").replace(\\\":\\\", \\\" \\\").replace(\\\"’\\\", \\\" \\\").replace(\\\"”\\\", \\\" \\\").replace(\\\"—\\\", \\\" \\\")\\n\\t\\t\\t\\t\\t\\t\\t\\t .replace(\\\"#\\\", \\\" \\\").replace(\\\"%\\\", \\\" \\\")//.replace(\\\"$\\\", \\\" \\\")\\n\\t\\t\\t\\t\\t\\t\\t\\t .replace(\\\"/\\\",\\\" \\\")\\n\\t\\t\\t\\t\\t\\t\\t\\t .replace(\\\" \\\", \\\" \\\");\\n\\t\\t\\t\\t \\n\\t\\t\\t\\t token=token.toLowerCase();\\n\\n\\t\\t\\t\\t \\n\\t\\t\\t\\t // \\n\\t\\t\\t\\t String [] arr_token=token.split(\\\" \\\");\\n\\t\\t\\t\\t int cnt=0;\\n\\t\\t\\t\\t // \\n\\t\\t\\t\\t while(cnt < arr_token.length){\\n\\t\\t\\t\\t\\t String temp= Ltrim.ltrim( arr_token[cnt]);\\n\\t\\t\\t\\t\\t \\n\\t\\t\\t\\t\\t // ignore stop words all together\\n\\t\\t\\t\\t\\t if(is_ignore_stop_words_all_together==true && Stopwords.is_stopword(temp)){\\n\\t\\t\\t\\t\\t\\t cnt++;\\n\\t\\t\\t\\t\\t\\t continue;\\n\\t\\t\\t\\t\\t }\\n\\t\\t\\t\\t\\t \\n\\t\\t\\t\\t\\t // do stemming\\n\\t\\t\\t\\t\\t if(is_do_stemming_on_word){\\n\\t\\t\\t\\t\\t\\t String orig_temp=temp;\\n\\t\\t\\t\\t\\t\\t //ltrim.ltrim(\\n\\t\\t\\t\\t\\t\\t temp= stemmer.stem(temp);\\n\\t\\t\\t\\t\\t\\t \\n\\t\\t\\t\\t\\t\\t if(!map_already_wrote.containsKey(orig_temp)){\\n\\t\\t\\t\\t\\t\\t\\t writer_word_stemmedWord.append(orig_temp+\\\"!!!\\\"+temp +\\\"\\\\n\\\");\\n\\t\\t\\t\\t\\t\\t\\t writer_word_stemmedWord.flush();\\n\\t\\t\\t\\t\\t\\t }\\n\\t\\t\\t\\t\\t\\t \\n\\t\\t\\t\\t\\t\\t map_already_wrote.put(orig_temp, -1);\\n\\t\\t\\t\\t\\t\\t \\n\\t\\t\\t\\t\\t }\\n\\t\\t\\t\\t\\t else \\n\\t\\t\\t\\t\\t\\t temp=temp;\\n\\n\\t\\t\\t\\t\\t\\t // \\n\\t\\t\\t\\t\\t\\t if(!mapVoc_Freq.containsKey(temp)){\\n\\t\\t\\t\\t\\t\\t\\t //vocabulary term-freq\\n\\t\\t\\t\\t\\t\\t\\t mapVoc_Freq.put(temp, 1);\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t \\n\\t\\t\\t\\t\\t\\t\\t //word-document freq- unique number of documents this word occurs.\\n\\t\\t\\t\\t\\t\\t\\t List l=new ArrayList<Integer>();\\n\\t\\t\\t\\t\\t\\t\\t l.add(curr_doc_id);\\n\\t\\t\\t\\t\\t\\t\\t map_Word_UniqueDocumentIdHavingIT.put(temp, l);\\n\\t\\t\\t\\t\\t\\t\\t \\n\\t\\t\\t\\t\\t\\t\\t //doc-wise frequency\\n\\t\\t\\t\\t\\t\\t\\t if(!map_DocID_wordFrequency.containsKey(curr_doc_id)){\\n\\t\\t\\t\\t\\t\\t\\t\\t TreeMap<String,Integer> t2=new TreeMap<String, Integer>();\\n\\t\\t\\t\\t\\t\\t\\t\\t t2.put( temp, 1 ) ;\\n\\t\\t\\t\\t\\t\\t\\t\\t map_DocID_wordFrequency.put(curr_doc_id, t2);\\n\\t\\t\\t\\t\\t\\t\\t }\\n\\t\\t\\t\\t\\t\\t\\t else{\\n\\t\\t\\t\\t\\t\\t\\t\\t TreeMap<String,Integer> t2=map_DocID_wordFrequency.get(curr_doc_id);\\n\\t\\t\\t\\t\\t\\t\\t\\t \\n\\t\\t\\t\\t\\t\\t\\t\\t if(!t2.containsKey(temp)){\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t TreeMap<String,Integer> t2_2=map_DocID_wordFrequency.get(curr_doc_id);\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t t2_2.put( temp, 1 ) ;\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t map_DocID_wordFrequency.put(curr_doc_id, t2_2);\\n\\t\\t\\t\\t\\t\\t\\t\\t }\\n\\t\\t\\t\\t\\t\\t\\t\\t else{\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t TreeMap<String,Integer> t2_2=map_DocID_wordFrequency.get(curr_doc_id);\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t int sz=t2.get(temp)+1;\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t t2_2.put( temp, sz ) ;\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t map_DocID_wordFrequency.put(curr_doc_id, t2_2);\\n\\t\\t\\t\\t\\t\\t\\t\\t }\\n\\t\\t\\t\\t\\t\\t\\t }\\n\\t\\t\\t\\t\\t\\t\\t \\n\\t\\t\\t\\t\\t\\t }\\n\\t\\t\\t\\t\\t\\t else{\\n\\t\\t\\t\\t\\t\\t\\t int freq=mapVoc_Freq.get(temp)+1;\\n\\t\\t\\t\\t\\t\\t\\t //System.out.println(\\\"last_doc_id!=curr_doc_id->\\\"+last_doc_id+\\\"<-->\\\"+curr_doc_id );\\n\\t\\t\\t\\t\\t\\t\\t //vocabulary term-freq\\n\\t\\t\\t\\t\\t\\t\\t mapVoc_Freq.put(temp, freq);\\n\\t\\t\\t\\t\\t\\t\\t // word-document freq- unique number of documents this word occurs.\\n\\t\\t\\t\\t\\t\\t\\t \\n\\t\\t\\t\\t\\t\\t\\t\\t List<Integer> uniq_doc=map_Word_UniqueDocumentIdHavingIT.get(temp);\\n\\t\\t\\t\\t\\t\\t\\t\\t // if this docID not contained before in list\\n\\t\\t\\t\\t\\t\\t\\t\\t if(!uniq_doc.contains(curr_doc_id)){\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t uniq_doc.add(curr_doc_id );\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t map_Word_UniqueDocumentIdHavingIT.put(temp, uniq_doc);\\n\\t\\t\\t\\t\\t\\t\\t\\t }\\n\\t\\t\\t\\t\\t\\t\\t\\t \\n\\t\\t\\t\\t\\t\\t\\t\\t //doc-wise frequency\\n\\t\\t\\t\\t\\t\\t\\t\\t if(!map_DocID_wordFrequency.containsKey(curr_doc_id)){\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t TreeMap<String,Integer> t2=new TreeMap<String, Integer>();\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t t2.put( temp, 1 ) ;\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t map_DocID_wordFrequency.put(curr_doc_id, t2);\\n\\t\\t\\t\\t\\t\\t\\t\\t }\\n\\t\\t\\t\\t\\t\\t\\t\\t else{\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t TreeMap<String,Integer> t2=map_DocID_wordFrequency.get(curr_doc_id);\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t \\n\\t\\t\\t\\t\\t\\t\\t\\t\\t if(!t2.containsKey(temp)){\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t TreeMap<String,Integer> t2_2=map_DocID_wordFrequency.get(curr_doc_id);\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t t2_2.put( temp, 1 ) ;\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t map_DocID_wordFrequency.put(curr_doc_id, t2_2);\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t }\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t else{\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t TreeMap<String,Integer> t2_2=map_DocID_wordFrequency.get(curr_doc_id);\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t int sz=t2.get(temp)+1;\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t t2_2.put( temp, sz ) ;\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t map_DocID_wordFrequency.put(curr_doc_id, t2_2);\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t }\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t \\n\\t\\t\\t\\t\\t\\t\\t\\t }\\n\\t\\t\\t\\t\\t\\t\\t\\t \\n\\t\\t\\t\\t\\t\\t }\\n\\t\\t\\t\\t\\tcnt++;\\n\\t\\t\\t\\t }\\n\\t\\t\\t\\t \\n\\t\\t\\t\\t if(isSOPprint){\\n\\t\\t\\t\\t\\t System.out.println(\\\"doc:\\\"+curr_doc_id+\\\" token-freq:\\\"+mapVoc_Freq.size()+\\\" token-doc.freq:\\\"+map_Word_UniqueDocumentIdHavingIT.size());\\n\\t\\t\\t\\t }\\n\\t\\t\\t\\t //\\n\\t\\t\\t\\t last_doc_id=curr_doc_id;\\n\\t\\t\\t}\\n\\t\\t\\tSystem.out.println(\\\" token-freq:\\\"+mapVoc_Freq.size()+\\\" token-doc.freq:\\\"+map_Word_UniqueDocumentIdHavingIT.size());\\n\\t\\t\\tint uniq_word_id=1;\\n\\t\\t\\tTreeMap<String, Integer> mapVocabulary_word_wordID= new TreeMap<String, Integer>();\\n\\t\\t\\t// create uniq_word_id for each word in vocabulary\\n\\t\\t\\tfor(String word:mapVoc_Freq.keySet()){\\n\\t\\t\\t\\tmapVocabulary_word_wordID.put(word, uniq_word_id);\\n\\t\\t\\t\\t\\n\\t\\t\\t\\twriter_voc.append(word+\\\"!!!\\\"+uniq_word_id+\\\"\\\\n\\\");\\n\\t\\t\\t\\twriter_voc.flush();\\n\\t\\t\\t\\t \\n\\t\\t\\t\\tuniq_word_id++;\\n\\t\\t\\t}\\n\\t\\t\\tSystem.out.println(\\\"step 1: running docid-wordid-tf-IDF\\\");\\n\\t\\t\\t//step 1: calculate tf-idf (DONT COMMENT BELOW)\\n\\t\\t\\tfor(int docID:map_DocID_wordFrequency.keySet()){\\n\\t\\t\\t\\t//System.out.println(\\\"docID:\\\"+docID+ \\\" size:\\\" +map_DocID_wordFrequency.get(docID).size()); //\\t+\\\" word-freq:\\\"+map_DocID_wordFrequency.get(docID));\\n\\t\\t\\t\\twriter_debug.append(\\\"docID:\\\"+docID+ \\\" size:\\\" +map_DocID_wordFrequency.get(docID).size()+\\\" word-freq:\\\"+map_DocID_wordFrequency.get(docID)+\\\"\\\\n\\\");\\n\\t\\t\\t\\twriter_debug.flush();\\n\\t\\t\\t\\tdouble tf_idf=0.0;\\n\\t\\t\\t\\t//Iterate each word in current document\\n\\t\\t\\t\\tfor(String word:map_DocID_wordFrequency.get(docID).keySet() ){\\n\\t\\t\\t\\t\\t//\\n\\t\\t\\t\\t\\tif(mapVoc_Freq.containsKey(word )){\\n\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t//System.out.println(\\\"param1,2:\\\"+map_DocID_wordFrequency.get(docID).get(word) +\\\" \\\"+map_Word_UniqueDocumentIdHavingIT.get(word).size() );\\n\\t\\t\\t\\t\\t\\t// tf-idf\\n\\t\\t\\t\\t\\t\\ttf_idf=map_DocID_wordFrequency.get(docID).get(word) * Math.log10( map_DocID_wordFrequency.size() / map_Word_UniqueDocumentIdHavingIT.get(word).size() );\\n\\t\\t\\t\\t\\t\\t//System.out.println();\\n\\t\\t\\t\\t\\t\\twriter.append( docID+\\\"!!!\\\"+word+\\\"!!!\\\"+tf_idf+\\\"\\\\n\\\");\\n\\t\\t\\t\\t\\t\\twriter.flush();\\n\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\twriter_wordID.append( docID+\\\"!!!\\\"+mapVocabulary_word_wordID.get(word)+\\\"!!!\\\"+tf_idf+\\\"\\\\n\\\");\\n\\t\\t\\t\\t\\t\\twriter_wordID.flush();\\n\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t// \\n\\t\\t\\t\\t\\t\\tif(!Stopwords.is_stopword(word.toLowerCase())){\\n\\t\\t\\t\\t\\t\\t\\twriter_no_stopword.append(docID+\\\"!!!\\\"+word+\\\"!!!\\\"+tf_idf+\\\"\\\\n\\\");\\n\\t\\t\\t\\t\\t\\t\\twriter_no_stopword.flush();\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\twriter_wordID_no_stopword.append(docID+\\\"!!!\\\"+ mapVocabulary_word_wordID.get(word) +\\\"!!!\\\"+tf_idf+\\\"\\\\n\\\");\\n\\t\\t\\t\\t\\t\\t\\twriter_wordID_no_stopword.flush();\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\telse{\\n\\t\\t\\t\\t\\t\\twriter_debug_2.append( \\\"(not exist in vocab) word->\\\"+word+\\\" for doc_id->\\\"+docID+\\\"\\\\n\\\");\\n\\t\\t\\t\\t\\t\\twriter_debug_2.flush();\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t}\\n\\t\\t\\t} //for(int docID:map_DocID_wordFrequency.keySet()){\\n\\t\\t\\t\\n\\t\\t\\tSystem.out.println(\\\"step 2: running docid-wordid-frquency\\\");\\n\\t\\t\\t//step 2: (DOC-WORDID AND FREQUENCY)another output - writing <docID!!!wordID!!!frequency>\\n\\t\\t\\tfor(int docID:map_DocID_wordFrequency.keySet()){\\n\\t\\t\\t\\t\\n\\t\\t\\t\\tSystem.out.println(\\\"2.docID:\\\"+docID+ \\\" size:\\\" +map_DocID_wordFrequency.get(docID).size()); //\\t+\\\" word-freq:\\\"+map_DocID_wordFrequency.get(docID));\\n\\t\\t\\t\\t//writer_debug.append(\\\"docID:\\\"+docID+ \\\" size:\\\" +map_DocID_wordFrequency.get(docID).size()+\\\" word-freq:\\\"+map_DocID_wordFrequency.get(docID)+\\\"\\\\n\\\");\\n\\t\\t\\t\\t//writer_debug.flush();\\n\\t\\t\\t\\tint frequency=0;\\n\\t\\t\\t\\t//Iterate each word in current document\\n\\t\\t\\t\\tfor(String word:map_DocID_wordFrequency.get(docID).keySet() ){\\n\\t\\t\\t\\t\\t//\\n\\t\\t\\t\\t\\tif(mapVoc_Freq.containsKey(word )){\\n\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t// System.out.println(\\\"param1,2:\\\"+map_DocID_wordFrequency.get(docID).get(word) +\\\" \\\"+map_Word_UniqueDocumentIdHavingIT.get(word).size() );\\n\\t\\t\\t\\t\\t\\t// frequency\\n\\t\\t\\t\\t\\t\\tfrequency=map_DocID_wordFrequency.get(docID).get(word);\\n\\t\\t\\t\\t\\t\\t//System.out.println();\\n\\t\\t\\t\\t\\t\\twriter2.append( docID+\\\"!!!\\\"+word+\\\"!!!\\\"+frequency+\\\"\\\\n\\\");\\n\\t\\t\\t\\t\\t\\twriter2.flush();\\n\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\twriter2_wordID.append( docID+\\\"!!!\\\"+mapVocabulary_word_wordID.get(word)+\\\"!!!\\\"+frequency+\\\"\\\\n\\\");\\n\\t\\t\\t\\t\\t\\twriter2_wordID.flush();\\n\\t\\t\\t\\t\\t\\t \\n\\t\\t\\t\\t\\t\\t// \\n\\t\\t\\t\\t\\t\\tif(!Stopwords.is_stopword(word.toLowerCase())){\\n\\t\\t\\t\\t\\t\\t\\twriter2_no_stopword.append(docID+\\\"!!!\\\"+word+\\\"!!!\\\"+frequency+\\\"\\\\n\\\");\\n\\t\\t\\t\\t\\t\\t\\twriter2_no_stopword.flush();\\n\\t\\t\\t\\t\\t\\t\\t//\\n\\t\\t\\t\\t\\t\\t\\twriter2_wordID_no_stopword.append(docID+\\\"!!!\\\"+ mapVocabulary_word_wordID.get(word) +\\\"!!!\\\"+frequency+\\\"\\\\n\\\");\\n\\t\\t\\t\\t\\t\\t\\twriter2_wordID_no_stopword.flush();\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\telse{\\n\\t\\t\\t\\t\\t\\twriter_debug_2.append( \\\"(not exist in vocab) word->\\\"+word+\\\" for doc_id->\\\"+docID+\\\"\\\\n\\\");\\n\\t\\t\\t\\t\\t\\twriter_debug_2.flush();\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t}\\n\\t\\t\\t} //for(int docID:map_DocID_wordFrequency.keySet()){\\n\\n\\t\\t\\tSystem.out.println(\\\"********************************************\\\");\\n\\t\\t\\tSystem.out.println(\\\"File holding the not found words in vocabulary: \\\"+\\\"outFile+\\\\\\\"_DEBUG_2.txt\\\\\\\"\\\");\\n\\t\\t\\tSystem.out.println(\\\"Doc-wise word freq: \\\"+\\\"outFile+\\\\\\\"_DEBUG.txt\\\\\\\"\\\");\\n\\t\\t\\tSystem.out.println(\\\"******Below files are docId-wordID-tfIDF\\\");\\n\\t\\t\\tSystem.out.println(\\\"with Word->\\\"+outFile);\\n\\t\\t\\tSystem.out.println(\\\"with Word(no stopword)->\\\"+outFile+\\\"_noStopWord.txt\\\");\\n\\t\\t\\tSystem.out.println(\\\"with WordID->\\\"+outFile+\\\"_WORD_ID.txt\\\");\\n\\t\\t\\tSystem.out.println(\\\"with WordID(no stopword)->\\\"+outFile+\\\"_noStopWord_WORD_ID.txt\\\");\\n\\t\\t\\tSystem.out.println(\\\"VOC FILE ->\\\"+baseFolder+\\\"unique_word_vocabulary.txt\\\");\\n\\t\\t\\t//**********/\\n\\t\\t\\tSystem.out.println(\\\"***********Below files are docId-wordID-frequency (file ends with \\\\\\\"format2.txt\\\\\\\"\\\");\\n\\t\\t\\tSystem.out.println( \\\"\\\"+outFile+\\\"_docWordID_freq2.txt\\\");\\n\\t\\t\\tSystem.out.println( \\\"\\\"+outFile+\\\"_noStopWord2.txt\\\");\\n\\t\\t\\tSystem.out.println( \\\"\\\"+outFile+\\\"_WORD_ID2.txt\\\");\\n\\t\\t\\tSystem.out.println( \\\"\\\"+outFile+\\\"_noStopWord_WORD_ID2.txt\\\");\\n\\t\\t\\tSystem.out.println( \\\"\\\"+outFile+\\\"_Word_stemmedWord2.txt\\\");\\n\\t\\t\\t \\n\\t\\t\\tmapOut.put(-99, outFile+\\\"_noStopWord_WORD_ID.txt\\\");\\n\\t\\t\\t//maximum word id\\n\\t\\t\\tmapOut.put(1, String.valueOf( uniq_word_id) );\\n\\t\\t}\\n\\t\\tcatch(Exception e){\\n\\t\\t\\te.printStackTrace();\\n\\t\\t}\\n\\t\\treturn mapOut;\\n\\t}\",\n \"public static void DocumentFrequencies() throws FileNotFoundException {\\n for (Entry<String, List<Integer>> entry : dictionary.entrySet()) {\\n List<Integer> termfrequency = new ArrayList<>();\\n\\n termfrequency = entry.getValue();\\t// getting each word's termfrequency list\\n int i = 0;\\n termfrequency.add(0); \\t\\t\\t//maintaining documentfrequency at the 57th index\\n Integer documentFrequency = termfrequency.get(totaldocument+1);\\n while(i<56) { //iterate 0 to 55 all speeches term frequency\\n if(termfrequency.get(i)>0) {\\t\\t//increment document frequency of that word if termfrequency is greater than 0.0\\n documentFrequency++;\\t\\t\\t//increment document frequency\\n }\\n i++;\\t\\t//increment index\\n }\\n termfrequency.set(57, documentFrequency);\\t//re-set the documentfrequency and save the current maintained document frequency from 0 to calculated value\\n dictionary.put(entry.getKey(), termfrequency);\\t\\t// place the incremented final value of that word back to the same list in dictionary hashmap\\n }\\n //save();\\n }\",\n \"public void createIDMap()\\n {\\n IDMap = new HashMap<>();\\n idFile.open(\\\"idpassword.txt\\\");\\n String line = idFile.getNextLine();\\n\\n\\n\\n while(line!=null) {\\n String[] fields = line.split(\\\",\\\");\\n IDMap.put(fields[0], fields[1]);\\n\\n line = idFile.getNextLine();\\n\\n }\\n\\n }\",\n \"public void indexDocument(String documentName, ArrayList<String> documentTokens) {\\n for (String token : documentTokens) {\\n if (!this.index.containsKey(token)) {\\n // Create a key with that token\\n this.index.put(token, new HashMap<>());\\n }\\n\\n // Get the HashMap associated with that term\\n HashMap<String, Integer> term = this.index.get(token);\\n\\n // Check if term has a posting for the document\\n if (term.containsKey(documentName)) {\\n // Increase its occurrence by 1\\n int occurrences = term.get(documentName);\\n term.put(documentName, ++occurrences);\\n } else {\\n // Create a new posting for the term\\n term.put(documentName, 1);\\n }\\n }\\n }\",\n \"public void buildWordFileMap(){\\n hashWords.clear();\\n DirectoryResource dr = new DirectoryResource();\\n for (File f : dr.selectedFiles()){ //for all the files selected make the hashWords hashmap\\n addWordsFromFile(f);\\n }\\n \\n }\",\n \"private void createTokenIndex(){\\n\\t\\tLinkedList<String> tokens = new LinkedList<>(tokenDict.keySet());\\n\\t\\tArrayList<ArrayList<Integer>> vals = new ArrayList<>(tokenDict.values());\\n\\t\\tint k = 8;\\n\\n\\t\\tKFront kf = new KFront(true);\\n\\t\\tkf.createKFront(k, tokens);\\n\\n\\t\\tTokensIndex tIdx = new TokensIndex(k, this.dir);\\n\\t\\ttIdx.insertData(kf.getTable(), vals, kf.getConcatString());\\n\\n\\t\\tsaveToDir(TOKEN_INDEX_FILE, tIdx);\\n\\t}\",\n \"private static Positional_inverted_index posindexCorpus(DocumentCorpus corpus) throws ClassNotFoundException, InstantiationException, IllegalAccessException, FileNotFoundException, IOException {\\n\\n NewTokenProcessor processor = new NewTokenProcessor();\\n Iterable<Document> docs = corpus.getDocuments(); //call registerFileDocumentFactory first?\\n\\n List<Double> Doc_length = new ArrayList<>();\\n Positional_inverted_index index = new Positional_inverted_index();\\n\\n double token_count = 0;\\n\\n // Iterate through the documents, and:\\n for (Document d : docs) {\\n //File f = new File(path + \\\"\\\\\\\\\\\" + d.getTitle());\\n File f = new File(path + \\\"\\\\\\\\\\\" + d.getFileName().toString());\\n double Filesize = f.length();\\n //edited by bhavya\\n double doc_weight = 0; //first entry in docweights.bin\\n double doc_tokens = 0;\\n double doc_length = 0;\\n HashMap<String, Integer> tftd = new HashMap<>();\\n // Tokenize the document's content by constructing an EnglishTokenStream around the document's content.\\n Reader reader = d.getContent();\\n EnglishTokenStream stream = new EnglishTokenStream(reader); //can access tokens through this stream\\n N++;\\n // Iterate through the tokens in the document, processing them using a BasicTokenProcessor,\\n //\\t\\tand adding them to the HashSet vocabulary.\\n Iterable<String> tokens = stream.getTokens();\\n int i = 0;\\n\\n for (String token : tokens) {\\n\\n //adding token in index\\n List<String> word = new ArrayList<String>();\\n word = processor.processToken(token);\\n //System.out.println(word.get(0));\\n if (word.get(0).matches(\\\"\\\")) {\\n continue;\\n } else {\\n\\n index.addTerm(word.get(0), i, d.getId());\\n\\n }\\n i = i + 1;\\n\\n //we check if token already exists in hashmap or not. \\n //if it exists, increase its freq by 1 else make a new entry.\\n if (tftd.containsKey(word.get(0))) {\\n doc_tokens++;\\n int count = tftd.get(word.get(0));\\n tftd.replace(word.get(0), count + 1);\\n } else {\\n doc_tokens++;\\n// token_count++; //gives total number of tokens.\\n tftd.put(word.get(0), 1);\\n }\\n\\n }\\n double length = 0;\\n double wdt = 0;\\n\\n double total_tftd = 0;\\n for (Map.Entry<String, Integer> entry : tftd.entrySet()) {\\n\\n wdt = 1 + log(entry.getValue());\\n\\n length = length + pow(wdt, 2);\\n total_tftd = total_tftd + entry.getValue();\\n }\\n token_count = token_count + doc_tokens;\\n doc_weight = pow(length, 0.5);\\n double avg_tftd = total_tftd / (double) tftd.size();\\n\\n Doc_length.add(doc_weight);\\n Doc_length.add(avg_tftd);\\n Doc_length.add(doc_tokens);\\n Doc_length.add(Filesize);\\n }\\n Doc_length.add(token_count / N);\\n\\n DiskIndexWriter d = new DiskIndexWriter();\\n d.write_doc(path, Doc_length);\\n\\n return index;\\n }\",\n \"static void idlize() throws IOException {\\r\\n\\t\\t/**give mid who has name a id, for other mid, keep using mid to identify them*/\\r\\n\\t\\t//\\t\\tHashMap<String, Integer> namedmid2name = new HashMap<String, Integer>(20000000);\\r\\n\\t\\t//\\t\\tHashMap<String, Integer> relationname2id = new HashMap<String, Integer>(1000000);\\r\\n\\t\\t//\\t\\tDelimitedWriter dw = new DelimitedWriter(Main.dir + \\\"/visible_idize\\\");\\r\\n\\t\\t//\\t\\tDelimitedWriter dw_debug = new DelimitedWriter(Main.dir + \\\"/visible_debug\\\");\\r\\n\\t\\t//\\t\\t{\\r\\n\\t\\t//\\t\\t\\tDelimitedReader dr = new DelimitedReader(Main.file_fbenglishname);\\r\\n\\t\\t//\\t\\t\\tString[] l;\\r\\n\\t\\t//\\t\\t\\twhile ((l = dr.read()) != null) {\\r\\n\\t\\t//\\t\\t\\t\\tnamedmid2name.put(l[0], namedmid2name.size());\\r\\n\\t\\t//\\t\\t\\t}\\r\\n\\t\\t//\\t\\t\\tD.p(\\\"load mid2name finished\\\");\\r\\n\\t\\t//\\t\\t\\tdr.close();\\r\\n\\t\\t//\\t\\t}\\r\\n\\t\\t//\\t\\t{\\r\\n\\t\\t//\\t\\t\\tDelimitedReader dr = new DelimitedReader(Main.file_visible_str);\\r\\n\\t\\t//\\t\\t\\tString[] l;\\r\\n\\t\\t//\\t\\t\\twhile ((l = dr.read()) != null) {\\r\\n\\t\\t//\\t\\t\\t\\tString mid = l[0];\\r\\n\\t\\t//\\t\\t\\t\\tInteger gid = namedmid2name.get(mid);\\r\\n\\t\\t//\\t\\t\\t\\tif (gid == null) {\\r\\n\\t\\t//\\t\\t\\t\\t\\tdw_debug.write(l);\\r\\n\\t\\t//\\t\\t\\t\\t\\tcontinue;\\r\\n\\t\\t//\\t\\t\\t\\t}\\r\\n\\t\\t//\\t\\t\\t\\tString relationname = l[2];\\r\\n\\t\\t//\\t\\t\\t\\tif (!relationname2id.containsKey(relationname)) {\\r\\n\\t\\t//\\t\\t\\t\\t\\trelationname2id.put(relationname, relationname2id.size());\\r\\n\\t\\t//\\t\\t\\t\\t}\\r\\n\\t\\t//\\t\\t\\t\\tint relid = relationname2id.get(relationname);\\r\\n\\t\\t//\\t\\t\\t\\tdw.write(l[1], gid, relid, l[3]);\\r\\n\\t\\t//\\t\\t\\t}\\r\\n\\t\\t//\\t\\t\\tdr.close();\\r\\n\\t\\t//\\t\\t}\\r\\n\\t\\t//\\t\\t{\\r\\n\\t\\t//\\t\\t\\tDelimitedReader dr = new DelimitedReader(Main.file_visible_str);\\r\\n\\t\\t//\\t\\t\\tString[] l;\\r\\n\\t\\t//\\t\\t\\twhile ((l = dr.read()) != null) {\\r\\n\\t\\t//\\t\\t\\t\\tString mid1 = l[0];\\r\\n\\t\\t//\\t\\t\\t\\tString mid2 = l[3];\\r\\n\\t\\t//\\t\\t\\t\\tInteger gid1 = namedmid2name.get(mid1);\\r\\n\\t\\t//\\t\\t\\t\\tInteger gid2 = namedmid2name.get(mid2);\\r\\n\\t\\t//\\t\\t\\t\\tif (gid1 == null || gid2 == null) {\\r\\n\\t\\t//\\t\\t\\t\\t\\tdw_debug.write(l);\\r\\n\\t\\t//\\t\\t\\t\\t\\tcontinue;\\r\\n\\t\\t//\\t\\t\\t\\t}\\r\\n\\t\\t//\\t\\t\\t\\tString relationname = l[2];\\r\\n\\t\\t//\\t\\t\\t\\tif (!relationname2id.containsKey(relationname)) {\\r\\n\\t\\t//\\t\\t\\t\\t\\trelationname2id.put(relationname, relationname2id.size());\\r\\n\\t\\t//\\t\\t\\t\\t}\\r\\n\\t\\t//\\t\\t\\t\\tint relid = relationname2id.get(relationname);\\r\\n\\t\\t//\\t\\t\\t\\tdw.write(l[1], gid1, relid, gid2, l[3]);\\r\\n\\t\\t//\\t\\t\\t}\\r\\n\\t\\t//\\t\\t\\tdr.close();\\r\\n\\t\\t//\\t\\t}\\r\\n\\t\\t//\\t\\tdw.close();\\r\\n\\t\\t//\\t\\t{\\r\\n\\t\\t//\\t\\t\\tDelimitedWriter dwrel = new DelimitedWriter(Main.dir + \\\"/visible_relations.temp\\\");\\r\\n\\t\\t//\\t\\t\\tfor (Entry<String, Integer> e : relationname2id.entrySet()) {\\r\\n\\t\\t//\\t\\t\\t\\tdwrel.write(e.getValue(), e.getKey());\\r\\n\\t\\t//\\t\\t\\t}\\r\\n\\t\\t//\\t\\t\\tdwrel.close();\\r\\n\\t\\t//\\t\\t\\tSort.sort(Main.dir + \\\"/visible_relations.temp\\\", Main.dir + \\\"/visible_relations\\\", Main.dir,\\r\\n\\t\\t//\\t\\t\\t\\t\\tnew Comparator<String[]>() {\\r\\n\\t\\t//\\t\\t\\t\\t\\t\\t@Override\\r\\n\\t\\t//\\t\\t\\t\\t\\t\\tpublic int compare(String[] o1, String[] o2) {\\r\\n\\t\\t//\\t\\t\\t\\t\\t\\t\\t// TODO Auto-generated method stub\\r\\n\\t\\t//\\t\\t\\t\\t\\t\\t\\treturn Integer.parseInt(o1[0]) - Integer.parseInt(o2[0]);\\r\\n\\t\\t//\\t\\t\\t\\t\\t\\t}\\r\\n\\t\\t//\\r\\n\\t\\t//\\t\\t\\t\\t\\t});\\r\\n\\t\\t//\\t\\t}\\r\\n\\t\\t//\\t\\t{\\r\\n\\t\\t//\\t\\t\\tDelimitedWriter dwmid = new DelimitedWriter(Main.dir + \\\"/visible_mid2gid.temp\\\");\\r\\n\\t\\t//\\t\\t\\tfor (Entry<String, Integer> e : namedmid2name.entrySet()) {\\r\\n\\t\\t//\\t\\t\\t\\tdwmid.write(e.getValue(), e.getKey());\\r\\n\\t\\t//\\t\\t\\t}\\r\\n\\t\\t//\\t\\t\\tdwmid.close();\\r\\n\\t\\t//\\t\\t\\tSort.sort(Main.dir + \\\"/visible_mid2gid.temp\\\", Main.dir + \\\"/visible_mid2gid\\\", Main.dir,\\r\\n\\t\\t//\\t\\t\\t\\t\\tnew Comparator<String[]>() {\\r\\n\\t\\t//\\t\\t\\t\\t\\t\\t@Override\\r\\n\\t\\t//\\t\\t\\t\\t\\t\\tpublic int compare(String[] o1, String[] o2) {\\r\\n\\t\\t//\\t\\t\\t\\t\\t\\t\\t// TODO Auto-generated method stub\\r\\n\\t\\t//\\t\\t\\t\\t\\t\\t\\treturn Integer.parseInt(o1[0]) - Integer.parseInt(o2[0]);\\r\\n\\t\\t//\\t\\t\\t\\t\\t\\t}\\r\\n\\t\\t//\\r\\n\\t\\t//\\t\\t\\t\\t\\t});\\r\\n\\t\\t//\\t\\t}\\r\\n\\t}\",\n \"public void map()\\n\\t{\\n\\t // key is the documentId\\n\\t\\t// value is the url\\n\\t\\t//fetch the document using the documentId\\n\\t\\t\\n\\t}\",\n \"private void saveMap() {\\r\\n new Thread(() -> {\\r\\n try {\\r\\n FileOutputStream f = new FileOutputStream(this.save_file);\\r\\n ObjectOutputStream S = new ObjectOutputStream(f);\\r\\n S.writeObject(this.music_map);\\r\\n S.close();\\r\\n f.close();\\r\\n if (!this.save_file.setLastModified(this.music_root.lastModified())) {\\r\\n throw new IllegalStateException(\\\"Impossibile aggiornare il file dizionario\\\");\\r\\n }\\r\\n } catch (IOException e) {\\r\\n e.printStackTrace();\\r\\n }\\r\\n }).start();\\r\\n }\",\n \"private static void collectVariables(Document document){\\n //collecting all the nodes inside a list\\n nodeList = document.selectNodes(NOTES);\\n\\n //initialising the lists\\n entriesList = new ArrayList<>();\\n locationsList = new ArrayList<>();\\n attachmentList = new ArrayList<>();\\n tagsForEntryList = new ArrayList<>();\\n\\n //hashSet for handling the duplicate fileNames\\n fileNameSet = new LinkedHashSet<>();\\n\\n //linkedHashMap for storing the uid for each tag\\n uidForEachTag = new LinkedHashMap<>();\\n uidForEachLocation = new LinkedHashMap<>();\\n\\n //id set for storing unique location id\\n locationsIdSet = new LinkedHashSet<>();\\n\\n Tags tags;\\n Location location;\\n Entry entry;\\n Attachment attachment;\\n\\n byte[] decoded = null;\\n\\n //looping through the list\\n for(Node node : nodeList){\\n\\n String title = \\\"\\\";\\n String parsedHtml = \\\"\\\";\\n String formattedDate = \\\"\\\";\\n String location_uid = \\\"\\\";\\n String mime = \\\"\\\";\\n String fileName = \\\"\\\";\\n String attachment_uid = null;\\n String entry_uid = \\\"\\\";\\n String type = \\\"photo\\\";\\n String baseEncoding;\\n String tag_uid = \\\"\\\";\\n\\n //get all tags including duplicates\\n if( node.selectSingleNode(TAG) !=null) {\\n List<Node> evernote_tags = node.selectNodes(TAG);\\n for (Node evenote_tag : evernote_tags) {\\n //generate unique id for the tag and map it.\\n //if the name id pair does not exist\\n if(!uidForEachTag.containsKey(evenote_tag.getText())) {\\n uidForEachTag.put(evenote_tag.getText(), Entry.generateRandomUid());\\n }\\n //create new diaro.Tags Object\\n tags = new Tags(uidForEachTag.get(evenote_tag.getText()),evenote_tag.getText());\\n tagsForEntryList.add(tags);\\n }\\n }\\n\\n //get all Locations\\n // using diaro.Entry.concatLatLng to add title as {<Latitude></Latitude>,<Longitude></Longitude>}\\n if( node.selectSingleNode(LATITUDE) != null && node.selectSingleNode(LONGITUDE) != null) {\\n String latitude = String.format(\\\"%.5f\\\",Double.parseDouble(node.selectSingleNode(LATITUDE).getText()));\\n String longitude = String.format(\\\"%.5f\\\",Double.parseDouble(node.selectSingleNode(LONGITUDE).getText()));\\n String location_title = (ImportUtils.concatLatLng(latitude, longitude));\\n\\n //mapping every uid to the address\\n if(!uidForEachLocation.containsKey(location_title)) {\\n uidForEachLocation.put(location_title, Entry.generateRandomUid());\\n }\\n location_uid = uidForEachLocation.get(location_title);\\n location = new Location(location_uid,latitude,longitude,location_title, location_title, DEFAULT_ZOOM);\\n if (!locationsIdSet.contains(location.location_uid)) {\\n locationsList.add(location);\\n locationsIdSet.add(location.location_uid);\\n }\\n }\\n\\n //get all Entries\\n if(node.selectSingleNode(TITLE) != null ){\\n title = node.selectSingleNode(TITLE).getText();\\n }\\n if(node.selectSingleNode(CONTENT) != null ){\\n String text = node.selectSingleNode(CONTENT).getText();\\n // using Jsoup to parseXml HTML inside Content\\n parsedHtml = Jsoup.parse(text).text();\\n }\\n if(node.selectSingleNode(CREATED) != null){\\n String date = node.selectSingleNode(CREATED).getText().substring(0, 8);\\n String month = date.substring(4, 6);\\n String day = date.substring(6, 8);\\n String year = date.substring(2, 4);\\n formattedDate = String.format(\\\"%s/%s/%s\\\", month, day, year);\\n }\\n\\n //get all the tags\\n //append all the string stringBuilder\\n if(tagsForEntryList.size() != 0){\\n for(Tags tag : tagsForEntryList) {\\n tag_uid = tag_uid + (\\\",\\\") + (String.join(\\\",\\\", tag.tagsId));\\n }\\n tag_uid = tag_uid + (\\\",\\\");\\n System.out.println(tag_uid);\\n\\n }\\n entry = new Entry();\\n entry.setUid(Entry.generateRandomUid());\\n entry.setTz_offset(OFFSET);\\n entry.setDate(formattedDate);\\n entry.setText(parsedHtml);\\n entry.setTitle(title);\\n entry.setFolder_uid(FOLDER_UID);\\n entry.setLocation_uid(location_uid);\\n entry.setTags(tag_uid);\\n //clear the list\\n //clear the tag_uid variable for next loop\\n tagsForEntryList.clear();\\n tag_uid = \\\"\\\";\\n //add entry in the list\\n entriesList.add(entry);\\n\\n //get all the attachments\\n if (node.selectSingleNode(RESOURCE) != null) {\\n List<Node> attachmentsForEachEntry = node.selectNodes(RESOURCE);\\n //loop through all the attachments for a single note/entry\\n for (Node attachmentForeach : attachmentsForEachEntry) {\\n try {\\n mime = attachmentForeach.selectSingleNode(MIME).getText();\\n\\n }catch( NullPointerException e){\\n e.printStackTrace();\\n }\\n // check for a valid attachment\\n if(checkForImageMime(mime)) {\\n try {\\n fileName = attachmentForeach.selectSingleNode(RESOURCE_ATTRIBUTE_FILENAME).getText();\\n attachment_uid = Entry.generateRandomUid();\\n entry_uid = entry.uid;\\n baseEncoding = attachmentForeach.selectSingleNode(DATA).getText();\\n //----- please do a check for valid Base64--\\n decoded = Base64.getMimeDecoder().decode(baseEncoding);\\n // assign primary_photo uid to entry\\n entry.primary_photo_uid = attachment_uid;\\n }catch(IllegalArgumentException | NullPointerException e){\\n e.printStackTrace();\\n }\\n // check if the fileName already exists\\n // if true generate a new fileName to prevent duplicates\\n if(fileNameSet.add(fileName)){\\n fileNameSet.add(fileName);\\n attachment = new Attachment(attachment_uid, entry_uid, type,fileName,decoded);\\n }else{\\n String newFileName = ImportUtils.generateNewFileName(fileName);\\n fileNameSet.add(newFileName);\\n attachment = new Attachment(attachment_uid, entry_uid, type,newFileName,decoded);\\n }\\n attachmentList.add(attachment);\\n }\\n }\\n }\\n }\\n\\n }\",\n \"private HashMap<String, HashSet<String>> convertIndexToMap(IndexReader reader) throws IOException{\\n\\t\\t HashMap<String, HashSet<String>> hmap = new HashMap<String, HashSet<String>>();\\n\\t\\t HashSet<String> docIdSet;\\n\\t\\t \\n\\t\\t for(int i=0; i<reader.numDocs(); i++){\\n\\t\\t\\t Fields termVect = reader.getTermVectors(i);\\n\\n\\t\\t\\t if(termVect == null)\\n\\t\\t\\t\\t continue;\\n\\t\\t\\t \\n\\t for (String field : termVect) {\\n\\t \\t \\n\\t Terms terms = termVect.terms(field);\\n\\t TermsEnum termsEnum = terms.iterator();\\n\\t Document doc = reader.document(i);\\n\\t \\n\\t while(termsEnum.next() != null){\\n\\t \\t BytesRef term = termsEnum.term();\\n\\t \\t String strTerm = term.utf8ToString();\\n\\t \\t \\n\\t \\t if (hmap.containsKey(strTerm)){\\n\\t \\t\\t docIdSet = hmap.get(strTerm);\\n\\t \\t\\t docIdSet.add(doc.get(\\\"url\\\"));\\n\\t \\t } else{\\n\\t \\t\\t docIdSet = new HashSet<String>();\\n\\t \\t\\t docIdSet.add(doc.get(\\\"url\\\"));\\n\\t \\t\\t hmap.put(strTerm, docIdSet);\\n\\t \\t }\\n\\t }\\n\\t }\\n\\t\\t }\\n\\t\\t \\n\\t\\t return hmap;\\n\\t}\",\n \"public void IndexADocument(String docno, String content) throws IOException {\\n\\t\\tthis.idWriter.write(docID+\\\":\\\"+docno);\\n\\t\\tthis.idWriter.newLine();\\n\\t\\tthis.idWriter.flush();\\n\\t\\tString[] words = content.split(\\\" \\\");\\n\\t\\tHashMap<String,Integer> count = new HashMap<>();\\n\\t\\tfor(String s:words){\\n\\t\\t\\tcount.put(s,count.getOrDefault(s,0)+1);\\n\\t\\t}\\n\\t\\tfor(String key: count.keySet()){\\n\\t\\t\\tif(this.map.containsKey(key)){\\n\\t\\t\\t\\tthis.map.get(key).append(docID).append(\\\":\\\").append(count.get(key)).append(\\\",\\\");\\n\\t\\t\\t}else {\\n\\t\\t\\t\\tStringBuilder sb = new StringBuilder();\\n\\t\\t\\t\\tthis.map.put(key, sb.append(docID).append(\\\":\\\").append(count.get(key)).append(\\\",\\\"));\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\tdocID++;\\n\\t}\",\n \"public void writeDocumentForA(String filename, String path) throws Exception\\r\\n\\t{\\n\\t\\tFile folder = new File(path);\\r\\n\\t\\tFile[] listOfFiles = folder.listFiles();\\r\\n\\t \\r\\n\\t \\r\\n\\t \\tFileWriter fwText;\\r\\n\\t\\tBufferedWriter bwText;\\r\\n\\t\\t\\r\\n\\t\\tfwText = new FileWriter(\\\"C:/Users/jipeng/Desktop/Qiang/updateSum/TAC2008/Parag/\\\"+ filename+\\\"/\\\" +\\\"A.txt\\\");\\r\\n\\t\\tbwText = new BufferedWriter(fwText);\\r\\n\\t\\t\\r\\n\\t \\tfor ( int i=0; i<listOfFiles.length; i++) {\\r\\n\\t \\t\\t//String name = listOfFiles[i].getName();\\r\\n\\t\\t\\t\\r\\n\\t\\t\\t\\r\\n\\t\\t\\tString text = readText(listOfFiles[i].getAbsolutePath());\\r\\n\\t\\t\\t\\r\\n\\t\\t\\tFileWriter fwWI = new FileWriter(\\\"C:/pun.txt\\\");\\r\\n\\t\\t\\tBufferedWriter bwWI = new BufferedWriter(fwWI);\\r\\n\\t\\t\\t\\r\\n\\t\\t\\tbwWI.write(text);\\r\\n\\t\\t\\t\\r\\n\\t\\t\\tbwWI.close();\\r\\n\\t\\t\\tfwWI.close();\\r\\n\\t\\t\\t\\r\\n\\t\\t\\t\\r\\n\\t\\t\\tList<List<HasWord>> sentences = MaxentTagger.tokenizeText(new BufferedReader(new FileReader(\\\"C:/pun.txt\\\")));\\r\\n\\t\\t\\t\\r\\n\\t\\t\\t//System.out.println(text);\\r\\n\\t\\t\\tArrayList<Integer> textList = new ArrayList<Integer>();\\r\\n\\t\\t\\t\\r\\n\\t\\t\\tfor (List<HasWord> sentence : sentences)\\r\\n\\t\\t\\t {\\r\\n\\t\\t\\t ArrayList<TaggedWord> tSentence = tagger.tagSentence(sentence);\\r\\n\\t\\t\\t \\r\\n\\t\\t\\t for(int j=0; j<tSentence.size(); j++)\\r\\n\\t\\t\\t {\\r\\n\\t\\t\\t \\t \\tString word = tSentence.get(j).value();\\r\\n\\t\\t\\t \\t \\t\\r\\n\\t\\t\\t \\t \\tString token = word.toLowerCase();\\r\\n\\t\\t\\t \\t \\r\\n\\t\\t\\t \\t \\tif(token.length()>2 )\\r\\n\\t\\t\\t\\t \\t{\\r\\n\\t\\t\\t \\t\\t\\t if (!m_EnStopwords.isStopword(token)) \\r\\n\\t\\t\\t \\t\\t\\t {\\r\\n\\t\\t\\t \\t\\t\\t\\t\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t if (word2IdHash.get(token)==null)\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t {\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t textList.add(id);\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t // bwText.write(String.valueOf(id)+ \\\" \\\");\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t word2IdHash.put(token, id);\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t \\r\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t allWordsArr.add(token);\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t \\r\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t id++;\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t } else\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t {\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t \\tint wid=(Integer)word2IdHash.get(token);\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t \\tif(!textList.contains(wid))\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t \\t\\ttextList.add(wid);\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t \\t//bwText.write(String.valueOf(wid)+ \\\" \\\");\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t }\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t \\t\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t }\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t \\r\\n\\t\\t\\t\\t\\t \\t}\\r\\n\\t\\t\\t \\t }\\r\\n\\t\\t\\t }\\r\\n\\t\\t\\tCollections.sort(textList);\\r\\n\\t\\t \\r\\n\\t\\t\\tString text2 = valueFromList(textList);\\r\\n\\t\\t bwText.write(text2);\\r\\n\\t\\t //System.out.println(text2);\\r\\n\\t\\t bwText.newLine();\\r\\n\\t\\t textList.clear();\\r\\n\\t\\t \\r\\n\\t \\t}\\r\\n\\t \\tbwText.close();\\r\\n\\t fwText.close();\\r\\n\\t}\",\n \"public static void pageRankmain() {\\n\\t\\t\\t\\n\\t\\t\\tstopWordStore();\\n\\t\\t\\t//File[] file_read= dir.listFiles();\\n\\t\\t\\t//textProcessor(file_read);// Will be called from LinkCrawler\\n\\t\\t\\t//queryProcess();\\n\\t\\t\\t//System.out.println(\\\"docsave \\\"+ docsave);\\n\\t\\t\\t/*for ( Map.Entry<String, ArrayList<String>> entry : docsave.entrySet()) {\\n\\t\\t\\t String key = entry.getKey();\\n\\t\\t\\t List<String> values = entry.getValue();\\n\\t\\t\\t System.out.print(\\\"Key = \\\" + key);\\n\\t\\t\\t System.out.println(\\\" , Values = \\\"+ values);\\n\\t\\t\\t}*/\\n\\t\\t\\t//########## RESPOINSIBLE FOR CREATING INVERTED INDEX OF TERMS ##########\\n\\t\\t\\tfor(int i=0;i<vocabulary.size();i++) {\\n\\t\\t\\t\\tint count=1;\\n\\t\\t\\t\\tMap<String, Integer> nestMap = new HashMap<String, Integer>();\\n\\t\\t\\t\\tfor ( Map.Entry<String, ArrayList<String>> entry : docsave.entrySet()) {\\n\\t\\t\\t\\t String keyMain = entry.getKey();\\n\\t\\t\\t\\t List<String> values = entry.getValue();\\n\\t\\t\\t\\t if(values.contains(vocabulary.get(i)))\\n\\t\\t\\t\\t \\t{\\n\\t\\t\\t\\t \\tentryDf.put(vocabulary.get(i), count);//entryDf stores documents frequency of vocabulary word \\\\\\\\it increase the count value for specific key\\n\\t\\t\\t\\t \\tcount++;\\n\\t\\t\\t\\t \\t}\\n\\t\\t\\t\\t \\n\\t\\t\\t\\t nestMap.put(keyMain, Collections.frequency(values,vocabulary.get(i)));\\n\\t\\t\\t \\t\\n\\t\\t\\t \\t//System.out.println(\\\"VOC \\\"+ vocabulary.get(i)+ \\\" KeyMain \\\" +keyMain+ \\\" \\\"+ Collections.frequency(values,vocabulary.get(i)));\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\ttfList.put(vocabulary.get(i), nestMap);\\n\\t\\t\\t}\\n\\t\\t\\t//########## RESPOINSIBLE FOR CREATING A MAP \\\"storeIdf\\\" TO STORE IDF VALUES OF TERMS ##########\\n\\t\\t\\tfor ( Map.Entry<String, Integer> endf : entryDf.entrySet()) {\\n\\t\\t\\t\\tString keydf = endf.getKey();\\n\\t\\t\\t\\tint valdf = endf.getValue();\\n\\t\\t\\t\\t//System.out.print(\\\"Key = \\\" + \\\"'\\\"+keydf+ \\\"'\\\");\\n\\t\\t\\t //System.out.print(\\\" , Values = \\\"+ valdf);\\n\\t\\t\\t double Hudai = (double) (docsave.size())/valdf;\\n\\t\\t\\t //System.out.println(\\\"docsave size \\\"+docsave.size()+ \\\" valdf \\\"+ valdf + \\\" Hudai \\\"+ Hudai+ \\\" log Value1 \\\"+ Math.log(Hudai)+ \\\" log Value2 \\\"+ Math.log(2));\\n\\t\\t\\t double idf= Math.log(Hudai)/Math.log(2);\\n\\t\\t\\t storeIdf.put(keydf, idf);\\n\\t\\t\\t //System.out.print(\\\" idf-> \\\"+ idf);\\n\\t\\t\\t //System.out.println();\\n\\t\\t\\t} \\n\\t\\t\\t\\n\\t\\t\\t//############ Just for Printing ##########NO WORK HERE########\\n\\t\\t\\tfor (Map.Entry<String, Map<String, Integer>> tokTf : tfList.entrySet()) {\\n\\t\\t\\t\\tString keyTf = tokTf.getKey();\\n\\t\\t\\t\\tMap<String, Integer> valTF = tokTf.getValue();\\n\\t\\t\\t\\tSystem.out.println(\\\"Inverted Indexing by Key Word = \\\" + \\\"'\\\"+keyTf+ \\\"'\\\");\\n\\t\\t\\t\\tfor (Map.Entry<String, Integer> nesTf : valTF.entrySet()) {\\n\\t\\t\\t\\t\\tString keyTF = nesTf.getKey();\\n\\t\\t\\t\\t\\tInteger valTf = nesTf.getValue();\\n\\t\\t\\t\\t\\tSystem.out.print(\\\" Document Consists This Key Word = \\\" + \\\"'\\\"+ keyTF+ \\\"'\\\");\\n\\t\\t\\t\\t\\tSystem.out.println(\\\" , Term Frequencies in This Doc = \\\"+ valTf);\\n\\t\\t\\t\\t} \\n\\t\\t\\t}\\n\\t\\t\\t//########### FOR CALCULATING DOCUMENT LENTH #############//\\n\\t\\t\\tfor ( Map.Entry<String, ArrayList<String>> entry_new : docsave.entrySet()) // Iterating Number of Documents\\n\\t\\t\\t{\\n\\t\\t\\t\\tString keyMain_new = entry_new.getKey();\\n\\t\\t\\t\\t//int countStop=0;\\n\\t\\t\\t\\tdouble sum=0;\\n\\t\\t\\t\\t for(Map.Entry<String, Map<String, Integer>> tokTf_new : tfList.entrySet()) // Iterating through the vocabulary\\n\\t\\t\\t\\t { \\n\\t\\t\\t\\t\\t Map<String, Integer> valTF_new = tokTf_new.getValue();\\n\\t\\t\\t\\t\\t for (Map.Entry<String, Integer> nesTf_new : valTF_new.entrySet()) // Iterating Through the Documents\\n\\t\\t\\t\\t\\t {\\n\\t\\t\\t\\t\\t\\t if(keyMain_new.equals(nesTf_new.getKey())) // Only doc name EQUAL with docsave name can enter here\\n\\t\\t\\t\\t\\t\\t {\\n\\t\\t\\t\\t\\t\\t\\t double val = nesTf_new.getValue()* (Double) storeIdf.get(tokTf_new.getKey());\\n\\t\\t\\t\\t\\t\\t\\t sum = sum+ Math.pow(val, 2);\\n\\t\\t\\t\\t\\t\\t }\\n\\t\\t\\t\\t\\t }\\n\\t\\t\\t\\t\\t \\n\\t\\t\\t\\t\\t //countStop++;\\n\\t\\t\\t\\t }\\n\\t\\t\\t\\t docLength.put(keyMain_new, Math.sqrt(sum));\\n\\t\\t\\t\\t sum=0;\\n\\t\\t\\t}\\n\\t\\t\\t\\n\\t\\t\\t\\n\\t\\t\\tSystem.out.println(\\\"Document Length \\\"+ docLength);\\n\\t\\t\\t//System.out.println(\\\"tfList \\\"+tfList);\\n\\t\\t\\t\\n\\t\\t\\t //########### FOR CALCULATING QUERY LENTH #############///\\n\\t\\t\\t\\tdouble qrySum=0;\\n\\t\\t\\t\\t for(String qryTerm: queryList) // Iterating through the vocabulary\\n\\t\\t\\t\\t {\\n\\t\\t\\t\\t\\t//entryQf.put(qryTerm, Collections.frequency(queryList,qryTerm));// VUl ase\\n\\t\\t\\t\\t\\t \\n\\t\\t\\t\\t\\t\\t if(storeIdf.get(qryTerm) != null) \\n\\t\\t\\t\\t\\t\\t {\\n\\t\\t\\t\\t\\t\\t\\t entryQf.put(qryTerm, Collections.frequency(queryList,qryTerm));\\n\\t\\t\\t\\t\\t\\t\\t double val = entryQf.get(qryTerm)* (Double) storeIdf.get(qryTerm);\\n\\t\\t\\t\\t\\t\\t\\t qrySum = qrySum+ Math.pow(val, 2);\\n\\t\\t\\t\\t\\t\\t }\\n\\t\\t\\t\\t\\t System.out.println(qryTerm+\\\" \\\"+entryQf.get(qryTerm)+ \\\" \\\"+ (Double) storeIdf.get(qryTerm));\\n\\t\\t\\t\\t }\\n\\t\\t\\t\\t qrySum=Math.sqrt(qrySum);\\n\\t\\t\\t\\t System.out.println(\\\"qrySum \\\" + qrySum);\\n\\t\\t\\t\\t \\n\\t\\t\\t\\t//########### FOR CALCULATING COSINE SIMILARITY #############///\\n\\t\\t\\t\\t for ( Map.Entry<String, ArrayList<String>> entry_dotP : docsave.entrySet()) // Iterating Number of Documents\\n\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\tdouble sumProduct=0;\\n\\t\\t\\t\\t\\t\\tdouble productTfIdf=0;\\n\\t\\t\\t\\t\\t\\tString keyMain_new = entry_dotP.getKey(); //Geting Doc Name\\n\\t\\t\\t\\t\\t\\t for(Map.Entry<String, Integer> qryTermItr : entryQf.entrySet()) // Iterating through the vocabulary\\n\\t\\t\\t\\t\\t\\t {\\n\\t\\t\\t\\t\\t\\t\\t \\n\\t\\t\\t\\t\\t\\t\\t Map<String, Integer> matchTerm = tfList.get(qryTermItr.getKey()); // Getting a map of doc Names by a Query Term as value of tfList\\n\\n\\t\\t\\t\\t\\t\\t\\t\\t if(matchTerm.containsKey(keyMain_new)) // Only doc name EQUAL with docsave name can enter here\\n\\t\\t\\t\\t\\t\\t\\t\\t {\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t //System.out.println(\\\"Test \\\"+ matchTerm.get(keyMain_new) +\\\" keyMain_new \\\" + keyMain_new);\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t double docTfIdf= matchTerm.get(keyMain_new) * storeIdf.get(qryTermItr.getKey());\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t double qryTfIdf= qryTermItr.getValue() * storeIdf.get(qryTermItr.getKey());\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t productTfIdf = docTfIdf * qryTfIdf;\\n\\t\\t\\t\\t\\t\\t\\t\\t }\\n\\t\\t\\t\\t\\t\\t\\t \\n\\t\\t\\t\\t\\t\\t\\t sumProduct= sumProduct+productTfIdf;\\n\\t\\t\\t\\t\\t\\t\\t //System.out.println(\\\"productTfIdf \\\"+productTfIdf+\\\" sumProduct \\\"+ sumProduct);\\n\\t\\t\\t\\t\\t\\t\\t productTfIdf=0;\\n\\t\\t\\t\\t\\t\\t }\\n\\t\\t\\t\\t\\t\\t cosineProd.put(entry_dotP.getKey(), sumProduct/(docLength.get(entry_dotP.getKey())*qrySum));\\n\\t\\t\\t\\t\\t\\t sumProduct=0;\\n\\t\\t\\t\\t\\t\\t //System.out.println(entry_dotP.getKey()+ \\\" \\\" + docLength.get(entry_dotP.getKey()));\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t System.out.println(\\\"cosineProd \\\"+ cosineProd);\\n\\t\\t\\t\\t \\n\\t\\t\\t\\t System.out.println(\\\"Number of Top Pages you want to see\\\");\\n\\t\\t\\t\\t int topRank = Integer.parseInt(scan.nextLine());\\n\\t\\t\\t\\t Map<String, Double> result = cosineProd.entrySet().stream()\\n\\t\\t\\t .sorted(Map.Entry.comparingByValue(Comparator.reverseOrder())).limit(topRank)\\n\\t\\t\\t .collect(Collectors.toMap(Map.Entry::getKey, Map.Entry::getValue,\\n\\t\\t\\t (oldValue, newValue) -> oldValue, LinkedHashMap::new));\\n\\n\\t\\t\\t\\t scan.close();\\n\\t\\t\\t //Alternative way\\n\\t\\t\\t //Map<String, Double> result2 = new LinkedHashMap<>();\\n\\t\\t\\t //cosineProd.entrySet().stream().sorted(Map.Entry.<String, Double>comparingByValue().reversed()).limit(2).forEachOrdered(x -> result2.put(x.getKey(), x.getValue()));\\n\\n\\t\\t\\t System.out.println(\\\"Sorted...\\\");\\n\\t\\t\\t System.out.println(result);\\n\\t\\t\\t //System.out.println(result2);\\n\\t}\",\n \"private ArrayList<String> loadIds() {\\n\\n\\t\\tArrayList<String> idArray = new ArrayList<String>();\\n\\t\\ttry {\\n\\t\\t\\tFileInputStream fileInputStream = context.openFileInput(SAVE_FILE);\\n\\t\\t\\tInputStreamReader inputStreamReader = new InputStreamReader(\\n\\t\\t\\t\\t\\tfileInputStream);\\n\\t\\t\\tType listType = new TypeToken<ArrayList<String>>() {\\n\\t\\t\\t}.getType();\\n\\t\\t\\tGsonBuilder builder = new GsonBuilder();\\n\\t\\t\\tGson gson = builder.create();\\n\\t\\t\\tArrayList<String> list = gson.fromJson(inputStreamReader, listType);\\n\\t\\t\\tidArray = list;\\n\\t\\t} catch (IOException e) {\\n\\t\\t\\te.printStackTrace();\\n\\t\\t}\\n\\t\\treturn idArray;\\n\\t}\",\n \"public List<K> getSavedIds() {\\n if (dbObjects.length > 0 && dbObjects[0] instanceof JacksonDBObject) {\\n throw new UnsupportedOperationException(\\n \\\"Generated _id retrieval not supported when using stream serialization\\\");\\n }\\n\\n List<K> ids = new ArrayList<K>();\\n for (DBObject dbObject : dbObjects) {\\n ids.add(jacksonDBCollection.convertFromDbId(dbObject.get(\\\"_id\\\")));\\n }\\n\\n return ids;\\n }\",\n \"private synchronized void saveInternal() {\\n if (relatedDocumentsCounter == 0) {\\r\\n return;\\r\\n }\\r\\n\\r\\n final TrigramIndexJsonModel model = new TrigramIndexJsonModel( relatedDocuments, indexGeneration, trigram );\\r\\n final TrigramDocumentCountJsonModel count = new TrigramDocumentCountJsonModel( trigram, globalRelatedDocumentsCounter );\\r\\n\\r\\n indexGeneration++;\\r\\n relatedDocuments = new TreeSet<>();\\r\\n relatedDocumentsCounter = 0;\\r\\n\\r\\n // put that save action and all unnecessary path calculations into a thread pool, \\r\\n // no need that other word can't be indexed, because of someone's save action... \\r\\n\\r\\n Runnable runnable = new Runnable() {\\r\\n @Override\\r\\n public void run() {\\r\\n Path trigramsPath = TrigramSubPathCalculator.getPathForTrigram( trigramsBasePath, trigram,\\r\\n \\\".\\\" + model.getIndexGeneration() + TRIGRAM_REFERENCE_SUFFIX );\\r\\n createTargetDirectoryIfNotExist( trigramsPath.getParent() );\\r\\n\\r\\n // write content of one part of the index\\r\\n try (BufferedWriter writer = Files.newBufferedWriter( trigramsPath, StandardCharsets.UTF_8 )) {\\r\\n Gson gson = new Gson();\\r\\n writer.write( gson.toJson( model ) );\\r\\n }\\r\\n catch (IOException e) {\\r\\n System.out.println( String.format( \\\"saving file: '%s' caused this error...\\\", trigramsPath ) );\\r\\n e.printStackTrace();\\r\\n }\\r\\n\\r\\n // write+overwrite the global documents counter as well\\r\\n Path trigramCountPath = TrigramSubPathCalculator.getPathForTrigram( trigramsBasePath, trigram, TRIGRAM_COUNT_SUFFIX );\\r\\n\\r\\n try (BufferedWriter writer = Files.newBufferedWriter( trigramCountPath, StandardCharsets.UTF_8 )) {\\r\\n Gson gson = new Gson();\\r\\n writer.write( gson.toJson( count ) );\\r\\n }\\r\\n catch (IOException e) {\\r\\n System.out.println( String.format( \\\"saving file: '%s' caused this error...\\\", trigramCountPath ) );\\r\\n e.printStackTrace();\\r\\n }\\r\\n\\r\\n }\\r\\n };\\r\\n\\r\\n // TODO: put into task thread-pool (deque) for really saving indexing time.\\r\\n runnable.run();\\r\\n }\",\n \"private void saveGenres(){\\n\\t\\tFile genreList = new File(Paths.get(\\\"genres.txt\\\").toString());\\n\\t\\ttry{\\n\\t\\t\\tBufferedWriter writer = new BufferedWriter(new FileWriter(genreList));\\n\\t\\t\\tfor (String s : genres){\\n\\t\\t\\t\\twriter.write(s);\\n\\t\\t\\t\\twriter.newLine();\\n\\t\\t\\t}\\n\\t\\t\\twriter.close();\\n\\t\\t} catch(IOException ex){\\n\\t\\t\\t\\n\\t\\t}\\n\\t}\",\n \"public static Map<String, AuthorMod> indexEmails(String fileName)\\n\\t{\\n\\t\\tMap<String, AuthorMod> authBank= new HashMap<String, AuthorMod>();\\t\\t \\n\\t\\tAuthorMod curAuth;\\n\\t\\t//vars for for loop - one loop per email\\n\\t\\tString curTok;\\n\\t\\tString lastTok;\\n\\t\\t\\n\\t\\ttry \\n\\t\\t{\\n\\t\\t\\tScanner scanner = new Scanner(new FileInputStream(fileName));\\n\\t\\t try \\n\\t\\t {\\n\\t\\t while (scanner.hasNextLine())\\n\\t\\t {\\n\\t\\t \\n\\t\\t \\t String[] emailToks= SimpleTokenizer.INSTANCE.tokenize(scanner.nextLine());\\n\\t\\t \\t\\n\\t\\t \\t lastTok = \\\"<s>\\\";\\n\\t\\t \\t curTok = emailToks[3]; //maybe 2, check output\\n\\t\\t \\t Pair<String, String> firstBg = new Pair<String, String>(lastTok, curTok);\\t\\t \\t \\n\\t\\t \\t //author check, possible set\\n\\t\\t \\t String authID = emailToks[0] + emailToks[1] + emailToks[2]; //check output from the tokenizer\\t \\t\\n\\t\\t \\t if (authBank.containsKey(authID)){\\n\\t\\t \\t\\t curAuth = authBank.get(authID);\\n\\t\\t \\t\\t curAuth.trainSize = curAuth.trainSize + (emailToks.length-2);\\n\\t\\t \\t\\t curAuth.ug.updateSeen(lastTok);\\n\\t\\t \\t } else {\\n\\t\\t \\t\\t curAuth = new AuthorMod();\\n\\t\\t \\t\\t curAuth.id = authID;\\n\\t\\t \\t\\t curAuth.trainSize = emailToks.length - 2;\\n\\t\\t\\t \\t curAuth.ug.addNew(lastTok);\\n\\t\\t \\t }\\n\\t\\t \\t \\n\\t\\t \\t //initalize loop\\n\\t\\t \\t if(curAuth.ug.contains(curTok)) {\\n\\t\\t \\t\\t curAuth.ug.updateSeen(curTok);\\n\\t\\t \\t } \\n\\t\\t \\t else {\\t\\t \\n\\t\\t \\t\\t curAuth.ug.addNew(curTok);\\n\\t\\t \\t }\\n\\n\\t\\t \\t if(curAuth.bg.containsBg(firstBg)) {\\n\\t\\t \\t\\t curAuth.bg.updateSeen(firstBg);\\n\\t\\t \\t } else {\\n\\t\\t \\t\\t curAuth.bg.addNew(firstBg);\\n\\t\\t \\t }\\n\\t\\t \\t \\t \\n\\t\\t \\t //index for that author, code very similar to bigram/unigram\\n\\t\\t \\t for(int i = 4; i < emailToks.length; i++)\\t\\t \\n\\t\\t \\t\\t {\\n\\t\\t \\t\\t\\t curTok= emailToks[i];\\n\\t\\t \\t\\t\\t Pair<String, String> loopBg = new Pair<String, String>(lastTok, curTok);\\n\\t\\t \\t\\t\\t \\n\\t\\t \\t\\t\\t //three cases. \\n\\t\\t \\t\\t\\t //1) bigram has been seen\\n\\t\\t \\t\\t\\t if (curAuth.bg.containsBg(loopBg))\\n\\t\\t \\t\\t\\t {\\n\\t\\t \\t\\t\\t\\t curAuth.bg.updateSeen(loopBg);\\n\\t\\t \\t\\t\\t\\t curAuth.ug.updateSeen(curTok);\\n\\t\\t \\t\\t\\t } \\n\\t\\t \\t\\t\\t //2) word seen, but not bigram\\n\\t\\t \\t\\t\\t else\\n\\t\\t \\t\\t\\t { \\n\\t\\t \\t\\t\\t\\t if (curAuth.ug.contains(curTok))\\n\\t\\t \\t\\t\\t \\t\\t{\\n\\t\\t \\t\\t\\t\\t\\t curAuth.bg.addNew(loopBg);\\n\\t\\t \\t\\t\\t\\t\\t curAuth.ug.updateSeen(curTok);\\n\\t\\t \\t\\t\\t\\t\\t} \\n\\t\\t \\t\\t\\t\\t //3) new word entirely\\n\\t\\t \\t\\t\\t\\t else\\n\\t\\t \\t\\t\\t\\t {\\n\\t\\t \\t\\t\\t\\t\\t curAuth.ug.addNew(curTok);\\n\\t\\t \\t\\t\\t\\t\\t curAuth.bg.addNew(loopBg); \\n\\t\\t \\t\\t\\t\\t } \\n\\t\\t \\t\\t\\t }\\t \\n\\t\\t \\t\\t\\t lastTok = curTok;\\n\\t\\t \\t\\t\\t} //end inner loop\\n\\t\\t \\tauthBank.put(curAuth.id, curAuth); \\n\\t\\t \\t\\t} //end outer loop \\n\\t\\t }\\t\\n\\t\\t finally\\n\\t\\t {\\n\\t\\t scanner.close();\\n\\t\\t }\\n\\t\\t}\\n\\t\\tcatch(Exception e)\\n\\t\\t{\\n\\t\\t\\tSystem.err.println(\\\"Error: \\\" + e.getMessage());\\n\\t\\t}\\n\\t\\treturn authBank;\\n\\t}\",\n \"Map<String, String> getTokens();\",\n \"private Map<String,Map<String,List<String>>> buildDictionary(Document doc){\\n\\t\\t\\n\\t\\tElement root = doc.getDocumentElement();\\n\\t\\t\\n\\t\\t\\n\\t\\tMap<String,Map<String,List<String>>> dictionary = new HashMap<String,Map<String,List<String>>>();\\n\\t\\tthis.termSet = new TreeSet<String>();\\n\\t\\t\\n\\t\\tNodeList termList = doc.getElementsByTagName(\\\"term\\\");\\n\\t\\tfor(int i = 0; i < termList.getLength(); i++){\\n\\t\\t\\tElement termElement = (Element) termList.item(i);\\n\\t\\t\\tElement nameElement = (Element) termElement.getElementsByTagName(\\\"name\\\").item(0);\\n\\t\\t\\tString name = nameElement.getTextContent();\\n\\t\\t\\tthis.termSet.add(name);\\n\\n\\t\\t\\tMap<String,List<String>> synonymGroup = new HashMap<String,List<String>>();\\n\\t\\t\\tsynonymGroup.put(\\\"exact\\\", new ArrayList<String>());\\n\\t\\t\\tsynonymGroup.put(\\\"related\\\", new ArrayList<String>());\\n\\t\\t\\tsynonymGroup.put(\\\"broad\\\", new ArrayList<String>());\\n\\t\\t\\tsynonymGroup.put(\\\"narrow\\\", new ArrayList<String>());\\n\\t\\t\\t\\n\\t\\t\\tNodeList synonyms = termElement.getElementsByTagName(\\\"synonym\\\");\\n\\t\\t\\tfor(int j=0; j<synonyms.getLength(); j++){\\n\\t\\t\\t\\tElement synonymElement = (Element) synonyms.item(j);\\n\\t\\t\\t\\tString synonym = synonymElement.getTextContent();\\n\\t\\t\\t\\tString scope = synonymElement.getAttribute(\\\"scope\\\");\\n\\t\\t\\t\\t//System.out.println(scope);\\n\\t\\t\\t\\tList<String> synonymList = (List<String>) synonymGroup.get(scope);\\n\\t\\t\\t\\t\\n\\t\\t\\t\\t//System.out.println(synonym);\\n\\t\\t\\t\\t\\n\\t\\t\\t\\tsynonymList.add(synonym);\\n\\t\\t\\t}\\n\\t\\t\\t\\n\\t\\t\\tdictionary.put(name,synonymGroup);\\t\\t\\n\\t\\t\\t\\n\\t\\t}\\n\\t\\t\\n\\t\\treturn dictionary;\\n\\t}\",\n \"public synchronized List<Integer> getDocIdsTodosDocumentos() throws Exception{\\r\\n\\t\\tList<Integer> lista = new ArrayList<Integer>();\\r\\n\\t\\t\\r\\n\\t\\tMTDIterator<MTDDocument> iterator = iterator();\\r\\n\\t\\twhile(iterator.hasNext()){\\r\\n\\t\\t\\tMTDDocument doc = iterator.next();\\r\\n\\t\\t\\tlista.add(doc.getDocId());\\r\\n\\t\\t}\\r\\n\\t\\titerator.close();\\r\\n\\t\\t\\r\\n\\t\\treturn lista;\\r\\n\\t}\",\n \"private static Map<String, List<List<String>>>[] splitYagoDataIntoDocumentSets(File yagoInputFile) {\\r\\n\\t\\tMap<String, List<List<String>>> trainData = new HashMap<String, List<List<String>>>();\\r\\n\\t\\tMap<String, List<List<String>>> testaData = new HashMap<String, List<List<String>>>();\\r\\n\\t\\tMap<String, List<List<String>>> testbData = new HashMap<String, List<List<String>>>();\\r\\n\\t\\t\\r\\n\\t\\tBufferedReader reader = FileUtil.getFileReader(yagoInputFile.getAbsolutePath());\\r\\n\\t\\ttry {\\r\\n\\t\\t\\tString documentName = null;\\r\\n\\t\\t\\tString documentSet = null;\\r\\n\\t\\t\\tList<List<String>> documentLines = null;\\r\\n\\t\\t\\tList<String> sentenceLines = null;\\r\\n\\t\\t\\tString line = null;\\r\\n\\t\\t\\twhile ((line = reader.readLine()) != null) {\\r\\n\\t\\t\\t\\tif (line.startsWith(\\\"-DOCSTART-\\\")) {\\r\\n\\t\\t\\t\\t\\tif (documentSet != null) {\\r\\n\\t\\t\\t\\t\\t\\tif (documentSet.equals(\\\"train\\\"))\\r\\n\\t\\t\\t\\t\\t\\t\\ttrainData.put(documentName, documentLines);\\r\\n\\t\\t\\t\\t\\t\\telse if (documentSet.equals(\\\"testa\\\"))\\r\\n\\t\\t\\t\\t\\t\\t\\ttestaData.put(documentName, documentLines);\\r\\n\\t\\t\\t\\t\\t\\telse if (documentSet.equals(\\\"testb\\\"))\\r\\n\\t\\t\\t\\t\\t\\t\\ttestbData.put(documentName, documentLines);\\r\\n\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\t\\r\\n\\t\\t\\t\\t\\tString docId = line.substring(\\\"-DOCSTART- (\\\".length(), line.length() - 1);\\r\\n\\t\\t\\t\\t\\tString[] docIdParts = docId.split(\\\" \\\");\\r\\n\\t\\t\\t\\t\\tdocumentName = docIdParts[0] + \\\"_\\\" + docIdParts[1];\\r\\n\\t\\t\\t\\t\\t\\r\\n\\t\\t\\t\\t\\tif (docIdParts[0].endsWith(\\\"testa\\\"))\\r\\n\\t\\t\\t\\t\\t\\tdocumentSet = \\\"testa\\\";\\r\\n\\t\\t\\t\\t\\telse if (docIdParts[0].endsWith(\\\"testb\\\"))\\r\\n\\t\\t\\t\\t\\t\\tdocumentSet = \\\"testb\\\";\\r\\n\\t\\t\\t\\t\\telse\\r\\n\\t\\t\\t\\t\\t\\tdocumentSet = \\\"train\\\";\\r\\n\\t\\t\\t\\t\\t\\r\\n\\t\\t\\t\\t\\tdocumentLines = new ArrayList<List<String>>();\\r\\n\\t\\t\\t\\t\\tsentenceLines = new ArrayList<String>();\\r\\n\\t\\t\\t\\t} else if (line.trim().length() == 0) {\\r\\n\\t\\t\\t\\t\\tdocumentLines.add(sentenceLines);\\r\\n\\t\\t\\t\\t\\tsentenceLines = new ArrayList<String>();\\r\\n\\t\\t\\t\\t} else {\\r\\n\\t\\t\\t\\t\\tsentenceLines.add(line);\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\t\\r\\n\\t\\t\\tif (documentSet.equals(\\\"train\\\"))\\r\\n\\t\\t\\t\\ttrainData.put(documentName, documentLines);\\r\\n\\t\\t\\telse if (documentSet.equals(\\\"testa\\\"))\\r\\n\\t\\t\\t\\ttestaData.put(documentName, documentLines);\\r\\n\\t\\t\\telse if (documentSet.equals(\\\"testb\\\"))\\r\\n\\t\\t\\t\\ttestbData.put(documentName, documentLines);\\r\\n\\t\\t} catch (IOException e) {\\r\\n\\t\\t\\treturn null;\\r\\n\\t\\t}\\r\\n\\r\\n\\t\\t@SuppressWarnings(\\\"unchecked\\\")\\r\\n\\t\\tMap<String, List<List<String>>>[] returnData = new HashMap[3];\\r\\n\\t\\treturnData[0] = trainData;\\r\\n\\t\\treturnData[1] = testaData;\\r\\n\\t\\treturnData[2] = testbData;\\r\\n\\t\\t\\r\\n\\t\\treturn returnData;\\r\\n\\t}\",\n \"private static void writeToCoordinateFile(String idNames, String[] id_to_coord_list, String outputFileName){\\n String[] stringToWrite = getStringBasedOnCoordinate( idNames, id_to_coord_list); //list of id we found, ignore the first 0th index\\n writeToFile(stringToWrite, outputFileName);\\n }\",\n \"public void allartongs() throws IOException{\\r\\n writefiles data=new writefiles(\\\"d:\\\\\\\\documents\\\\\\\\textfiles\\\\\\\\AllArtSongs.txt\\\",true);\\r\\n Map<String,String> ArrangerNamesLineMap=new HashMap<>();\\r\\n for(int songid:ArrangerLinesMap.keySet()){\\r\\n int arrangerid=ArrangerLinesMap.get(songid);\\r\\n ArrangersMap.get((songid));\\r\\n ArrangerNamesLineMap.put(test.getsongName(songid), ArrangersMap.get(arrangerid));\\r\\n }\\r\\n for(String songname:ArrangerNamesLineMap.keySet()){\\r\\n System.out.println(\\\"The artist is:\\\"+ArrangerNamesLineMap.get(songname)+\\\" The song is:\\\"+songname);\\r\\n data.writeToFile(\\\"The artist is:\\\"+ArrangerNamesLineMap.get(songname)+\\\" The song is:\\\"+songname);\\r\\n }\\r\\n System.out.println(ArrangerNamesLineMap.size());\\r\\n }\",\n \"public synchronized List<MTDDocument> getDocumentos(Collection<Integer> ids){\\r\\n\\t\\tArrayList<MTDDocument> listaRetorno = new ArrayList<MTDDocument>();\\r\\n\\t\\tDirectoryReader reader;\\r\\n\\t\\ttry {\\r\\n\\t\\t\\treader = DirectoryReader.open(getCopiaDiretorioMemoria());\\r\\n\\t\\tIndexSearcher searcher = new IndexSearcher(reader);\\t\\t\\r\\n\\t for(Integer docId: ids){\\r\\n \\t\\tDocument documento = searcher.doc(docId.intValue());\\r\\n \\t\\tif(documento != null){\\r\\n \\t\\tMTDDocument doc = new MTDDocumentBuilder().buildDocument(documento).build();\\r\\n \\t\\tdoc.setDocId(docId.intValue());\\r\\n \\t\\tlistaRetorno.add(doc);\\r\\n \\t\\t}else\\r\\n \\t\\t{System.out.println(\\\"Document with docId \\\"+docId.intValue()+\\\" not found.\\\");}\\r\\n\\t }\\r\\n\\t\\t} catch (IOException e) {\\r\\n\\t\\t\\t// TODO Auto-generated catch block\\r\\n\\t\\t\\te.printStackTrace();\\r\\n\\t\\t}\\r\\n\\t\\treturn listaRetorno;\\r\\n\\t}\",\n \"private static void writeMappingsToFile(String releaseNumber, List<List<Object>> stableIdsToOldIdsMappings, Set<String> currentStableIdentifiers) throws IOException {\\n\\t\\tPath oldStableIdsMappingFilePath = Paths.get(releaseNumber, \\\"reactome_stable_ids.txt\\\");\\n\\t\\tString header = \\\"# Reactome stable IDs for release \\\" + releaseNumber + \\\"\\\\n\\\" + \\\"Stable_ID\\\\told_identifier(s)\\\\n\\\";\\n\\t\\tFiles.write(oldStableIdsMappingFilePath, header.getBytes(), StandardOpenOption.CREATE, StandardOpenOption.TRUNCATE_EXISTING);\\n\\t\\tfor (List<Object> stableIdsArray : stableIdsToOldIdsMappings)\\n\\t\\t{\\n\\t\\t\\tString primaryId = (String) stableIdsArray.get(0);\\n\\t\\t\\t@SuppressWarnings(\\\"unchecked\\\")\\n\\t\\t\\tList<String> secondaryIds = (ArrayList<String>) stableIdsArray.get(1);\\n\\t\\t\\tif (currentStableIdentifierWithMapping(currentStableIdentifiers, primaryId, secondaryIds)) {\\n\\t\\t\\t\\tString line = primaryId + \\\"\\\\t\\\" + String.join(\\\",\\\", secondaryIds) + \\\"\\\\n\\\";\\n\\t\\t\\t\\tFiles.write(oldStableIdsMappingFilePath, line.getBytes(), StandardOpenOption.APPEND);\\n\\t\\t\\t}\\n\\t\\t}\\n\\t}\",\n \"private void savePoSTag(PoSTag poSTag){\\n Long num;\\n num = poSTagPerWordMap.get(poSTag.getWord());\\n poSTagPerWordMap.put(poSTag.getWord(), (num == null) ? (long)1 : num+1);\\n\\n num = poSTagMap.get(poSTag);\\n poSTagMap.put(poSTag, (num == null) ? (long)1 : num+1);\\n\\n\\n }\",\n \"public void getVector() throws IOException {\\n\\t\\tint i=1;\\r\\n\\t\\tfor(String key:keyword){\\r\\n\\t\\t\\tWord w=new Word();\\r\\n\\t\\t\\tdouble tf=calTF(key);\\r\\n\\t\\t\\tdouble idf=calIDF(key);\\r\\n\\t\\t\\tdouble tfidf=tf*idf;\\r\\n\\t\\t\\tw.setId(i);\\r\\n\\t\\t\\ti++;\\r\\n\\t\\t\\tw.setName(key);\\r\\n\\t\\t\\tw.setTfidf(tfidf);\\r\\n\\t\\t\\tif(word.containsKey(key)){\\r\\n\\t\\t\\t\\tw.setCount((Integer) word.get(key));\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\tkeymap.add(w);\\r\\n\\t\\t}\\r\\n\\t\\tFileHelper.writeTrainFile(keymap);\\r\\n\\t\\tFileHelper.writeTestFile(keymap);\\r\\n\\t}\",\n \"public void saveToReadID(ArrayList<String> idList) {\\n\\n\\t\\tSAVE_FILE = TO_READ_FILE;\\n\\t\\tsaveIds(idList);\\n\\t}\",\n \"private void saveMarkerPrefs(){\\n String latLngsList = new Gson().toJson(latLngs);\\n String namesList = new Gson().toJson(locationNames);\\n dataStorage.setLatLngList(latLngsList);\\n dataStorage.setLocNameList(namesList);\\n }\",\n \"private void outputResults()\\n{\\n try {\\n PrintWriter pw = new PrintWriter(new FileWriter(output_file));\\n pw.println(total_documents);\\n for (Map.Entry<String,Integer> ent : document_counts.entrySet()) {\\n String wd = ent.getKey();\\n int ct = ent.getValue();\\n pw.println(ct + \\\" \\\" + wd);\\n }\\n pw.println(START_KGRAMS);\\n pw.println(total_kdocuments);\\n for (Map.Entry<String,Integer> ent : kgram_counts.entrySet()) {\\n String wd = ent.getKey();\\n int ct = ent.getValue();\\n pw.println(ct + \\\" \\\" + wd);\\n } \\n pw.close();\\n }\\n catch (IOException e) {\\n IvyLog.logE(\\\"SWIFT\\\",\\\"Problem generating output\\\",e);\\n }\\n}\",\n \"public static void docWtgArray() {\\n int docCount = 0;\\n\\n while(docCount<totaldocument) {\\n List<Double> pass = new ArrayList();\\n for(Entry<String,List<Double>> entry : wtgMap.entrySet()) {\\n List<Double> docList = new ArrayList();\\n docList = entry.getValue();\\n double temp = docList.get(docCount);\\n pass.add(temp);\\n }\\n\\n double answer = CosineSimilarity(pass,query);\\n if(answer >= alpha) {\\n DocID.put(docCount,answer);\\n }\\n docCount++;\\n }\\n }\",\n \"static private void printSentenceTokens( final String documentId, final Iterable<String> tokenizedSentences ) {\\n System.out.println( \\\"=========================== \\\" + documentId + \\\" ===========================\\\" );\\n for ( String tokenizedSentence : tokenizedSentences ) {\\n System.out.println( tokenizedSentence );\\n }\\n }\",\n \"public VSM(String[] docs) {\\n\\t\\tmyDocs = docs;\\n\\t\\ttermList = new ArrayList<String>();\\n\\t\\tdocLists = new ArrayList<ArrayList<Doc>>();\\n\\t\\tArrayList<Doc> docList;\\n\\t\\t// parse the documents to construct the index and collect the raw\\n\\t\\t// frequencies.\\n\\t\\tfor (int i = 0; i < myDocs.length; i++) {\\n\\t\\t\\tString[] tokens = myDocs[i].split(\\\" \\\");\\n\\t\\t\\tString token;\\n\\t\\t\\tfor (int j = 0; j < tokens.length; j++) {\\n\\t\\t\\t\\ttoken = tokens[j];\\n\\t\\t\\t\\tif (!termList.contains(token)) {\\n\\t\\t\\t\\t\\ttermList.add(token);\\n\\t\\t\\t\\t\\tdocList = new ArrayList<Doc>();\\n\\t\\t\\t\\t\\tDoc doc = new Doc(i, 1); // initial raw frequency is 1\\n\\t\\t\\t\\t\\tdocList.add(doc);\\n\\t\\t\\t\\t\\tdocLists.add(docList);\\n\\t\\t\\t\\t} else {\\n\\t\\t\\t\\t\\tint index = termList.indexOf(token);\\n\\t\\t\\t\\t\\tdocList = docLists.get(index);\\n\\t\\t\\t\\t\\tint k = 0;\\n\\t\\t\\t\\t\\tboolean match = false;\\n\\n\\t\\t\\t\\t\\t// search the postings list for a document id, if match,\\n\\t\\t\\t\\t\\t// insert a new position number to the document id\\n\\t\\t\\t\\t\\tfor (Doc doc : docList) {\\n\\t\\t\\t\\t\\t\\tif (doc.docId == i) {\\n\\t\\t\\t\\t\\t\\t\\tdoc.tw++; // increase word count\\n\\t\\t\\t\\t\\t\\t\\tmatch = true;\\n\\t\\t\\t\\t\\t\\t\\tbreak;\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\tk++;\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t// if no match, add a new document id along with the\\n\\t\\t\\t\\t\\t// position number\\n\\t\\t\\t\\t\\tif (!match) {\\n\\t\\t\\t\\t\\t\\tDoc doc = new Doc(i, 1);\\n\\t\\t\\t\\t\\t\\tdocList.add(doc);\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t}\\n\\t\\t\\t}//\\n\\t\\t}// end with parsing\\n\\n\\t\\t// compute the tf-idf term weights and the doc lengths\\n\\t\\tint N = myDocs.length;\\n\\t\\tdocLength = new double[N];\\n\\t\\tfor (int i = 0; i < termList.size(); i++) {\\n\\t\\t\\tdocList = docLists.get(i);\\n\\t\\t\\tint df = docList.size();\\n\\t\\t\\tDoc doc;\\n\\t\\t\\tfor (int j = 0; j < docList.size(); j++) {\\n\\t\\t\\t\\tdoc = docList.get(j);\\n\\t\\t\\t\\tdouble tfidf = (1 + Math.log(doc.tw))\\n\\t\\t\\t\\t\\t\\t* Math.log(N / (df * 1.0));\\n\\t\\t\\t\\tdocLength[doc.docId] += Math.pow(tfidf, 2);\\n\\t\\t\\t\\tdoc.tw = tfidf;\\n\\t\\t\\t\\tdocList.set(j, doc);\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\t// update the length\\n\\t\\tfor (int i = 0; i < N; i++) {\\n\\t\\t\\tdocLength[i] = Math.sqrt(docLength[i]);\\n\\t\\t}\\n\\n\\t}\",\n \"public static void saveAsMultipleFiles(Map<Atto, List<ITerm>> atti, String path)\\n\\t{\\n\\t\\tFile dir = new File(path);\\n\\t\\tif (!dir.exists() || !dir.isDirectory())\\n\\t\\t\\tthrow new IllegalArgumentException(\\\"!dir.exists() || !dir.isDirectory()\\\");\\n\\t\\t\\n\\t\\tFileUtils.clearDirectory(dir);\\n\\t\\t\\n\\t\\ttry\\n\\t\\t{\\n\\t\\t\\tint counter = 0;\\n\\t\\t\\tfor (Entry<Atto, List<ITerm>> entry : atti.entrySet())\\n\\t\\t\\t{\\n\\t\\n\\t\\t\\t\\tString filename = path + File.separator + attoTermsPrefix + counter + jsonExtension;\\n\\t\\t\\t\\tJSONActDescriptorSaver saver = new JSONActDescriptorSaver(WritersFactory.newUTF8FileWriter(filename));\\n\\t\\t\\t\\tsaver.save(entry);\\n\\t\\t\\t\\t\\n\\t\\t\\t\\tcounter++;\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\tcatch (IOException e)\\n\\t\\t{\\n\\t\\t\\tSystem.err.println(e);\\n\\t\\t}\\n\\t}\",\n \"public void insert( String token, int docID, int offset ) {\\n // Add to map of postingslist\\n //if (docID % 100 == 0)\\n //System.err.println(\\\"Trying to insert ''\\\" + token + \\\"'' found in doc \\\"+docID);\\n if (this.index.containsKey(token)){\\n //System.err.println(token+\\\" already in memory\\\");\\n this.index.get(token).insert(docID, offset);\\n }\\n else{\\n //System.err.println(\\\"new token: \\\" +token+\\\" stored\\\");\\n PostingsList postingslist = new PostingsList();\\n postingslist.insert(docID, offset);\\n this.index.put(token, postingslist);\\n }\\n\\n // Add to matrix of tf\\n if (!this.tfMap.containsKey(docID)){\\n HashMap<String, Integer> m = new HashMap<String, Integer>();\\n m.put(token, 1);\\n this.tfMap.put(docID, m);\\n\\n if (this.idfMap.containsKey(token))\\n this.idfMap.put(token, this.idfMap.get(token)+1);\\n else\\n this.idfMap.put(token, 1);\\n }\\n\\n else if (!this.tfMap.get(docID).containsKey(token)){\\n this.tfMap.get(docID).put(token, 1);\\n\\n if (this.idfMap.containsKey(token))\\n this.idfMap.put(token, this.idfMap.get(token)+1);\\n else\\n this.idfMap.put(token, 1);\\n }\\n\\n else{\\n int v = this.tfMap.get(docID).get(token) + 1;\\n this.tfMap.get(docID).put(token, v);\\n }\\n }\",\n \"public long getDocumentName();\",\n \"public abstract Set<String> getTerms(Document doc);\",\n \"public String addStudent (String name,String admin){\\n Document doc = new Document(\\\"name\\\", name);\\n doc.put(\\\"skills\\\",Arrays.asList());\\n studentSkills.insertOne(doc);\\n this.createNewToken(doc.get(\\\"_id\\\").toString(),admin);\\n return doc.get(\\\"_id\\\").toString();\\n}\",\n \"public void saveBooks(){\\n\\t\\ttry{\\t\\n\\t\\t\\tPrintWriter pw = new PrintWriter(new FileWriter(\\\"../bin/books.csv\\\"));\\t\\n\\t\\t\\tIterator bookIterator = bookMap.keySet().iterator();\\n\\t\\t\\twhile(bookIterator.hasNext() != false){\\n\\t\\t\\t\\tString current = bookIterator.next().toString();\\n\\t\\t\\t\\tfor(int i=0;i<bookMap.get(current).size();i++){\\t\\n\\t\\t\\t\\t\\tpw.write(bookMap.get(current).get(i).getTitle() \\n\\t\\t\\t\\t\\t\\t+ \\\",\\\" + bookMap.get(current).get(i).getAuthor()\\n\\t\\t\\t\\t\\t\\t+ \\\",\\\" + bookMap.get(current).get(i).getYear()\\n\\t\\t\\t\\t\\t\\t+ \\\",\\\" + bookMap.get(current).get(i).getType()\\n\\t\\t\\t\\t\\t\\t+ \\\",\\\" + bookMap.get(current).get(i).getId());\\n\\t\\t\\t\\t\\tpw.write(\\\"\\\\n\\\");\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\t\\n\\t\\t\\tpw.close();\\n\\t\\t\\tSystem.out.println(\\\"\\\\tDone!\\\");\\n\\t\\t}catch(IOException e){\\n\\t\\t\\tSystem.out.println(e.toString());\\n\\t\\t}\\n\\n\\t}\",\n \"public void readIDs() {\\n try {\\n FileInputStream fileIn = new FileInputStream(\\\"temp/ids.ser\\\");\\n ObjectInputStream in = new ObjectInputStream(fileIn);\\n ids = (HashMap<String, Member>) in.readObject();\\n in.close();\\n fileIn.close();\\n } catch (IOException e) {\\n ids = new HashMap<>();\\n } catch (ClassNotFoundException c) {\\n System.out.println(\\\"Class HashMap not found\\\");\\n c.printStackTrace();\\n return;\\n }\\n\\n }\",\n \"@Override\\n public void run() {\\n final Location location = getLastBestLocation();\\n\\n\\n location.getLatitude();\\n location.getLongitude();\\n\\n\\n\\n\\n\\n // Create a new user with a first and last name\\n Map<String, Object> user = new HashMap<>();\\n user.put(\\\"lat\\\", location.getLatitude());\\n user.put(\\\"long\\\", location.getLongitude());\\n\\n// Add a new document with a generated ID\\n\\n db.collection(\\\"gps\\\").document(\\\"QvFfCM86QQJRAIk68MQv\\\").update(user)\\n .addOnSuccessListener(new OnSuccessListener<Void>() {\\n @Override\\n public void onSuccess(Void aVoid) {\\nString locs= location.getLatitude()+\\\",\\\"+location.getLongitude();\\n loc.setText(locs);\\n Log.w(TAG, \\\"onSuccess\\\"+count);\\n count = count+1;\\n }\\n })\\n .addOnFailureListener(new OnFailureListener() {\\n @Override\\n public void onFailure(@NonNull Exception e) {\\n Log.w(TAG, \\\"Error adding document\\\", e);\\n }\\n });\\n\\n // Repeat every 2 seconds\\n handler.postDelayed(runnable, 500);\\n }\",\n \"private void createDocWords() {\\n\\t\\tArrayList<DocWords> docList=new ArrayList<>();\\n\\t\\ttry {\\n\\t\\t\\tBufferedReader in = new BufferedReader(new FileReader(\\\"E:\\\\\\\\graduate\\\\\\\\cloud\\\\\\\\project\\\\\\\\data\\\\\\\\docWords.txt\\\"));\\n\\t\\t\\tString line = \\\"\\\";\\n\\t\\t\\twhile ((line = in.readLine()) != null) {\\n\\t\\t\\t\\tString parts[] = line.split(\\\" \\\");\\n\\t\\t\\t\\tDocWords docWords=new DocWords();\\n\\t\\t\\t\\tdocWords.setDocName(parts[0].replace(\\\".txt\\\", \\\"\\\"));\\n\\t\\t\\t\\tdocWords.setCount(Float.parseFloat(parts[1]));\\n\\t\\t\\t\\tdocList.add(docWords);\\n\\t\\t\\t}\\n\\t\\t\\tin.close();\\n\\t\\t} catch (IOException e) {\\n\\t\\t\\te.printStackTrace();\\n\\t\\t}\\n\\t\\tDBUtil.insertDocWords(docList);\\n\\t}\",\n \"private void createDicts(String inputFile){\\n\\t\\tproductIds = new TreeMap<>();\\n\\t\\ttokenDict = new TreeMap<>();\\n\\t\\treviewIds = new TreeMap<>();\\n\\n\\t\\tDataParser dataParser = null;\\n\\t\\ttry {\\n\\t\\t\\tdataParser = new DataParser(inputFile);\\n\\t\\t} catch (IOException e) {\\n\\t\\t\\tSystem.out.println(\\\"Error occurred while reading the reviews input file.\\\");\\n\\t\\t\\tSystem.exit(1);\\n\\t\\t}\\n\\n\\t\\tfor (int i = 0; i < dataParser.allReviews.size(); i++) {\\n\\t\\t\\taddProductId(dataParser.allReviews.get(i).get(\\\"productId\\\"), i + 1);\\n\\t\\t\\tint length = addReviewText(dataParser.allReviews.get(i).get(\\\"text\\\"), i + 1);\\n\\t\\t\\taddReviewId(dataParser.allReviews.get(i), i, length);\\n\\t\\t}\\n\\t}\",\n \"@SuppressWarnings(\\\"empty-statement\\\")\\n public ArrayList process(String input){\\n //public static void main(String[] args) throws SQLException {\\n\\n //Scanner in = new Scanner(System.in);\\n //String InputStr = in.nextLine(); // to read user input;\\n String InputStr = input;\\n \\n System.out.println(input);\\n \\n boolean quotated = false; // to know input with quotation or not;\\n try {\\n ConnectToDB();\\n int TotalnumDoc = GetNumDocs();\\n\\n if (InputStr.startsWith(\\\"\\\\\\\"\\\") && InputStr.endsWith(\\\"\\\\\\\"\\\")) {\\n System.out.println(\\\"quotation\\\");\\n quotated = true;\\n GetDoc_Word(InputStr, TotalnumDoc);\\n System.out.println(\\\"total number of doc =\\\" + TotalnumDoc);\\n Postions();\\n } else {\\n GetDoc_StemWord(InputStr, TotalnumDoc);\\n quotated = false;\\n }\\n\\n for (Map.Entry<String, SrchWord> entry1 : WordList.entrySet()) /// for\\n /// printing\\n {\\n System.out.println(entry1.getKey() + \\\"\\tIDF: \\\" + entry1.getValue().IDf);\\n\\n SrchWord w1 = entry1.getValue();\\n w1.PrintSrchWord();\\n System.out.println(\\\"___________________________\\\");\\n\\n }\\n System.out.println(\\\"================================================================\\\");\\n Ranker();\\n \\n for (Map.Entry<Integer, DocRank> entry1 : pages.entrySet()) \\n {\\n entry1.getValue().ID = entry1.getKey();\\n }\\n \\n List<DocRank> sortedRank = new ArrayList<>(pages.values());\\n \\n if (!quotated)\\n { \\n sortedRank.sort( new SortByPageRank());\\n }\\n else\\n {\\n sortedRank.sort( new SortByValidFlag());\\n }\\n //*****************************************************************\\n // sortedRank now contains objects DocRank containing the pageRank and the DocID(choose ascendingly or descendingly\\n // from SortByPageRank.java compare function)\\n // the ID should enable the retrieval of the URL and title from the table Docs_URL\\n //****************************************************************\\n \\n ArrayList sortedIds = new ArrayList();\\n \\n for (int i=0; i<sortedRank.size(); i++)\\n {\\n System.out.println(\\\"DocID : \\\" +sortedRank.get(i).ID);\\n System.out.println(\\\"pageRank: \\\" + sortedRank.get(i).rank);\\n \\n sortedIds.add(sortedRank.get(i).ID); // dont forget to change the comparator to descending\\n //System.out.println(sortedRank.get(i).ID);\\n }\\n \\n pages.clear();\\n return sortedIds;\\n \\n } catch (Exception e) {\\n\\n e.printStackTrace();\\n return null;\\n\\n } finally {\\n\\n WordList.clear(); // clearing map after searching\\n if (con != null) {\\n try {\\n con.close();\\n } catch (Exception e) {\\n }\\n }\\n }\\n\\n }\",\n \"public void getThesaurusMap (String wordTofind) {\\r\\n\\t \\tfor (Entry<String, List> entry : tMap.entrySet()) {\\r\\n\\t \\t\\tList singleListofSynonims = entry.getValue();\\r\\n\\t \\t\\tif (singleListofSynonims.contains(wordTofind)){\\r\\n\\t \\t\\t\\t\\r\\n\\t \\t\\t\\tmappedList.add(singleListofSynonims);\\r\\n\\t \\t\\t\\tGoogleToThesarus.put(wordTofind,singleListofSynonims);\\r\\n\\t \\t\\t}\\r\\n\\t \\t\\telse {\\r\\n\\t \\t\\t\\t//System.out.println(\\\"value not in map\\\");\\r\\n\\t \\t}\\r\\n\\t \\t}\\r\\n\\t }\",\n \"void genIDFData(String vocabFile, String outFile) throws Exception {\\n List<String> lines = FileUtils.readLines(new File(vocabFile), Charset.defaultCharset());\\n BufferedWriter bw = new BufferedWriter(new FileWriter(outFile));\\n int N = reader.numDocs();\\n for (String line: lines) {\\n String word = TrecDocIndexer.analyze(indexer.getAnalyzer(), line).trim();\\n int df = reader.docFreq(new Term(TrecDocIndexer.FIELD_ANALYZED_CONTENT, word));\\n bw.write(line.trim() + \\\"\\\\t\\\");\\n bw.write(String.valueOf(Math.log(N/(double)df)));\\n bw.newLine();\\n }\\n bw.close();\\n }\",\n \"public void saveReadID(ArrayList<String> idList) {\\n\\n\\t\\tSAVE_FILE = READ_FILE;\\n\\t\\tsaveIds(idList);\\n\\t}\",\n \"public static void loadTargetTerm2IdMapping(File input) throws IOException {\\n\\t\\t\\tm_namesMap = new SimpleBidirectionalMap<String, Integer>();\\n\\t\\t\\tString encoding = FileUtils.getFileEncoding(input);\\n\\t\\t\\tBufferedReader reader = new BufferedReader(new InputStreamReader(new FileInputStream(input), encoding));\\n\\t\\t\\tString line = reader.readLine();\\n\\t\\t\\tint lineNum = 1;\\n\\t\\t\\tboolean testFormat = false;\\n\\t\\t\\tif(StringUtils.checkIfNumber(line.split(\\\"\\\\t\\\")[0]))\\n\\t\\t\\t\\ttestFormat = true;\\n\\t\\t\\twhile(line!= null) {\\n\\t\\t\\t\\tif(line.equals(\\\"@@@\\\"))\\n\\t\\t\\t\\t\\tbreak;\\n\\t\\t\\t\\tif(testFormat) {\\n\\t\\t\\t\\t\\tString num = line.split(\\\"\\\\t\\\")[0];\\n\\t\\t\\t\\t\\tSystem.out.println(\\\"key: \\\"+line.trim().substring(num.length()+1) + \\\" value: \\\" + Integer.parseInt(num));\\n\\t\\t\\t\\t\\tm_namesMap.put(line.trim().substring(num.length()+1), Integer.parseInt(num));\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\telse {\\n\\t\\t\\t\\t\\tSystem.out.println(\\\"key????\\\" + lineNum + \\\"instead of \\\" + line.split(\\\"\\\\t\\\")[0]);\\n\\t\\t\\t\\t\\tm_namesMap.put(line.trim(), lineNum);\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\tline = reader.readLine();\\n\\t\\t\\t\\tlineNum ++;\\n\\t\\t\\t}\\n\\t\\t}\",\n \"public static void main(String[] args) throws FileNotFoundException, IOException {\\n \\n \\n File textBank = new File(\\\"textbank/\\\");\\n Hashtable<Integer,Integer> frequency;\\n Hashtable<Integer, String> table;\\n table = new Hashtable<>();\\n frequency = new Hashtable<>();\\n Scanner input = new Scanner(new File(\\\"stoplist.txt\\\"));\\n int max=0;\\n while (input.hasNext()) {\\n String next;\\n next = input.next();\\n if(next.length()>max)\\n max=next.length();\\n table.put(next.hashCode(), next); //to set up the hashmap with the wordsd\\n \\n }\\n \\n System.out.println(max);\\n \\n Pattern p0=Pattern.compile(\\\"[\\\\\\\\,\\\\\\\\=\\\\\\\\{\\\\\\\\}\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\"\\\\\\\\_\\\\\\\\+\\\\\\\\*\\\\\\\\#\\\\\\\\<\\\\\\\\>\\\\\\\\!\\\\\\\\`\\\\\\\\-\\\\\\\\?\\\\\\\\'\\\\\\\\:\\\\\\\\;\\\\\\\\~\\\\\\\\^\\\\\\\\&\\\\\\\\%\\\\\\\\$\\\\\\\\(\\\\\\\\)\\\\\\\\]\\\\\\\\[]\\\") \\n ,p1=Pattern.compile(\\\"[\\\\\\\\.\\\\\\\\,\\\\\\\\@\\\\\\\\d]+(?=(?:\\\\\\\\s+|$))\\\");\\n \\n \\n \\n wor = new ConcurrentSkipListMap<>();\\n \\n ConcurrentMap<String , Map<String,Integer>> wordToDoc = new ConcurrentMap<String, Map<String, Integer>>() {\\n @Override\\n public Map<String, Integer> putIfAbsent(String key, Map<String, Integer> value) {\\n throw new UnsupportedOperationException(\\\"Not supported yet.\\\"); //To change body of generated methods, choose Tools | Templates.\\n }\\n\\n @Override\\n public boolean remove(Object key, Object value) {\\n throw new UnsupportedOperationException(\\\"Not supported yet.\\\"); //To change body of generated methods, choose Tools | Templates.\\n }\\n\\n @Override\\n public boolean replace(String key, Map<String, Integer> oldValue, Map<String, Integer> newValue) {\\n throw new UnsupportedOperationException(\\\"Not supported yet.\\\"); //To change body of generated methods, choose Tools | Templates.\\n }\\n\\n @Override\\n public Map<String, Integer> replace(String key, Map<String, Integer> value) {\\n throw new UnsupportedOperationException(\\\"Not supported yet.\\\"); //To change body of generated methods, choose Tools | Templates.\\n }\\n\\n @Override\\n public int size() {\\n throw new UnsupportedOperationException(\\\"Not supported yet.\\\"); //To change body of generated methods, choose Tools | Templates.\\n }\\n\\n @Override\\n public boolean isEmpty() {\\n throw new UnsupportedOperationException(\\\"Not supported yet.\\\"); //To change body of generated methods, choose Tools | Templates.\\n }\\n\\n @Override\\n public boolean containsKey(Object key) {\\n throw new UnsupportedOperationException(\\\"Not supported yet.\\\"); //To change body of generated methods, choose Tools | Templates.\\n }\\n\\n @Override\\n public boolean containsValue(Object value) {\\n throw new UnsupportedOperationException(\\\"Not supported yet.\\\"); //To change body of generated methods, choose Tools | Templates.\\n }\\n\\n @Override\\n public Map<String, Integer> get(Object key) {\\n return wor.get((String)key);//To change body of generated methods, choose Tools | Templates.\\n }\\n\\n @Override\\n public Map<String, Integer> put(String key, Map<String, Integer> value) {\\n wor.put(key, value); // this saving me n \\n //if(frequency.get(key.hashCode())== null)\\n \\n //frequency.put(key.hashCode(), )\\n return null;\\n }\\n\\n @Override\\n public Map<String, Integer> remove(Object key) {\\n throw new UnsupportedOperationException(\\\"Not supported yet.\\\"); //To change body of generated methods, choose Tools | Templates.\\n }\\n\\n @Override\\n public void putAll(Map<? extends String, ? extends Map<String, Integer>> m) {\\n throw new UnsupportedOperationException(\\\"Not supported yet.\\\"); //To change body of generated methods, choose Tools | Templates.\\n }\\n\\n @Override\\n public void clear() {\\n throw new UnsupportedOperationException(\\\"Not supported yet.\\\"); //To change body of generated methods, choose Tools | Templates.\\n }\\n\\n @Override\\n public Set<String> keySet() {\\n throw new UnsupportedOperationException(\\\"Not supported yet.\\\"); //To change body of generated methods, choose Tools | Templates.\\n }\\n\\n @Override\\n public Collection<Map<String, Integer>> values() {\\n throw new UnsupportedOperationException(\\\"Not supported yet.\\\"); //To change body of generated methods, choose Tools | Templates.\\n }\\n\\n @Override\\n public Set<Map.Entry<String, Map<String, Integer>>> entrySet() {\\n throw new UnsupportedOperationException(\\\"Not supported yet.\\\"); //To change body of generated methods, choose Tools | Templates.\\n }\\n };\\n totalFiles = textBank.listFiles().length;\\n for (File textFile : textBank.listFiles()) {\\n totalReadFiles++;\\n //checking whether file has txt extension and file size is higher than 0\\n if(textFile.getName().contains(\\\".txt\\\") && textFile.length() > 0){\\n docName.add(textFile.getName().replace(\\\".txt\\\", \\\".stp\\\"));\\n StopListHandler sp = new StopListHandler(textFile, table,System.currentTimeMillis(),p0,p1,wordToDoc);\\n sp.setFinished(() -> {\\n \\n tmp++;\\n \\n if(tmp==counter)\\n //printTable(counter);\\n \\n if(totalReadFiles == totalFiles)\\n {\\n printTable(counter);\\n }\\n \\n });\\n \\n sp.start();\\n counter ++;}\\n \\n \\n }\\n System.out.println(counter);\\n //while(true){if(tmp==counter-1) break;}\\n System.out.println(\\\"s\\\");\\n \\n }\",\n \"private void initIDFMap(List<List<Map<String,List<Double>>>> tfMap){\\n\\t\\tfor (int i = 0; i < tfMap.size(); i++) {\\n\\t\\t\\tList<Map<String,List<Double>>> gestureDocument = tfMap.get(i);\\n\\t\\t\\tfor (int j = 0; j < gestureDocument.size(); j++) {\\n\\t\\t\\t\\tMap<String,List<Double>> tempMap = gestureDocument.get(j);\\n\\t\\t\\t\\tIterator<Entry<String, List<Double>>> it = tempMap.entrySet().iterator();\\n\\t\\t\\t\\t while (it.hasNext()) {\\n\\t\\t\\t\\t Map.Entry<String,Integer> pairs = (Map.Entry)it.next(); \\n\\t\\t\\t\\t if(getTfIDFMapGlobal().containsKey(pairs.getKey()))\\n\\t\\t\\t\\t \\tgetTfIDFMapGlobal().put(pairs.getKey(), getTfIDFMapGlobal().get(pairs.getKey())+1);\\n\\t\\t\\t\\t else\\n\\t\\t\\t\\t \\tgetTfIDFMapGlobal().put(pairs.getKey(), 1);\\n\\t\\t\\t\\t }\\n\\t\\t\\t}\\n\\t\\t}\\n\\t}\",\n \"private static void saveMapToFile(HashMap<String, Integer> posCounts, String fileName) throws FileNotFoundException, IOException {\\n\\t\\tProperties properties = new Properties();\\r\\n\\r\\n\\t for (Map.Entry<String,Integer> entry : posCounts.entrySet()) {\\r\\n\\t properties.put(entry.getKey(), entry.getValue().toString());\\r\\n\\t }\\r\\n\\t \\r\\n\\t properties.store(new FileOutputStream(fileName), null);\\r\\n\\t}\",\n \"public static void save(String fname, ArrayList<Tweet> tw) {\\n\\ttry {\\n\\t FileOutputStream fout = new FileOutputStream(fname);\\n\\t ObjectOutputStream oos = new ObjectOutputStream(fout);\\n\\t oos.writeObject(tw);\\n\\t oos.close();\\n\\t} catch (FileNotFoundException ex) {\\n\\t ex.printStackTrace();\\n\\t} catch (IOException ioex) {\\n\\t ioex.printStackTrace();\\n\\t}\\n }\",\n \"public static void printHashMapSS(Map<String, String> map) throws IOException{\\n\\t\\tPrintWriter writer = new PrintWriter(\\\"C:/Users/Naveen/Desktop/TestRuns/LastRun/documentHash\\\");\\n\\t\\tfor (Entry<String, String> entry : map.entrySet())\\n\\t {\\t \\t\\t\\n\\t \\t\\twriter.println(entry.getKey()+\\\":\\\"+entry.getValue());\\n\\t }\\n\\t writer.close();\\n\\t}\",\n \"public void writeFile() {\\n\\t\\ttry {\\n\\t\\t\\tFile dir = Environment.getExternalStorageDirectory();\\n\\t\\t\\tFile myFile = new File(dir.toString() + File.separator + FILENAME);\\n\\t\\t\\tLog.i(\\\"MyMovies\\\", \\\"SeSus write : \\\" + myFile.toString());\\n\\t\\t\\tmyFile.createNewFile();\\n\\t\\t\\tFileOutputStream fOut = new FileOutputStream(myFile);\\n\\t\\t\\tOutputStreamWriter myOutWriter = \\n\\t\\t\\t\\t\\tnew OutputStreamWriter(fOut);\\n\\t\\t\\tfor (Map.Entry<String, ValueElement> me : hm.entrySet()) {\\n\\t\\t\\t\\tString refs = (me.getValue().cRefMovies>0? \\\"MOVIE\\\" : \\\"\\\");\\n\\t\\t\\t\\trefs += (me.getValue().cRefBooks>0? \\\"BOOK\\\" : \\\"\\\");\\n\\t\\t\\t\\tString line = me.getKey() + DELIMITER + me.getValue().zweiteZeile \\n\\t\\t\\t\\t\\t\\t //+ DELIMITER\\n\\t\\t\\t\\t\\t\\t //+ me.getValue().count\\n\\t\\t\\t\\t\\t \\t+ DELIMITER\\n\\t\\t\\t\\t\\t \\t+ refs\\n\\t\\t\\t\\t\\t \\t + System.getProperty(\\\"line.separator\\\");\\n\\t\\t\\t\\t//Log.i(\\\"MyMovies\\\", \\\"SeSus extracted : \\\" + line);\\n\\t\\t\\t\\tmyOutWriter.write(line);\\n\\t\\t\\t}\\n\\t\\t\\tmyOutWriter.close();\\n\\t\\t\\tfOut.close();\\n\\t\\t} catch (IOException e) {\\n\\t\\t\\t//\\n\\t\\t\\tLog.i(\\\"MyMovies\\\", \\\"SeSus write Exception : \\\");\\n\\t\\t\\te.printStackTrace();\\n\\t\\t}\\n\\t}\",\n \"void addWordsToDoc(int doc,List<VocabWord> words);\",\n \"public void saveUsers() {\\n FileWriter fileWriter = null;\\n PrintWriter printWriter = null;\\n try {\\n fileWriter = new FileWriter(pathData);\\n printWriter = new PrintWriter(fileWriter);\\n if (users != null) {\\n \\n for (Map.Entry m : users.entrySet()) {\\n printWriter.println(m.getKey() + spChar + m.getValue() + \\\"\\\\n\\\");\\n }\\n }\\n printWriter.close();\\n } catch (IOException e) {\\n }\\n }\",\n \"public void map(LongWritable docID, Text value, OutputCollector<Text, Text> output, Reporter reporter) throws IOException {\\n FileSplit fileSplit = (FileSplit) reporter.getInputSplit();\\n String filename = \\\"\\\" + fileSplit.getPath().getName();\\n\\n int argc = Integer.parseInt(conf.get(\\\"argc\\\"));\\n java.util.Map<String, Integer> keywords = new HashMap<String, Integer>();\\n\\n for (int i = 0; i < argc; i++) {\\n String inputString = conf.get(\\\"keyword\\\" + i);\\n\\n keywords.put(inputString, 0);\\n\\n\\n }\\n\\n String line = value.toString();\\n StringTokenizer tokenizer = new StringTokenizer(line);\\n while (tokenizer.hasMoreTokens()) {\\n\\n String token = tokenizer.nextToken();\\n for (java.util.Map.Entry<String, Integer> me : keywords.entrySet()) {\\n if (token.equalsIgnoreCase(me.getKey())) {\\n\\n keywords.put(me.getKey(), me.getValue() + 1);\\n\\n }\\n }\\n }\\n\\n for (java.util.Map.Entry<String, Integer> me : keywords.entrySet()) {\\n\\n keyword.set(me.getKey());\\n filenameCount.set(filename + \\\"_\\\" + me.getValue());\\n\\n output.collect(keyword, filenameCount);\\n }\\n }\",\n \"private void saveToStorage() {\\n FileOutputStream fos = null;\\n try {\\n fos = context.openFileOutput(\\\"GeoFences\\\", Context.MODE_PRIVATE);\\n ObjectOutputStream oos = new ObjectOutputStream(fos);\\n oos.writeObject(currentList);\\n oos.close();\\n } catch (IOException e) {\\n e.printStackTrace();\\n }\\n }\",\n \"private void reLoadIndexesFromFileToIndexMap(File file) throws IOException {\\n BufferedReader reader = new BufferedReader(new FileReader(file));\\n for (String line = reader.readLine(); line != null; line = reader\\n .readLine()) {\\n String[] termIndex = line.split(\\\" \\\");\\n String key = termIndex[0];\\n LinkedList<TermPositions> value = new LinkedList<>();\\n String postingList = termIndex[1];\\n // split the posting lists 1:1,2,4;2:4\\n String[] subPostings = postingList.split(\\\";\\\");\\n for (String posting : subPostings) {\\n String[] docPosting = posting.split(\\\":\\\");\\n int docId = Integer.parseInt(docPosting[0]);\\n String[] positions = docPosting[1].split(\\\",\\\");\\n LinkedList<Integer> positionsList = new LinkedList<>();\\n for (String position : positions) {\\n positionsList.add(Integer.parseInt(position));\\n }\\n TermPositions termPositions = new TermPositions(docId, positionsList);\\n value.add(termPositions);\\n }\\n indexMap.put(key, value);\\n\\n }\\n\\n }\",\n \"public static void update(String indexFileName, String listOfDoc) throws IOException{\\n\\t\\tHashMap<String, String> sCurrentHashMap = null;\\n\\t\\tboolean hasFile = true;\\n\\t\\t\\n\\t\\tif(globalHash.containsKey(indexFileName)){\\n\\t\\t\\t//ถ้ามีใน global แล้ว เอาออกมาแล้วเอามารวมกับที่เพิ่งอ่านไฟล์ได้เลย\\n\\t\\t\\tsCurrentHashMap = globalHash.get(indexFileName);\\n\\t\\t\\n\\t\\t}else{ \\n\\t\\t\\t//if no hashmap in globalHash, then check if there's this fileName.txt in directory\\n\\t\\t\\t\\n\\t\\t\\tif(!new File(indexFileName+\\\".txt\\\").isFile()){\\n\\t\\t\\t\\t\\tSystem.out.println(\\\"ERROR: The inverted file is not found.\\\");\\n\\t\\t\\t\\t\\thasFile = false;\\n\\t\\t\\t}else{\\n\\t \\t sCurrentHashMap = genHashMapFromInvertedIndexFile(indexFileName);\\n\\t\\t\\t \\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\t\\n\\t\\tif(hasFile){\\n\\t\\t\\tArrayList<Term> newTermList = extractDoc(listOfDoc);\\n\\t\\t\\t//if the new term list has value (not doc not found)\\n\\t\\t\\tif(newTermList.size()>0){\\n\\t\\t\\t\\t\\n\\t\\t\\t\\t\\n\\t\\t\\t\\tsCurrentHashMap = addListToHashMap(sCurrentHashMap, newTermList);\\n\\t\\t\\t\\t\\n\\t\\t\\t\\t/*เพิ่มเงื่อนไขกรณี ลบคำออกจากไฟล์ \\n\\t\\t\\t\\t * 1.ทำ list เป็น hashMap อีกอันไว้เซิชไวไว\\n\\t\\t\\t\\t * loop amount of doc\\n\\t\\t\\t\\t * 2.ไล่ iterative ของ hashMap ว่ามี value อันไหน contain ชื่อไฟล์บ้าง ถ้าcontain ให้เช็คกลับว่า key นั้น มีในแฮชอีกอันหรือเปล่า\\n\\t\\t\\t\\t*/\\n\\t\\t\\t\\t\\n\\t\\t\\t\\t/* // Convert new word (from file) list to HashMap\\n\\t\\t\\t\\tHashMap<String, String> newWordHashMap = new HashMap<String, String>();\\n\\t\\t\\t\\tfor(Term i: newTermList){\\n\\t\\t\\t\\t\\tnewWordHashMap.put(i.getTerm(), i.getDocNumber()+\\\"\\\");\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\n\\t\\t\\t\\t\\n\\t\\t\\t\\tIterator it = sCurrentHashMap.entrySet().iterator();\\n\\t\\t\\t\\twhile(it.hasNext()){\\n\\t\\t\\t\\t\\tHashMap.Entry<String, String> entry = (HashMap.Entry<String, String>) it.next();\\n\\t\\t\\t\\t\\t//if its value contains the doc number, then check if its key is in the newTermHash or note\\n\\t\\t\\t\\t\\t// if not --> this term was removed --> remove this key out from sCurrentHashMap\\n\\t\\t\\t\\t\\tif(entry.getValue().contains(s)) {\\n\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\t*/\\n\\t\\t\\t\\t\\n\\t\\t\\t\\tglobalHash.put(indexFileName, sCurrentHashMap);\\n\\n\\t\\t\\t\\t\\n\\t\\t\\t}\\n\\t\\t\\t\\n\\t\\t}\\n\\t\\t\\n\\t\\t\\n\\t\\t\\n\\t\\t\\n\\t}\",\n \"public static void getAllDocumentIds(ArrayList idList, String collectionName) {\\n idList.clear();\\n MainActivity.db.collection(collectionName).get().addOnCompleteListener(new OnCompleteListener<QuerySnapshot>() {\\n @Override\\n public void onComplete(@NonNull Task<QuerySnapshot> task) {\\n if (task.isSuccessful()) {\\n for (QueryDocumentSnapshot document : task.getResult()) {\\n idList.add(document.getId());\\n Log.d(TAG, document.getId() + \\\" => \\\" + document.getData());\\n }\\n } else {\\n Log.w(TAG, \\\"Error getting documents.\\\", task.getException());\\n }\\n }\\n });\\n }\",\n \"private void invertedToDatabase(){\\r\\n cleFreq = new HashMap<>();\\r\\n System.out.println(\\\"Strat collecting\\\");\\r\\n Map<String,List<Invertedindex>> collects = collecting();\\r\\n System.out.println(\\\"Ending collecting\\\");\\r\\n Database.getInstance().invertedIndex(collects);\\r\\n Database.getInstance().addPoids(cleFreq);\\r\\n }\",\n \"private void storeData() {\\r\\n final File tweetsFile = new File(tweetsStorePath);\\r\\n final File usersFile = new File(usersStorePath);\\r\\n final Set<TweetEntity> tweetEntities = new HashSet();\\r\\n final Set<UserEntity> userEntities = new HashSet();\\r\\n \\r\\n tweets.entrySet().stream().forEach(entry -> {\\r\\n entry.getValue().stream().forEach(\\r\\n status -> {\\r\\n try {\\r\\n tweetEntities.add(\\r\\n new TweetEntity(status,\\r\\n entry.getKey()));\\r\\n userEntities.add(\\r\\n new UserEntity(status.getUser()));\\r\\n } catch (UnsupportedEncodingException ex) {\\r\\n \\r\\n }\\r\\n });\\r\\n });\\r\\n\\r\\n try {\\r\\n try (PrintWriter tweetWriter = new PrintWriter(tweetsFile)) {\\r\\n tweetEntities.stream().forEach(entity -> {\\r\\n tweetWriter.println(entity.toString());\\r\\n });\\r\\n }\\r\\n try (PrintWriter userWriter = new PrintWriter(usersFile)) {\\r\\n userEntities.stream().forEach(entity -> {\\r\\n userWriter.println(entity.toString());\\r\\n });\\r\\n }\\r\\n } catch (IOException ex) {\\r\\n System.out.println(\\\"DBLIS - storeData() - error storing data\\\" + ex);\\r\\n }\\r\\n }\",\n \"public void parseThesaurus() throws IOException {\\r\\n\\t\\t\\t//We create an object below to read the thesaurus file\\r\\n\\t\\t\\tFileInputStream fis = new FileInputStream(\\\"src//ie//gmit//dip//resources//MobyThesaurus3.txt\\\");\\r\\n\\t\\t\\tBufferedReader br=new BufferedReader(new InputStreamReader(fis));\\r\\n\\t\\t\\t List <List<String>> listOflist= new ArrayList<>();\\r\\n\\t\\t\\t// HashMap<String,List> tMap = new HashMap<>();\\t\\t\\r\\n\\t\\t\\t List <String> individualListOfSynonyms= new ArrayList <String>();\\r\\n\\r\\n\\t\\t\\t \\r\\n\\t\\t\\t //we create a hashmap with the first word being the key value and the rest a list of synonims we will use\\r\\n\\t\\t\\twhile(br.readLine()!=null) {\\r\\n\\t\\t\\t\\t\\r\\n\\t\\t\\t\\tString somestring = br.readLine();\\r\\n\\t\\t\\t\\tString[] testsplit= somestring.split(\\\",\\\");\\r\\n\\t\\t\\t\\tindividualListOfSynonyms=Arrays.asList(testsplit);\\r\\n\\t\\t\\t\\tString indexvalue=individualListOfSynonyms.get(0).toString();\\r\\n\\t\\t\\t tMap.put(indexvalue, individualListOfSynonyms);\\r\\n\\t\\t\\t //br.close();\\r\\n\\t\\t\\t //System.out.println(tMap);\\r\\n\\t\\t\\t }\\r\\n\\t\\t\\t}\",\n \"public void setDocsInfo(String path) {\\n BufferedReader br = null;\\n try {\\n br = new BufferedReader(new FileReader(new File(path)));\\n String line = \\\"\\\";\\n while ((line = (br.readLine())) != null) {\\n String [] splitLineByDelimiter = line.split(\\\", \\\");\\n String docId = splitLineByDelimiter[0].substring(0, splitLineByDelimiter[0].indexOf(\\\":\\\"));\\n String docLength = splitLineByDelimiter[1];\\n docsInfo.put(docId, Integer.parseInt(docLength));\\n }\\n br.close();\\n } catch (IOException e) {\\n e.printStackTrace();\\n }\\n\\n }\",\n \"private void createDocs() {\\n\\t\\t\\n\\t\\tArrayList<Document> docs=new ArrayList<>();\\n\\t\\tString foldername=\\\"E:\\\\\\\\graduate\\\\\\\\cloud\\\\\\\\project\\\\\\\\data\\\\\\\\input\\\";\\n\\t\\tFile folder=new File(foldername);\\n\\t\\tFile[] listOfFiles = folder.listFiles();\\n\\t\\tfor (File file : listOfFiles) {\\n\\t\\t\\ttry {\\n\\t\\t\\t\\tFileInputStream fisTargetFile = new FileInputStream(new File(foldername+\\\"\\\\\\\\\\\"+file.getName()));\\n\\t\\t\\t\\tString fileContents = IOUtils.toString(fisTargetFile, \\\"UTF-8\\\");\\n\\t\\t\\t\\tString[] text=fileContents.split(\\\"ParseText::\\\");\\n\\t\\t\\t\\tif(text.length>1){\\n\\t\\t\\t\\t\\tString snippet=text[1].trim().length()>100 ? text[1].trim().substring(0, 100): text[1].trim();\\n\\t\\t\\t\\t\\tDocument doc=new Document();\\n\\t\\t\\t\\t\\tdoc.setFileName(file.getName().replace(\\\".txt\\\", \\\"\\\"));\\n\\t\\t\\t\\t\\tdoc.setUrl(text[0].split(\\\"URL::\\\")[1].trim());\\n\\t\\t\\t\\t\\tdoc.setText(snippet+\\\"...\\\");\\n\\t\\t\\t\\t\\tdocs.add(doc);\\n\\t\\t\\t\\t}\\n\\t\\t\\t}catch(IOException e){\\n\\t\\t\\t\\te.printStackTrace();\\n\\t\\t\\t}\\t\\n\\t\\t}\\t\\n\\t\\tDBUtil.insertDocs(docs);\\n\\t}\",\n \"private void setUpPlaces(){\\n db.collection(\\\"Tokens\\\").get()\\n .addOnCompleteListener(new OnCompleteListener<QuerySnapshot>() {\\n @Override\\n public void onComplete(@NonNull Task<QuerySnapshot> task) {\\n if (task.isSuccessful()) {\\n for (QueryDocumentSnapshot document : task.getResult()) {\\n String id = document.getId();\\n String name = document.get(\\\"name\\\").toString();\\n String desc = document.get(\\\"description\\\").toString();\\n String[] latLng = document.get(\\\"latlng\\\").toString().split(\\\",\\\");\\n double latitude = Double.parseDouble(latLng[0]);\\n double longitude = Double.parseDouble(latLng[1]);\\n places.add(new PlaceToken(id, name, desc, new LatLng(latitude, longitude)));\\n }\\n }\\n }\\n });\\n }\",\n \"public void map(Object key, Text value, Context context\\n\\t\\t ) throws IOException, InterruptedException {\\n\\n\\t\\t\\t\\n\\t\\t\\t\\n\\t\\t\\t \\n\\t\\t\\t String curr_string=value.toString();\\n\\t\\t\\t /// splitting based on \\\"*\\\" as a delimiter...\\n\\t\\t\\t String [] parts=curr_string.split(\\\"\\\\\\\\*\\\");\\n\\t\\t\\t String curr_key=parts[0];\\n\\t\\t\\t // Removing spaces from both left and right part of the string..\\n\\t\\t\\t String curr_value=parts[1].trim();\\n\\t\\t\\t String [] small_parts=curr_value.split(\\\",\\\");\\n\\t\\t\\t // Taking the count of unique files which are present in the input given to tfidf\\n\\t\\t\\t int no_of_unique_files=Integer.parseInt(small_parts[small_parts.length-1]);\\n\\t\\t\\t /// The formula to compute idf is log((1+no_of_files)/no_of_unique_files))....\\n\\t\\t\\t Configuration conf=context.getConfiguration();\\n\\t\\t\\t String value_count=conf.get(\\\"test\\\");\\n\\t\\t\\t if(!value_count.isEmpty())\\n\\t\\t\\t {\\n\\t\\t\\t int total_no_files=Integer.parseInt(value_count);\\n\\t\\t\\t double x=(total_no_files/no_of_unique_files);\\n\\t\\t\\t // Formula fo rcomputing the idf value....\\n\\t\\t\\t double idf_value=Math.log10(1+x);\\n\\t\\t\\t for(int i=0;i<small_parts.length-1;i++)\\n\\t\\t\\t {\\n\\t\\t\\t\\t String [] waste=small_parts[i].split(\\\"=\\\");\\n\\t\\t\\t\\t String file_name=waste[0];\\n\\t\\t\\t\\t // Computing the tfidf on the fly...\\n\\t\\t\\t\\t double tf_idf=idf_value*Double.parseDouble(waste[1]);\\n\\t\\t\\t\\t Text word3 = new Text();\\n\\t\\t\\t\\t Text word4 = new Text();\\n\\t\\t\\t\\t word3.set(curr_key+\\\"#####\\\"+file_name+\\\",\\\");\\n\\t\\t\\t\\t word4.set(tf_idf+\\\"\\\");\\n\\t\\t\\t\\t context.write(word3,word4);\\n\\t\\t\\t\\t \\n\\t\\t\\t }\\n\\t\\t\\t //word1.set(curr_key);\\n\\t\\t\\t //word2.set(idf_value+\\\"\\\");\\n\\t\\t\\t //context.write(word1,word2); \\n\\t\\t\\t} \\n\\t\\t}\",\n \"public static void DumpLocationCoordinatestoKMLRevised(Places places) throws IOException{\\n\\n String filen = folder_path+\\\"loc2kmlRevised.txt\\\";\\n File file = new File(filen);\\n if (!file.exists()) {\\n file.createNewFile();\\n }\\n BufferedWriter output = new BufferedWriter(new FileWriter(file));\\n\\n for(int i=0;i<places.places.size();i++){\\n LocationCluster locationcls=places.places.get(i);\\n output.write(locationcls.placeID+\\\"~\\\");\\n\\n List<UserPhoto> sublist=locationcls.getIdenticalsubLocations();\\n if(sublist.size()>2){\\n\\n for(int j=0;j<sublist.size()-1;j++){\\n\\n output.write(sublist.get(j).geotag.lat+\\\",\\\"+sublist.get(j).geotag.lng);\\n if(j<sublist.size()-2){\\n output.write(\\\"|\\\");\\n }\\n }\\n\\n }\\n else{\\n\\n GeoTag center =locationcls.GetCentriod();\\n output.write(center.lat+\\\",\\\"+center.lng);\\n }\\n\\n\\n output.write(\\\"\\\\n\\\");\\n\\n\\n\\n\\n }\\noutput.flush();\\n\\n }\",\n \"private void loadLoreEntries() {\\n entryIDMap = new ConcurrentHashMap<>();\\n entryIDThreads = new ThreadGroup(\\\"entryIDThreads\\\");\\n\\n for (int i = 0; i < bookSelectionData.size(); i++) {\\n\\n final String entryName = bookSelectionData.get(i).getBookName();\\n final long entryID = bookSelectionData.get(i).getBookID();\\n\\n new Thread(entryIDThreads, new Runnable() {\\n @Override\\n public void run() {\\n try {\\n ArrayList<Long> arraylist = new ArrayList<>();\\n arraylist.add(entryID);\\n DataAccessObject_LoreBookSelectionDefinition node = database.getDao().getPresentationNodeById(arraylist).get(0);\\n JsonObject json = node.getJson();\\n JsonArray entryNodes = json.getAsJsonObject(\\\"children\\\").getAsJsonArray(\\\"records\\\");\\n\\n long[] ID = new long[entryNodes.size()];\\n for (int j = 0; j < entryNodes.size(); j++) {\\n JsonObject entry = (JsonObject) entryNodes.get(j);\\n long hash = Long.parseLong(entry.get(\\\"recordHash\\\").getAsString());\\n ID[j] = convertHash(hash);\\n }\\n entryIDMap.put(entryName, ID);\\n } catch (Exception ignored) {\\n }\\n }\\n }).start();\\n }\\n }\",\n \"private void saveInFile() {\\n\\t\\tthis.deleteFile();\\n\\t\\tfor (CounterModel obj : counterListModel.getCounterList()) {\\n\\t\\t\\ttry {\\n\\t\\t\\t\\tGson gson = new Gson();\\n\\t\\t\\t\\tif (obj.getCounterName().equals(counterModel.getCounterName())) {\\n\\t\\t\\t\\t\\tobj = counterModel;\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\tString json = gson.toJson(obj) +'\\\\n';\\n\\t\\t\\t\\tFileOutputStream fos = openFileOutput(FILENAME,\\n\\t\\t\\t\\t\\t\\tContext.MODE_APPEND);\\n\\t\\t\\t\\tfos.write(json.getBytes());\\n\\t\\t\\t\\tfos.close();\\n\\t\\t\\t} catch (FileNotFoundException e) {\\n\\t\\t\\t\\t// TODO Auto-generated catch block\\n\\t\\t\\t\\te.printStackTrace();\\n\\t\\t\\t} catch (IOException e) {\\n\\t\\t\\t\\t// TODO Auto-generated catch block\\n\\t\\t\\t\\te.printStackTrace();\\n\\t\\t\\t}\\n\\t\\t}\\n\\t}\",\n \"public void allartistsongs() throws IOException{\\r\\n List<String> ArrangersAndTheirSongs=new ArrayList<>();\\r\\n String allsongs=\\\"\\\";\\r\\n int counter=0;\\r\\n for(int id: ArrangersMap.keySet()){\\r\\n String ArrangerName=ArrangersMap.get(id);\\r\\n for(String song:ArrangerLinesList){\\r\\n String perform[];\\r\\n perform=song.split(\\\"/\\\");\\r\\n int arrangeid=Integer.parseInt(perform[1]);\\r\\n if(id==arrangeid){\\r\\n int songid= Integer.parseInt(perform[0]);\\r\\n String songname=test.getsongName(songid);\\r\\n allsongs+=songname+\\\" \\\";\\r\\n counter++;\\r\\n } \\r\\n }\\r\\n ArrangersAndTheirSongs.add(\\\"The Arranger's Name is:\\\"+ArrangerName+\\\" The number of songs is:\\\"+counter+ \\\" Their songs are:\\\"+allsongs);\\r\\n allsongs=\\\"\\\";\\r\\n counter=0;\\r\\n }\\r\\n writeListToTextFile(\\\"d:\\\\\\\\documents\\\\\\\\textfiles\\\\\\\\ArrangersAndTheirSongs.txt\\\",ArrangersAndTheirSongs);\\r\\n // test.writeSongs(\\\"d:\\\\\\\\documents\\\\\\\\textfiles\\\\\\\\ArrangersAndTheirSongs.txt\\\");\\r\\n // Path path=Paths.get()\\r\\n for(String line:ArrangersAndTheirSongs){\\r\\n System.out.println(line);\\r\\n }\\r\\n System.out.println(ArrangersAndTheirSongs.size());\\r\\n \\r\\n System.out.println(\\\"The size of ArrangersMap is:\\\"+ArrangersMap.size());\\r\\n System.out.println(\\\"The counter is:\\\"+counter);\\r\\n }\",\n \"private static void readAndWriteNodes(String name) throws IOException {\\n System.out.println(name);\\n Map<Long, Long> nodeMap = new HashMap<>();\\n boolean firstLine = true;\\n fileReader = new BufferedReader(new FileReader(PATH + name));\\n fileWriter = new BufferedWriter(new FileWriter(PATH + \\\"/uid/\\\" + name));\\n String line;\\n while ((line = fileReader.readLine()) != null) {\\n if (!firstLine) {\\n long globalId = getGlobalId();\\n String[] lineTokens = LINE_TOKEN_SEPARATOR.split(line);\\n long ID = Long.parseLong(lineTokens[0]);\\n nodeMap.put(ID, globalId);\\n String writeLine = \\\"\\\";\\n for (int i = 0; i < lineTokens.length; i++) {\\n if (i == 0) {\\n writeLine += globalId;\\n } else {\\n writeLine += lineTokens[i];\\n }\\n writeLine += \\\"|\\\";\\n }\\n fileWriter.write(writeLine);\\n fileWriter.newLine();\\n vertexCount++;\\n globalVertexCount++;\\n } else {\\n fileWriter.write(line);\\n fileWriter.newLine();\\n firstLine = false;\\n }\\n }\\n fileWriter.close();\\n fileReader.close();\\n counterMapNodes.put(name, vertexCount);\\n vertexCount = 0;\\n vertexList.add(nodeMap);\\n }\",\n \"BsonToken getCurrentToken();\",\n \"public void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException\\n {\\n String line = value.toString().toLowerCase();\\n\\n // Splitting into doc number and its text\\n String document_split[] = line.split(\\\"\\\\t\\\",2);\\n Text document_number = new Text(document_split[0]);\\n\\n // Replace all non alphabetic characters and non spaces with a space\\n String document_content=document_split[1].replaceAll(\\\"[^ a-z]+\\\", \\\" \\\");\\n\\n String bigram_word_1=null;\\n String bigram_word_2=null;\\n // Tokenize into words\\n StringTokenizer tokenizer = new StringTokenizer(document_content);\\n int x=0;\\n while(tokenizer.hasMoreTokens())\\n {\\n x+=1;\\n if(x==1)\\n {\\n bigram_word_1=tokenizer.nextToken();\\n }\\n else\\n {\\n bigram_word_2=tokenizer.nextToken();\\n String bigram_pair_string=bigram_word_1+\\\" \\\"+bigram_word_2;\\n bigram_pair.set(bigram_pair_string);\\n context.write(bigram_pair, document_number);\\n break;\\n }\\n }\\n while(tokenizer.hasMoreTokens())\\n {\\n bigram_word_1=bigram_word_2;\\n bigram_word_2=tokenizer.nextToken();\\n String bigram_pair_string=bigram_word_1+\\\" \\\"+bigram_word_2;\\n bigram_pair.set(bigram_pair_string);\\n context.write(bigram_pair, document_number);\\n }\\n }\",\n \"public void indexCreate()\\n {\\n try{\\n Directory dir = FSDirectory.open(Paths.get(\\\"indice/\\\"));\\n Analyzer analyzer = new StandardAnalyzer();\\n IndexWriterConfig iwc = new IndexWriterConfig(analyzer);\\n iwc.setOpenMode(OpenMode.CREATE);\\n IndexWriter writer = new IndexWriter(dir,iwc);\\n MongoConnection mongo = MongoConnection.getMongo();\\n mongo.OpenMongoClient();\\n DBCursor cursor = mongo.getTweets();\\n Document doc = null;\\n\\n while (cursor.hasNext()) {\\n DBObject cur = cursor.next();\\n if (cur.get(\\\"retweet\\\").toString().equals(\\\"false\\\")) {\\n doc = new Document();\\n doc.add(new StringField(\\\"id\\\", cur.get(\\\"_id\\\").toString(), Field.Store.YES));\\n doc.add(new TextField(\\\"text\\\", cur.get(\\\"text\\\").toString(), Field.Store.YES));\\n doc.add(new StringField(\\\"analysis\\\", cur.get(\\\"analysis\\\").toString(), Field.Store.YES));\\n //doc.add(new StringField(\\\"finalCountry\\\",cur.get(\\\"finalCountry\\\").toString(),Field.Store.YES));\\n doc.add(new StringField(\\\"userScreenName\\\", cur.get(\\\"userScreenName\\\").toString(), Field.Store.YES));\\n doc.add(new StringField(\\\"userFollowersCount\\\", cur.get(\\\"userFollowersCount\\\").toString(), Field.Store.YES));\\n doc.add(new StringField(\\\"favoriteCount\\\", cur.get(\\\"favoriteCount\\\").toString(), Field.Store.YES));\\n\\n if (writer.getConfig().getOpenMode() == OpenMode.CREATE) {\\n System.out.println(\\\"Indexando el tweet: \\\" + doc.get(\\\"text\\\") + \\\"\\\\n\\\");\\n writer.addDocument(doc);\\n System.out.println(doc);\\n } else {\\n System.out.println(\\\"Actualizando el tweet: \\\" + doc.get(\\\"text\\\") + \\\"\\\\n\\\");\\n writer.updateDocument(new Term(\\\"text\\\" + cur.get(\\\"text\\\")), doc);\\n System.out.println(doc);\\n }\\n }\\n }\\n cursor.close();\\n writer.close();\\n }\\n catch(IOException ioe){\\n System.out.println(\\\" Error en \\\"+ ioe.getClass() + \\\"\\\\n mensaje: \\\" + ioe.getMessage());\\n }\\n }\",\n \"private void indexDocumentHelper(HashMap<String, StringBuilder> fm)\\n\\t\\t\\tthrows IOException {\\n\\n\\t\\tIndexWriter writer = getIndexWriter();\\n\\n\\t\\tDocument doc = new Document();\\n\\n\\t\\tfor (int i = 0; i < fieldNames.length; i++) {\\n\\n\\t\\t\\tif (fieldNames[i].equals(\\\"DOCNO\\\")) {\\n\\n\\t\\t\\t\\tdoc.add(new StringField(fieldNames[i], fm.get(fieldNames[i])\\n\\t\\t\\t\\t\\t\\t.toString(), Field.Store.YES));\\n\\t\\t\\t}\\n\\n\\t\\t\\telse {\\n\\t\\t\\t\\tdoc.add(new TextField(fieldNames[i], fm.get(fieldNames[i])\\n\\t\\t\\t\\t\\t\\t.toString(), Field.Store.YES));\\n\\t\\t\\t}\\n\\t\\t}\\n\\n\\t\\twriter.addDocument(doc);\\n\\n\\t}\",\n \"java.lang.String getDocumentId();\",\n \"@Override\\n\\tpublic String getDocumentKey() {\\n\\t\\treturn uid.toString();\\n\\t}\",\n \"public void updateMapsRecords(){\\n\\n // The file to save the maps records\\n File file= new File(MAPS_FILE_PATH);\\n Document document = DocumentHelper.createDocument();\\n Element rootElement = document.addElement(\\\"xml\\\");\\n if(mapsList==null)\\n return;\\n for(GridMap themap:mapsList){\\n rootElement.add(themap.encode());\\n }\\n FileOperator.fileWriter(file,document);\\n }\",\n \"@Override\\n public void run() {\\n FirebaseFirestore.getInstance().collection(\\\"users/\\\" + companyID + \\\"/trips\\\")\\n .addSnapshotListener(new EventListener<QuerySnapshot>() {\\n @Override\\n public void onEvent(@Nullable QuerySnapshot value, @Nullable FirebaseFirestoreException e) {\\n if (e != null) {\\n Log.w(TAG, \\\"Listen failed.\\\", e);\\n return;\\n }\\n tripList.clear();//clear the ArrayList, because this method get all the document id instead of\\n //the one that just created\\n for (QueryDocumentSnapshot doc : value) {\\n if (doc.getId() != null) {\\n tripList.add(doc.getId());//store the document IDs to ArrayList\\n\\n Log.d(TAG, \\\"Retrieved data: \\\" + doc.getId());\\n }\\n }\\n showTripList();//show trip name to listView\\n }\\n });\\n }\",\n \"@RequestMapping(\\\"/showUpload\\\")\\n\\tpublic String showDocument(ModelMap map){\\n\\t\\t//get all DB records and send to UI\\n\\t\\tList<Object[]> ob=service.getFileIdAndNames();\\n\\t\\tmap.addAttribute(\\\"listOb\\\", ob);\\n\\t\\treturn \\\"UploadFile\\\";\\n\\t}\",\n \"public static void main(String[] args) throws Exception \\n\\t{\\n\\t\\tList<String> stopWords = new ArrayList<String>();\\n\\t\\tstopWords = stopWordsCreation();\\n\\n\\n\\t\\t\\n\\t\\tHashMap<Integer, String> hmap = new HashMap<Integer, String>();\\t//Used in tittle, all terms are unique, and any dups become \\\" \\\"\\n\\t\\n\\t\\t\\n\\t\\tList<String> uniqueTerms = new ArrayList<String>();\\n\\t\\tList<String> allTerms = new ArrayList<String>();\\n\\t\\t\\t\\t\\n\\t\\t\\n\\t\\tHashMap<Integer, String> hmap2 = new HashMap<Integer, String>();\\n\\t\\tHashMap<Integer, String> allValues = new HashMap<Integer, String>();\\n\\t\\tHashMap<Integer, Double> docNorms = new HashMap<Integer, Double>();\\n\\t\\t\\n\\t\\t\\n\\t\\t\\n\\t\\t\\n\\t\\tMap<Integer, List<String>> postingsFileListAllWords = new HashMap<>();\\t\\t\\n\\t\\tMap<Integer, List<String>> postingsFileList = new HashMap<>();\\n\\t\\t\\n\\t\\tMap<Integer, List<StringBuilder>> docAndTitles = new HashMap<>();\\n\\t\\tMap<Integer, List<StringBuilder>> docAndAbstract = new HashMap<>();\\n\\t\\tMap<Integer, List<StringBuilder>> docAndAuthors = new HashMap<>();\\n\\t\\t\\n\\t\\t\\n\\t\\tMap<Integer, List<Double>> termWeights = new HashMap<>();\\n\\t\\t\\n\\t\\tList<Integer> docTermCountList = new ArrayList<Integer>();\\n\\t\\t\\n\\t\\tBufferedReader br = null;\\n\\t\\tFileReader fr = null;\\n\\t\\tString sCurrentLine;\\n\\n\\t\\tint documentCount = 0;\\n\\t\\tint documentFound = 0;\\n\\t\\tint articleNew = 0;\\n\\t\\tint docTermCount = 0;\\n\\t\\t\\n\\t\\t\\n\\t\\tboolean abstractReached = false;\\n\\n\\t\\ttry {\\n\\t\\t\\tfr = new FileReader(FILENAME);\\n\\t\\t\\tbr = new BufferedReader(fr);\\n\\n\\t\\t\\t// Continues to get 1 line from document until it reaches the end of EVERY doc\\n\\t\\t\\twhile ((sCurrentLine = br.readLine()) != null) \\n\\t\\t\\t{\\n\\t\\t\\t\\t// sCurrentLine now contains the 1 line from the document\\n\\n\\t\\t\\t\\t// Take line and split each word and place them into array\\n\\t\\t\\t\\tString[] arr = sCurrentLine.split(\\\" \\\");\\n\\n\\n\\t\\t\\t\\t//Go through the entire array\\n\\t\\t\\t\\tfor (String ss : arr) \\n\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t/*\\n\\t\\t\\t\\t\\t * This section takes the array and checks to see if it has reached a new\\n\\t\\t\\t\\t\\t * document or not. If the current line begins with an .I, then it knows that a\\n\\t\\t\\t\\t\\t * document has just started. If it incounters another .I, then it knows that a\\n\\t\\t\\t\\t\\t * new document has started.\\n\\t\\t\\t\\t\\t */\\n\\t\\t\\t\\t\\t//System.out.println(\\\"Before anything: \\\"+sCurrentLine);\\n\\t\\t\\t\\t\\tif (arr[0].equals(\\\".I\\\")) \\n\\t\\t\\t\\t\\t{\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\tif (articleNew == 0) \\n\\t\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\t\\tarticleNew = 1;\\n\\t\\t\\t\\t\\t\\t\\tdocumentFound = Integer.parseInt(arr[1]);\\n\\t\\t\\t\\t\\t\\t} \\n\\t\\t\\t\\t\\t\\telse if (articleNew == 1) \\n\\t\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\t\\tarticleNew = 0;\\n\\t\\t\\t\\t\\t\\t\\tdocumentFound = Integer.parseInt(arr[1]);\\n\\t\\t\\t\\t\\t\\t}\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t//System.out.println(documentFound);\\n\\t\\t\\t\\t\\t\\t//count++;\\n\\t\\t\\t\\t\\t\\tbreak;\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t/* This section detects that after a document has entered,\\n\\t\\t\\t\\t\\t * it has to gather all the words contained in the title \\n\\t\\t\\t\\t\\t * section.\\n\\t\\t\\t\\t\\t */\\n\\t\\t\\t\\t\\tif (arr[0].equals(\\\".T\\\") ) \\n\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t// Go to line UNDER .T since that is where tittle is located\\n\\t\\t\\t\\t\\t\\t//sCurrentLine = br.readLine();\\n\\t\\t\\t\\t\\t\\tdocAndTitles.put(documentFound, new ArrayList<StringBuilder>());\\n\\t\\t\\t\\t\\t\\t//System.out.println(\\\"docAndTitles.get(documentCount+1): \\\" +docAndTitles.get(documentFound));\\n\\t\\t\\t\\t\\t\\t//System.out.println(\\\"Docs and titles: \\\"+docAndTitles);\\n\\t\\t\\t\\t\\t\\tStringBuilder title = new StringBuilder();\\n\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\twhile ( !(sCurrentLine = br.readLine()).matches(\\\".B|.A|.N|.X|.K|.C\\\") )\\n\\t\\t\\t\\t\\t\\t{\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t/* In this section, there are 2 lists being made. One list\\n\\t\\t\\t\\t\\t\\t\\t * is for all the unique words in every title in the document (hmap).\\n\\t\\t\\t\\t\\t\\t\\t * Hmap contains all unique words, and anytime a duplicate word is \\n\\t\\t\\t\\t\\t\\t\\t * found, it is replaced with an empty space in the map.\\n\\t\\t\\t\\t\\t\\t\\t * All Values \\n\\t\\t\\t\\t\\t\\t\\t * \\n\\t\\t\\t\\t\\t\\t\\t */\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t//postingsFileList.put(documentFound - 1, new ArrayList<String>());\\n\\t\\t\\t\\t\\t\\t\\t//postingsFileList.get(documentFound - 1).add(term2);\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t//System.out.println(\\\"current line: \\\"+sCurrentLine);\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\tString[] tittle = sCurrentLine.split(\\\" \\\");\\n\\t\\t\\t\\t\\t\\t\\tif (tittle[0].equals(\\\".W\\\") )\\n\\t\\t\\t\\t\\t\\t\\t{\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\tabstractReached = true;\\n\\t\\t\\t\\t\\t\\t\\t\\tbreak;\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\ttitle.append(sCurrentLine);\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\tfor (String tittleWords : tittle)\\n\\t\\t\\t\\t\\t\\t\\t{\\t\\n\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\ttittleWords = tittleWords.toLowerCase();\\n\\t\\t\\t\\t\\t\\t\\t\\ttittleWords = tittleWords.replaceAll(\\\"[-&^%'{}*|$+\\\\\\\\/\\\\\\\\?!<>=.,;_:()\\\\\\\\[\\\\\\\\]\\\\\\\"\\\\\\\\d]\\\", \\\"\\\");\\n\\t\\t\\t\\t\\t\\t\\t\\ttittleWords = tittleWords.replaceAll(\\\"[-&^%'*{}|$+\\\\\\\\/\\\\\\\\?!<>=.,;_:()\\\\\\\\[\\\\\\\\]\\\\\\\"\\\\\\\\d]\\\", \\\"\\\");\\n\\t\\t\\t\\t\\t\\t\\t\\ttittleWords = tittleWords.replaceAll(\\\"[-&^%'{}*|$+\\\\\\\\/\\\\\\\\?!<>=.,;_:()\\\\\\\\[\\\\\\\\]\\\\\\\"\\\\\\\\d]\\\", \\\"\\\");\\n\\t\\t\\t\\t\\t\\t\\t\\t//System.out.println(tittleWords);\\n\\t\\t\\t\\t\\t\\t\\t\\tif (hmap.containsValue(tittleWords)) \\n\\t\\t\\t\\t\\t\\t\\t\\t{\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\t\\thmap.put(documentCount, \\\" \\\");\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tallValues.put(documentCount, tittleWords);\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tallTerms.add(tittleWords);\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tdocumentCount++;\\n\\t\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\t\\telse \\n\\t\\t\\t\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tallTerms.add(tittleWords);\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tallValues.put(documentCount, tittleWords);\\n\\t\\t\\t\\t\\t\\t\\t\\t\\thmap.put(documentCount, tittleWords);\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tif (!(uniqueTerms.contains(tittleWords)))\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tif ((stopWordsSetting && !(stopWords.contains(tittleWords))))\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tuniqueTerms.add(tittleWords);\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tdocumentCount++;\\n\\t\\t\\t\\t\\t\\t\\t\\t}\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\t//docAndTitles.get(documentCount).add(\\\" \\\");\\n\\t\\t\\t\\t\\t\\t\\ttitle.append(\\\"\\\\n\\\");\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t//System.out.println(\\\"Title: \\\"+title);\\n\\t\\t\\t\\t\\t\\t//System.out.println(\\\"docAndTitles.get(documentCount+1): \\\" +docAndTitles.get(documentFound));\\n\\t\\t\\t\\t\\t\\tdocAndTitles.get(documentFound).add(title);\\n\\t\\t\\t\\t\\t\\t//System.out.println(\\\"Done!: \\\"+ docAndTitles);\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\tif (arr[0].equals(\\\".A\\\") ) \\n\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t// Go to line UNDER .T since that is where tittle is located\\n\\t\\t\\t\\t\\t\\t//sCurrentLine = br.readLine();\\n\\t\\t\\t\\t\\t\\tdocAndAuthors.put(documentFound, new ArrayList<StringBuilder>());\\n\\t\\t\\t\\t\\t\\t//System.out.println(\\\"docAndTitles.get(documentCount+1): \\\" +docAndTitles.get(documentFound));\\n\\t\\t\\t\\t\\t\\t//System.out.println(\\\"Docs and titles: \\\"+docAndTitles);\\n\\t\\t\\t\\t\\t\\tStringBuilder author = new StringBuilder();\\n\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\twhile ( !(sCurrentLine = br.readLine()).matches(\\\".N|.X|.K|.C\\\") )\\n\\t\\t\\t\\t\\t\\t{\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t/* In this section, there are 2 lists being made. One list\\n\\t\\t\\t\\t\\t\\t\\t * is for all the unique words in every title in the document (hmap).\\n\\t\\t\\t\\t\\t\\t\\t * Hmap contains all unique words, and anytime a duplicate word is \\n\\t\\t\\t\\t\\t\\t\\t * found, it is replaced with an empty space in the map.\\n\\t\\t\\t\\t\\t\\t\\t * All Values \\n\\t\\t\\t\\t\\t\\t\\t * \\n\\t\\t\\t\\t\\t\\t\\t */\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t//postingsFileList.put(documentFound - 1, new ArrayList<String>());\\n\\t\\t\\t\\t\\t\\t\\t//postingsFileList.get(documentFound - 1).add(term2);\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t//System.out.println(\\\"current line: \\\"+sCurrentLine);\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\tString[] tittle = sCurrentLine.split(\\\" \\\");\\n\\t\\t\\t\\t\\t\\t\\tif (tittle[0].equals(\\\".W\\\") )\\n\\t\\t\\t\\t\\t\\t\\t{\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\tabstractReached = true;\\n\\t\\t\\t\\t\\t\\t\\t\\tbreak;\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\tauthor.append(sCurrentLine);\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t//docAndTitles.get(documentCount).add(\\\" \\\");\\n\\t\\t\\t\\t\\t\\t\\tauthor.append(\\\"\\\\n\\\");\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t//System.out.println(\\\"Title: \\\"+title);\\n\\t\\t\\t\\t\\t\\t//System.out.println(\\\"docAndTitles.get(documentCount+1): \\\" +docAndTitles.get(documentFound));\\n\\t\\t\\t\\t\\t\\tdocAndAuthors.get(documentFound).add(author);\\n\\t\\t\\t\\t\\t\\t//System.out.println(\\\"Done!: \\\"+ docAndTitles);\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t/* Since there may or may not be an asbtract after\\n\\t\\t\\t\\t\\t * the title, we need to check what the next section\\n\\t\\t\\t\\t\\t * is. We know that every doc has a publication date,\\n\\t\\t\\t\\t\\t * so it can end there, but if there is no abstract,\\n\\t\\t\\t\\t\\t * then it will keep scanning until it reaches the publication\\n\\t\\t\\t\\t\\t * date. If abstract is empty (in tests), it will also finish instantly\\n\\t\\t\\t\\t\\t * since it's blank and goes straight to .B (the publishing date).\\n\\t\\t\\t\\t\\t * Works EXACTLY like Title \\t\\t \\n\\t\\t\\t\\t\\t */\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\tif (abstractReached) \\n\\t\\t\\t\\t\\t{\\t\\n\\t\\t\\t\\t\\t\\t//System.out.println(\\\"\\\\n\\\");\\n\\t\\t\\t\\t\\t\\t//System.out.println(\\\"REACHED ABSTRACT and current line is: \\\" +sCurrentLine);\\n\\t\\t\\t\\t\\t\\tdocAndAbstract.put(documentFound, new ArrayList<StringBuilder>());\\n\\t\\t\\t\\t\\t\\tStringBuilder totalAbstract = new StringBuilder();\\n\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\twhile ( !(sCurrentLine = br.readLine()).matches(\\\".T|.I|.A|.N|.X|.K|.C\\\") )\\n\\t\\t\\t\\t\\t\\t{\\t\\n\\t\\t\\t\\t\\t\\t\\tString[] abstaract = sCurrentLine.split(\\\" \\\");\\n\\t\\t\\t\\t\\t\\t\\tif (abstaract[0].equals(\\\".B\\\") )\\n\\t\\t\\t\\t\\t\\t\\t{\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\tabstractReached = false;\\n\\t\\t\\t\\t\\t\\t\\t\\tbreak;\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\ttotalAbstract.append(sCurrentLine);\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\tString[] misc = sCurrentLine.split(\\\" \\\");\\n\\t\\t\\t\\t\\t\\t\\tfor (String miscWords : misc) \\n\\t\\t\\t\\t\\t\\t\\t{\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\tmiscWords = miscWords.toLowerCase(); \\n\\t\\t\\t\\t\\t\\t\\t\\tmiscWords = miscWords.replaceAll(\\\"[-&^%'*$+|{}?!\\\\\\\\/<\\\\\\\\>=.,;_:()\\\\\\\\[\\\\\\\\]\\\\\\\"\\\\\\\\d]\\\", \\\"\\\");\\n\\t\\t\\t\\t\\t\\t\\t\\tmiscWords = miscWords.replaceAll(\\\"[-&^%'*$+|?{}!\\\\\\\\/<\\\\\\\\>=.,;_:()\\\\\\\\[\\\\\\\\]\\\\\\\"\\\\\\\\d]\\\", \\\"\\\");\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\tmiscWords = miscWords.replaceAll(\\\"[-&^%'*$+|{}?!\\\\\\\\/<\\\\\\\\>=.,;_:()\\\\\\\\[\\\\\\\\]\\\\\\\"\\\\\\\\d]\\\", \\\"\\\");\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\t//System.out.println(miscWords);\\n\\t\\t\\t\\t\\t\\t\\t\\tif (hmap.containsValue(miscWords)) \\n\\t\\t\\t\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\t\\t\\t\\thmap.put(documentCount, \\\" \\\");\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tallValues.put(documentCount, miscWords);\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tallTerms.add(miscWords);\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tdocumentCount++;\\n\\t\\n\\t\\t\\t\\t\\t\\t\\t\\t} \\n\\t\\t\\t\\t\\t\\t\\t\\telse \\n\\t\\t\\t\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tallTerms.add(miscWords);\\n\\t\\t\\t\\t\\t\\t\\t\\t\\thmap.put(documentCount, miscWords);\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tallValues.put(documentCount, miscWords);\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tif (!(uniqueTerms.contains(miscWords)))\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tif ((stopWordsSetting && !(stopWords.contains(miscWords))))\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tuniqueTerms.add(miscWords);\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tdocumentCount++;\\n\\t\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\t}\\t\\n\\t\\t\\t\\t\\t\\t\\ttotalAbstract.append(\\\"\\\\n\\\");\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\tdocAndAbstract.get(documentFound).add(totalAbstract);\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t}\\t\\n\\t\\t\\t\\t\\n\\t\\t\\t\\t//Once article is found, we enter all of of it's title and abstract terms \\n\\t\\t\\t\\tif (articleNew == 0) \\n\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\tdocumentFound = documentFound - 1;\\n\\t\\t\\t\\t\\t//System.out.println(\\\"Words found in Doc: \\\" + documentFound);\\n\\t\\t\\t\\t\\t//System.out.println(\\\"Map is\\\" +allValues);\\n\\t\\t\\t\\t\\tSet set = hmap.entrySet();\\n\\t\\t\\t\\t\\tIterator iterator = set.iterator();\\n\\n\\t\\t\\t\\t\\tSet set2 = allValues.entrySet();\\n\\t\\t\\t\\t\\tIterator iterator2 = set2.iterator();\\n\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\tpostingsFileList.put(documentFound - 1, new ArrayList<String>());\\n\\t\\t\\t\\t\\tpostingsFileListAllWords.put(documentFound - 1, new ArrayList<String>());\\n\\t\\t\\t\\t\\twhile (iterator.hasNext()) {\\n\\t\\t\\t\\t\\t\\tMap.Entry mentry = (Map.Entry) iterator.next();\\n\\t\\t\\t\\t\\t\\t// (\\\"key is: \\\"+ mentry.getKey() + \\\" & Value is: \\\" + mentry.getValue());\\n\\t\\t\\t\\t\\t\\t// (\\\"Value is: \\\" + mentry.getValue());\\n\\t\\t\\t\\t\\t\\t// );\\n\\t\\t\\t\\t\\t\\tString term = mentry.getValue().toString();\\n\\t\\t\\t\\t\\t\\t// //\\\"This is going to be put in doc3: \\\"+ (documentFound-1));\\n\\t\\t\\t\\t\\t\\tpostingsFileList.get(documentFound - 1).add(term);\\n\\t\\t\\t\\t\\t\\t// if ( !((mentry.getValue()).equals(\\\" \\\")) )\\n\\t\\t\\t\\t\\t\\tdocTermCount++;\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t// \\\"BEFORE its put in, this is what it looks like\\\" + hmap);\\n\\t\\t\\t\\t\\thmap2.putAll(hmap);\\n\\t\\t\\t\\t\\thmap.clear();\\n\\t\\t\\t\\t\\tarticleNew = 1;\\n\\n\\t\\t\\t\\t\\tdocTermCountList.add(docTermCount);\\n\\t\\t\\t\\t\\tdocTermCount = 0;\\n\\n\\t\\t\\t\\t\\twhile (iterator2.hasNext()) {\\n\\t\\t\\t\\t\\t\\tMap.Entry mentry2 = (Map.Entry) iterator2.next();\\n\\t\\t\\t\\t\\t\\t// (\\\"key is: \\\"+ mentry.getKey() + \\\" & Value is: \\\" + mentry.getValue());\\n\\t\\t\\t\\t\\t\\t// (\\\"Value2 is: \\\" + mentry2.getValue());\\n\\t\\t\\t\\t\\t\\t// );\\n\\t\\t\\t\\t\\t\\tString term = mentry2.getValue().toString();\\n\\t\\t\\t\\t\\t\\t// //\\\"This is going to be put in doc3: \\\"+ (documentFound-1));\\n\\t\\t\\t\\t\\t\\tpostingsFileListAllWords.get(documentFound - 1).add(term);\\n\\t\\t\\t\\t\\t\\t// if ( !((mentry.getValue()).equals(\\\" \\\")) )\\n\\t\\t\\t\\t\\t\\t// docTermCount++;\\n\\t\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\t\\tallValues.clear();\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\tdocumentFound = Integer.parseInt(arr[1]);\\n\\n\\t\\t\\t\\t\\t// \\\"MEANWHILE THESE ARE ALL VALUES\\\" + postingsFileListAllWords);\\n\\n\\t\\t\\t\\t}\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t}\\n\\t\\t\\t\\n\\t\\t\\t\\n\\t\\t\\t\\n\\t\\t\\t//System.out.println(\\\"Looking at final doc!\\\");\\n\\t\\t\\t//Final loop for last sets\\n\\t\\t\\tSet set = hmap.entrySet();\\n\\t\\t\\tIterator iterator = set.iterator();\\n\\n\\t\\t\\tSet setA = allValues.entrySet();\\n\\t\\t\\tIterator iteratorA = setA.iterator();\\n\\t\\t\\tpostingsFileList.put(documentFound - 1, new ArrayList<String>());\\n\\t\\t\\tpostingsFileListAllWords.put(documentFound - 1, new ArrayList<String>());\\n\\t\\t\\twhile (iterator.hasNext()) {\\n\\t\\t\\t\\tMap.Entry mentry = (Map.Entry) iterator.next();\\n\\t\\t\\t\\t// (\\\"key is: \\\"+ mentry.getKey() + \\\" & Value is: \\\" + mentry.getValue());\\n\\t\\t\\t\\t// (\\\"Value is: \\\" + mentry.getValue());\\n\\t\\t\\t\\t// //);\\n\\t\\t\\t\\t// if ( !((mentry.getValue()).equals(\\\" \\\")) )\\n\\t\\t\\t\\tString term2 = mentry.getValue().toString();\\n\\t\\t\\t\\tpostingsFileList.get(documentFound - 1).add(term2);\\n\\n\\t\\t\\t\\tdocTermCount++;\\n\\t\\t\\t}\\n\\t\\t\\t//System.out.println(\\\"Done looking at final doc!\\\");\\n\\t\\t\\t\\n\\t\\t\\t\\n\\t\\t\\t//System.out.println(\\\"Sorting time!\\\");\\n\\t\\t\\twhile (iteratorA.hasNext()) {\\n\\t\\t\\t\\tMap.Entry mentry2 = (Map.Entry) iteratorA.next();\\n\\t\\t\\t\\t// (\\\"key is: \\\"+ mentry.getKey() + \\\" & Value is: \\\" + mentry.getValue());\\n\\t\\t\\t\\t// (\\\"Value2 is: \\\" + mentry2.getValue());\\n\\t\\t\\t\\t// //);\\n\\t\\t\\t\\tString term = mentry2.getValue().toString();\\n\\t\\t\\t\\t// //\\\"This is going to be put in doc3: \\\"+ (documentFound-1));\\n\\t\\t\\t\\tpostingsFileListAllWords.get(documentFound - 1).add(term);\\n\\t\\t\\t\\t// if ( !((mentry.getValue()).equals(\\\" \\\")) )\\n\\t\\t\\t\\t// docTermCount++;\\n\\t\\t\\t}\\n\\n\\t\\t\\thmap2.putAll(hmap);\\n\\t\\t\\thmap.clear();\\n\\t\\t\\tdocTermCountList.add(docTermCount);\\n\\t\\t\\tdocTermCount = 0;\\n\\n\\n\\t\\t\\t\\n\\t\\t\\n\\t\\t\\t// END OF LOOKING AT ALL DOCS\\n\\t\\t\\t\\n\\t\\t\\t//System.out.println(\\\"Docs and titles: \\\"+docAndTitles);\\n\\t\\t\\t\\n\\t\\t\\t//System.out.println(\\\"All terms\\\" +allTerms);\\n\\t\\t\\tString[] sortedArray = allTerms.toArray(new String[0]);\\n\\t\\t\\tString[] sortedArrayUnique = uniqueTerms.toArray(new String[0]);\\n\\t\\t\\t//System.out.println(Arrays.toString(sortedArray));\\n\\t\\t\\t\\n\\t\\t\\tArrays.sort(sortedArray);\\n\\t\\t\\tArrays.sort(sortedArrayUnique);\\n\\t\\t\\t\\n\\t\\t\\t\\n\\t\\t\\t\\n\\t\\t\\t//Sortings \\n\\t\\t\\tSet set3 = hmap2.entrySet();\\n\\t\\t\\tIterator iterator3 = set3.iterator();\\n\\n\\t\\t\\t// Sorting the map\\n\\t\\t\\t//System.out.println(\\\"Before sorting \\\" +hmap2);\\t\\t\\t\\n\\t\\t\\tMap<Integer, String> map = sortByValues(hmap2);\\n\\t\\t\\t//System.out.println(\\\"after sorting \\\" +map);\\n\\t\\t\\t// //\\\"After Sorting:\\\");\\n\\t\\t\\tSet set2 = map.entrySet();\\n\\t\\t\\tIterator iterator2 = set2.iterator();\\n\\t\\t\\tint docCount = 1;\\n\\t\\t\\twhile (iterator2.hasNext()) {\\n\\t\\t\\t\\tMap.Entry me2 = (Map.Entry) iterator2.next();\\n\\t\\t\\t\\t// (me2.getKey() + \\\": \\\");\\n\\t\\t\\t\\t// //me2.getValue());\\n\\t\\t\\t}\\n\\t\\t\\t\\n\\t\\t\\t//System.out.println(\\\"Done sorting!\\\");\\n\\t\\t\\n\\t\\t\\t\\n\\t\\t\\t\\n\\t\\t\\t\\n\\t\\t\\t//System.out.println(\\\"Posting starts \\\");\\n\\t\\t\\t//\\\"THIS IS START OF DICTIONARTY\\\" \\n\\t\\t\\tBufferedWriter bw = null;\\n\\t\\t\\tFileWriter fw = null;\\n\\t\\t\\t\\n\\t\\t\\t\\n\\t\\t\\t//System.out.println(\\\"Start making an array thats big as every doc total \\\");\\n\\t\\t\\tfor (int z = 1; z < documentFound+1; z++)\\n\\t\\t\\t{\\n\\t\\t\\t\\ttermWeights.put(z, new ArrayList<Double>());\\n\\t\\t\\t}\\n\\t\\t\\t//System.out.println(\\\"Done making that large array Doc \\\");\\n\\t\\t\\t\\n\\t\\t\\t//System.out.println(\\\"Current Weights: \\\"+termWeights);\\n\\t\\t\\t\\n\\t\\t\\t//System.out.println(\\\"All terms\\\" +allTerms)\\n\\t\\t\\t//System.out.println(Arrays.toString(sortedArray));\\n\\t\\t\\t//System.out.println(Arrays.toString(sortedArrayUnique));\\n\\t\\t\\t//System.out.println(uniqueTerms);\\n\\t\\t\\t\\n\\t\\t\\t\\n\\t\\t\\t\\n\\t\\t\\t//\\tSystem.out.println(\\\"Posting starts \\\");\\n\\t\\t\\t// \\tPOSTING FILE STARTS \\n\\t\\t\\ttry {\\n\\t\\t\\t\\t// Posting File\\n\\t\\t\\t\\t//System.out.println(\\\"postingsFileListAllWords: \\\"+postingsFileListAllWords); //Contains every word including Dups, seperated per doc\\n\\t\\t\\t\\t//System.out.println(\\\"postingsFileList: \\\"+postingsFileList); \\t\\t //Contains unique words, dups are \\\" \\\", seperated per doc\\n\\t\\t\\t\\t//System.out.println(\\\"postingsFileListAllWords.size(): \\\" +postingsFileListAllWords.size()); //Total # of docs \\n\\t\\t\\t\\t//System.out.println(\\\"Array size: \\\"+sortedArrayUnique.length);\\n\\n\\t\\t\\t\\tfw = new FileWriter(POSTING);\\n\\t\\t\\t\\tbw = new BufferedWriter(fw);\\n\\t\\t\\t\\tString temp = \\\" \\\";\\n\\t\\t\\t\\tDouble termFreq = 0.0;\\n\\t\\t\\t\\t// //postingsFileListAllWords);\\n\\t\\t\\t\\tList<String> finalTermList = new ArrayList<String>();\\n\\t\\t\\t\\t\\n\\t\\t\\t\\t\\n\\t\\t\\t\\n\\t\\t\\t\\t\\t// //postingsFileList.get(i).size());\\n\\t\\t\\t\\t\\tfor (int j = 0; j < sortedArrayUnique.length; ++j)\\t\\t\\t\\t\\t // go thru each word, CURRENT TERM\\n\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\t//System.out.println(\\\"Term is: \\\" + sortedArrayUnique[j]);\\n\\t\\t\\t\\t\\t\\ttemp = sortedArrayUnique[j];\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\tif ((stopWordsSetting && stopWords.contains(temp))) \\n\\t\\t\\t\\t\\t\\t{\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\tcontinue;\\n\\t\\t\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\t\\t\\tif (!(finalTermList.contains(temp))) \\n\\t\\t\\t\\t\\t\\t{\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t//PART TO FIND DOCUMENT FREQ\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\tint docCountIDF = 0;\\n\\t\\t\\t\\t\\t\\t\\t//Start here for dictionary \\n\\t\\t\\t\\t\\t\\t\\tfor (int totalWords = 0; totalWords < sortedArray.length; totalWords++) \\t\\t\\n\\t\\t\\t\\t\\t\\t\\t{\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\tif (temp.compareTo(\\\" \\\") == 0 || (stopWordsSetting && stopWords.contains(temp))) \\n\\t\\t\\t\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t//EITHER BLANK OR STOPWORD \\n\\t\\t\\t\\t\\t\\t\\t\\t\\t//System.out.println(\\\"fOUND STOP WORD\\\");\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tcontinue;\\n\\t\\t\\t\\t\\t\\t\\t\\t}\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tString temp2 = sortedArray[totalWords];\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t//System.out.println(\\\"Compare: \\\"+temp+ \\\" with \\\" +temp2);\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tif (temp.compareTo(temp2) == 0) {\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t// (temp2+\\\" \\\");\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tdocCountIDF++;\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\t//System.out.println(\\\"Total Number: \\\" +docCountIDF);\\n\\t\\t\\t\\t\\t\\t\\t//System.out.println(\\\"documentFound: \\\" +documentFound);\\n\\t\\t\\t\\t\\t\\t\\t//System.out.println(\\\"So its \\\" + documentFound + \\\" dividied by \\\" +docCountIDF);\\n\\t\\t\\t\\t\\t\\t\\t//docCountIDF = 1;\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\tdouble idf = (Math.log10(((double)documentFound/(double)docCountIDF)));\\n\\t\\t\\t\\t\\t\\t\\t//System.out.println(\\\"Calculated IDF: \\\"+idf);\\n\\t\\t\\t\\t\\t\\t\\tif (idf < 0.0)\\n\\t\\t\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\t\\t\\tidf = 0.0;\\n\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\t//System.out.println(\\\"IDF is: \\\" +idf);\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t//System.out.println(\\\"Size of doc words: \\\" + postingsFileListAllWords.size());\\n\\t\\t\\t\\t\\t\\t\\tfor (int k = 0; k < postingsFileListAllWords.size(); k++) \\t\\t//Go thru each doc. Since only looking at 1 term, it does it once per doc\\n\\t\\t\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\t\\t\\t//System.out.println(\\\"Current Doc: \\\" +(k+1));\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\t\\ttermFreq = 1 + (Math.log10(Collections.frequency(postingsFileListAllWords.get(k), temp)));\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t//System.out.println(\\\"Freq is: \\\" +Collections.frequency(postingsFileListAllWords.get(k), temp));\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t//System.out.println(termFreq + \\\": \\\" + termFreq.isInfinite());\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tif (termFreq.isInfinite() || termFreq <= 0)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\ttermFreq = 0.0;\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t}\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t//System.out.println(\\\"termFreq :\\\" +termFreq); \\n\\t\\t\\t\\t\\t\\t\\t\\t\\t//System.out.println(\\\"idf: \\\" +idf);\\n\\t\\t\\t\\t\\t\\t\\t\\t\\ttermWeights.get(k+1).add( (idf*termFreq) );\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t//System.out.println(\\\"\\\");\\n\\t\\t\\t\\t\\t\\t\\tfinalTermList.add(temp);\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t}\\t\\n\\t\\t\\t\\t\\t\\t//System.out.println(\\\"Current Weights: \\\"+termWeights);\\n\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t//FINALCOUNTER\\n\\t\\t\\t\\t\\t\\t//System.out.println(\\\"Done looking at word: \\\" +j);\\n\\t\\t\\t\\t\\t\\t//System.out.println(\\\"\\\");\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t//System.out.println(\\\"Current Weights: \\\"+termWeights);\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\twhile (true)\\n\\t\\t\\t\\t {\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\tSystem.out.println(\\\"Enter a query: \\\");\\n\\t\\t\\t\\t\\t\\n\\t \\tScanner scanner = new Scanner(System.in);\\n\\t \\tString enterQuery = scanner.nextLine();\\n\\t \\t\\n\\t \\t\\n\\t\\t\\t\\t\\tList<Double> queryWeights = new ArrayList<Double>();\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t// Query turn\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\tenterQuery = enterQuery.toLowerCase();\\t\\t\\n\\t\\t\\t\\t\\tenterQuery = enterQuery.replaceAll(\\\"[-&^%'*$+|{}?!\\\\\\\\/<\\\\\\\\>=.,;_:()\\\\\\\\[\\\\\\\\]\\\\\\\"]\\\", \\\"\\\");\\n\\t\\t\\t\\t\\t//System.out.println(\\\"Query is: \\\" + enterQuery);\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\tif (enterQuery.equals(\\\"exit\\\"))\\n\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\tbreak;\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\tString[] queryArray = enterQuery.split(\\\" \\\");\\n\\t\\t\\t\\t\\tArrays.sort(queryArray);\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t//Find the query weights for each term in vocab\\n\\t\\t\\t\\t\\tfor (int j = 0; j < sortedArrayUnique.length; ++j)\\t\\t\\t\\t\\t // go thru each word, CURRENT TERM\\n\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\t//System.out.println(\\\"Term is: \\\" + sortedArrayUnique[j]);\\n\\t\\t\\t\\t\\t\\ttemp = sortedArrayUnique[j];\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\tif ((stopWordsSetting && stopWords.contains(temp))) \\n\\t\\t\\t\\t\\t\\t{\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\tcontinue;\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\tint docCountDF = 0;\\n\\t\\t\\t\\t\\t\\t//Start here for dictionary \\n\\t\\t\\t\\t\\t\\tfor (int totalWords = 0; totalWords < queryArray.length; totalWords++) \\t\\t\\n\\t\\t\\t\\t\\t\\t{\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\tif (temp.compareTo(\\\" \\\") == 0 || (stopWordsSetting && stopWords.contains(temp))) \\n\\t\\t\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\t\\t\\t//EITHER BLANK OR STOPWORD\\n\\t\\t\\t\\t\\t\\t\\t\\tcontinue;\\n\\t\\t\\t\\t\\t\\t\\t}\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\tString temp2 = queryArray[totalWords];\\n\\t\\t\\t\\t\\t\\t\\t\\t//System.out.println(\\\"Compare: \\\"+temp+ \\\" with \\\" +temp2);\\n\\t\\t\\t\\t\\t\\t\\t\\tif (temp.compareTo(temp2) == 0) {\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t// (temp2+\\\" \\\");\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tdocCountDF++;\\n\\t\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\tDouble queryWeight = 1 + (Math.log10(docCountDF));\\n\\t\\t\\t\\t\\t\\tif (queryWeight.isInfinite())\\n\\t\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\t\\tqueryWeight = 0.0;\\n\\t\\t\\t\\t\\t\\t}\\t\\t\\n\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\tqueryWeights.add(queryWeight);\\n\\t\\t\\t\\t\\t}\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t//System.out.println(\\\"Query WEights is: \\\"+queryWeights);\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t// Finding the norms for DOCS\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\tfor (int norms = 1; norms < documentFound+1; norms++)\\n\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\tdouble currentTotal = 0.0;\\n\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\tfor (int weightsPerDoc = 0; weightsPerDoc < termWeights.get(norms).size(); weightsPerDoc++)\\n\\t\\t\\t\\t\\t\\t{\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\tdouble square = Math.pow(termWeights.get(norms).get(weightsPerDoc), 2);\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t//System.out.println(\\\"Current square: \\\" + termWeights.get(norms).get(weightsPerDoc));\\n\\t\\t\\t\\t\\t\\t\\tcurrentTotal = currentTotal + square;\\n\\t\\t\\t\\t\\t\\t\\t//System.out.println(\\\"Current total: \\\" + currentTotal);\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t//System.out.println(\\\"About to square root this: \\\" +currentTotal);\\n\\t\\t\\t\\t\\t\\tdouble root = Math.sqrt(currentTotal);\\n\\t\\t\\t\\t\\t\\tdocNorms.put(norms, root);\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t//System.out.println(\\\"All of the docs norms: \\\"+docNorms);\\n\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t//Finding the norm for the query\\n\\t\\t\\t\\t\\tdouble currentTotal = 0.0;\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\tfor (int weightsPerDoc = 0; weightsPerDoc < queryWeights.size(); weightsPerDoc++)\\n\\t\\t\\t\\t\\t{\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\tdouble square = Math.pow(queryWeights.get(weightsPerDoc), 2);\\n\\t\\t\\t\\t\\t\\tcurrentTotal = currentTotal + square;\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\tdouble root = Math.sqrt(currentTotal);\\n\\t\\t\\t\\t\\tdouble queryNorm = root; \\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t//System.out.println(\\\"Query norm \\\" + queryNorm);\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t//Finding the cosine sim\\n\\t\\t\\t\\t\\t//System.out.println(\\\"Term Weights \\\" + termWeights);\\n\\t\\t\\t\\t\\tHashMap<Integer, Double> cosineScore = new HashMap<Integer, Double>();\\n\\t\\t\\t\\t\\tfor (int cosineSim = 1; cosineSim < documentFound+1; cosineSim++)\\n\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\tdouble total = 0.0;\\n\\t\\t\\t\\t\\t\\tfor (int docTerms = 0; docTerms < termWeights.get(cosineSim).size(); docTerms++)\\n\\t\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\tdouble docTermWeight = termWeights.get(cosineSim).get(docTerms);\\n\\t\\t\\t\\t\\t\\t\\tdouble queryTermWeight = queryWeights.get(docTerms);\\n\\t\\t\\t\\t\\t\\t\\t//System.out.println(\\\"queryTermWeight \\\" + queryTermWeight);\\n\\t\\t\\t\\t\\t\\t\\t//System.out.println(\\\"docTermWeight \\\" + docTermWeight);\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\ttotal = total + (docTermWeight*queryTermWeight);\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\tdouble cosineSimScore = 0.0;\\n\\t\\t\\t\\t\\t\\tif (!(total == 0.0 || (docNorms.get(cosineSim) * queryNorm) == 0))\\n\\t\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\t\\tcosineSimScore = total / (docNorms.get(cosineSim) * queryNorm);\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\telse\\n\\t\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\t\\tcosineSimScore = 0.0;\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\tcosineScore.put(cosineSim, cosineSimScore);\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\tcosineScore = sortByValues2(cosineScore);\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t//System.out.println(\\\"This is the cosineScores: \\\" +cosineScore);\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t//System.out.println(\\\"docAndTitles: \\\"+ docAndTitles);\\n\\t\\t\\t\\t\\tint topK = 0;\\n\\t\\t\\t\\t\\tint noValue = 0;\\n\\t\\t\\t\\t\\tfor (Integer name: cosineScore.keySet())\\n\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\tif (topK < 50)\\n\\t\\t\\t\\t\\t\\t{\\t\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t String key =name.toString();\\n\\t\\t\\t\\t //String value = cosineScore.get(name).toString(); \\n\\t\\t\\t\\t if (!(cosineScore.get(name) <= 0))\\n\\t\\t\\t\\t {\\n\\t\\t\\t\\t \\tSystem.out.println(\\\"Doc: \\\"+key);\\t\\t\\t\\t \\t\\t\\t\\t\\t \\t\\t\\t\\t\\t \\t\\n\\t\\t\\t\\t \\t\\n\\t\\t\\t\\t \\tStringBuilder builder = new StringBuilder();\\n\\t\\t\\t\\t \\tfor (StringBuilder value : docAndTitles.get(name)) {\\n\\t\\t\\t\\t \\t builder.append(value);\\n\\t\\t\\t\\t \\t}\\n\\t\\t\\t\\t \\tString text = builder.toString();\\t\\t\\t\\t \\t\\n\\t\\t\\t\\t \\t//System.out.println(\\\"Title:\\\\n\\\" +docAndTitles.get(name));\\n\\t\\t\\t\\t \\tSystem.out.println(\\\"Title: \\\" +text);\\n\\t\\t\\t\\t \\t\\n\\t\\t\\t\\t \\t\\n\\t\\t\\t\\t \\t\\n\\t\\t\\t\\t \\t\\n\\t\\t\\t\\t \\t\\n\\t\\t\\t\\t \\t//System.out.println(\\\"Authors:\\\\n\\\" +docAndAuthors.get(name));\\n\\t\\t\\t\\t \\t\\n\\t\\t\\t\\t \\tif (docAndAuthors.get(name) == null || docAndAuthors.get(name).toString().equals(\\\"\\\"))\\n\\t\\t\\t\\t \\t{\\n\\t\\t\\t\\t \\t\\tSystem.out.println(\\\"Authors: N\\\\\\\\A\\\\n\\\");\\n\\t\\t\\t\\t \\t}\\n\\t\\t\\t\\t \\telse \\n\\t\\t\\t\\t \\t{\\t\\t\\t\\t \\t\\t\\t\\t\\t\\t \\t\\n\\t\\t\\t\\t\\t \\tStringBuilder builder2 = new StringBuilder();\\n\\t\\t\\t\\t\\t \\tfor (StringBuilder value : docAndAuthors.get(name)) {\\n\\t\\t\\t\\t\\t \\t builder2.append(value);\\n\\t\\t\\t\\t\\t \\t}\\n\\t\\t\\t\\t\\t \\tString text2 = builder2.toString();\\t\\t\\t\\t \\t\\n\\t\\t\\t\\t\\t \\t\\n\\t\\t\\t\\t\\t \\tSystem.out.println(\\\"Authors found: \\\" +text2);\\n\\t\\t\\t\\t \\t}\\t\\n\\t\\t\\t\\t \\t\\n\\t\\t\\t\\t \\t\\n\\t\\t\\t\\t \\t/* ABSTRACT \\n\\t\\t\\t\\t \\tif (docAndAbstract.get(name) == null)\\n\\t\\t\\t\\t \\t{\\n\\t\\t\\t\\t \\t\\tSystem.out.println(\\\"Abstract: N\\\\\\\\A\\\\n\\\");\\n\\t\\t\\t\\t \\t}\\n\\t\\t\\t\\t \\telse \\n\\t\\t\\t\\t \\t{\\t\\t\\t\\t \\t\\t\\t\\t\\t\\t \\t\\n\\t\\t\\t\\t\\t \\tStringBuilder builder2 = new StringBuilder();\\n\\t\\t\\t\\t\\t \\tfor (StringBuilder value : docAndAbstract.get(name)) {\\n\\t\\t\\t\\t\\t \\t builder2.append(value);\\n\\t\\t\\t\\t\\t \\t}\\n\\t\\t\\t\\t\\t \\tString text2 = builder2.toString();\\t\\t\\t\\t \\t\\n\\t\\t\\t\\t\\t \\t\\n\\t\\t\\t\\t\\t \\tSystem.out.println(\\\"Abstract: \\\" +text2);\\n\\t\\t\\t\\t \\t}\\t\\n\\t\\t\\t\\t \\t*/\\n\\t\\t\\t\\t \\t\\n\\t\\t\\t\\t \\tSystem.out.println(\\\"\\\");\\n\\t\\t\\t\\t }\\n\\t\\t\\t\\t else {\\n\\t\\t\\t\\t \\tnoValue++;\\n\\t\\t\\t\\t }\\n\\t\\t\\t\\t topK++;\\n\\t\\t\\t\\t \\n\\t\\t\\t\\t\\t\\t}\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\tif (noValue == documentFound)\\n\\t\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\t\\tSystem.out.println(\\\"No documents contain query!\\\");\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t} \\n\\t\\t\\t\\t\\ttopK=0;\\n\\t\\t\\t\\t\\tnoValue = 0;\\n\\t\\t\\t\\t }\\n\\t\\t\\t\\t\\n\\t\\t\\t} finally {\\n\\t\\t\\t\\ttry {\\n\\t\\t\\t\\t\\tif (bw != null)\\n\\t\\t\\t\\t\\t\\tbw.close();\\n\\n\\t\\t\\t\\t\\tif (fw != null)\\n\\t\\t\\t\\t\\t\\tfw.close();\\n\\n\\t\\t\\t\\t} catch (IOException ex) {\\n\\n\\t\\t\\t\\t\\tex.printStackTrace();\\n\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t}\\n\\t\\t\\t\\n\\n\\t\\t} catch (IOException e) {\\n\\t\\t\\te.printStackTrace();\\n\\t\\t} finally {\\n\\t\\t\\ttry {\\n\\t\\t\\t\\tif (br != null)\\n\\t\\t\\t\\t\\tbr.close();\\n\\n\\t\\t\\t\\tif (fr != null)\\n\\t\\t\\t\\t\\tfr.close();\\n\\n\\t\\t\\t} catch (IOException ex) {\\n\\n\\t\\t\\t\\tex.printStackTrace();\\n\\n\\t\\t\\t}\\n\\n\\t\\t}\\n\\t\\t\\t\\n\\t\\t\\t\\n\\t\\t\\t\\n\\t\\t\\t\\n\\t\\t\\t\\n\\n\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\tint itemCount = uniqueTerms.size();\\n\\t\\t\\t//System.out.println(allValues);\\n\\t\\t\\tSystem.out.println(\\\"Total Terms BEFORE STEMING: \\\" +itemCount);\\n\\t\\t\\tSystem.out.println(\\\"Total Documents \\\" + documentFound);\\n\\t\\t\\t\\t\\t\\t\\n\\t\\t \\n\\t\\t\\t \\n\\t\\t\\t \\n\\t\\t\\t//END OF MAIN\\n\\t\\t}\",\n \"public static Map<Object, Object> processDocuments(\\n\\t\\t\\tString trainingSetFolderPath,boolean removeStopWords, boolean doSmoothing) {\\n\\t\\tint numTokens = 0; \\n\\n\\t\\t// Map to store the processed results.\\n\\t\\tMap<Object, Object> result = new HashMap<Object, Object>(); \\n\\n\\t\\t// Map to keep track of words and its frequency\\n\\n\\t\\tMap<String, Integer> tokenCntMap = new HashMap<String, Integer>(); \\n\\n\\t\\tFile trainingSetFolder = new File(trainingSetFolderPath);\\n\\t\\tFile[] documents = trainingSetFolder.listFiles();\\n\\t\\tfor (File doc : documents) {\\n\\t\\t\\ttry {\\n\\t\\t\\t\\t\\n\\t\\t\\t\\tBufferedReader bufferedReader = new BufferedReader(\\n\\t\\t\\t\\t\\t\\tnew FileReader(doc));\\n\\t\\t\\t\\tString line;\\n\\t\\t\\t\\twhile ((line = bufferedReader.readLine()) != null) {\\n\\t\\t\\t\\t\\tString[] tokens = line.split(\\\"\\\\\\\\s+\\\");\\n\\t\\t\\t\\t\\tnumTokens += tokens.length;\\n\\t\\t\\t\\t\\tif(removeStopWords == false){\\n\\t\\t\\t\\t\\t\\tfor (String token : tokens) {\\n\\t\\t\\t\\t\\t\\t\\ttoken = token.replaceAll(\\\"[^a-zA-Z]\\\", \\\"\\\");\\n\\t\\t\\t\\t\\t\\t\\ttoken = token.toLowerCase();\\n\\t\\t\\t\\t\\t\\t\\tif(!token.isEmpty()){\\n\\t\\t\\t\\t\\t\\t\\t\\tif (tokenCntMap.containsKey(token)) {\\n\\t\\t\\t\\t\\t\\t\\t\\t\\ttokenCntMap.put(token, tokenCntMap.get(token)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.intValue() + 1);\\n\\t\\t\\t\\t\\t\\t\\t\\t} else {\\n\\t\\t\\t\\t\\t\\t\\t\\t\\ttokenCntMap.put(token, 1);\\n\\t\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\telse{\\n\\t\\t\\t\\t\\t\\tfor (String token : tokens) {\\n\\t\\t\\t\\t\\t\\t\\ttoken = token.replaceAll(\\\"[^a-zA-Z]\\\", \\\"\\\");\\n\\t\\t\\t\\t\\t\\t\\ttoken = token.toLowerCase();\\n\\t\\t\\t\\t\\t\\t\\tif(!token.isEmpty() && !stopWords.contains(token)){\\n\\t\\t\\t\\t\\t\\t\\t\\tif (tokenCntMap.containsKey(token)) {\\n\\t\\t\\t\\t\\t\\t\\t\\t\\ttokenCntMap.put(token, tokenCntMap.get(token)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.intValue() + 1);\\n\\t\\t\\t\\t\\t\\t\\t\\t} else {\\n\\t\\t\\t\\t\\t\\t\\t\\t\\ttokenCntMap.put(token, 1);\\n\\t\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\tbufferedReader.close();\\n\\t\\t\\t} catch (Exception e) {\\n\\t\\t\\t\\te.printStackTrace();\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\tresult.put(\\\"NumTokens\\\", numTokens);\\n\\t\\tresult.put(\\\"NumDocuments\\\", documents.length);\\n\\t\\tresult.put(\\\"TokenCntMap\\\", tokenCntMap);\\n\\t\\treturn result;\\n\\n\\t}\",\n \"public void fileSaved(OpenDefinitionsDocument doc) { }\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.61611456","0.588707","0.5825966","0.5631039","0.56064516","0.5588778","0.5588274","0.5588257","0.5482481","0.54597014","0.53377825","0.53221774","0.5288427","0.5280946","0.5271845","0.526328","0.52533746","0.5247164","0.5237755","0.52139837","0.5147063","0.5143095","0.5139286","0.51007867","0.5065813","0.5048442","0.5041212","0.5037475","0.5032802","0.5023923","0.50215435","0.5006723","0.500668","0.49713916","0.49678943","0.49669752","0.49610227","0.49518725","0.49502826","0.49481288","0.49297896","0.49252555","0.49239096","0.4916581","0.49081257","0.49066624","0.4906592","0.49014223","0.48978886","0.48976412","0.48922306","0.48879686","0.48848957","0.48791248","0.48732713","0.48731962","0.48714042","0.48681888","0.48643652","0.4849195","0.4844192","0.48410356","0.48381498","0.48316827","0.4831313","0.48312816","0.48264974","0.48211884","0.481908","0.480654","0.48015672","0.48009118","0.47905332","0.47892487","0.47891122","0.47871354","0.47860894","0.47832796","0.47741818","0.4766521","0.47650522","0.47635826","0.4760822","0.47568697","0.47553137","0.47517624","0.47443023","0.47428954","0.47390237","0.47360379","0.4733088","0.47323674","0.47308633","0.47210333","0.4713181","0.47122255","0.47119135","0.4710721","0.47097856","0.47086433"],"string":"[\n \"0.61611456\",\n \"0.588707\",\n \"0.5825966\",\n \"0.5631039\",\n \"0.56064516\",\n \"0.5588778\",\n \"0.5588274\",\n \"0.5588257\",\n \"0.5482481\",\n \"0.54597014\",\n \"0.53377825\",\n \"0.53221774\",\n \"0.5288427\",\n \"0.5280946\",\n \"0.5271845\",\n \"0.526328\",\n \"0.52533746\",\n \"0.5247164\",\n \"0.5237755\",\n \"0.52139837\",\n \"0.5147063\",\n \"0.5143095\",\n \"0.5139286\",\n \"0.51007867\",\n \"0.5065813\",\n \"0.5048442\",\n \"0.5041212\",\n \"0.5037475\",\n \"0.5032802\",\n \"0.5023923\",\n \"0.50215435\",\n \"0.5006723\",\n \"0.500668\",\n \"0.49713916\",\n \"0.49678943\",\n \"0.49669752\",\n \"0.49610227\",\n \"0.49518725\",\n \"0.49502826\",\n \"0.49481288\",\n \"0.49297896\",\n \"0.49252555\",\n \"0.49239096\",\n \"0.4916581\",\n \"0.49081257\",\n \"0.49066624\",\n \"0.4906592\",\n \"0.49014223\",\n \"0.48978886\",\n \"0.48976412\",\n \"0.48922306\",\n \"0.48879686\",\n \"0.48848957\",\n \"0.48791248\",\n \"0.48732713\",\n \"0.48731962\",\n \"0.48714042\",\n \"0.48681888\",\n \"0.48643652\",\n \"0.4849195\",\n \"0.4844192\",\n \"0.48410356\",\n \"0.48381498\",\n \"0.48316827\",\n \"0.4831313\",\n \"0.48312816\",\n \"0.48264974\",\n \"0.48211884\",\n \"0.481908\",\n \"0.480654\",\n \"0.48015672\",\n \"0.48009118\",\n \"0.47905332\",\n \"0.47892487\",\n \"0.47891122\",\n \"0.47871354\",\n \"0.47860894\",\n \"0.47832796\",\n \"0.47741818\",\n \"0.4766521\",\n \"0.47650522\",\n \"0.47635826\",\n \"0.4760822\",\n \"0.47568697\",\n \"0.47553137\",\n \"0.47517624\",\n \"0.47443023\",\n \"0.47428954\",\n \"0.47390237\",\n \"0.47360379\",\n \"0.4733088\",\n \"0.47323674\",\n \"0.47308633\",\n \"0.47210333\",\n \"0.4713181\",\n \"0.47122255\",\n \"0.47119135\",\n \"0.4710721\",\n \"0.47097856\",\n \"0.47086433\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.55061305"},"document_rank":{"kind":"string","value":"8"}}},{"rowIdx":13884,"cells":{"query":{"kind":"string","value":"[NEW] Saves object \"o\" as a JSON file called fileName"},"document":{"kind":"string","value":"public void saveJSON(String fileName, Object o){\n // System.err.println(\"accessing disk\");\n Gson gson = new Gson();\n try(FileWriter writer = new FileWriter(fileName)){\n gson.toJson(o, writer);\n //System.err.println(\"\\n Token stored\");\n }catch (IOException e) {\n e.printStackTrace();\n }\n }"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["public static void writeJsonObjectFile(JsonEntity objectToWrite, String filePath) \n\t{\n\t\tGson gsonParser = new Gson();\n\t\t\n\t\ttry \n\t\t{\n\t\t\tFiles.write(gsonParser.toJson(objectToWrite).getBytes(), new File(filePath));\n\t\t}\n\t\tcatch (IOException e) \n\t\t{\n\t\t\tSystem.err.println(\"Can't write to the json file\" + e.getMessage());\n\t\t}\n\t}","public static void writeToJsonGzFile(Object jsonObj, Path filePath) throws JsonGenerationException, JsonMappingException, IOException {\n\n GZIPOutputStream gzipOS = new GZIPOutputStream(Files.newOutputStream(filePath));\n WritableByteChannel out = Channels.newChannel(gzipOS);\n\n ObjectMapper mapper = new ObjectMapper();\n byte[] jsonOut = mapper.writeValueAsBytes(jsonObj);\n out.write(ByteBuffer.wrap(jsonOut));\n out.close();\n\n }","public void exportAsJsonFile(String path) throws IOException {\n Gson gson = new GsonBuilder().setPrettyPrinting().create();\n String json = gson.toJson(this);\n\n FileWriter writer = new FileWriter(path);\n writer.write(json);\n writer.close();\n }","private void writeToFile() {\n try {\n FileOutputStream fos = new FileOutputStream(f);\n String toWrite = myJSON.toString(4);\n byte[] b = toWrite.getBytes();\n fos.write(b);\n fos.close();\n } catch (Exception e) {\n e.printStackTrace();\n }\n }","public static void createJsonFile(JsonObject json) throws IOException {\n\r\n FileWriter file = new FileWriter(\"outputfile\", false);\r\n try {\r\n file.write(Jsoner.prettyPrint(json.toJson(),2));\r\n file.flush();\r\n } catch (IOException e) {\r\n out.println(\"Error \" + e);\r\n }\r\n }","String saveToFile(Object data, String fileName, FileFormat fileFormat) throws IOException;","@Override\n\tpublic void save(Object o, String file) {\n\t\t\n\t}","public void guardarEnJSON () {\n Gson gson = new GsonBuilder().setPrettyPrinting().create();\n String s = gson.toJson(this);\n try {\n FileWriter fw = new FileWriter(\"files/graph.json\");\n fw.write(s);\n fw.close();\n } catch (IOException e) {\n e.printStackTrace();\n }\n }","public void saveGame(String fileName){\n Gson gson = new Gson();\n String userJson = gson.toJson(player);\n\n try(Writer w = new BufferedWriter(new OutputStreamWriter( new FileOutputStream(fileName), \"UTF-8\"))) {\n w.write(userJson);\n } catch (FileNotFoundException e) {\n e.printStackTrace();\n } catch (IOException e) {\n e.printStackTrace();\n }\n }","private void writeToFile(String filename, Object object) {\n try {\n FileOutputStream fileOutputStream = openFileOutput(filename, MODE_PRIVATE);\n ObjectOutputStream objectOutputStream = new ObjectOutputStream(fileOutputStream);\n objectOutputStream.writeObject(object);\n objectOutputStream.close();\n } catch (IOException e) {\n e.printStackTrace();\n }\n }","private static void exportJsonFile(File configFile) {\n Gson gson = new Gson();\n \n // Java object to JSON, and assign to a String\n String jsonInString = gson.toJson(GameConfig.getInstance());\n \n try {\n FileWriter writer = new FileWriter(configFile);\n \n writer.append(jsonInString);\n writer.flush();\n writer.close();\n } catch (IOException e) {\n LogUtils.error(\"exportJsonFile => \",e);\n }\n }","private void writeObject(String filePath, Object obj) throws IOException {\n OutputStream file = new FileOutputStream(filePath);\n OutputStream buffer = new BufferedOutputStream(file);\n ObjectOutput output = new ObjectOutputStream(buffer);\n output.writeObject(obj);\n output.close();\n }","public static void writeListToJsonFile(Object jsonObj, Path filePath) throws JsonGenerationException, JsonMappingException, IOException {\n\n final OutputStream out = new ByteArrayOutputStream();\n ObjectMapper mapper = new ObjectMapper();\n mapper.writeValue(out, jsonObj);\n\n final byte[] data = ((ByteArrayOutputStream) out).toByteArray();\n\n Files.write(filePath, data);\n\n }","private void saveInFile() {\n try {\n FileOutputStream fos = openFileOutput(FILENAME,\n Context.MODE_PRIVATE);//goes stream based on filename\n BufferedWriter out = new BufferedWriter(new OutputStreamWriter(fos)); //create buffer writer\n Gson gson = new Gson();\n gson.toJson(countbookList, out);//convert java object to json string & save in output\n out.flush();\n fos.close();\n } catch (FileNotFoundException e) {\n throw new RuntimeException();\n } catch (IOException e) {\n throw new RuntimeException();\n }\n }","private void saveInFile() {\n try {\n FileOutputStream fos = openFileOutput(FILENAME, Context.MODE_PRIVATE);\n\n BufferedWriter out = new BufferedWriter(new OutputStreamWriter(fos));\n\n Gson gson = new Gson();\n Log.d(\"PersonList\", personList.toString());\n gson.toJson(personList, out);\n out.flush();\n\n fos.close();\n\n } catch (FileNotFoundException e){\n throw new RuntimeException();\n } catch (IOException e){\n e.printStackTrace();\n }\n\n }","public static void saveObj(Object obj, File file)\n {\n try(ObjectOutputStream oos = new ObjectOutputStream(new FileOutputStream(file)))\n {\n oos.writeObject(obj);\n }\n \n catch(IOException e)\n {\n JOptionPane.showMessageDialog(null, \"[Error] Failed to save file: \" + e.getMessage());\n }\n }","@SuppressWarnings(\"unused\")\n public void SaveJsonCollectionsToFiles(){\n try {\n String formattedDate = FileNameUtils.DATE_FORMAT.format(new Date());\n ObjectWriter writer = mapper.writer(new DefaultPrettyPrinter());\n writer.writeValue(new File(FileNameUtils.GetValuesFileName(formattedDate)), jsonObjects);\n }\n catch(IOException exp){\n System.err.println(\"Error while creating JSON file. Reason: \" + exp.getMessage());\n }\n }","public static void saveJSON(List<JSONObject> objects, String outputFile) {\n try (FileWriter file = new FileWriter(outputFile)) {\n for (JSONObject obj: objects)\n file.write(obj.toString() + '\\n');\n } catch (IOException e) {\n e.printStackTrace();\n }\n }","public static boolean saveToFile(Object o, String fileName) {\n FileOutputStream fos = null;\n BufferedOutputStream bos = null;\n ObjectOutputStream oos = null;\n File objectFile = null;\n\n objectFile = new File(fileName);\n try {\n fos = new FileOutputStream(objectFile);\n bos = new BufferedOutputStream(fos);\n oos = new ObjectOutputStream(bos);\n oos.writeObject(o);\n oos.close();\n bos.close();\n fos.close();\n } catch (FileNotFoundException e) {\n return false;\n } catch (IOException e) {\n return false;\n }\n return true;\n }","private void saveInFile() {\n\t\tthis.deleteFile();\n\t\tfor (CounterModel obj : counterListModel.getCounterList()) {\n\t\t\ttry {\n\t\t\t\tGson gson = new Gson();\n\t\t\t\tif (obj.getCounterName().equals(counterModel.getCounterName())) {\n\t\t\t\t\tobj = counterModel;\n\t\t\t\t}\n\t\t\t\tString json = gson.toJson(obj) +'\\n';\n\t\t\t\tFileOutputStream fos = openFileOutput(FILENAME,\n\t\t\t\t\t\tContext.MODE_APPEND);\n\t\t\t\tfos.write(json.getBytes());\n\t\t\t\tfos.close();\n\t\t\t} catch (FileNotFoundException e) {\n\t\t\t\t// TODO Auto-generated catch block\n\t\t\t\te.printStackTrace();\n\t\t\t} catch (IOException e) {\n\t\t\t\t// TODO Auto-generated catch block\n\t\t\t\te.printStackTrace();\n\t\t\t}\n\t\t}\n\t}","public <T> String SerializeJson(T obj, String pathToRoot) {\n this.lastPath = pathToRoot + obj.getClass().getSimpleName().toLowerCase() + \"_object-\" + Math.abs(new Random().nextLong()) + \".json\";\n File file = new File(this.lastPath);\n ObjectMapper mapper = new ObjectMapper();\n\n mapper.configure(DeserializationFeature.FAIL_ON_UNKNOWN_PROPERTIES, false);\n mapper.registerModule(new JavaTimeModule());\n mapper.disable(SerializationFeature.WRITE_DATES_AS_TIMESTAMPS);\n\n try {\n file.createNewFile();\n mapper.writeValue(file, obj);\n System.out.println(mapper.writerWithDefaultPrettyPrinter().writeValueAsString(obj));\n return mapper.writeValueAsString(obj);\n } catch (IOException e) {\n e.printStackTrace();\n }\n return \"\";\n }","public static void save(Object o, String filename) {\n\t\ttry\n\t {\n\t\t\tfilename = \"save\" + File.separator + filename + \".hsc\";\n\t\t\tcreateSaveDirIfNotExisting();\n\t\t\tprepareSaveFile(filename);\n\t FileOutputStream fileOut = new FileOutputStream(filename);\n\t ObjectOutputStream out = new ObjectOutputStream(fileOut);\n\t out.writeObject(o.getClass().cast(o));\n\t out.close();\n\t fileOut.close();\n\t //System.out.println(\"Serialized object is saved in \" + filename);\n\t }catch(NotSerializableException e) {\n\t \t System.out.println(\"Object to be saved does not implement java.io.Serializable!\");\n\t \t e.printStackTrace();\n\t }\n\t\tcatch(IOException i)\n\t {\n\t i.printStackTrace();\n\t } \n\t}","public void writeToFile(Object obj) throws FileNotFoundException, IOException\n {\n ObjectOutputStream writeToFile = null;\n\n try\n {\n FileOutputStream fileOutStream = new FileOutputStream(FILE_NAME);\n writeToFile = new ObjectOutputStream(fileOutStream);\n\n writeToFile.writeObject(obj);\n }\n finally\n {\n if (writeToFile != null)\n {\n try\n {\n writeToFile.close();\n }\n catch (IOException e)\n {\n displayErrorMessage(\"IO File error on\", FILE_NAME);\n }\n }\n }\n }","private static void jsonWriter(JSONObject bookList) throws Exception{\r\n FileWriter file = new FileWriter(\"libreria.json\");\r\n file.write(bookList.toJSONString());\r\n file.flush();\r\n }","public void escribirFichero(String textoenjson){\n {\n OutputStreamWriter escritor=null;\n try\n {\n escritor=new OutputStreamWriter(openFileOutput(\"datos.json\", Context.MODE_PRIVATE));\n escritor.write(textoenjson);\n }\n catch (Exception ex)\n {\n Log.e(\"ivan\", \"Error al escribir fichero a memoria interna\");\n }\n finally\n {\n try {\n if(escritor!=null)\n escritor.close();\n } catch (IOException e) {\n e.printStackTrace();\n }\n }\n }\n\n\n }","public static void writeObjectToDisk(Object obj, String name) throws IOException {\r\n\t\t// Create file output stream\r\n\t\tFileOutputStream fileOutStr = new FileOutputStream(name);\r\n\t\t// Create object output stream and write object\r\n\t\tObjectOutputStream objOutStr = new ObjectOutputStream(fileOutStr);\r\n\t\tobjOutStr.writeObject(obj);\r\n\t\t// Close all streams\r\n\t\tobjOutStr.close();\r\n\t\tfileOutStr.close();\r\n\t\tSystem.out.printf(\"Serialized data is saved in a file - \" + name); // Printing message and file name which is\r\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t// saved\r\n\t}","public void writeToFile (String json) {\n // reset fos to null for checks\n FileOutputStream fos = null;\n try {\n String FILE_NAME = \"ExportedLearningCards.json\";\n fos = openFileOutput(FILE_NAME, MODE_PRIVATE);\n fos.write(json.getBytes());\n Toast.makeText(this, \"Saved to \" + getFilesDir() + \"/\" + FILE_NAME,\n Toast.LENGTH_LONG).show();\n } catch (FileNotFoundException e) {\n e.printStackTrace();\n } catch (IOException e) {\n e.printStackTrace();\n } finally {\n if (fos != null) {\n try {\n fos.close();\n } catch (IOException e) {\n e.printStackTrace();\n }\n }\n }\n }","public static void serialize(Object obj, String fileName) throws IOException {\n\t\tFileOutputStream fos = new FileOutputStream(fileName);\n\t\tObjectOutputStream oos = new ObjectOutputStream(fos);\n\t\toos.writeObject(obj);\n\n\t\tfos.close();\n\t}","public static void save(final String filename, final Serializable object)\r\n throws IOException {\r\n FileOutputStream fos = null;\r\n ObjectOutputStream out = null;\r\n\r\n fos = new FileOutputStream(filename);\r\n out = new ObjectOutputStream(fos);\r\n out.writeObject(object);\r\n out.close();\r\n }","public void exportJSON()\n {\n Gson JSONConverter = new Gson();\n FileWriter writer;\n\n try\n {\n // wipe the file\n PrintWriter write = new PrintWriter(new File(fp));\n write.print(\"\");\n write.close();\n\n // Initialize FileWriter to write Strings into JSON file.\n writer = new FileWriter(fp + \"/queue.json\");\n\n Iterator<ComparableCalendar> iter = this.queue.iterator();\n // Loop through the PQ.\n while(iter.hasNext())\n {\n ComparableCalendar nextObject = iter.next();\n // Convert an issue object into a JSON-formatted representation of it, as a String.\n String representationJSON = JSONConverter.toJson(nextObject);\n\n // Write that String to the file.\n writer.write(representationJSON + \"\\n\");\n }\n // Close the FileWriter to conserve system resources.\n writer.close();\n\n }\n catch (Exception e)\n {\n // Print any error messages that results to the console.\n e.printStackTrace();\n }\n\n }","public JSONObject save();","void saveToFile() {\n\t\ttry {\n\t\t\tFile directory = GameApplication.getInstance().getExternalFilesDir(Environment.DIRECTORY_DOCUMENTS);\n\t\t\tFile target = new File(directory, FILE_NAME);\n\t\t\tif (!target.exists()) {\n\t\t\t\ttarget.createNewFile();\n\t\t\t}\n\t\t\tJsonWriter writer = new JsonWriter(new FileWriter(target));\n\t\t\twriter.setIndent(\" \");\n\t\t\twriter.beginArray();\n\t\t\tfor (Scoreboard scoreboard : scoreboards.values()) {\n\t\t\t\twriteScoreboard(writer, scoreboard);\n\t\t\t}\n\t\t\twriter.endArray();\n\t\t\twriter.flush();\n\t\t\twriter.close();\n\t\t} catch (IOException e) {\n\t\t\te.printStackTrace();\n\t\t}\n\t}","public static void writeJsonToFile(List<Object> objLst, File file) throws Exception {\n writeJsonToFile(objLst, file, false);\n }","public void saveToFile(Map<String, T> data) throws IOException{\n\t\tOutputStream file = new FileOutputStream(filePath);\n OutputStream buffer = new BufferedOutputStream(file);\n ObjectOutput output = new ObjectOutputStream(buffer);\n\n // serialize the Map\n output.writeObject(data);\n output.close();\n\t}","public static void storeObject(Object object, String filename) throws IOException\n {\n storeObject(object, new File(filename));\n }","private void saveInFile() {\n try {\n FileOutputStream fOut = openFileOutput(FILENAME,\n Context.MODE_PRIVATE);\n\n OutputStreamWriter writer = new OutputStreamWriter(fOut);\n Gson gson = new Gson();\n gson.toJson(counters, writer);\n writer.flush();\n\n fOut.close();\n\n } catch (FileNotFoundException e) {\n throw new RuntimeException();\n } catch (IOException e) {\n throw new RuntimeException();\n }\n }","private void serializeObject(String filename, Object content)\n throws IOException\n {\n synchronized(filename)\n {\n FileOutputStream fileOut = new FileOutputStream(filename);\n ObjectOutputStream out = new ObjectOutputStream(fileOut);\n out.writeObject(content);\n out.close();\n fileOut.close();\n }\n }","public static boolean writeToJson(Quote[] quotes, String filename) throws IOException {\n Gson write = new Gson();\n OutputStream outStream = new FileOutputStream(filename);\n BufferedWriter buffer = new BufferedWriter(new OutputStreamWriter(outStream));\n write.toJson(quotes, buffer);\n buffer.close();\n return true;\n }","public static void writeJSONToFile(File file, JSONObject jsonObject) throws IOException {\n writeToFile(file, JSONObject.toJSONString(jsonObject));\n }","public static void writeObjectToFile(Serializable object, String fileName) throws IOException {\n try (FileOutputStream fos = new FileOutputStream(fileName);\n ObjectOutputStream oos = new ObjectOutputStream(fos);) {\n oos.writeObject(object);\n }\n }","public void saveData() {\n try {\n JsonWriter jw = new JsonWriter(openFileOutput(DATA_FILE, Context.MODE_PRIVATE));\n jw.write(user);\n jw.close();\n } catch(Exception e) {\n Log.i(\"Exception :\", e.toString());\n }\n }","public static void saveObjToFile(Object obj, String filePath) throws IOException {\n // create the enclosing folders if it doesn't exist\n createDir(filePath);\n\n FileOutputStream file = new FileOutputStream(filePath);\n ObjectOutputStream out = new ObjectOutputStream(file);\n out.writeObject(obj);\n out.close();\n }","public void saveTodo() {\r\n File file = new File(\"C:\\\\Users\\\\Dalia\\\\Desktop\\\\CPSC 210\\\\Project\\\\project_b2h3b\\\\data\");\r\n JFileChooser chooser = new JFileChooser();\r\n chooser.setDialogTitle(\"Specify a file to save\");\r\n chooser.setCurrentDirectory(file);\r\n int userSelection = chooser.showSaveDialog(null);\r\n if (userSelection == JFileChooser.APPROVE_OPTION) {\r\n File f = chooser.getSelectedFile();\r\n System.out.println(\"Save as file: \" + f.getAbsolutePath());\r\n String tempFileName = f.getAbsolutePath();\r\n writer = new MyTodoJsonWriter(tempFileName);\r\n try {\r\n writer.open();\r\n writer.write(myTodo);\r\n fileName = tempFileName;\r\n playSound(\"c1.wav\");\r\n } catch (IOException ioException) {\r\n JOptionPane.showMessageDialog(null, \"Cannot save todolist!\");\r\n } finally {\r\n writer.close();\r\n JOptionPane.showMessageDialog(null, \"Save successful!\");\r\n }\r\n todoListGui();\r\n }\r\n }","private static boolean saveMOTD(JSONObject motdObj) {\n File JSONFile = new File(plugin.getDataFolder() + \"/motd.json\");\n\n try ( //open our writer and write the player file\n PrintWriter writer = new PrintWriter(JSONFile)) {\n //System.out.println(obj);\n writer.print(motdObj.toString(4));\n writer.close();\n Logger.getLogger(MOTDHandler.class.getName()).log(Level.INFO, \"Successfully updated motd.json\");\n return true;\n } catch (FileNotFoundException ex) {\n\n Logger.getLogger(MOTDHandler.class.getName()).log(Level.SEVERE, null, ex);\n return false;\n }\n }","void generateJSON(JSONObject object, String name);","public void writeObject(Object obj, String path)throws IOException{\n FileOutputStream fos = new FileOutputStream(path);\n ObjectOutputStream oos = new ObjectOutputStream(fos);\n\n oos.writeObject(obj);\n oos.close();\n }","public void saveArchive() throws FileNotFoundException {\n jsonWriter.open();\n Archive archive = new Archive(cameraCollection, filmCollection);\n jsonWriter.write(archive);\n jsonWriter.close();\n }","public void WriteJSON(Costumer costumer) {\n\n JSONObject costumerDetails = new JSONObject();\n JSONObject documentDetails = new JSONObject();\n\n documentDetails.put(\"type\", costumer.getDocument().getType());\n documentDetails.put(\"nDocument\", costumer.getDocument().getnDocument());\n documentDetails.put(\"ExpiryDate\", costumer.getDocument().getDateExpiry());\n\n System.out.println(\"dco \" + documentDetails);\n\n costumerDetails.put(\"name\", costumer.getName());\n costumerDetails.put(\"surname\", costumer.getSurname());\n costumerDetails.put(\"dateOfBirth\", costumer.getDateOfBirth());\n costumerDetails.put(\"cityOfBirth\", costumer.getCityOfBirth());\n costumerDetails.put(\"cityOfResidence\", costumer.getCityOfResidence());\n costumerDetails.put(\"address\", costumer.getAddress());\n costumerDetails.put(\"telephone\", costumer.getTelephone());\n costumerDetails.put(\"fiscalCode\", costumer.getFiscalCode());\n costumerDetails.put(\"province\", costumer.getProvince());\n costumerDetails.put(\"document\", documentDetails);\n\n costumerObject.put(\"costumer\", costumerDetails);\n\n //Add costumer to list\n costumerList.add(costumerObject);\n\n //add costumer ot the object list\n this.cList.add(costumer);\n\n //Write JSON file\n try (FileWriter file = new FileWriter(\"costumers.json\")) {\n\n file.write(costumerList.toJSONString());\n file.flush();\n\n } catch (IOException e) {\n e.printStackTrace();\n }\n\n }","public static void saveConfig(Object config, File file) throws IOException {\n file.createNewFile();\n String json = gson.toJson(parser.parse(gson.toJson(config)));\n try (PrintWriter out = new PrintWriter(file)) {\n out.println(json);\n }\n }","public static void writeObject(Activity activity, Object object, String filename) {\n FileOutputStream fos = null;\n ObjectOutputStream oos = null;\n try {\n fos = activity.openFileOutput(filename, Context.MODE_PRIVATE);\n oos = new ObjectOutputStream(fos);\n oos.writeObject(object);\n } catch (IOException e) {\n e.printStackTrace();\n }\n finally {\n closeOutputStream(fos);\n closeOutputStream(oos);\n }\n }","public void createJSON(String filePath, JSONObject jsonObject) throws ExistException, UnimplementedException, UnderlyingStorageException {\n \t\tSystem.err.println(jsonObject);\n \t\tjsonObject=cspace264Hack_munge(jsonObject,filePath);\n \t\tautocreateJSON(\"\",jsonObject);\n \t\t// XXX End of here's what we do because of CSPACE-264\t\t\n \t\t// Here's what we should do ->\n \t\t// throw new UnimplementedException(\"Cannot create collectionobject at known path, use autocreateJSON\");\n \t}","public static File writeObjectToTempFile(Serializable o, String filename)\n/* */ throws IOException\n/* */ {\n/* 76 */ File file = File.createTempFile(filename, \".tmp\");\n/* 77 */ file.deleteOnExit();\n/* 78 */ ObjectOutputStream oos = new ObjectOutputStream(new BufferedOutputStream(new GZIPOutputStream(new FileOutputStream(file))));\n/* 79 */ oos.writeObject(o);\n/* 80 */ oos.close();\n/* 81 */ return file;\n/* */ }","@Override\n\tpublic void saveData(Object objectsToSave, String path) {\n\t\t\n\t\ttry {\n\t\t\tString objects = (String) objectsToSave;\n\t\t\tFileOutputStream fileOutputStream = new FileOutputStream(path);\n\t\t\tfileOutputStream.write(objects.getBytes());\n\t\t\tfileOutputStream.close();\n\t\t} catch (FileNotFoundException e) {\n\t\t\te.printStackTrace();\n\t\t} catch (IOException e){\n\t\t\te.printStackTrace();\n\t\t}\n\t\t\n\t}","public void save(){\n Player temp = Arena.CUR_PLAYER;\n try{\n FileOutputStream outputFile = new FileOutputStream(\"./data.sec\");\n ObjectOutputStream objectOut = new ObjectOutputStream(outputFile);\n objectOut.writeObject(temp);\n objectOut.close();\n outputFile.close();\n }\n catch(FileNotFoundException e){\n System.out.print(\"Cannot create a file at that location\");\n }\n catch(SecurityException e){\n System.out.print(\"Permission Denied!\");\n }\n catch(IOException e){\n System.out.println(\"Error 203\");\n } \n }","private File getOpenApiFile(String oasDefinition) throws IOException {\n File oasTempFile = File.createTempFile(\"oasTempFile\", \".json\");\n try (BufferedWriter bw = new BufferedWriter(new OutputStreamWriter(new FileOutputStream(oasTempFile),\n StandardCharsets.UTF_8))) {\n bw.write(oasDefinition);\n }\n return oasTempFile;\n }","public static void appendJsonToFile(List<Object> objLst, File file) throws Exception {\n writeJsonToFile(objLst, file, true);\n }","private void setFile(Serializable object, String path) throws Exception {\t\t\n\t\t\n FileOutputStream fileOut = new FileOutputStream(path);\n ObjectOutputStream objectOut = new ObjectOutputStream(fileOut);\n objectOut.writeObject(object);\n objectOut.close(); \n\t\t\n\t}","public static void jsonWrite() \n\t{\n JSONArray arrJson = new JSONArray(); \n FileWriter writeFile = null;\n Iterator<Taxi_Model> taxiIterator = L.iterator();\n\n while(taxiIterator.hasNext()) \n {\n \tJSONObject jsonObject = new JSONObject();\n \tTaxi_Model aux = new Taxi_Model();\n \taux = taxiIterator.next();\n \tJSONArray array = new JSONArray();\n \tarray.add(aux.getLocalizacao()[0]);\n \tarray.add(aux.getLocalizacao()[1]);\n \t\n \t//Armazena dados em um Objeto JSON\n \tjsonObject.put(\"Usuario\", aux.getUsuario());\n jsonObject.put(\"Nome\", aux.getNome());\n jsonObject.put(\"Senha\", aux.getSenha());\n jsonObject.put(\"CPF\", aux.getCpf());\n jsonObject.put(\"Cor do Carro\", aux.getCorCarro());\n jsonObject.put(\"Modelo do Carro\", aux.getModeloCarro());\n jsonObject.put(\"Placa do Carro\", aux.getPlaca());\n jsonObject.put(\"Localizacao\", array);\n jsonObject.put(\"Pontuacao\", aux.getPontuacao());\n jsonObject.put(\"Corridas\", aux.getTotalCorridas());\n jsonObject.put(\"Tempo total\", aux.getTempoTotal());\n jsonObject.put(\"Tempo programado\", aux.getTempoProgramada());\n arrJson.add(jsonObject);\n }\n \n try\n {\n writeFile = new FileWriter(\"taxis.json\");\n //Escreve no arquivo conteudo do Objeto JSON\n writeFile.write(arrJson.toJSONString());\n writeFile.close();\n }\n catch(IOException e)\n {\n e.printStackTrace();\n }\n\t}","private void saveInFile(final String fileName, ArrayList<Habit> habitArray) {\r\n try {\r\n FileOutputStream fos = openFileOutput(fileName, 0);\r\n BufferedWriter out = new BufferedWriter(new OutputStreamWriter(fos));\r\n Gson gson = new Gson();\r\n gson.toJson(habitArray, out);\r\n out.flush();\r\n\r\n fos.close();\r\n } catch (FileNotFoundException e) {\r\n // TODO Auto-generated catch block\r\n throw new RuntimeException();\r\n } catch (IOException e) {\r\n // TODO Auto-generated catch block\r\n throw new RuntimeException();\r\n }\r\n }","public static void writeuser(String modelJson, Context context){\n\t\ttry {\n\t\t\t\n\t\t\tOutputStream outputStream = context.getApplicationContext()\n\t\t\t\t\t.openFileOutput(filename, Context.MODE_PRIVATE);\n\t\t\tOutputStreamWriter fileWriter = new OutputStreamWriter(outputStream);\n\t\t\tfileWriter.write(modelJson + \"\\r\\n\");\n\t\t\tfileWriter.close();\n\t\t\t\n\t\t} catch (Exception e) {\n\t\t\te.printStackTrace();\n\t\t}\n\t}","private void serialize(String file_name) {\n\t\t//Saving of object in a file\n\t\ttry {\n\t\t\tFileOutputStream file = new FileOutputStream(file_name);\n\t\t\tObjectOutputStream out = new ObjectOutputStream(file);\n\t\t\t// Method for serialization of object\n\t\t\tout.writeObject(this.GA);\n\n\t\t\tout.close();\n\t\t\tfile.close();\n\n\t\t\tSystem.out.println(\"Object has benn serialized\");\n\t\t} catch (IOException e) {\n\t\t\tSystem.err.println(\"IOException is caught,Object didnt save.\");\n\t\t}\n\t}","public void save(String json, Map<String,Object> properties);","private void saveWorld() {\n try {\n jsonWriter.open();\n jsonWriter.write(world);\n jsonWriter.close();\n System.out.println(\"Saved world to \" + JSON_STORE);\n } catch (FileNotFoundException e) {\n System.out.println(\"Unable to write to file: \" + JSON_STORE);\n }\n }","public void logEmissions(JSONObject object, Context context) {\n try {\n JSONArray jsonArray = readEmissionsLog(context);\n if (jsonArray == null) {\n jsonArray = new JSONArray();\n }\n FileOutputStream fos = context.openFileOutput(profileManager.getActiveUserName() + \"Nutrition.json\", Context.MODE_PRIVATE);\n JSONObject jsonObject = new JSONObject();\n jsonObject.put(\"Nutrition data\", object);\n jsonArray.put(jsonObject);\n fos.write(jsonArray.toString().getBytes());\n fos.close();\n } catch (IOException | JSONException e) {\n Log.e(\"IOException\", \"Error occurred writing file \");\n }\n }","public synchronized void saveTableInJson(Table table) throws IOException {\r\n Gson gson = new GsonBuilder().setPrettyPrinting().create();\r\n\r\n /*\r\n * I don't know why but this line below doesn't work...\r\n * The strange thing is it was working fine, but just in one moment stopped.\r\n * I checked everything, I even reverted the done work to the initial state.\r\n * Nothing helped.\r\n */\r\n //gson.toJson(table, new FileWriter(stringPathToTable));\r\n\r\n String jsonTable = gson.toJson(table);\r\n FileWriter fileWriter = new FileWriter(stringPathToTable);\r\n fileWriter.write(jsonTable);\r\n fileWriter.close();\r\n }","public static void write(String modelJson, Context context){\n\t\ttry {\n\t\t\t\n\t\t\tOutputStream outputStream = context.getApplicationContext()\n\t\t\t\t\t.openFileOutput(filename, Context.MODE_APPEND);\n\t\t\tOutputStreamWriter fileWriter = new OutputStreamWriter(outputStream);\n\t\t\tfileWriter.write(modelJson + \"\\r\\n\");\n\t\t\tfileWriter.close();\n\t\t\t\n\t\t} catch (Exception e) {\n\t\t\te.printStackTrace();\n\t\t}\n\t}","public static final void serializeToFile(Object object,String filename)\n\t{\n\t\t// Define local constants.\n\n\t\tString METHOD_NAME = \"serializeToFile\";\n\n\t\t// Check the parameters received and throw the appropriate\n\t\t// exception if necessary.\n\n\t\tif ((null == object) || (null == filename))\n\t\t{\n\t\t\tthrow new NullPointerException(Messages.buildErrorMessage(CLASS_NAME,\n\t\t\t METHOD_NAME,\n\t\t\t Messages.NULL_PARAMETER_MSG));\n\t\t}\n\n\t\tif (0 == filename.length())\n\t\t{\n\t\t\tthrow new IllegalArgumentException(Messages.buildErrorMessage(CLASS_NAME,\n\t\t\t METHOD_NAME,\n\t\t\t Messages.ZERO_LENGTH_PARAMETER_MSG));\n\t\t}\n\n\t\ttry\n\t\t{\n\t\t\tObjectOutputStream objectOutputStream =\n\t\t\t\tnew ObjectOutputStream(new FileOutputStream(filename));\n\t\t\tobjectOutputStream.writeObject(object);\n\t\t\tobjectOutputStream.close();\n\t\t}\n\n\t\tcatch (IOException exception)\n\t\t{\n\t\t\tSystem.out.println(\"Caught: \" + exception);\n\t\t}\n\t}","public static File writeObjectToTempFileNoExceptions(Serializable o, String filename)\n/* */ {\n/* */ try\n/* */ {\n/* 93 */ return writeObjectToTempFile(o, filename);\n/* */ } catch (Exception e) {\n/* 95 */ System.err.println(\"Error writing object to file \" + filename);\n/* 96 */ e.printStackTrace(); }\n/* 97 */ return null;\n/* */ }","private void writeMapToFile() {\r\n\t\ttry {\r\n\t\t\tString dm = gson.toJson(daoMap);// gson.toJson(entity);\r\n\t\t\tFileWriter fileWriter = new FileWriter(path);\r\n\t\t\t\r\n\t\t\tfileWriter.write(dm);\r\n\t\t\tfileWriter.close();\r\n\t\t} catch (Exception e) {\r\n\t\t\te.printStackTrace();\r\n\t\t}\r\n\t}","static void WriteEmployeeObjectIntoFile(Employee emp,String filename)\n\t{\n\t\t\n\t try\n\t {\n\t FileOutputStream fileOut =\n\t new FileOutputStream(filename);\n\t ObjectOutputStream out = new ObjectOutputStream(fileOut);\n\t //Main write method\n\t out.writeObject(emp);\n\t out.close();\n\t fileOut.close();\n\t System.out.printf(\"Serialized data is saved in \" + filename);\n\t }catch(IOException i)\n\t {\n\t i.printStackTrace();\n\t }\n\t}","public boolean saveJson(String pathFile) {\n try {\n jsonObject.put(\"namespace\", this.numNamespace);\n jsonObject.put(\"class\", this.numClasses);\n jsonObject.put(\"interface\", this.numInterfaces);\n jsonObject.put(\"method\", this.numMethods);\n jsonObject.put(\"enumItem\", this.numEnumItem);\n jsonObject.put(\"enum\", this.numEnum);\n jsonObject.put(\"page\", this.numLinks);\n jsonObject.put(\"Classes\", classlist);\n jsonObject.put(\"Interfaces\", interfacelist);\n jsonObject.put(\"Enum\", enumlist);\n FileWriter file = new FileWriter(pathFile + this.fileName + \".json\");\n file.write(jsonObject.toJSONString());\n file.flush();\n file.close();\n return true;\n } catch (IOException e) {\n return false;\n }\n }","String toJson() throws IOException;","public void writeObject(Object obj) throws IOException;","private static void saveJsonFile() {\n Log.println(Log.INFO, \"FileAccessing\", \"Writing settings file.\");\n JsonObject toSave = new JsonObject();\n JsonArray mappingControls = new JsonArray();\n for (int i = 0; i < TaskDetail.actionToTask.size(); i++) {\n JsonObject individualMapping = new JsonObject();\n TaskDetail detail = TaskDetail.actionToTask.valueAt(i);\n byte combinedAction = (byte) TaskDetail.actionToTask.keyAt(i);\n assert detail != null;\n int outerControl = detail.getTask();\n individualMapping.addProperty(\"combinedAction\", combinedAction);\n individualMapping.addProperty(\"task\", outerControl);\n mappingControls.add(individualMapping);\n }\n toSave.add(\"mappingControls\", mappingControls);\n\n JsonArray generalSettings = new JsonArray();\n for (SettingDetail setting : SettingDetail.settingDetails) {\n JsonObject individualSetting = new JsonObject();\n int status = setting.getCurrentIdx();\n individualSetting.addProperty(\"status\", status);\n generalSettings.add(individualSetting);\n }\n toSave.add(\"generalSettings\", generalSettings);\n\n JsonArray deviceList = new JsonArray();\n for (DeviceDetail device : DeviceDetail.deviceDetails) {\n JsonObject individualDevice = new JsonObject();\n individualDevice.addProperty(\"name\", device.deviceName);\n individualDevice.addProperty(\"mac\", device.macAddress);\n deviceList.add(individualDevice);\n }\n toSave.add(\"devices\", deviceList);\n\n JsonArray sensitivityList = new JsonArray();\n for (SensitivitySetting sensitivity : SensitivitySetting.sensitivitySettings) {\n JsonObject individualSensitivity = new JsonObject();\n individualSensitivity.addProperty(\"factor\", sensitivity.multiplicativeFactor);\n individualSensitivity.addProperty(\"sensitivity\", sensitivity.sensitivity);\n sensitivityList.add(individualSensitivity);\n }\n toSave.add(\"sensitivities\", sensitivityList);\n\n toSave.addProperty(\"currentlySelected\", DeviceDetail.getIndexSelected());\n\n try {\n FileOutputStream outputStreamWriter = context.openFileOutput(\"settingDetails.json\", Context.MODE_PRIVATE);\n outputStreamWriter.write(toSave.toString().getBytes());\n outputStreamWriter.close();\n } catch (IOException e) {\n Log.println(Log.ERROR, \"FileAccessing\", \"Settings file writing error.\");\n }\n }","private void save(String fileName, String json){\n mJSonNotifications = getSharedPreferences(fileName, MODE_PRIVATE);\n mJSonNotifications.edit().putString(fileName, json).apply();\n }","public static void saveTestSequenceToJson(TestSequenceList testSequenceList, String absoluteFilePath) {\n Gson gson = new GsonBuilder().enableComplexMapKeySerialization().setPrettyPrinting().create();\r\n String jsonString = gson.toJson(testSequenceList);\r\n try {\r\n FileWriter fileWriter = new FileWriter(absoluteFilePath);\r\n fileWriter.write(jsonString);\r\n System.out.println(\"File saved successfully\");\r\n fileWriter.close();\r\n } catch (IOException e) {\r\n e.printStackTrace();\r\n }\r\n }","public static File writeObjectToFileNoExceptions(Serializable o, String filename)\n/* */ {\n/* 47 */ file = null;\n/* 48 */ ObjectOutputStream oos = null;\n/* */ try {\n/* 50 */ file = new File(filename);\n/* */ \n/* 52 */ oos = new ObjectOutputStream(new BufferedOutputStream(new GZIPOutputStream(new FileOutputStream(file))));\n/* 53 */ oos.writeObject(o);\n/* 54 */ oos.close();\n/* */ \n/* */ \n/* */ \n/* */ \n/* */ \n/* */ \n/* */ \n/* */ \n/* */ \n/* */ \n/* 65 */ return file;\n/* */ }\n/* */ catch (Exception e)\n/* */ {\n/* 56 */ e.printStackTrace();\n/* */ } finally {\n/* 58 */ if (oos != null) {\n/* */ try {\n/* 60 */ oos.close();\n/* */ }\n/* */ catch (Exception ioe) {}\n/* */ }\n/* */ }\n/* */ }","public void serialize(JsonObject dest);","public void writeToJSON(String filePath) throws IOException {\n try (PrintWriter pw = new PrintWriter(filePath)) {\n pw.printf(\"{\\n\\t\\\"patients\\\": [\\n\");\n for (int i = 0; i < dataFrame.getRowCount(); i++) {\n pw.printf(\"\\t\\t{\\n\");\n Iterator<String> it = dataFrame.getColumnNames().iterator();\n while (it.hasNext()){\n String colName = it.next();\n if (it.hasNext())\n pw.printf(\"\\t\\t\\t\\\"%s\\\":\\\"%s\\\",\\n\", colName, dataFrame.getValue(colName, i));\n else\n pw.printf(\"\\t\\t\\t\\\"%s\\\":\\\"%s\\\"\\n\", colName, dataFrame.getValue(colName, i));\n }\n if (i+1<dataFrame.getRowCount())\n pw.printf(\"\\t\\t},\\n\");\n else\n pw.printf(\"\\t\\t}\\n\\t]\\n\");\n }\n pw.printf(\"}\\n\");\n }\n }","private void save() {\n if (mCacheFile.exists()) {\n mCacheFile.delete();\n }\n\n try (JsonWriter writer = new JsonWriter(new BufferedWriter(new FileWriter(mCacheFile)))) {\n writer.beginObject();\n writer.name(PRINTER_LIST_NAMES.get(0));\n writer.beginArray();\n for (DiscoveredPrinter printer : mSavedPrinters) {\n printer.write(writer);\n }\n writer.endArray();\n writer.endObject();\n } catch (NullPointerException | IOException e) {\n Log.w(TAG, \"Error while storing to \" + mCacheFile, e);\n }\n }","public void saveToDoList() {\n try {\n jsonWriter.open();\n jsonWriter.write(toDoList);\n jsonWriter.close();\n\n System.out.println(\"Saved \" + toDoList.getName() + \" to \" + JSON_STORE);\n } catch (FileNotFoundException e) {\n System.out.println(\"Unable to write to file: \" + JSON_STORE);\n }\n }","public static void save(DSAGraph objToSave, String filename)\n {\n FileOutputStream fileStrm;\n ObjectOutputStream objStrm;\n\n try\n {\n fileStrm = new FileOutputStream(filename); //Underlying stream\n objStrm = new ObjectOutputStream(fileStrm); //Object serialization stream\n objStrm.writeObject(objToSave); //Serialize and save to filename\n objStrm.close();//Clean up\n }\n catch (Exception e)\n { //should do more here\n throw new IllegalArgumentException(\"Unable to save object to file: \" + e);\n }\n }","private String convertToJSON(Object o) throws JsonProcessingException {\n return new ObjectMapper().writeValueAsString(o);\n }","public void WriteJSON(Dog dog) {\n\n JSONObject dogDetails = new JSONObject();\n\n dogDetails.put(\"id\", (dList.size()));\n dogDetails.put(\"name\", dog.getName());\n dogDetails.put(\"race\", dog.getRace());\n dogDetails.put(\"color\", dog.getColor());\n dogDetails.put(\"domestic\", dog.getDomestic());\n dogDetails.put(\"age\", dog.getAge());\n dogDetails.put(\"gender\", dog.getGender());\n dogDetails.put(\"size\", dog.getSize());\n dogDetails.put(\"medicalRecords\", null);\n dogDetails.put(\"quarantine\", \"No\");\n\n dogObject.put(\"dog\", dogDetails);\n\n //Add dog to Jsonlist\n dogList.add(dogObject);\n\n //Add dog to ObjectList\n this.dList.add(dog);\n\n //Write JSON file\n try (FileWriter file = new FileWriter(\"dogs.json\")) {\n\n file.write(dogList.toJSONString());\n file.flush();\n\n } catch (IOException e) {\n e.printStackTrace();\n }\n\n }","public static void generarFicheroJSON(App aplicacion) throws IOException {\n\n ObjectMapper mapeador = new ObjectMapper();\n\n mapeador.configure(SerializationFeature.INDENT_OUTPUT, true);\n\n // Escribe en un fichero JSON el objeto que le pasamos\n mapeador.writeValue(new File(\"./aplicaciones/\" + aplicacion.getNombre() + \".json\"), aplicacion);\n\n }","public void writeObjectToFile(ClickerCounterModel[] temp) {\n\t\ttry {\n\t\t\tGson gson = new Gson();\n\t\t\tString string = gson.toJson(temp);\n\t\t\tFileOutputStream outputStream = openFileOutput(filename,\n\t\t\t\t\tContext.MODE_PRIVATE);\n\t\t\toutputStream.write(string.getBytes());\n\t\t\toutputStream.close();\n\t\t} catch (Exception e) {\n\t\t\te.printStackTrace();\n\t\t}\n\t}","String parseObjectToJson(Object obj);","public String autocreateJSON(String filePath, JSONObject jsonObject) throws ExistException, UnderlyingStorageException, UnimplementedException {\n \t\ttry {\n \t\t\tDocument doc=cspace266Hack_munge(jxj.json2xml(jsonObject));\n \t\t\tSystem.err.println(\"153 got \"+doc.asXML());\n \t\t\tReturnedURL url = conn.getURL(RequestMethod.POST,\"collectionobjects/\",doc);\n \t\t\tif(url.getStatus()>299 || url.getStatus()<200)\n \t\t\t\tthrow new UnderlyingStorageException(\"Bad response \"+url.getStatus());\n \t\t\treturn url.getURLTail();\n \t\t} catch (BadRequestException e) {\n \t\t\tthrow new UnderlyingStorageException(\"Service layer exception\",e);\n \t\t} catch (InvalidXTmplException e) {\n \t\t\tthrow new UnimplementedException(\"Error in template\",e);\n \t\t}\n \t}","public String objectToJson(Object o){\n Gson gson = new Gson();\n String json = gson.toJson(o);\n return json;\n }","public static boolean writeObjectToFile(Object obj, File f) {\r\n try {\r\n FileOutputStream fout = new FileOutputStream(f);\r\n ObjectOutputStream oos = new ObjectOutputStream(fout);\r\n oos.writeObject(obj);\r\n oos.close();\r\n } catch (Exception e) {\r\n System.out.println(\"Error writing Object to file: \"\r\n + e.getMessage());\r\n return false;\r\n }\r\n return true;\r\n }","public interface JStorable {\n\t/**\n\t * Return the Object as an JSONObject\n\t */\n\tpublic JSONObject save();\n\t/**\n\t * Load the Object from a JSONObject\n\t * @param obj\n\t * \t\tThe JSONObject\n\t */\n\tpublic void load(JSONObject obj);\n}","private void writeToFile(String pathName,Object logs) {\r\n try {\r\n File save = new File(pathName);\r\n FileOutputStream fileOutputStream = new FileOutputStream(save);\r\n ObjectOutputStream objectOutputStream = new ObjectOutputStream(fileOutputStream);\r\n objectOutputStream.writeObject(logs);\r\n // System.out.println(\"write successful for\"+pathName);\r\n } catch (IOException e) {\r\n e.printStackTrace();\r\n }\r\n }","public void write(JSONDocument doc,File fl){\n try(FileWriter fw = new FileWriter(fl)){\n fw.write(doc.toString());\n fw.flush();\n }catch(Exception ex){\n ex.printStackTrace();\n }\n }","private void saveToDir(String name, Object obj) {\n\t\tFileOutputStream fileOut = null;\n\t\ttry {\n\t\t\tfileOut = new FileOutputStream(this.dir + \"/\" + name);\n\t\t\tObjectOutputStream out = new ObjectOutputStream(fileOut);\n\t\t\tout.writeObject(obj);\n\t\t\tout.close();\n\t\t\tfileOut.close();\n\t\t} catch (IOException e) {\n\t\t\tSystem.out.println(\"Error occurred while saving the index file: \" + name);\n\t\t\te.printStackTrace();\n\t\t\tSystem.exit(1);\n\t\t}\n\t}","void toJSON(Path path);","public boolean save(Object o) {\n if (o instanceof String) {\n\n JsonParser parser = new JsonParser();\n\n JsonElement jsonElement = null;\n String jsonString = (String) o;\n\n try{\n while(!jsonString.startsWith(\"{\")){\n jsonString = jsonString.substring(1, jsonString.length()-2);\n }\n\n jsonElement = parser.parse(jsonString);\n dbClient.save(jsonElement.getAsJsonObject());\n return true;\n\n }catch(Exception e){\n e.printStackTrace();\n return false;\n }\n\n }\n\n return false;\n }","public void serializeObject(String fileName, Automobile automobile) {\n try {\n String path = System.getProperty(\"user.dir\");\n String fileNameWithPath = path + File.separator + fileName;\n if(DEBUG) {\n System.out.printf(\" File Name with Path : %s\", fileNameWithPath);\n }\n FileOutputStream fileOut = new FileOutputStream(fileNameWithPath);\n ObjectOutputStream out = new ObjectOutputStream(fileOut);\n out.writeObject(automobile);\n out.close();\n fileOut.close();\n System.out.printf(\"Serialized data is saved in automotive.ser %s%n\", fileName);\n } catch (IOException i) {\n i.printStackTrace();\n }\n }","public static void save(Serializable data, String fileName) throws Exception {\r\n\t\ttry(ObjectOutputStream out = new ObjectOutputStream( Files.newOutputStream(Paths.get(fileName)) )) {\r\n\t\t\tout.writeObject(data);\r\n\t\t}\r\n\t}","public void crearPrimerFichero(){\n File f=new File(getApplicationContext().getFilesDir(),\"datos.json\");\n // si no existe lo creo\n if(!f.exists()) {\n String filename = \"datos.json\";\n String fileContents = \"[]\";\n FileOutputStream outputStream;\n\n try {\n outputStream = openFileOutput(filename, Context.MODE_PRIVATE);\n outputStream.write(fileContents.getBytes());\n outputStream.close();\n } catch (Exception e) {\n e.printStackTrace();\n }\n }\n\n }","public void saveGame(String fileName){\n try {\n File file1 = new File(fileName);\n FileOutputStream fileOutputStream = new FileOutputStream(file1);\n ObjectOutputStream objectOutputStream = new ObjectOutputStream(fileOutputStream);\n objectOutputStream.writeObject(this);\n }catch (Exception e){\n System.err.println(\"Error when saving file\");\n }\n }"],"string":"[\n \"public static void writeJsonObjectFile(JsonEntity objectToWrite, String filePath) \\n\\t{\\n\\t\\tGson gsonParser = new Gson();\\n\\t\\t\\n\\t\\ttry \\n\\t\\t{\\n\\t\\t\\tFiles.write(gsonParser.toJson(objectToWrite).getBytes(), new File(filePath));\\n\\t\\t}\\n\\t\\tcatch (IOException e) \\n\\t\\t{\\n\\t\\t\\tSystem.err.println(\\\"Can't write to the json file\\\" + e.getMessage());\\n\\t\\t}\\n\\t}\",\n \"public static void writeToJsonGzFile(Object jsonObj, Path filePath) throws JsonGenerationException, JsonMappingException, IOException {\\n\\n GZIPOutputStream gzipOS = new GZIPOutputStream(Files.newOutputStream(filePath));\\n WritableByteChannel out = Channels.newChannel(gzipOS);\\n\\n ObjectMapper mapper = new ObjectMapper();\\n byte[] jsonOut = mapper.writeValueAsBytes(jsonObj);\\n out.write(ByteBuffer.wrap(jsonOut));\\n out.close();\\n\\n }\",\n \"public void exportAsJsonFile(String path) throws IOException {\\n Gson gson = new GsonBuilder().setPrettyPrinting().create();\\n String json = gson.toJson(this);\\n\\n FileWriter writer = new FileWriter(path);\\n writer.write(json);\\n writer.close();\\n }\",\n \"private void writeToFile() {\\n try {\\n FileOutputStream fos = new FileOutputStream(f);\\n String toWrite = myJSON.toString(4);\\n byte[] b = toWrite.getBytes();\\n fos.write(b);\\n fos.close();\\n } catch (Exception e) {\\n e.printStackTrace();\\n }\\n }\",\n \"public static void createJsonFile(JsonObject json) throws IOException {\\n\\r\\n FileWriter file = new FileWriter(\\\"outputfile\\\", false);\\r\\n try {\\r\\n file.write(Jsoner.prettyPrint(json.toJson(),2));\\r\\n file.flush();\\r\\n } catch (IOException e) {\\r\\n out.println(\\\"Error \\\" + e);\\r\\n }\\r\\n }\",\n \"String saveToFile(Object data, String fileName, FileFormat fileFormat) throws IOException;\",\n \"@Override\\n\\tpublic void save(Object o, String file) {\\n\\t\\t\\n\\t}\",\n \"public void guardarEnJSON () {\\n Gson gson = new GsonBuilder().setPrettyPrinting().create();\\n String s = gson.toJson(this);\\n try {\\n FileWriter fw = new FileWriter(\\\"files/graph.json\\\");\\n fw.write(s);\\n fw.close();\\n } catch (IOException e) {\\n e.printStackTrace();\\n }\\n }\",\n \"public void saveGame(String fileName){\\n Gson gson = new Gson();\\n String userJson = gson.toJson(player);\\n\\n try(Writer w = new BufferedWriter(new OutputStreamWriter( new FileOutputStream(fileName), \\\"UTF-8\\\"))) {\\n w.write(userJson);\\n } catch (FileNotFoundException e) {\\n e.printStackTrace();\\n } catch (IOException e) {\\n e.printStackTrace();\\n }\\n }\",\n \"private void writeToFile(String filename, Object object) {\\n try {\\n FileOutputStream fileOutputStream = openFileOutput(filename, MODE_PRIVATE);\\n ObjectOutputStream objectOutputStream = new ObjectOutputStream(fileOutputStream);\\n objectOutputStream.writeObject(object);\\n objectOutputStream.close();\\n } catch (IOException e) {\\n e.printStackTrace();\\n }\\n }\",\n \"private static void exportJsonFile(File configFile) {\\n Gson gson = new Gson();\\n \\n // Java object to JSON, and assign to a String\\n String jsonInString = gson.toJson(GameConfig.getInstance());\\n \\n try {\\n FileWriter writer = new FileWriter(configFile);\\n \\n writer.append(jsonInString);\\n writer.flush();\\n writer.close();\\n } catch (IOException e) {\\n LogUtils.error(\\\"exportJsonFile => \\\",e);\\n }\\n }\",\n \"private void writeObject(String filePath, Object obj) throws IOException {\\n OutputStream file = new FileOutputStream(filePath);\\n OutputStream buffer = new BufferedOutputStream(file);\\n ObjectOutput output = new ObjectOutputStream(buffer);\\n output.writeObject(obj);\\n output.close();\\n }\",\n \"public static void writeListToJsonFile(Object jsonObj, Path filePath) throws JsonGenerationException, JsonMappingException, IOException {\\n\\n final OutputStream out = new ByteArrayOutputStream();\\n ObjectMapper mapper = new ObjectMapper();\\n mapper.writeValue(out, jsonObj);\\n\\n final byte[] data = ((ByteArrayOutputStream) out).toByteArray();\\n\\n Files.write(filePath, data);\\n\\n }\",\n \"private void saveInFile() {\\n try {\\n FileOutputStream fos = openFileOutput(FILENAME,\\n Context.MODE_PRIVATE);//goes stream based on filename\\n BufferedWriter out = new BufferedWriter(new OutputStreamWriter(fos)); //create buffer writer\\n Gson gson = new Gson();\\n gson.toJson(countbookList, out);//convert java object to json string & save in output\\n out.flush();\\n fos.close();\\n } catch (FileNotFoundException e) {\\n throw new RuntimeException();\\n } catch (IOException e) {\\n throw new RuntimeException();\\n }\\n }\",\n \"private void saveInFile() {\\n try {\\n FileOutputStream fos = openFileOutput(FILENAME, Context.MODE_PRIVATE);\\n\\n BufferedWriter out = new BufferedWriter(new OutputStreamWriter(fos));\\n\\n Gson gson = new Gson();\\n Log.d(\\\"PersonList\\\", personList.toString());\\n gson.toJson(personList, out);\\n out.flush();\\n\\n fos.close();\\n\\n } catch (FileNotFoundException e){\\n throw new RuntimeException();\\n } catch (IOException e){\\n e.printStackTrace();\\n }\\n\\n }\",\n \"public static void saveObj(Object obj, File file)\\n {\\n try(ObjectOutputStream oos = new ObjectOutputStream(new FileOutputStream(file)))\\n {\\n oos.writeObject(obj);\\n }\\n \\n catch(IOException e)\\n {\\n JOptionPane.showMessageDialog(null, \\\"[Error] Failed to save file: \\\" + e.getMessage());\\n }\\n }\",\n \"@SuppressWarnings(\\\"unused\\\")\\n public void SaveJsonCollectionsToFiles(){\\n try {\\n String formattedDate = FileNameUtils.DATE_FORMAT.format(new Date());\\n ObjectWriter writer = mapper.writer(new DefaultPrettyPrinter());\\n writer.writeValue(new File(FileNameUtils.GetValuesFileName(formattedDate)), jsonObjects);\\n }\\n catch(IOException exp){\\n System.err.println(\\\"Error while creating JSON file. Reason: \\\" + exp.getMessage());\\n }\\n }\",\n \"public static void saveJSON(List<JSONObject> objects, String outputFile) {\\n try (FileWriter file = new FileWriter(outputFile)) {\\n for (JSONObject obj: objects)\\n file.write(obj.toString() + '\\\\n');\\n } catch (IOException e) {\\n e.printStackTrace();\\n }\\n }\",\n \"public static boolean saveToFile(Object o, String fileName) {\\n FileOutputStream fos = null;\\n BufferedOutputStream bos = null;\\n ObjectOutputStream oos = null;\\n File objectFile = null;\\n\\n objectFile = new File(fileName);\\n try {\\n fos = new FileOutputStream(objectFile);\\n bos = new BufferedOutputStream(fos);\\n oos = new ObjectOutputStream(bos);\\n oos.writeObject(o);\\n oos.close();\\n bos.close();\\n fos.close();\\n } catch (FileNotFoundException e) {\\n return false;\\n } catch (IOException e) {\\n return false;\\n }\\n return true;\\n }\",\n \"private void saveInFile() {\\n\\t\\tthis.deleteFile();\\n\\t\\tfor (CounterModel obj : counterListModel.getCounterList()) {\\n\\t\\t\\ttry {\\n\\t\\t\\t\\tGson gson = new Gson();\\n\\t\\t\\t\\tif (obj.getCounterName().equals(counterModel.getCounterName())) {\\n\\t\\t\\t\\t\\tobj = counterModel;\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\tString json = gson.toJson(obj) +'\\\\n';\\n\\t\\t\\t\\tFileOutputStream fos = openFileOutput(FILENAME,\\n\\t\\t\\t\\t\\t\\tContext.MODE_APPEND);\\n\\t\\t\\t\\tfos.write(json.getBytes());\\n\\t\\t\\t\\tfos.close();\\n\\t\\t\\t} catch (FileNotFoundException e) {\\n\\t\\t\\t\\t// TODO Auto-generated catch block\\n\\t\\t\\t\\te.printStackTrace();\\n\\t\\t\\t} catch (IOException e) {\\n\\t\\t\\t\\t// TODO Auto-generated catch block\\n\\t\\t\\t\\te.printStackTrace();\\n\\t\\t\\t}\\n\\t\\t}\\n\\t}\",\n \"public <T> String SerializeJson(T obj, String pathToRoot) {\\n this.lastPath = pathToRoot + obj.getClass().getSimpleName().toLowerCase() + \\\"_object-\\\" + Math.abs(new Random().nextLong()) + \\\".json\\\";\\n File file = new File(this.lastPath);\\n ObjectMapper mapper = new ObjectMapper();\\n\\n mapper.configure(DeserializationFeature.FAIL_ON_UNKNOWN_PROPERTIES, false);\\n mapper.registerModule(new JavaTimeModule());\\n mapper.disable(SerializationFeature.WRITE_DATES_AS_TIMESTAMPS);\\n\\n try {\\n file.createNewFile();\\n mapper.writeValue(file, obj);\\n System.out.println(mapper.writerWithDefaultPrettyPrinter().writeValueAsString(obj));\\n return mapper.writeValueAsString(obj);\\n } catch (IOException e) {\\n e.printStackTrace();\\n }\\n return \\\"\\\";\\n }\",\n \"public static void save(Object o, String filename) {\\n\\t\\ttry\\n\\t {\\n\\t\\t\\tfilename = \\\"save\\\" + File.separator + filename + \\\".hsc\\\";\\n\\t\\t\\tcreateSaveDirIfNotExisting();\\n\\t\\t\\tprepareSaveFile(filename);\\n\\t FileOutputStream fileOut = new FileOutputStream(filename);\\n\\t ObjectOutputStream out = new ObjectOutputStream(fileOut);\\n\\t out.writeObject(o.getClass().cast(o));\\n\\t out.close();\\n\\t fileOut.close();\\n\\t //System.out.println(\\\"Serialized object is saved in \\\" + filename);\\n\\t }catch(NotSerializableException e) {\\n\\t \\t System.out.println(\\\"Object to be saved does not implement java.io.Serializable!\\\");\\n\\t \\t e.printStackTrace();\\n\\t }\\n\\t\\tcatch(IOException i)\\n\\t {\\n\\t i.printStackTrace();\\n\\t } \\n\\t}\",\n \"public void writeToFile(Object obj) throws FileNotFoundException, IOException\\n {\\n ObjectOutputStream writeToFile = null;\\n\\n try\\n {\\n FileOutputStream fileOutStream = new FileOutputStream(FILE_NAME);\\n writeToFile = new ObjectOutputStream(fileOutStream);\\n\\n writeToFile.writeObject(obj);\\n }\\n finally\\n {\\n if (writeToFile != null)\\n {\\n try\\n {\\n writeToFile.close();\\n }\\n catch (IOException e)\\n {\\n displayErrorMessage(\\\"IO File error on\\\", FILE_NAME);\\n }\\n }\\n }\\n }\",\n \"private static void jsonWriter(JSONObject bookList) throws Exception{\\r\\n FileWriter file = new FileWriter(\\\"libreria.json\\\");\\r\\n file.write(bookList.toJSONString());\\r\\n file.flush();\\r\\n }\",\n \"public void escribirFichero(String textoenjson){\\n {\\n OutputStreamWriter escritor=null;\\n try\\n {\\n escritor=new OutputStreamWriter(openFileOutput(\\\"datos.json\\\", Context.MODE_PRIVATE));\\n escritor.write(textoenjson);\\n }\\n catch (Exception ex)\\n {\\n Log.e(\\\"ivan\\\", \\\"Error al escribir fichero a memoria interna\\\");\\n }\\n finally\\n {\\n try {\\n if(escritor!=null)\\n escritor.close();\\n } catch (IOException e) {\\n e.printStackTrace();\\n }\\n }\\n }\\n\\n\\n }\",\n \"public static void writeObjectToDisk(Object obj, String name) throws IOException {\\r\\n\\t\\t// Create file output stream\\r\\n\\t\\tFileOutputStream fileOutStr = new FileOutputStream(name);\\r\\n\\t\\t// Create object output stream and write object\\r\\n\\t\\tObjectOutputStream objOutStr = new ObjectOutputStream(fileOutStr);\\r\\n\\t\\tobjOutStr.writeObject(obj);\\r\\n\\t\\t// Close all streams\\r\\n\\t\\tobjOutStr.close();\\r\\n\\t\\tfileOutStr.close();\\r\\n\\t\\tSystem.out.printf(\\\"Serialized data is saved in a file - \\\" + name); // Printing message and file name which is\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t// saved\\r\\n\\t}\",\n \"public void writeToFile (String json) {\\n // reset fos to null for checks\\n FileOutputStream fos = null;\\n try {\\n String FILE_NAME = \\\"ExportedLearningCards.json\\\";\\n fos = openFileOutput(FILE_NAME, MODE_PRIVATE);\\n fos.write(json.getBytes());\\n Toast.makeText(this, \\\"Saved to \\\" + getFilesDir() + \\\"/\\\" + FILE_NAME,\\n Toast.LENGTH_LONG).show();\\n } catch (FileNotFoundException e) {\\n e.printStackTrace();\\n } catch (IOException e) {\\n e.printStackTrace();\\n } finally {\\n if (fos != null) {\\n try {\\n fos.close();\\n } catch (IOException e) {\\n e.printStackTrace();\\n }\\n }\\n }\\n }\",\n \"public static void serialize(Object obj, String fileName) throws IOException {\\n\\t\\tFileOutputStream fos = new FileOutputStream(fileName);\\n\\t\\tObjectOutputStream oos = new ObjectOutputStream(fos);\\n\\t\\toos.writeObject(obj);\\n\\n\\t\\tfos.close();\\n\\t}\",\n \"public static void save(final String filename, final Serializable object)\\r\\n throws IOException {\\r\\n FileOutputStream fos = null;\\r\\n ObjectOutputStream out = null;\\r\\n\\r\\n fos = new FileOutputStream(filename);\\r\\n out = new ObjectOutputStream(fos);\\r\\n out.writeObject(object);\\r\\n out.close();\\r\\n }\",\n \"public void exportJSON()\\n {\\n Gson JSONConverter = new Gson();\\n FileWriter writer;\\n\\n try\\n {\\n // wipe the file\\n PrintWriter write = new PrintWriter(new File(fp));\\n write.print(\\\"\\\");\\n write.close();\\n\\n // Initialize FileWriter to write Strings into JSON file.\\n writer = new FileWriter(fp + \\\"/queue.json\\\");\\n\\n Iterator<ComparableCalendar> iter = this.queue.iterator();\\n // Loop through the PQ.\\n while(iter.hasNext())\\n {\\n ComparableCalendar nextObject = iter.next();\\n // Convert an issue object into a JSON-formatted representation of it, as a String.\\n String representationJSON = JSONConverter.toJson(nextObject);\\n\\n // Write that String to the file.\\n writer.write(representationJSON + \\\"\\\\n\\\");\\n }\\n // Close the FileWriter to conserve system resources.\\n writer.close();\\n\\n }\\n catch (Exception e)\\n {\\n // Print any error messages that results to the console.\\n e.printStackTrace();\\n }\\n\\n }\",\n \"public JSONObject save();\",\n \"void saveToFile() {\\n\\t\\ttry {\\n\\t\\t\\tFile directory = GameApplication.getInstance().getExternalFilesDir(Environment.DIRECTORY_DOCUMENTS);\\n\\t\\t\\tFile target = new File(directory, FILE_NAME);\\n\\t\\t\\tif (!target.exists()) {\\n\\t\\t\\t\\ttarget.createNewFile();\\n\\t\\t\\t}\\n\\t\\t\\tJsonWriter writer = new JsonWriter(new FileWriter(target));\\n\\t\\t\\twriter.setIndent(\\\" \\\");\\n\\t\\t\\twriter.beginArray();\\n\\t\\t\\tfor (Scoreboard scoreboard : scoreboards.values()) {\\n\\t\\t\\t\\twriteScoreboard(writer, scoreboard);\\n\\t\\t\\t}\\n\\t\\t\\twriter.endArray();\\n\\t\\t\\twriter.flush();\\n\\t\\t\\twriter.close();\\n\\t\\t} catch (IOException e) {\\n\\t\\t\\te.printStackTrace();\\n\\t\\t}\\n\\t}\",\n \"public static void writeJsonToFile(List<Object> objLst, File file) throws Exception {\\n writeJsonToFile(objLst, file, false);\\n }\",\n \"public void saveToFile(Map<String, T> data) throws IOException{\\n\\t\\tOutputStream file = new FileOutputStream(filePath);\\n OutputStream buffer = new BufferedOutputStream(file);\\n ObjectOutput output = new ObjectOutputStream(buffer);\\n\\n // serialize the Map\\n output.writeObject(data);\\n output.close();\\n\\t}\",\n \"public static void storeObject(Object object, String filename) throws IOException\\n {\\n storeObject(object, new File(filename));\\n }\",\n \"private void saveInFile() {\\n try {\\n FileOutputStream fOut = openFileOutput(FILENAME,\\n Context.MODE_PRIVATE);\\n\\n OutputStreamWriter writer = new OutputStreamWriter(fOut);\\n Gson gson = new Gson();\\n gson.toJson(counters, writer);\\n writer.flush();\\n\\n fOut.close();\\n\\n } catch (FileNotFoundException e) {\\n throw new RuntimeException();\\n } catch (IOException e) {\\n throw new RuntimeException();\\n }\\n }\",\n \"private void serializeObject(String filename, Object content)\\n throws IOException\\n {\\n synchronized(filename)\\n {\\n FileOutputStream fileOut = new FileOutputStream(filename);\\n ObjectOutputStream out = new ObjectOutputStream(fileOut);\\n out.writeObject(content);\\n out.close();\\n fileOut.close();\\n }\\n }\",\n \"public static boolean writeToJson(Quote[] quotes, String filename) throws IOException {\\n Gson write = new Gson();\\n OutputStream outStream = new FileOutputStream(filename);\\n BufferedWriter buffer = new BufferedWriter(new OutputStreamWriter(outStream));\\n write.toJson(quotes, buffer);\\n buffer.close();\\n return true;\\n }\",\n \"public static void writeJSONToFile(File file, JSONObject jsonObject) throws IOException {\\n writeToFile(file, JSONObject.toJSONString(jsonObject));\\n }\",\n \"public static void writeObjectToFile(Serializable object, String fileName) throws IOException {\\n try (FileOutputStream fos = new FileOutputStream(fileName);\\n ObjectOutputStream oos = new ObjectOutputStream(fos);) {\\n oos.writeObject(object);\\n }\\n }\",\n \"public void saveData() {\\n try {\\n JsonWriter jw = new JsonWriter(openFileOutput(DATA_FILE, Context.MODE_PRIVATE));\\n jw.write(user);\\n jw.close();\\n } catch(Exception e) {\\n Log.i(\\\"Exception :\\\", e.toString());\\n }\\n }\",\n \"public static void saveObjToFile(Object obj, String filePath) throws IOException {\\n // create the enclosing folders if it doesn't exist\\n createDir(filePath);\\n\\n FileOutputStream file = new FileOutputStream(filePath);\\n ObjectOutputStream out = new ObjectOutputStream(file);\\n out.writeObject(obj);\\n out.close();\\n }\",\n \"public void saveTodo() {\\r\\n File file = new File(\\\"C:\\\\\\\\Users\\\\\\\\Dalia\\\\\\\\Desktop\\\\\\\\CPSC 210\\\\\\\\Project\\\\\\\\project_b2h3b\\\\\\\\data\\\");\\r\\n JFileChooser chooser = new JFileChooser();\\r\\n chooser.setDialogTitle(\\\"Specify a file to save\\\");\\r\\n chooser.setCurrentDirectory(file);\\r\\n int userSelection = chooser.showSaveDialog(null);\\r\\n if (userSelection == JFileChooser.APPROVE_OPTION) {\\r\\n File f = chooser.getSelectedFile();\\r\\n System.out.println(\\\"Save as file: \\\" + f.getAbsolutePath());\\r\\n String tempFileName = f.getAbsolutePath();\\r\\n writer = new MyTodoJsonWriter(tempFileName);\\r\\n try {\\r\\n writer.open();\\r\\n writer.write(myTodo);\\r\\n fileName = tempFileName;\\r\\n playSound(\\\"c1.wav\\\");\\r\\n } catch (IOException ioException) {\\r\\n JOptionPane.showMessageDialog(null, \\\"Cannot save todolist!\\\");\\r\\n } finally {\\r\\n writer.close();\\r\\n JOptionPane.showMessageDialog(null, \\\"Save successful!\\\");\\r\\n }\\r\\n todoListGui();\\r\\n }\\r\\n }\",\n \"private static boolean saveMOTD(JSONObject motdObj) {\\n File JSONFile = new File(plugin.getDataFolder() + \\\"/motd.json\\\");\\n\\n try ( //open our writer and write the player file\\n PrintWriter writer = new PrintWriter(JSONFile)) {\\n //System.out.println(obj);\\n writer.print(motdObj.toString(4));\\n writer.close();\\n Logger.getLogger(MOTDHandler.class.getName()).log(Level.INFO, \\\"Successfully updated motd.json\\\");\\n return true;\\n } catch (FileNotFoundException ex) {\\n\\n Logger.getLogger(MOTDHandler.class.getName()).log(Level.SEVERE, null, ex);\\n return false;\\n }\\n }\",\n \"void generateJSON(JSONObject object, String name);\",\n \"public void writeObject(Object obj, String path)throws IOException{\\n FileOutputStream fos = new FileOutputStream(path);\\n ObjectOutputStream oos = new ObjectOutputStream(fos);\\n\\n oos.writeObject(obj);\\n oos.close();\\n }\",\n \"public void saveArchive() throws FileNotFoundException {\\n jsonWriter.open();\\n Archive archive = new Archive(cameraCollection, filmCollection);\\n jsonWriter.write(archive);\\n jsonWriter.close();\\n }\",\n \"public void WriteJSON(Costumer costumer) {\\n\\n JSONObject costumerDetails = new JSONObject();\\n JSONObject documentDetails = new JSONObject();\\n\\n documentDetails.put(\\\"type\\\", costumer.getDocument().getType());\\n documentDetails.put(\\\"nDocument\\\", costumer.getDocument().getnDocument());\\n documentDetails.put(\\\"ExpiryDate\\\", costumer.getDocument().getDateExpiry());\\n\\n System.out.println(\\\"dco \\\" + documentDetails);\\n\\n costumerDetails.put(\\\"name\\\", costumer.getName());\\n costumerDetails.put(\\\"surname\\\", costumer.getSurname());\\n costumerDetails.put(\\\"dateOfBirth\\\", costumer.getDateOfBirth());\\n costumerDetails.put(\\\"cityOfBirth\\\", costumer.getCityOfBirth());\\n costumerDetails.put(\\\"cityOfResidence\\\", costumer.getCityOfResidence());\\n costumerDetails.put(\\\"address\\\", costumer.getAddress());\\n costumerDetails.put(\\\"telephone\\\", costumer.getTelephone());\\n costumerDetails.put(\\\"fiscalCode\\\", costumer.getFiscalCode());\\n costumerDetails.put(\\\"province\\\", costumer.getProvince());\\n costumerDetails.put(\\\"document\\\", documentDetails);\\n\\n costumerObject.put(\\\"costumer\\\", costumerDetails);\\n\\n //Add costumer to list\\n costumerList.add(costumerObject);\\n\\n //add costumer ot the object list\\n this.cList.add(costumer);\\n\\n //Write JSON file\\n try (FileWriter file = new FileWriter(\\\"costumers.json\\\")) {\\n\\n file.write(costumerList.toJSONString());\\n file.flush();\\n\\n } catch (IOException e) {\\n e.printStackTrace();\\n }\\n\\n }\",\n \"public static void saveConfig(Object config, File file) throws IOException {\\n file.createNewFile();\\n String json = gson.toJson(parser.parse(gson.toJson(config)));\\n try (PrintWriter out = new PrintWriter(file)) {\\n out.println(json);\\n }\\n }\",\n \"public static void writeObject(Activity activity, Object object, String filename) {\\n FileOutputStream fos = null;\\n ObjectOutputStream oos = null;\\n try {\\n fos = activity.openFileOutput(filename, Context.MODE_PRIVATE);\\n oos = new ObjectOutputStream(fos);\\n oos.writeObject(object);\\n } catch (IOException e) {\\n e.printStackTrace();\\n }\\n finally {\\n closeOutputStream(fos);\\n closeOutputStream(oos);\\n }\\n }\",\n \"public void createJSON(String filePath, JSONObject jsonObject) throws ExistException, UnimplementedException, UnderlyingStorageException {\\n \\t\\tSystem.err.println(jsonObject);\\n \\t\\tjsonObject=cspace264Hack_munge(jsonObject,filePath);\\n \\t\\tautocreateJSON(\\\"\\\",jsonObject);\\n \\t\\t// XXX End of here's what we do because of CSPACE-264\\t\\t\\n \\t\\t// Here's what we should do ->\\n \\t\\t// throw new UnimplementedException(\\\"Cannot create collectionobject at known path, use autocreateJSON\\\");\\n \\t}\",\n \"public static File writeObjectToTempFile(Serializable o, String filename)\\n/* */ throws IOException\\n/* */ {\\n/* 76 */ File file = File.createTempFile(filename, \\\".tmp\\\");\\n/* 77 */ file.deleteOnExit();\\n/* 78 */ ObjectOutputStream oos = new ObjectOutputStream(new BufferedOutputStream(new GZIPOutputStream(new FileOutputStream(file))));\\n/* 79 */ oos.writeObject(o);\\n/* 80 */ oos.close();\\n/* 81 */ return file;\\n/* */ }\",\n \"@Override\\n\\tpublic void saveData(Object objectsToSave, String path) {\\n\\t\\t\\n\\t\\ttry {\\n\\t\\t\\tString objects = (String) objectsToSave;\\n\\t\\t\\tFileOutputStream fileOutputStream = new FileOutputStream(path);\\n\\t\\t\\tfileOutputStream.write(objects.getBytes());\\n\\t\\t\\tfileOutputStream.close();\\n\\t\\t} catch (FileNotFoundException e) {\\n\\t\\t\\te.printStackTrace();\\n\\t\\t} catch (IOException e){\\n\\t\\t\\te.printStackTrace();\\n\\t\\t}\\n\\t\\t\\n\\t}\",\n \"public void save(){\\n Player temp = Arena.CUR_PLAYER;\\n try{\\n FileOutputStream outputFile = new FileOutputStream(\\\"./data.sec\\\");\\n ObjectOutputStream objectOut = new ObjectOutputStream(outputFile);\\n objectOut.writeObject(temp);\\n objectOut.close();\\n outputFile.close();\\n }\\n catch(FileNotFoundException e){\\n System.out.print(\\\"Cannot create a file at that location\\\");\\n }\\n catch(SecurityException e){\\n System.out.print(\\\"Permission Denied!\\\");\\n }\\n catch(IOException e){\\n System.out.println(\\\"Error 203\\\");\\n } \\n }\",\n \"private File getOpenApiFile(String oasDefinition) throws IOException {\\n File oasTempFile = File.createTempFile(\\\"oasTempFile\\\", \\\".json\\\");\\n try (BufferedWriter bw = new BufferedWriter(new OutputStreamWriter(new FileOutputStream(oasTempFile),\\n StandardCharsets.UTF_8))) {\\n bw.write(oasDefinition);\\n }\\n return oasTempFile;\\n }\",\n \"public static void appendJsonToFile(List<Object> objLst, File file) throws Exception {\\n writeJsonToFile(objLst, file, true);\\n }\",\n \"private void setFile(Serializable object, String path) throws Exception {\\t\\t\\n\\t\\t\\n FileOutputStream fileOut = new FileOutputStream(path);\\n ObjectOutputStream objectOut = new ObjectOutputStream(fileOut);\\n objectOut.writeObject(object);\\n objectOut.close(); \\n\\t\\t\\n\\t}\",\n \"public static void jsonWrite() \\n\\t{\\n JSONArray arrJson = new JSONArray(); \\n FileWriter writeFile = null;\\n Iterator<Taxi_Model> taxiIterator = L.iterator();\\n\\n while(taxiIterator.hasNext()) \\n {\\n \\tJSONObject jsonObject = new JSONObject();\\n \\tTaxi_Model aux = new Taxi_Model();\\n \\taux = taxiIterator.next();\\n \\tJSONArray array = new JSONArray();\\n \\tarray.add(aux.getLocalizacao()[0]);\\n \\tarray.add(aux.getLocalizacao()[1]);\\n \\t\\n \\t//Armazena dados em um Objeto JSON\\n \\tjsonObject.put(\\\"Usuario\\\", aux.getUsuario());\\n jsonObject.put(\\\"Nome\\\", aux.getNome());\\n jsonObject.put(\\\"Senha\\\", aux.getSenha());\\n jsonObject.put(\\\"CPF\\\", aux.getCpf());\\n jsonObject.put(\\\"Cor do Carro\\\", aux.getCorCarro());\\n jsonObject.put(\\\"Modelo do Carro\\\", aux.getModeloCarro());\\n jsonObject.put(\\\"Placa do Carro\\\", aux.getPlaca());\\n jsonObject.put(\\\"Localizacao\\\", array);\\n jsonObject.put(\\\"Pontuacao\\\", aux.getPontuacao());\\n jsonObject.put(\\\"Corridas\\\", aux.getTotalCorridas());\\n jsonObject.put(\\\"Tempo total\\\", aux.getTempoTotal());\\n jsonObject.put(\\\"Tempo programado\\\", aux.getTempoProgramada());\\n arrJson.add(jsonObject);\\n }\\n \\n try\\n {\\n writeFile = new FileWriter(\\\"taxis.json\\\");\\n //Escreve no arquivo conteudo do Objeto JSON\\n writeFile.write(arrJson.toJSONString());\\n writeFile.close();\\n }\\n catch(IOException e)\\n {\\n e.printStackTrace();\\n }\\n\\t}\",\n \"private void saveInFile(final String fileName, ArrayList<Habit> habitArray) {\\r\\n try {\\r\\n FileOutputStream fos = openFileOutput(fileName, 0);\\r\\n BufferedWriter out = new BufferedWriter(new OutputStreamWriter(fos));\\r\\n Gson gson = new Gson();\\r\\n gson.toJson(habitArray, out);\\r\\n out.flush();\\r\\n\\r\\n fos.close();\\r\\n } catch (FileNotFoundException e) {\\r\\n // TODO Auto-generated catch block\\r\\n throw new RuntimeException();\\r\\n } catch (IOException e) {\\r\\n // TODO Auto-generated catch block\\r\\n throw new RuntimeException();\\r\\n }\\r\\n }\",\n \"public static void writeuser(String modelJson, Context context){\\n\\t\\ttry {\\n\\t\\t\\t\\n\\t\\t\\tOutputStream outputStream = context.getApplicationContext()\\n\\t\\t\\t\\t\\t.openFileOutput(filename, Context.MODE_PRIVATE);\\n\\t\\t\\tOutputStreamWriter fileWriter = new OutputStreamWriter(outputStream);\\n\\t\\t\\tfileWriter.write(modelJson + \\\"\\\\r\\\\n\\\");\\n\\t\\t\\tfileWriter.close();\\n\\t\\t\\t\\n\\t\\t} catch (Exception e) {\\n\\t\\t\\te.printStackTrace();\\n\\t\\t}\\n\\t}\",\n \"private void serialize(String file_name) {\\n\\t\\t//Saving of object in a file\\n\\t\\ttry {\\n\\t\\t\\tFileOutputStream file = new FileOutputStream(file_name);\\n\\t\\t\\tObjectOutputStream out = new ObjectOutputStream(file);\\n\\t\\t\\t// Method for serialization of object\\n\\t\\t\\tout.writeObject(this.GA);\\n\\n\\t\\t\\tout.close();\\n\\t\\t\\tfile.close();\\n\\n\\t\\t\\tSystem.out.println(\\\"Object has benn serialized\\\");\\n\\t\\t} catch (IOException e) {\\n\\t\\t\\tSystem.err.println(\\\"IOException is caught,Object didnt save.\\\");\\n\\t\\t}\\n\\t}\",\n \"public void save(String json, Map<String,Object> properties);\",\n \"private void saveWorld() {\\n try {\\n jsonWriter.open();\\n jsonWriter.write(world);\\n jsonWriter.close();\\n System.out.println(\\\"Saved world to \\\" + JSON_STORE);\\n } catch (FileNotFoundException e) {\\n System.out.println(\\\"Unable to write to file: \\\" + JSON_STORE);\\n }\\n }\",\n \"public void logEmissions(JSONObject object, Context context) {\\n try {\\n JSONArray jsonArray = readEmissionsLog(context);\\n if (jsonArray == null) {\\n jsonArray = new JSONArray();\\n }\\n FileOutputStream fos = context.openFileOutput(profileManager.getActiveUserName() + \\\"Nutrition.json\\\", Context.MODE_PRIVATE);\\n JSONObject jsonObject = new JSONObject();\\n jsonObject.put(\\\"Nutrition data\\\", object);\\n jsonArray.put(jsonObject);\\n fos.write(jsonArray.toString().getBytes());\\n fos.close();\\n } catch (IOException | JSONException e) {\\n Log.e(\\\"IOException\\\", \\\"Error occurred writing file \\\");\\n }\\n }\",\n \"public synchronized void saveTableInJson(Table table) throws IOException {\\r\\n Gson gson = new GsonBuilder().setPrettyPrinting().create();\\r\\n\\r\\n /*\\r\\n * I don't know why but this line below doesn't work...\\r\\n * The strange thing is it was working fine, but just in one moment stopped.\\r\\n * I checked everything, I even reverted the done work to the initial state.\\r\\n * Nothing helped.\\r\\n */\\r\\n //gson.toJson(table, new FileWriter(stringPathToTable));\\r\\n\\r\\n String jsonTable = gson.toJson(table);\\r\\n FileWriter fileWriter = new FileWriter(stringPathToTable);\\r\\n fileWriter.write(jsonTable);\\r\\n fileWriter.close();\\r\\n }\",\n \"public static void write(String modelJson, Context context){\\n\\t\\ttry {\\n\\t\\t\\t\\n\\t\\t\\tOutputStream outputStream = context.getApplicationContext()\\n\\t\\t\\t\\t\\t.openFileOutput(filename, Context.MODE_APPEND);\\n\\t\\t\\tOutputStreamWriter fileWriter = new OutputStreamWriter(outputStream);\\n\\t\\t\\tfileWriter.write(modelJson + \\\"\\\\r\\\\n\\\");\\n\\t\\t\\tfileWriter.close();\\n\\t\\t\\t\\n\\t\\t} catch (Exception e) {\\n\\t\\t\\te.printStackTrace();\\n\\t\\t}\\n\\t}\",\n \"public static final void serializeToFile(Object object,String filename)\\n\\t{\\n\\t\\t// Define local constants.\\n\\n\\t\\tString METHOD_NAME = \\\"serializeToFile\\\";\\n\\n\\t\\t// Check the parameters received and throw the appropriate\\n\\t\\t// exception if necessary.\\n\\n\\t\\tif ((null == object) || (null == filename))\\n\\t\\t{\\n\\t\\t\\tthrow new NullPointerException(Messages.buildErrorMessage(CLASS_NAME,\\n\\t\\t\\t METHOD_NAME,\\n\\t\\t\\t Messages.NULL_PARAMETER_MSG));\\n\\t\\t}\\n\\n\\t\\tif (0 == filename.length())\\n\\t\\t{\\n\\t\\t\\tthrow new IllegalArgumentException(Messages.buildErrorMessage(CLASS_NAME,\\n\\t\\t\\t METHOD_NAME,\\n\\t\\t\\t Messages.ZERO_LENGTH_PARAMETER_MSG));\\n\\t\\t}\\n\\n\\t\\ttry\\n\\t\\t{\\n\\t\\t\\tObjectOutputStream objectOutputStream =\\n\\t\\t\\t\\tnew ObjectOutputStream(new FileOutputStream(filename));\\n\\t\\t\\tobjectOutputStream.writeObject(object);\\n\\t\\t\\tobjectOutputStream.close();\\n\\t\\t}\\n\\n\\t\\tcatch (IOException exception)\\n\\t\\t{\\n\\t\\t\\tSystem.out.println(\\\"Caught: \\\" + exception);\\n\\t\\t}\\n\\t}\",\n \"public static File writeObjectToTempFileNoExceptions(Serializable o, String filename)\\n/* */ {\\n/* */ try\\n/* */ {\\n/* 93 */ return writeObjectToTempFile(o, filename);\\n/* */ } catch (Exception e) {\\n/* 95 */ System.err.println(\\\"Error writing object to file \\\" + filename);\\n/* 96 */ e.printStackTrace(); }\\n/* 97 */ return null;\\n/* */ }\",\n \"private void writeMapToFile() {\\r\\n\\t\\ttry {\\r\\n\\t\\t\\tString dm = gson.toJson(daoMap);// gson.toJson(entity);\\r\\n\\t\\t\\tFileWriter fileWriter = new FileWriter(path);\\r\\n\\t\\t\\t\\r\\n\\t\\t\\tfileWriter.write(dm);\\r\\n\\t\\t\\tfileWriter.close();\\r\\n\\t\\t} catch (Exception e) {\\r\\n\\t\\t\\te.printStackTrace();\\r\\n\\t\\t}\\r\\n\\t}\",\n \"static void WriteEmployeeObjectIntoFile(Employee emp,String filename)\\n\\t{\\n\\t\\t\\n\\t try\\n\\t {\\n\\t FileOutputStream fileOut =\\n\\t new FileOutputStream(filename);\\n\\t ObjectOutputStream out = new ObjectOutputStream(fileOut);\\n\\t //Main write method\\n\\t out.writeObject(emp);\\n\\t out.close();\\n\\t fileOut.close();\\n\\t System.out.printf(\\\"Serialized data is saved in \\\" + filename);\\n\\t }catch(IOException i)\\n\\t {\\n\\t i.printStackTrace();\\n\\t }\\n\\t}\",\n \"public boolean saveJson(String pathFile) {\\n try {\\n jsonObject.put(\\\"namespace\\\", this.numNamespace);\\n jsonObject.put(\\\"class\\\", this.numClasses);\\n jsonObject.put(\\\"interface\\\", this.numInterfaces);\\n jsonObject.put(\\\"method\\\", this.numMethods);\\n jsonObject.put(\\\"enumItem\\\", this.numEnumItem);\\n jsonObject.put(\\\"enum\\\", this.numEnum);\\n jsonObject.put(\\\"page\\\", this.numLinks);\\n jsonObject.put(\\\"Classes\\\", classlist);\\n jsonObject.put(\\\"Interfaces\\\", interfacelist);\\n jsonObject.put(\\\"Enum\\\", enumlist);\\n FileWriter file = new FileWriter(pathFile + this.fileName + \\\".json\\\");\\n file.write(jsonObject.toJSONString());\\n file.flush();\\n file.close();\\n return true;\\n } catch (IOException e) {\\n return false;\\n }\\n }\",\n \"String toJson() throws IOException;\",\n \"public void writeObject(Object obj) throws IOException;\",\n \"private static void saveJsonFile() {\\n Log.println(Log.INFO, \\\"FileAccessing\\\", \\\"Writing settings file.\\\");\\n JsonObject toSave = new JsonObject();\\n JsonArray mappingControls = new JsonArray();\\n for (int i = 0; i < TaskDetail.actionToTask.size(); i++) {\\n JsonObject individualMapping = new JsonObject();\\n TaskDetail detail = TaskDetail.actionToTask.valueAt(i);\\n byte combinedAction = (byte) TaskDetail.actionToTask.keyAt(i);\\n assert detail != null;\\n int outerControl = detail.getTask();\\n individualMapping.addProperty(\\\"combinedAction\\\", combinedAction);\\n individualMapping.addProperty(\\\"task\\\", outerControl);\\n mappingControls.add(individualMapping);\\n }\\n toSave.add(\\\"mappingControls\\\", mappingControls);\\n\\n JsonArray generalSettings = new JsonArray();\\n for (SettingDetail setting : SettingDetail.settingDetails) {\\n JsonObject individualSetting = new JsonObject();\\n int status = setting.getCurrentIdx();\\n individualSetting.addProperty(\\\"status\\\", status);\\n generalSettings.add(individualSetting);\\n }\\n toSave.add(\\\"generalSettings\\\", generalSettings);\\n\\n JsonArray deviceList = new JsonArray();\\n for (DeviceDetail device : DeviceDetail.deviceDetails) {\\n JsonObject individualDevice = new JsonObject();\\n individualDevice.addProperty(\\\"name\\\", device.deviceName);\\n individualDevice.addProperty(\\\"mac\\\", device.macAddress);\\n deviceList.add(individualDevice);\\n }\\n toSave.add(\\\"devices\\\", deviceList);\\n\\n JsonArray sensitivityList = new JsonArray();\\n for (SensitivitySetting sensitivity : SensitivitySetting.sensitivitySettings) {\\n JsonObject individualSensitivity = new JsonObject();\\n individualSensitivity.addProperty(\\\"factor\\\", sensitivity.multiplicativeFactor);\\n individualSensitivity.addProperty(\\\"sensitivity\\\", sensitivity.sensitivity);\\n sensitivityList.add(individualSensitivity);\\n }\\n toSave.add(\\\"sensitivities\\\", sensitivityList);\\n\\n toSave.addProperty(\\\"currentlySelected\\\", DeviceDetail.getIndexSelected());\\n\\n try {\\n FileOutputStream outputStreamWriter = context.openFileOutput(\\\"settingDetails.json\\\", Context.MODE_PRIVATE);\\n outputStreamWriter.write(toSave.toString().getBytes());\\n outputStreamWriter.close();\\n } catch (IOException e) {\\n Log.println(Log.ERROR, \\\"FileAccessing\\\", \\\"Settings file writing error.\\\");\\n }\\n }\",\n \"private void save(String fileName, String json){\\n mJSonNotifications = getSharedPreferences(fileName, MODE_PRIVATE);\\n mJSonNotifications.edit().putString(fileName, json).apply();\\n }\",\n \"public static void saveTestSequenceToJson(TestSequenceList testSequenceList, String absoluteFilePath) {\\n Gson gson = new GsonBuilder().enableComplexMapKeySerialization().setPrettyPrinting().create();\\r\\n String jsonString = gson.toJson(testSequenceList);\\r\\n try {\\r\\n FileWriter fileWriter = new FileWriter(absoluteFilePath);\\r\\n fileWriter.write(jsonString);\\r\\n System.out.println(\\\"File saved successfully\\\");\\r\\n fileWriter.close();\\r\\n } catch (IOException e) {\\r\\n e.printStackTrace();\\r\\n }\\r\\n }\",\n \"public static File writeObjectToFileNoExceptions(Serializable o, String filename)\\n/* */ {\\n/* 47 */ file = null;\\n/* 48 */ ObjectOutputStream oos = null;\\n/* */ try {\\n/* 50 */ file = new File(filename);\\n/* */ \\n/* 52 */ oos = new ObjectOutputStream(new BufferedOutputStream(new GZIPOutputStream(new FileOutputStream(file))));\\n/* 53 */ oos.writeObject(o);\\n/* 54 */ oos.close();\\n/* */ \\n/* */ \\n/* */ \\n/* */ \\n/* */ \\n/* */ \\n/* */ \\n/* */ \\n/* */ \\n/* */ \\n/* 65 */ return file;\\n/* */ }\\n/* */ catch (Exception e)\\n/* */ {\\n/* 56 */ e.printStackTrace();\\n/* */ } finally {\\n/* 58 */ if (oos != null) {\\n/* */ try {\\n/* 60 */ oos.close();\\n/* */ }\\n/* */ catch (Exception ioe) {}\\n/* */ }\\n/* */ }\\n/* */ }\",\n \"public void serialize(JsonObject dest);\",\n \"public void writeToJSON(String filePath) throws IOException {\\n try (PrintWriter pw = new PrintWriter(filePath)) {\\n pw.printf(\\\"{\\\\n\\\\t\\\\\\\"patients\\\\\\\": [\\\\n\\\");\\n for (int i = 0; i < dataFrame.getRowCount(); i++) {\\n pw.printf(\\\"\\\\t\\\\t{\\\\n\\\");\\n Iterator<String> it = dataFrame.getColumnNames().iterator();\\n while (it.hasNext()){\\n String colName = it.next();\\n if (it.hasNext())\\n pw.printf(\\\"\\\\t\\\\t\\\\t\\\\\\\"%s\\\\\\\":\\\\\\\"%s\\\\\\\",\\\\n\\\", colName, dataFrame.getValue(colName, i));\\n else\\n pw.printf(\\\"\\\\t\\\\t\\\\t\\\\\\\"%s\\\\\\\":\\\\\\\"%s\\\\\\\"\\\\n\\\", colName, dataFrame.getValue(colName, i));\\n }\\n if (i+1<dataFrame.getRowCount())\\n pw.printf(\\\"\\\\t\\\\t},\\\\n\\\");\\n else\\n pw.printf(\\\"\\\\t\\\\t}\\\\n\\\\t]\\\\n\\\");\\n }\\n pw.printf(\\\"}\\\\n\\\");\\n }\\n }\",\n \"private void save() {\\n if (mCacheFile.exists()) {\\n mCacheFile.delete();\\n }\\n\\n try (JsonWriter writer = new JsonWriter(new BufferedWriter(new FileWriter(mCacheFile)))) {\\n writer.beginObject();\\n writer.name(PRINTER_LIST_NAMES.get(0));\\n writer.beginArray();\\n for (DiscoveredPrinter printer : mSavedPrinters) {\\n printer.write(writer);\\n }\\n writer.endArray();\\n writer.endObject();\\n } catch (NullPointerException | IOException e) {\\n Log.w(TAG, \\\"Error while storing to \\\" + mCacheFile, e);\\n }\\n }\",\n \"public void saveToDoList() {\\n try {\\n jsonWriter.open();\\n jsonWriter.write(toDoList);\\n jsonWriter.close();\\n\\n System.out.println(\\\"Saved \\\" + toDoList.getName() + \\\" to \\\" + JSON_STORE);\\n } catch (FileNotFoundException e) {\\n System.out.println(\\\"Unable to write to file: \\\" + JSON_STORE);\\n }\\n }\",\n \"public static void save(DSAGraph objToSave, String filename)\\n {\\n FileOutputStream fileStrm;\\n ObjectOutputStream objStrm;\\n\\n try\\n {\\n fileStrm = new FileOutputStream(filename); //Underlying stream\\n objStrm = new ObjectOutputStream(fileStrm); //Object serialization stream\\n objStrm.writeObject(objToSave); //Serialize and save to filename\\n objStrm.close();//Clean up\\n }\\n catch (Exception e)\\n { //should do more here\\n throw new IllegalArgumentException(\\\"Unable to save object to file: \\\" + e);\\n }\\n }\",\n \"private String convertToJSON(Object o) throws JsonProcessingException {\\n return new ObjectMapper().writeValueAsString(o);\\n }\",\n \"public void WriteJSON(Dog dog) {\\n\\n JSONObject dogDetails = new JSONObject();\\n\\n dogDetails.put(\\\"id\\\", (dList.size()));\\n dogDetails.put(\\\"name\\\", dog.getName());\\n dogDetails.put(\\\"race\\\", dog.getRace());\\n dogDetails.put(\\\"color\\\", dog.getColor());\\n dogDetails.put(\\\"domestic\\\", dog.getDomestic());\\n dogDetails.put(\\\"age\\\", dog.getAge());\\n dogDetails.put(\\\"gender\\\", dog.getGender());\\n dogDetails.put(\\\"size\\\", dog.getSize());\\n dogDetails.put(\\\"medicalRecords\\\", null);\\n dogDetails.put(\\\"quarantine\\\", \\\"No\\\");\\n\\n dogObject.put(\\\"dog\\\", dogDetails);\\n\\n //Add dog to Jsonlist\\n dogList.add(dogObject);\\n\\n //Add dog to ObjectList\\n this.dList.add(dog);\\n\\n //Write JSON file\\n try (FileWriter file = new FileWriter(\\\"dogs.json\\\")) {\\n\\n file.write(dogList.toJSONString());\\n file.flush();\\n\\n } catch (IOException e) {\\n e.printStackTrace();\\n }\\n\\n }\",\n \"public static void generarFicheroJSON(App aplicacion) throws IOException {\\n\\n ObjectMapper mapeador = new ObjectMapper();\\n\\n mapeador.configure(SerializationFeature.INDENT_OUTPUT, true);\\n\\n // Escribe en un fichero JSON el objeto que le pasamos\\n mapeador.writeValue(new File(\\\"./aplicaciones/\\\" + aplicacion.getNombre() + \\\".json\\\"), aplicacion);\\n\\n }\",\n \"public void writeObjectToFile(ClickerCounterModel[] temp) {\\n\\t\\ttry {\\n\\t\\t\\tGson gson = new Gson();\\n\\t\\t\\tString string = gson.toJson(temp);\\n\\t\\t\\tFileOutputStream outputStream = openFileOutput(filename,\\n\\t\\t\\t\\t\\tContext.MODE_PRIVATE);\\n\\t\\t\\toutputStream.write(string.getBytes());\\n\\t\\t\\toutputStream.close();\\n\\t\\t} catch (Exception e) {\\n\\t\\t\\te.printStackTrace();\\n\\t\\t}\\n\\t}\",\n \"String parseObjectToJson(Object obj);\",\n \"public String autocreateJSON(String filePath, JSONObject jsonObject) throws ExistException, UnderlyingStorageException, UnimplementedException {\\n \\t\\ttry {\\n \\t\\t\\tDocument doc=cspace266Hack_munge(jxj.json2xml(jsonObject));\\n \\t\\t\\tSystem.err.println(\\\"153 got \\\"+doc.asXML());\\n \\t\\t\\tReturnedURL url = conn.getURL(RequestMethod.POST,\\\"collectionobjects/\\\",doc);\\n \\t\\t\\tif(url.getStatus()>299 || url.getStatus()<200)\\n \\t\\t\\t\\tthrow new UnderlyingStorageException(\\\"Bad response \\\"+url.getStatus());\\n \\t\\t\\treturn url.getURLTail();\\n \\t\\t} catch (BadRequestException e) {\\n \\t\\t\\tthrow new UnderlyingStorageException(\\\"Service layer exception\\\",e);\\n \\t\\t} catch (InvalidXTmplException e) {\\n \\t\\t\\tthrow new UnimplementedException(\\\"Error in template\\\",e);\\n \\t\\t}\\n \\t}\",\n \"public String objectToJson(Object o){\\n Gson gson = new Gson();\\n String json = gson.toJson(o);\\n return json;\\n }\",\n \"public static boolean writeObjectToFile(Object obj, File f) {\\r\\n try {\\r\\n FileOutputStream fout = new FileOutputStream(f);\\r\\n ObjectOutputStream oos = new ObjectOutputStream(fout);\\r\\n oos.writeObject(obj);\\r\\n oos.close();\\r\\n } catch (Exception e) {\\r\\n System.out.println(\\\"Error writing Object to file: \\\"\\r\\n + e.getMessage());\\r\\n return false;\\r\\n }\\r\\n return true;\\r\\n }\",\n \"public interface JStorable {\\n\\t/**\\n\\t * Return the Object as an JSONObject\\n\\t */\\n\\tpublic JSONObject save();\\n\\t/**\\n\\t * Load the Object from a JSONObject\\n\\t * @param obj\\n\\t * \\t\\tThe JSONObject\\n\\t */\\n\\tpublic void load(JSONObject obj);\\n}\",\n \"private void writeToFile(String pathName,Object logs) {\\r\\n try {\\r\\n File save = new File(pathName);\\r\\n FileOutputStream fileOutputStream = new FileOutputStream(save);\\r\\n ObjectOutputStream objectOutputStream = new ObjectOutputStream(fileOutputStream);\\r\\n objectOutputStream.writeObject(logs);\\r\\n // System.out.println(\\\"write successful for\\\"+pathName);\\r\\n } catch (IOException e) {\\r\\n e.printStackTrace();\\r\\n }\\r\\n }\",\n \"public void write(JSONDocument doc,File fl){\\n try(FileWriter fw = new FileWriter(fl)){\\n fw.write(doc.toString());\\n fw.flush();\\n }catch(Exception ex){\\n ex.printStackTrace();\\n }\\n }\",\n \"private void saveToDir(String name, Object obj) {\\n\\t\\tFileOutputStream fileOut = null;\\n\\t\\ttry {\\n\\t\\t\\tfileOut = new FileOutputStream(this.dir + \\\"/\\\" + name);\\n\\t\\t\\tObjectOutputStream out = new ObjectOutputStream(fileOut);\\n\\t\\t\\tout.writeObject(obj);\\n\\t\\t\\tout.close();\\n\\t\\t\\tfileOut.close();\\n\\t\\t} catch (IOException e) {\\n\\t\\t\\tSystem.out.println(\\\"Error occurred while saving the index file: \\\" + name);\\n\\t\\t\\te.printStackTrace();\\n\\t\\t\\tSystem.exit(1);\\n\\t\\t}\\n\\t}\",\n \"void toJSON(Path path);\",\n \"public boolean save(Object o) {\\n if (o instanceof String) {\\n\\n JsonParser parser = new JsonParser();\\n\\n JsonElement jsonElement = null;\\n String jsonString = (String) o;\\n\\n try{\\n while(!jsonString.startsWith(\\\"{\\\")){\\n jsonString = jsonString.substring(1, jsonString.length()-2);\\n }\\n\\n jsonElement = parser.parse(jsonString);\\n dbClient.save(jsonElement.getAsJsonObject());\\n return true;\\n\\n }catch(Exception e){\\n e.printStackTrace();\\n return false;\\n }\\n\\n }\\n\\n return false;\\n }\",\n \"public void serializeObject(String fileName, Automobile automobile) {\\n try {\\n String path = System.getProperty(\\\"user.dir\\\");\\n String fileNameWithPath = path + File.separator + fileName;\\n if(DEBUG) {\\n System.out.printf(\\\" File Name with Path : %s\\\", fileNameWithPath);\\n }\\n FileOutputStream fileOut = new FileOutputStream(fileNameWithPath);\\n ObjectOutputStream out = new ObjectOutputStream(fileOut);\\n out.writeObject(automobile);\\n out.close();\\n fileOut.close();\\n System.out.printf(\\\"Serialized data is saved in automotive.ser %s%n\\\", fileName);\\n } catch (IOException i) {\\n i.printStackTrace();\\n }\\n }\",\n \"public static void save(Serializable data, String fileName) throws Exception {\\r\\n\\t\\ttry(ObjectOutputStream out = new ObjectOutputStream( Files.newOutputStream(Paths.get(fileName)) )) {\\r\\n\\t\\t\\tout.writeObject(data);\\r\\n\\t\\t}\\r\\n\\t}\",\n \"public void crearPrimerFichero(){\\n File f=new File(getApplicationContext().getFilesDir(),\\\"datos.json\\\");\\n // si no existe lo creo\\n if(!f.exists()) {\\n String filename = \\\"datos.json\\\";\\n String fileContents = \\\"[]\\\";\\n FileOutputStream outputStream;\\n\\n try {\\n outputStream = openFileOutput(filename, Context.MODE_PRIVATE);\\n outputStream.write(fileContents.getBytes());\\n outputStream.close();\\n } catch (Exception e) {\\n e.printStackTrace();\\n }\\n }\\n\\n }\",\n \"public void saveGame(String fileName){\\n try {\\n File file1 = new File(fileName);\\n FileOutputStream fileOutputStream = new FileOutputStream(file1);\\n ObjectOutputStream objectOutputStream = new ObjectOutputStream(fileOutputStream);\\n objectOutputStream.writeObject(this);\\n }catch (Exception e){\\n System.err.println(\\\"Error when saving file\\\");\\n }\\n }\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7685922","0.7182024","0.7159729","0.7137173","0.7057812","0.70540637","0.7053874","0.7003681","0.6954736","0.6898823","0.6881606","0.6876142","0.6826735","0.6755188","0.67119867","0.6710243","0.66534215","0.66483724","0.6613342","0.6548435","0.65134025","0.65053004","0.6435646","0.6428433","0.64227045","0.640159","0.64012986","0.6393006","0.638613","0.6371547","0.63695705","0.636046","0.63603544","0.6346562","0.63159305","0.62941784","0.6283597","0.62831455","0.6278853","0.6270947","0.625138","0.6244548","0.6243257","0.62135744","0.61912733","0.61713266","0.61698884","0.61684686","0.61576027","0.6152752","0.6103259","0.6099513","0.6088831","0.6067302","0.6062078","0.60598576","0.60543954","0.60519904","0.60390824","0.60383993","0.6034346","0.6012126","0.6011708","0.60072654","0.59989035","0.59986806","0.59970623","0.59934556","0.59718555","0.59684795","0.5959771","0.5956077","0.5955544","0.5951574","0.59496313","0.59426713","0.5922695","0.59179956","0.5913995","0.591144","0.5902395","0.59003776","0.5897416","0.5889253","0.5889145","0.588301","0.58726054","0.5837218","0.5834598","0.5833659","0.58324337","0.5832432","0.58291715","0.58149","0.58120763","0.5808438","0.57989734","0.5784852","0.57792753","0.5777469"],"string":"[\n \"0.7685922\",\n \"0.7182024\",\n \"0.7159729\",\n \"0.7137173\",\n \"0.7057812\",\n \"0.70540637\",\n \"0.7053874\",\n \"0.7003681\",\n \"0.6954736\",\n \"0.6898823\",\n \"0.6881606\",\n \"0.6876142\",\n \"0.6826735\",\n \"0.6755188\",\n \"0.67119867\",\n \"0.6710243\",\n \"0.66534215\",\n \"0.66483724\",\n \"0.6613342\",\n \"0.6548435\",\n \"0.65134025\",\n \"0.65053004\",\n \"0.6435646\",\n \"0.6428433\",\n \"0.64227045\",\n \"0.640159\",\n \"0.64012986\",\n \"0.6393006\",\n \"0.638613\",\n \"0.6371547\",\n \"0.63695705\",\n \"0.636046\",\n \"0.63603544\",\n \"0.6346562\",\n \"0.63159305\",\n \"0.62941784\",\n \"0.6283597\",\n \"0.62831455\",\n \"0.6278853\",\n \"0.6270947\",\n \"0.625138\",\n \"0.6244548\",\n \"0.6243257\",\n \"0.62135744\",\n \"0.61912733\",\n \"0.61713266\",\n \"0.61698884\",\n \"0.61684686\",\n \"0.61576027\",\n \"0.6152752\",\n \"0.6103259\",\n \"0.6099513\",\n \"0.6088831\",\n \"0.6067302\",\n \"0.6062078\",\n \"0.60598576\",\n \"0.60543954\",\n \"0.60519904\",\n \"0.60390824\",\n \"0.60383993\",\n \"0.6034346\",\n \"0.6012126\",\n \"0.6011708\",\n \"0.60072654\",\n \"0.59989035\",\n \"0.59986806\",\n \"0.59970623\",\n \"0.59934556\",\n \"0.59718555\",\n \"0.59684795\",\n \"0.5959771\",\n \"0.5956077\",\n \"0.5955544\",\n \"0.5951574\",\n \"0.59496313\",\n \"0.59426713\",\n \"0.5922695\",\n \"0.59179956\",\n \"0.5913995\",\n \"0.591144\",\n \"0.5902395\",\n \"0.59003776\",\n \"0.5897416\",\n \"0.5889253\",\n \"0.5889145\",\n \"0.588301\",\n \"0.58726054\",\n \"0.5837218\",\n \"0.5834598\",\n \"0.5833659\",\n \"0.58324337\",\n \"0.5832432\",\n \"0.58291715\",\n \"0.58149\",\n \"0.58120763\",\n \"0.5808438\",\n \"0.57989734\",\n \"0.5784852\",\n \"0.57792753\",\n \"0.5777469\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.86886233"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":13885,"cells":{"query":{"kind":"string","value":"No need for cleanup in a HashedIndex."},"document":{"kind":"string","value":"public void cleanup() {\n this.index = new TreeMap<String, PostingsList>();\n this.count = 0;\n }"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["@AfterClass\n\tpublic static void cleanIndex() {\n\t\tEntityTest et = new EntityTest(id, \"EntityTest\");\n\t\tRedisQuery.remove(et, id);\n\t}","void indexReset();","public void clear() {\n index.clear();\n }","private Reindex() {}","private Reindex() {}","void clearAllIndexes();","public H_index() {\n\t\tsuper();\n\t}","@Override\n\tpublic void clearIndex(String indexName) {\n\t\t\n\t}","public void onIndexReset();","@Override\n public void close()\n {\n notifyLegacyIndexOperationQueue();\n\n }","@Override\n\tpublic void unIndexObject(ModelKey obj) throws ASException {\n\t\t\n\t}","public void truncate() {\n\t\ttry {\n\t\t\t_reopenToken = _trackingIndexWriter.deleteAll();\n\t\t\tlog.warn(\"lucene index truncated\");\n\t\t} catch(IOException ioEx) {\n\t\t\tlog.error(\"Error truncating lucene index: {}\",ioEx.getMessage(),\n\t\t\t\t\t\t\t\t\t\t\t \t\t \t ioEx);\t\t\t\n\t\t} finally {\n\t\t\ttry {\n\t\t\t\t_indexWriter.commit(); \n\t\t\t} catch (IOException ioEx) {\n\t\t\t\tlog.error(\"Error truncating lucene index: {}\",ioEx.getMessage(),\n\t\t\t\t\t\t\t\t\t\t\t\t \t\t\t ioEx);\n\t\t\t}\n\t\t}\n\t}","@Override\n\tpublic void unIndexObject(String indexName, String key) throws ASException {\n\t\t\n\t}","@Test\n public void testIndexMaintenanceWithIndexOnMethodEntrySet() throws Exception {\n Index i1 = qs.createIndex(\"indx1\", IndexType.FUNCTIONAL, \"entries.value.getID\",\n SEPARATOR + \"portfolio.entrySet() entries\");\n CacheUtils.getCache();\n region = CacheUtils.getRegion(SEPARATOR + \"portfolio\");\n region.put(\"4\", new Portfolio(4));\n region.put(\"5\", new Portfolio(5));\n CompactRangeIndex ri = (CompactRangeIndex) i1;\n validateIndexForEntries(ri);\n }","@Test\n public void testIndexMaintenanceWithIndexOnMethodKeys() throws Exception {\n Index i1 = qs.createIndex(\"indx1\", IndexType.FUNCTIONAL, \"ks.toString\",\n SEPARATOR + \"portfolio.keys() ks\");\n CacheUtils.getCache();\n region = CacheUtils.getRegion(SEPARATOR + \"portfolio\");\n region.put(\"4\", new Portfolio(4));\n region.put(\"5\", new Portfolio(5));\n CompactRangeIndex ri = (CompactRangeIndex) i1;\n validateIndexForKeys(ri);\n }","private void cleanUp() {\n if (rehash()) {\n // If we rehashed, we needn't clean up (clean up happens as\n // a side effect).\n return;\n }\n\n if (size == 0) {\n // No live entries == nothing to clean.\n return;\n }\n\n // Clean log(table.length) entries picking up where we left off\n // last time.\n int index = clean;\n Object[] table = this.table;\n for (int counter = table.length; counter > 0; counter >>= 1,\n index = next(index)) {\n Object k = table[index];\n\n if (k == TOMBSTONE || k == null) {\n continue; // on to next entry\n }\n\n // The table can only contain null, tombstones and references.\n @SuppressWarnings(\"unchecked\")\n Reference<ThreadLocal<?>> reference\n = (Reference<ThreadLocal<?>>) k;\n if (reference.get() == null) {\n // This thread local was reclaimed by the garbage collector.\n table[index] = TOMBSTONE;\n table[index + 1] = null;\n tombstones++;\n size--;\n }\n }\n\n // Point cursor to next index.\n clean = index;\n }","private void ensureHashingIndexExists() {\n DB metadataDB = client.getDB(\"cacheManagerMetadata\");\n if (!metadataDB.collectionExists(\"hashingIndex\")) {\n DBCollection hashingIndex = metadataDB.getCollection(\"hashingIndex\");\n hashingIndex.createIndex(new BasicDBObject(\"hashValue\", 1),\n new BasicDBObject(\"unique\", 1));\n }\n }","@Test\n public void testIndexMaintenanceWithIndexOnMethodKeySet() throws Exception {\n Index i1 =\n qs.createIndex(\"indx1\", IndexType.FUNCTIONAL, \"ks.toString\",\n SEPARATOR + \"portfolio.keySet() ks\");\n CacheUtils.getCache();\n region = CacheUtils.getRegion(SEPARATOR + \"portfolio\");\n region.put(\"4\", new Portfolio(4));\n region.put(\"5\", new Portfolio(5));\n CompactRangeIndex ri = (CompactRangeIndex) i1;\n validateIndexForKeys(ri);\n }","@Test\n public void testIndexMaintenanceWithIndexOnMethodGetEntries() throws Exception {\n Index i1 = qs.createIndex(\"indx1\", IndexType.FUNCTIONAL, \"entries.value.getID\",\n SEPARATOR + \"portfolio.getEntries() entries\");\n CacheUtils.getCache();\n region = CacheUtils.getRegion(SEPARATOR + \"portfolio\");\n region.put(\"4\", new Portfolio(4));\n region.put(\"5\", new Portfolio(5));\n CompactRangeIndex ri = (CompactRangeIndex) i1;\n validateIndexForEntries(ri);\n }","@Override\n\tpublic void clearIndex(Class<? extends ModelKey> clazz) {\n\t\t\n\t}","public void close() throws IndexerException {\n\t\t//TODO\n\t\t\n\t}","public abstract void deselectAllIndexes();","@Override\n public void beforeRerunningIndexCreationQuery() {\n Thread th = new Thread(() -> {\n // Assert that the size of region is now 0\n assertTrue(region.size() == 0);\n region.put(\"\" + 8, new Portfolio(8));\n });\n th.start();\n ThreadUtils.join(th, 30 * 1000);\n assertTrue(region.size() == 1);\n }","@Test\n public void testIndexMaintenanceWithHeterogenousObjects() throws Exception {\n DefaultQueryService.TEST_QUERY_HETEROGENEOUS_OBJECTS = true;\n IndexManager.TEST_RANGEINDEX_ONLY = true;\n Cache cache = CacheUtils.getCache();\n qs = cache.getQueryService();\n region = CacheUtils.createRegion(\"portfolio1\", null);\n idSet.clear();\n Portfolio p = new Portfolio(4);\n region.put(\"4\", p);\n idSet.add(\"\" + p.getID());\n p = new Portfolio(5);\n region.put(\"5\", p);\n idSet.add(\"\" + p.getID());\n region.put(\"6\", 6);\n Index i1 =\n qs.createIndex(\"indx1\", IndexType.FUNCTIONAL, \"pf.getID()\", SEPARATOR + \"portfolio1 pf\");\n RangeIndex ri = (RangeIndex) i1;\n assertEquals(2, ri.valueToEntriesMap.size());\n Iterator itr = ri.valueToEntriesMap.values().iterator();\n while (itr.hasNext()) {\n RangeIndex.RegionEntryToValuesMap re2ValMap = (RangeIndex.RegionEntryToValuesMap) itr.next();\n assertEquals(1, re2ValMap.map.size());\n Object obj = re2ValMap.map.values().iterator().next();\n assertFalse(obj instanceof Collection);\n assertTrue(obj instanceof Portfolio);\n Portfolio pf = (Portfolio) obj;\n assertTrue(idSet.contains(String.valueOf(pf.getID())));\n }\n assertEquals(1, ri.undefinedMappedEntries.map.size());\n Map.Entry entry = (Map.Entry) ri.undefinedMappedEntries.map.entrySet().iterator().next();\n assertFalse(entry.getValue() instanceof Collection);\n assertTrue(entry.getValue() instanceof Integer);\n assertTrue(entry.getValue().equals(6));\n\n region.put(\"7\", 7);\n idSet.add(7);\n assertEquals(2, ri.undefinedMappedEntries.map.size());\n itr = ri.undefinedMappedEntries.map.entrySet().iterator();\n while (itr.hasNext()) {\n entry = (Map.Entry) itr.next();\n assertFalse(entry.getValue() instanceof Collection);\n assertTrue(entry.getValue() instanceof Integer);\n idSet.contains(entry.getValue());\n }\n\n region.remove(\"7\");\n idSet.remove(7);\n Index i2 =\n qs.createIndex(\"indx2\", IndexType.FUNCTIONAL, \"pf.pkid\", SEPARATOR + \"portfolio1 pf\");\n ri = (RangeIndex) i2;\n assertEquals(2, ri.valueToEntriesMap.size());\n itr = ri.valueToEntriesMap.values().iterator();\n while (itr.hasNext()) {\n RangeIndex.RegionEntryToValuesMap re2ValMap = (RangeIndex.RegionEntryToValuesMap) itr.next();\n assertEquals(1, re2ValMap.map.size());\n Object obj = re2ValMap.map.values().iterator().next();\n assertFalse(obj instanceof Collection);\n assertTrue(obj instanceof Portfolio);\n Portfolio pf = (Portfolio) obj;\n assertTrue(idSet.contains(String.valueOf(pf.getID())));\n }\n assertEquals(1, ri.undefinedMappedEntries.map.size());\n entry = (Map.Entry) ri.undefinedMappedEntries.map.entrySet().iterator().next();\n assertFalse(entry.getValue() instanceof Collection);\n assertTrue(entry.getValue() instanceof Integer);\n assertTrue(entry.getValue().equals(6));\n\n region.put(\"7\", 7);\n idSet.add(7);\n assertEquals(2, ri.undefinedMappedEntries.map.size());\n itr = ri.undefinedMappedEntries.map.entrySet().iterator();\n while (itr.hasNext()) {\n entry = (Map.Entry) itr.next();\n assertFalse(entry.getValue() instanceof Collection);\n assertTrue(entry.getValue() instanceof Integer);\n idSet.contains(entry.getValue());\n }\n }","@Override\n @Secured(SecurityRoles.ADMINISTRATOR)\n public void reindex() {\n revisionDao.deleteAll();\n // OK, launches a new indexation\n indexFromLatest();\n }","@Test\n @Ignore\n public void testDelete_Index() throws Exception {\n System.out.println(\"delete\");\n Index entity = TestUtils.getTestIndex();\n Identifier identifier = entity.getId();\n instance.create(entity);\n assertTrue(instance.exists(identifier));\n instance.delete(entity);\n assertFalse(instance.exists(identifier));\n }","public void flush() {\n synchronized (getLock()) {\n sIndexWritersCache.flush(this);\n sIndexReadersCache.removeIndexReader(this);\n }\n }","@Test\n public void testIndexMaintenanceWithIndexOnMethodGetKeys() throws Exception {\n Index i1 =\n qs.createIndex(\"indx1\", IndexType.FUNCTIONAL, \"ks.toString\",\n SEPARATOR + \"portfolio.getKeys() ks\");\n CacheUtils.getCache();\n region = CacheUtils.getRegion(SEPARATOR + \"portfolio\");\n region.put(\"4\", new Portfolio(4));\n region.put(\"5\", new Portfolio(5));\n CompactRangeIndex ri = (CompactRangeIndex) i1;\n validateIndexForKeys(ri);\n }","public void testCreIdx(){\r\n\t \r\n\t String dataDir = \"C:\\\\study\\\\Lucene\\\\Data\";\r\n\t String idxDir = \"C:\\\\study\\\\Lucene\\\\Index\";\r\n\t \r\n\t LuceneUtils.delAll(idxDir);\r\n\t \r\n\t CreateIndex ci = new CreateIndex();\r\n\t \r\n\t ci.Indexer(new File(idxDir), new File(dataDir));\r\n\t \r\n\t\t\r\n\t}","public ThreadSafeInvertedIndex() {\n\t\tsuper();\n\t\tthis.lock = new ReadWriteLock();\n\t}","@Test\n public void testCoh3733()\n {\n doSingleServerTest(\"IdxTestCoh3733\", new Runnable()\n {\n public void run()\n {\n NamedCache cache = getNamedCache(\"coh3733\");\n\n cache.addIndex(new IndexAwareExtractor()\n {\n public MapIndex createIndex(boolean fOrdered, Comparator comparator, Map mapIndex,\n BackingMapContext ctx)\n {\n MapIndex index = new SimpleMapIndex(this, false, null, ctx)\n {\n protected void removeInverseMapping(Map mapIndex, Object oIxValue, Object oKey)\n {\n Set setKeys = (Set) mapIndex.get(oIxValue);\n\n assertTrue(\"Attempted to remove non-existent index entry\",\n setKeys != null && setKeys.contains(oKey));\n super.removeInverseMapping(mapIndex, oIxValue, oKey);\n }\n };\n mapIndex.put(this, index);\n return index;\n }\n\n public MapIndex destroyIndex(Map mapIndex)\n {\n return (MapIndex) mapIndex.remove(this);\n }\n\n public Object extract(Object oTarget)\n {\n return oTarget;\n }\n }, false, null);\n cache.addMapListener(new MultiplexingMapListener()\n {\n protected void onMapEvent(MapEvent evt)\n {\n fail(\"Observed unexpected event: \" + evt);\n }\n });\n\n cache.remove(\"non-existent-key\");\n\n validateIndex(cache);\n }\n });\n }","@Test\n public void testIndexMaintenanceWithIndexOnMethodtoArray() throws Exception {\n Index i1 = qs.createIndex(\"indx1\", IndexType.FUNCTIONAL, \"pf.getID\",\n SEPARATOR + \"portfolio.toArray() pf\");\n assertTrue(i1 instanceof CompactRangeIndex);\n Cache cache = CacheUtils.getCache();\n region = CacheUtils.getRegion(SEPARATOR + \"portfolio\");\n region.put(\"4\", new Portfolio(4));\n region.put(\"5\", new Portfolio(5));\n CompactRangeIndex ri = (CompactRangeIndex) i1;\n validateIndexForValues(ri);\n }","void initiateRemoveIndexes(HarvestResultDTO harvestResult) throws DigitalAssetStoreException;","private void close() throws CorruptIndexException, IOException {\n\n\t\tidxWriter.forceMerge(1);\n\t\tidxWriter.commit();\n\t\tidxWriter.close();\n\t}","private void removeContentAfterIndexLink()\r\n \t{\r\n \t\tdeleteNodes(XPath.AFTER_INDEX_LINK.query);\r\n \t}","@Test\n public void testIndexMaintenanceWithIndexOnMethodValues() throws Exception {\n Index i1 = qs.createIndex(\"indx1\", IndexType.FUNCTIONAL, \"pf.getID\",\n SEPARATOR + \"portfolio.values() pf\");\n assertTrue(i1 instanceof CompactRangeIndex);\n Cache cache = CacheUtils.getCache();\n region = CacheUtils.getRegion(SEPARATOR + \"portfolio\");\n region.put(\"4\", new Portfolio(4));\n region.put(\"5\", new Portfolio(5));\n CompactRangeIndex ri = (CompactRangeIndex) i1;\n validateIndexForValues(ri);\n }","public void clear()\n\t\t{\n\t\t\tindices.clear();\n\t\t}","public void tIndex(IndexShort < O > index) throws Exception {\n File query = new File(testProperties.getProperty(\"test.query.input\"));\n File dbFolder = new File(testProperties.getProperty(\"test.db.path\"));\n\n int cx = 0;\n\n initIndex(index);\n //search(index, (short) 3, (byte) 3);\n //search(index, (short) 7, (byte) 1);\n //search(index, (short) 12, (byte) 3);\n \n search(index, (short) 1000, (byte) 1);\n\n search(index, (short) 1000, (byte) 3);\n\n search(index, (short) 1000, (byte) 10);\n \n search(index, (short) 1000, (byte) 50);\n \n long i = 0;\n // int realIndex = 0;\n // test special methods that only apply to\n // SynchronizableIndex\n \n\n // now we delete elements from the DB\n logger.info(\"Testing deletes\");\n i = 0;\n long max = index.databaseSize();\n while (i < max) {\n O x = index.getObject(i);\n OperationStatus ex = index.exists(x);\n assertTrue(ex.getStatus() == Status.EXISTS);\n assertTrue(ex.getId() == i);\n ex = index.delete(x);\n assertTrue(\"Status is: \" + ex.getStatus() + \" i: \" + i , ex.getStatus() == Status.OK);\n assertEquals(i, ex.getId());\n ex = index.exists(x); \n assertTrue( \"Exists after delete\" + ex.getStatus() + \" i \" + i, ex.getStatus() == Status.NOT_EXISTS);\n i++;\n }\n index.close();\n Directory.deleteDirectory(dbFolder);\n }","public void updateIndex() {\n int i = this.index;\n if (i == -1 || i > HashBiMap.this.size || !Objects.equal(HashBiMap.this.keys[this.index], this.key)) {\n this.index = HashBiMap.this.findEntryByKey(this.key);\n }\n }","public void clear() throws IOException {\n\t\tindexWriter.deleteAll();\n\t\tforceCommit();\n\t}","public void onIndexUpdate();","public void testIndexCosts() {\n this.classHandler.applyIndexes();\n }","LuceneMemoryIndex createLuceneMemoryIndex();","void stopIndexing();","public long index() {\n return manager.compactIndex();\n }","@Test\n public void testIndexMaintenanceWithIndexOnMethodAsSet() throws Exception {\n Index i1 = qs.createIndex(\"indx1\", IndexType.FUNCTIONAL, \"pf.getID\",\n SEPARATOR + \"portfolio.asSet() pf\");\n CacheUtils.getCache();\n region = CacheUtils.getRegion(SEPARATOR + \"portfolio\");\n region.put(\"4\", new Portfolio(4));\n region.put(\"5\", new Portfolio(5));\n CompactRangeIndex ri = (CompactRangeIndex) i1;\n validateIndexForValues(ri);\n }","public void afterIndexCreated(IndexService indexService) {\n\n }","@Override\r\n\tpublic void delete(int r_idx) throws Exception {\n\r\n\t}","public void deleteIndex() throws Exception {\n\n\t\tRetryingRunnable runnable = new RetryingRunnable() \n\t\t{\t\n\t\t\tpublic void run() throws Exception \n\t\t\t{\n\t\t\t\tIndexWriter w = createIndexWriter(true); // open for writing and close (make empty)\n\t\t\t\tw.deleteAll();\n\t\t\t\tw.commit();\n\t\t\t\tw.close(true);\n\t\t\t\t\n\t\t\t\tDirectory dir = getIndexDir();\n\t\t\t\tfor(String file: dir.listAll())\n\t\t\t\t{\n\t\t\t\t\tif( dir.fileExists(file) ) // still exits\n\t\t\t\t\t{\n\t\t\t\t\t\tdir.sync(file);\n\t\t\t\t\t\tdir.deleteFile(file);\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t\tdir.close();\n\t\t\t}\n\t\t\t\n\t\t\tpublic boolean handleException(Throwable e) \n\t\t\t{\n\t\t\t\treturn true;\n\t\t\t}\n\t\t};\n\t\t\n\t\tchangeListener.onIndexReset(); // close searcher because index is deleted\n\t\t\n\t\trunRetryingRunnable(runnable); // delete index with retry\n\t}","private void syncIndex(FundamentalData fd) throws Exception {\n\n List<MarketIndex> indexes = marketIndexService.findBySymbol(fd.getSymbol());\n if(indexes.size()>1){\n throw new Exception(\"Multiple instances (\"+indexes.size()+\") of symbol \"+fd.getSymbol()+\" present in the database.\");\n }\n\n MarketIndex index;\n if(indexes.size()==0){ // does not exist in db\n index=new MarketIndex();\n index.setSymbol(fd.getSymbol());\n index.setName(fd.getName());\n index.setCategory(fd.getType().getCode());\n\n }else{ // index exists in db\n index = indexes.get(0);\n if(fd.getName()!=null){\n index.setName(fd.getName());\n }\n if(fd.getType()!=null){\n index.setCategory(fd.getType().getCode());\n }\n\n }\n\n updateIcon(index);\n marketIndexService.update(index);\n\n }","@Test\n public void testIndexMaintenanceWithIndexOnMethodGetValues() throws Exception {\n Index i1 =\n qs.createIndex(\"indx1\", IndexType.FUNCTIONAL, \"pf.getID\",\n SEPARATOR + \"portfolio.getValues() pf\");\n assertTrue(i1 instanceof CompactRangeIndex);\n Cache cache = CacheUtils.getCache();\n region = CacheUtils.getRegion(SEPARATOR + \"portfolio\");\n region.put(\"4\", new Portfolio(4));\n region.put(\"5\", new Portfolio(5));\n CompactRangeIndex ri = (CompactRangeIndex) i1;\n validateIndexForValues(ri);\n }","@Test\n public void testIndexMaintenanceOnCacheLoadedData() throws Exception {\n IndexManager.TEST_RANGEINDEX_ONLY = true;\n Cache cache = CacheUtils.getCache();\n qs = cache.getQueryService();\n region = CacheUtils.createRegion(\"portfolio1\", null);\n AttributesMutator am = region.getAttributesMutator();\n am.setCacheLoader(new CacheLoader() {\n\n @Override\n public Object load(LoaderHelper helper) throws CacheLoaderException {\n String key = (String) helper.getKey();\n Portfolio p = new Portfolio(Integer.parseInt(key));\n return p;\n }\n\n @Override\n public void close() {\n // nothing\n }\n });\n\n Index i1 =\n qs.createIndex(\"indx1\", IndexType.FUNCTIONAL, \"pf.getID()\", SEPARATOR + \"portfolio1 pf\");\n List keys = new ArrayList();\n keys.add(\"1\");\n keys.add(\"2\");\n keys.add(\"3\");\n keys.add(\"4\");\n\n region.getAll(keys);\n }","private void flushCurrentIndexBlock() throws IOException {\n if (currentMemoryIndex.documentsInIndex() < 1) {\n return;\n }\n\n logger.info(\"Flushing current memory Index. id = \" + indexBlockCount);\n\n final MemoryIndex flushingMemoryIndex = currentMemoryIndex;\n final File shardFolder = getNextIndexShardFolder(1);\n\n try {\n // reset the current index\n // - this makes the flush operation thread safe while continuing to add new documents.\n resetCurrentMemoryIndex();\n } catch (Exception ex) {\n throw new IOException(ex);\n }\n\n try {\n // first flush the index to disk\n FlushToDisk.flushMemoryIndex(flushingMemoryIndex, shardFolder.getAbsolutePath(), false);\n\n // indicate that the flushing part of this thread is done\n synchronized (geometricParts) {\n // add flushed index to the set of bins -- needs to be a synconeous action\n geometricParts.add(0, shardFolder.getAbsolutePath());\n updateIndex();\n flushingMemoryIndex.close();\n }\n\n } catch (IOException e) {\n logger.severe(e.toString());\n }\n }","@Override\n protected void cleanup(Context context) throws IOException, InterruptedException {\n logger.info(\"Cleanup\");\n super.cleanup(context);\n for (java.util.Map.Entry<String, FullImageMetadata> entry : indexer.getEntries().entrySet()) {\n String surt = entry.getKey();\n context.write(new Text(surt), entry.getValue());\n }\n }","public void close() {\n\t\t\n\t\ttry {\n\t\t\tindexWriter.optimize();\n\t\t\t\n\t\t\tindexWriter.close();\n\t\t\t\n\t\t\tIndexSearcher = new IndexSearcher(idx);\n\t\t\t\n\t\t} catch (CorruptIndexException e) {\n\t\t\t// TODO Auto-generated catch block\n\t\t\te.printStackTrace();\n\t\t} catch (IOException e) {\n\t\t\t// TODO Auto-generated catch block\n\t\t\te.printStackTrace();\n\t\t}\n\t\t\n\t\t\n\t}","@Test\n public void testIndexMaintenanceOnPutAll() throws Exception {\n IndexManager.TEST_RANGEINDEX_ONLY = true;\n Cache cache = CacheUtils.getCache();\n qs = cache.getQueryService();\n region = CacheUtils.createRegion(\"portfolio1\", null);\n region.put(\"1\", new Portfolio(1));\n Index i1 = qs.createIndex(\"indx1\", IndexType.FUNCTIONAL, \"posvals.secId\",\n SEPARATOR + \"portfolio1 pf, pf.positions.values posvals \");\n Map data = new HashMap();\n for (int i = 1; i < 11; ++i) {\n data.put(\"\" + i, new Portfolio(i + 2));\n }\n\n region.putAll(data);\n }","public void clear(long index);","public Object migrateWords2index(String wordhash) throws IOException {\n File db = plasmaWordIndexFile.wordHash2path(oldDatabaseRoot, wordhash);\r\n if (!(db.exists())) return \"not available\";\r\n plasmaWordIndexFile entity = null;\r\n try {\r\n entity = new plasmaWordIndexFile(oldDatabaseRoot, wordhash, true);\r\n int size = entity.size();\r\n indexContainer container = new indexContainer(wordhash, payloadrow(), useCollectionIndex);\r\n \r\n try {\r\n Iterator entries = entity.elements(true);\r\n indexRWIEntry entry;\r\n while (entries.hasNext()) {\r\n entry = (indexRWIEntry) entries.next();\r\n // System.out.println(\"ENTRY = \" + entry.getUrlHash());\r\n container.add(new indexRWIEntry[] { entry }, System.currentTimeMillis());\r\n }\r\n // we have read all elements, now delete the entity\r\n entity.deleteComplete();\r\n entity.close();\r\n entity = null;\r\n \r\n indexContainer feedback = collections.addEntries(container, container.updated(), false);\r\n if (feedback != null) return feedback;\r\n return new Integer(size);\r\n } catch (kelondroException e) {\r\n // database corrupted, we simply give up the database and delete it\r\n try { entity.close(); } catch (Exception ee) { }\r\n entity = null;\r\n try { db.delete(); } catch (Exception ee) { }\r\n return \"database corrupted; deleted\";\r\n }\r\n } finally {\r\n if (entity != null) try {entity.close();}catch(Exception e){}\r\n }\r\n }","public abstract void updateIndex();","public void close() throws IndexException {\n }","public void refresh() {\n getIndexOperations().refresh();\n }","public interface FieldIndex<T> extends GenericIndex<T> \r\n{ \r\n /**\r\n * Put new object in the index. \r\n * @param obj object to be inserted in index. Object should contain indexed field. \r\n * Object can be not yet peristent, in this case\r\n * its forced to become persistent by assigning OID to it.\r\n * @return <code>true</code> if object is successfully inserted in the index, \r\n * <code>false</code> if index was declared as unique and there is already object with such value\r\n * of the key in the index. \r\n */\r\n public boolean put(T obj);\r\n\r\n /**\r\n * Associate new object with the key specified by object field value. \r\n * If there is already object with such key in the index, \r\n * then it will be removed from the index and new value associated with this key.\r\n * @param obj object to be inserted in index. Object should contain indexed field. \r\n * Object can be not yet peristent, in this case\r\n * its forced to become persistent by assigning OID to it.\r\n * @return object previously associated with this key, <code>null</code> if there was no such object\r\n */\r\n public T set(T obj);\r\n\r\n /**\r\n * Assign to the integer indexed field unique autoicremented value and \r\n * insert object in the index. \r\n * @param obj object to be inserted in index. Object should contain indexed field\r\n * of integer (<code>int</code> or <code>long</code>) type.\r\n * This field is assigned unique value (which will not be reused while \r\n * this index exists) and object is marked as modified.\r\n * Object can be not yet peristent, in this case\r\n * its forced to become persistent by assigning OID to it.\r\n * @exception StorageError(StorageError.INCOMPATIBLE_KEY_TYPE) when indexed field\r\n * has type other than <code>int</code> or <code>long</code>\r\n */\r\n public void append(T obj);\r\n\r\n /**\r\n * Remove object with specified key from the unique index\r\n * @param key value of removed key\r\n * @return removed object\r\n * @exception StorageError(StorageError.KEY_NOT_FOUND) exception if there is no such key in the index,\r\n * or StorageError(StorageError.KEY_NOT_UNIQUE) if index is not unique.\r\n */\r\n public T remove(Key key);\r\n\r\n /**\r\n * Remove object with specified key from the unique index\r\n * @param key value of removed key\r\n * @return removed object\r\n * @exception StorageError(StorageError.KEY_NOT_FOUND) exception if there is no such key in the index,\r\n * or StorageError(StorageError.KEY_NOT_UNIQUE) if index is not unique.\r\n */\r\n public T removeKey(Object key);\r\n\r\n /**\r\n * Check if index contains specified object instance.\r\n * @param obj object to be searched in the index. Object should contain indexed field. \r\n * @return <code>true</code> if object is present in the index, <code>false</code> otherwise\r\n */\r\n public boolean containsObject(T obj);\r\n\r\n /**\r\n * Locate objects with the same value of the key as specified object\r\n * @param obj object specifying search key value\r\n * @return selection iterator\r\n */\r\n public IterableIterator<T> queryByExample(T obj);\r\n\r\n /**\r\n * Get class obejct objects which can be inserted in this index\r\n * @return class specified in Storage.createFielIndex method\r\n */\r\n public Class getIndexedClass();\r\n\r\n /**\r\n * Get fields used as a key\r\n * @return array of index key fields\r\n */\r\n public Field[] getKeyFields();\r\n\r\n /**\r\n * Select members of the collection using search predicate\r\n * This iterator doesn't support remove() method.\r\n * To make it possible to update, remove or add members to the index \r\n * during iteration it is necessary to set \"perst.concurrent.iterator\"\r\n * property (by default it is not supported because it cause extra overhead during iteration)\r\n * @param predicate JSQL condition\r\n * @return iterator through members of the collection matching search condition\r\n */\r\n public IterableIterator<T> select(String predicate);\r\n\r\n /**\r\n * Check if field index is case insensitive\r\n * @return true if index ignore case of string keys\r\n */\r\n boolean isCaseInsensitive(); \r\n}","public void finishedDirectIndexBuild()\n\t{\n\t\tif(logger.isInfoEnabled()){\n\t\t\tlogger.info(\"flushing utf block lexicon to disk after the direct index completed\");\n\t\t}\n\t\t//only write a temporary lexicon if there are any items in it\n\t\tif (TempLex.getNumberOfNodes() > 0)\n\t\t\twriteTemporaryLexicon();\n\n\t\t//merges the temporary lexicons\n\t\tif (tempLexFiles.size() > 0)\n\t\t{\n\t\t\ttry{\n\t\t\t\tmerge(tempLexFiles);\n\t\n\t\t\t\t//creates the offsets file\n\t\t\t\tfinal String lexiconFilename = \n\t\t\t\t\tindexPath + ApplicationSetup.FILE_SEPARATOR + \n\t\t\t\t\tindexPrefix + ApplicationSetup.LEXICONSUFFIX;\n\t\t\t\tLexiconInputStream lis = getLexInputStream(lexiconFilename);\n\t\t\t\tcreateLexiconIndex(\n\t\t\t\t\tlis,\n\t\t\t\t\tlis.numberOfEntries(),\n\t\t\t\t\t/* after inverted index is built, the lexicon will be transformed into a\n\t\t\t\t\t * normal lexicon, without block frequency */\n\t\t\t\t\tUTFLexicon.lexiconEntryLength\n\t\t\t\t\t); \n\t\t\t\tTermCount = lis.numberOfEntries();\n\t\t\t\tif (index != null)\n\t\t\t\t{\n\t\t\t\t\tindex.addIndexStructure(\"lexicon\", \"uk.ac.gla.terrier.structures.UTFBlockLexicon\");\n\t\t\t\t\tindex.addIndexStructureInputStream(\"lexicon\", \"uk.ac.gla.terrier.structures.UTFBlockLexiconInputStream\");\n\t\t\t\t\tindex.setIndexProperty(\"num.Terms\", \"\"+lis.numberOfEntries());\n\t\t\t\t\tindex.setIndexProperty(\"num.Pointers\", \"\"+lis.getNumberOfPointersRead());\n\t\t\t\t}\n\t\t\t} catch(IOException ioe){\n\t\t\t\tlogger.error(\"Indexing failed to write a lexicon index file to disk\", ioe);\n\t\t\t}\t\n\t\t}\n\t\telse\n\t\t\tlogger.warn(\"No temporary lexicons to merge, skipping\");\n\t\t\n\t}","private IndexingManager() {\n Provider provider = new BouncyCastleProvider();\n Security.addProvider(provider);\n utility = Database_Utility.getInstance();\n conn = utility.getConnection();\n IMbuffer = IndexingManagerBuffer.getInstance();\n\n // This statement is to create purge table.\n\n boolean k = checkTable1(\"PurgeTable\");\n if (!k) {\n utility.createtable2(\"PurgeTable\");\n }\n boolean k1 = checkTable1(\"UserToCertMap\");\n if (!k1) {\n utility.createtable1();\n }\n\n // This statement is to run maintenance thread on loading of class to purge entries whose timer has expired.\n\n //maintenancethread();\n\n // This statement is to run maintenance thread on loading of class to ascertain root nodes.\n\n // maintenancethread1();\n\n // This statement is to run maintenance thread on loading of class to delete entries from purge table.\n\n // maintenancethread2();\n\n }","protected void removeFromIndex(SimpleFeature feature) {\n\t\tif (feature==null) return;\n\t\t\n\t\t// ID Index\n\t\tidIndex.remove( feature.getID() );\n\t\t\n\t\t// Type name index\n\t\tName type = feature.getType().getName();\n\t\tSet<SimpleFeature> prev = typeNameIndex.get(type);\n\t\tif ( prev.remove( feature ) ) {\n\t\t\tif (prev.size()>0) {\n\t\t\t\ttypeNameIndex.put(type,prev);\n\t\t\t} else {\n\t\t\t\ttypeNameIndex.remove(type);\n\t\t\t}\n\t\t}\n\t\t\n\t\t// Tile Index\n\t\tif (feature.getID().matches(\".*-[0-9]+-[0-9]+-[0-9]+\")) {\n\t\t\tOSMTile tile = new OSMTile(feature.getID());\n\t\t\tprev = tileIndex.get( tile );\n\t\t\tif ( prev.remove( feature ) ) {\n\t\t\t\tif (prev.size()>0) {\n\t\t\t\t\ttileIndex.put(tile, prev);\n\t\t\t\t} else {\n\t\t\t\t\ttileIndex.remove(type);\n\t\t\t\t}\n\t\t\t}\n\t\t} else {\n\t\t\t// Whatever for features\n\t\t}\n\t}","public void beforeIndexClosed(IndexService indexService) {\n\n }","@Test\n public void testIndexMaintenanceWithIndexOnMethodAsList() throws Exception {\n Index i1 = qs.createIndex(\"indx1\", IndexType.FUNCTIONAL, \"pf.getID\",\n SEPARATOR + \"portfolio.asList() pf\");\n CacheUtils.getCache();\n region = CacheUtils.getRegion(SEPARATOR + \"portfolio\");\n region.put(\"4\", new Portfolio(4));\n region.put(\"5\", new Portfolio(5));\n CompactRangeIndex ri = (CompactRangeIndex) i1;\n validateIndexForValues(ri);\n }","private void readIndex() throws IOException {\n\t\t\tif (this.keys != null)\n\t\t\t\treturn;\n\t\t\tkeys = new HashMap<K, Long>(1024);\n\t\t\ttry {\n\t\t\t\twhile (index.hasNext()) {\n\t\t\t\t\tPair<K, Long> pair;// = new Pair<K, Long>(index.getSchema());\n\t\t\t\t\tpair = index.next();\n\t\t\t\t\tkeys.put(pair.key(), pair.value());\n\t\t\t\t\tif (firstKey == null)\n\t\t\t\t\t\tfirstKey = pair.key();\n\t\t\t\t\tfinalKey = pair.key();\n\t\t\t\t\tcount++;\n\t\t\t\t}\n\n\t\t\t}finally {\n\t\t\t\tindexClosed = true;\n\t\t\t\tindex.close();\n\t\t\t}\n\t\t}","@Override\n public void reindexImpl()\n {\n List<StoreRef> storeRefs = nodeService.getStores();\n int count = 0;\n for (StoreRef storeRef : storeRefs)\n {\n // prompt the FTS reindexing\n if (!ftsIndexerCalled)\n {\n ftsIndexer.requiresIndex(storeRef);\n }\n // reindex missing content\n count += reindexMissingContent(storeRef);\n // check if we have to break out\n if (isShuttingDown())\n {\n break;\n }\n }\n \n // The FTS indexer only needs to be prompted once\n ftsIndexerCalled = true;\n\n // done\n if (logger.isDebugEnabled())\n {\n logger.debug(\"Missing content indexing touched \" + count + \" content nodes\");\n }\n }","@Override\n public void close() throws IOException {\n flushCurrentIndexBlock();\n\n // logger.info(\"Performing final merge\");\n // try {\n //Bin finalMergeBin = geometricParts.getAllShards();\n //doMerge(finalMergeBin, getNextIndexShardFolder(finalMergeBin.size + 1));\n // check point is updated by the merge op.\n\n // } catch (IOException ex) {\n // Logger.getLogger(GeometricRetrieval.class.getName()).log(Level.SEVERE, null, ex);\n //}\n\n }","public interface IndexBuilder {\n\n /**\n * Rebuilds the index only when the existing index is not populated.\n */\n void rebuildIfNecessary();\n\n}","@Override\n protected boolean preserveIndicesUponCompletion() {\n return true;\n }","private static void deleteTest() throws SailException{\n\n\t\tString dir2 = \"repo-temp\";\n\t\tSail sail2 = new NativeStore(new File(dir2));\n\t\tsail2 = new IndexingSail(sail2, IndexManager.getInstance());\n\t\t\n//\t\tsail.initialize();\n\t\tsail2.initialize();\n\t\t\n//\t\tValueFactory factory = sail2.getValueFactory();\n//\t\tCloseableIteration<? extends Statement, SailException> statements = sail2\n//\t\t\t\t.getConnection().getStatements(null, null, null, false);\n\n\t\tSailConnection connection = sail2.getConnection();\n\n\t\tint cachesize = 1000;\n\t\tint cached = 0;\n\t\tlong count = 0;\n\t\tconnection.removeStatements(null, null, null, null);\n//\t\tconnection.commit();\n\t}","public Object preparePut(Object object)\r\n {\n FullUniqueIndex perThreadAddedIndex = new FullUniqueIndex(this.hashStrategy);\r\n perThreadAddedIndex.setUnderlyingObjectGetter(transactionalUnderlyingObjectGetter);\r\n perThreadAddedIndex.putUsingUnderlying(object, ((MithraTransactionalObject) object).zGetNonTxData());\r\n synchronized (this.preparedIndices)\r\n {\r\n this.preparedIndices.add(perThreadAddedIndex);\r\n }\r\n return perThreadAddedIndex;\r\n }","public void destroy() {\n //Write hit count to DB!!\n }","private void resetCurrentMemoryIndex() throws Exception {\n // by using the globalParameters, the memory index can startup counters etc.\n // we set the documentCount to ensure all documents are given a unique number.\n tupleFlowParameters.getJSON().set(\"documentNumberOffset\", this.globalDocumentCount);\n currentMemoryIndex = new MemoryIndex(tupleFlowParameters);\n }","@Test\n public void testIndexCreationThreshold() throws Exception {\n SchemaModel sm;\n //\n // sm = Util.loadSchemaModel2(\"resources/performance2/B.xsd\"); // NOI18N\n sm = Util.loadSchemaModel2(\"resources/performance2.zip\", \"B.xsd\"); // NOI18N\n //\n assertTrue(sm.getState() == State.VALID);\n //\n assertTrue(sm instanceof SchemaModelImpl);\n SchemaModelImpl smImpl = SchemaModelImpl.class.cast(sm);\n GlobalComponentsIndexSupport indexSupport = smImpl.getGlobalComponentsIndexSupport();\n assertNotNull(indexSupport);\n GlobalComponentsIndexSupport.JUnitTestSupport testSupport =\n indexSupport.getJUnitTestSupport();\n assertNotNull(testSupport);\n //\n // Initiate index building\n GlobalElement found = sm.findByNameAndType(\"B000\", GlobalElement.class);\n assertNotNull(found);\n Thread.sleep(500); // Wait the index is build\n //\n assertTrue(testSupport.isSupportIndex());\n int indexSise = testSupport.getIndexSize();\n assertEquals(indexSise, 90);\n //\n UndoManager um = new javax.swing.undo.UndoManager();\n AbstractDocumentModel.class.cast(sm).addUndoableEditListener(um);\n //\n sm.startTransaction();\n try {\n Schema schema = sm.getSchema();\n java.util.List<SchemaComponent> gChildren = schema.getChildren();\n int counter = 0;\n for (SchemaComponent child : gChildren) {\n //\n assertTrue(child instanceof GlobalElement);\n GlobalElement gElem = GlobalElement.class.cast(child);\n schema.removeElement(gElem);\n //\n counter++;\n if (counter >= 50) {\n break;\n }\n }\n } finally {\n sm.endTransaction();\n }\n //\n int childrenCount = sm.getSchema().getChildren().size();\n assertEquals(childrenCount, 40);\n assertFalse(testSupport.isSupportIndex());\n //\n //\n um.undo();\n //\n // Initiate index building again\n found = sm.findByNameAndType(\"B000\", GlobalElement.class);\n assertNotNull(found);\n Thread.sleep(500); // Wait the index is build\n //\n assertTrue(testSupport.isSupportIndex());\n indexSise = testSupport.getIndexSize();\n assertEquals(indexSise, 90);\n //\n System.out.println(\"=============================\"); // NOI18N\n System.out.println(\" testIndexCreationThreshold \"); // NOI18N\n System.out.println(\"=============LOG=============\"); // NOI18N\n String log = testSupport.printLog();\n System.out.print(log);\n System.out.println(\"=============================\"); // NOI18N\n //\n }","abstract void onIndexDisrupted(String caseId);","@Override\n public void cleanup() {\n \n }","@Override\n public void cleanup() {\n \n }","private void updateIndex() throws IOException {\n // maintain the document store (corpus) - if there is one\n if (currentMemoryIndex.containsPart(\"corpus\")) {\n // get all corpora + shove into document store\n ArrayList<DocumentReader> readers = new ArrayList<>();\n readers.add((DocumentReader) currentMemoryIndex.getIndexPart(\"corpus\"));\n for (String path : geometricParts.getAllShards().getBinPaths()) {\n String corpus = path + File.separator + \"corpus\";\n readers.add(new CorpusReader(corpus));\n }\n }\n // finally write new checkpointing data (checkpoints the disk indexes)\n Parameters checkpoint = createCheckpoint();\n this.checkpointer.saveCheckpoint(checkpoint);\n }","@Override\n public void visit(Index node) {\n }","@Override\r\n public ParaMap index(ParaMap inMap) throws Exception {\n return null;\r\n }","void commit() throws IndexTransactionException;","void remove(ThreadLocal<?> key) {\n cleanUp();\n\n for (int index = key.hash & mask;; index = next(index)) {\n Object reference = table[index];\n\n if (reference == key.reference) {\n // Success!\n table[index] = TOMBSTONE;\n table[index + 1] = null;\n tombstones++;\n size--;\n return;\n }\n\n if (reference == null) {\n // No entry found.\n return;\n }\n }\n }","public void beforeIndexCreated(Index index) {\n\n }","@Override\n\tpublic void clear() {\n\t\tsuper.clear();\n\t\tidIndex = new HashMap<String, SimpleFeature>();\n\t\ttypeNameIndex = new HashMap<Name, Set<SimpleFeature>>();\n\t\ttileIndex = new HashMap<OSMTile, Set<SimpleFeature>>();\n\t}","public void unIndex(final Term idTerm) {\n\t\ttry {\n\t\t\t_reopenToken = _trackingIndexWriter.deleteDocuments(idTerm);\n\t\t\tlog.debug(\"{}={} term matching records un-indexed from lucene\",idTerm.field(),\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t idTerm.text());\n\t\t} catch(IOException ioEx) {\n\t\t\tlog.error(\"Error in un-index lucene operation: {}\",ioEx.getMessage(),\n\t\t\t\t\t\t\t\t\t\t\t \t\t \t\t ioEx);\t\t\t\n\t\t} finally {\n\t\t\ttry {\n\t\t\t\t_indexWriter.commit(); \n\t\t\t} catch (IOException ioEx) {\n\t\t\t\tlog.error(\"Error while commiting changes to Lucene index: {}\",ioEx.getMessage(),\n\t\t\t\t\t\t\t\t\t\t\t\t \t\t \t\t\t\t\t ioEx);\n\t\t\t}\n\t\t}\n\t}","public void clear(){\n\t\tcontenido = getName() + ':';\n\t\tindices.clear();\n\t\tindices.add(0);\n\t}","@Override\n public void clear() {\n hashtableBean = null;\n\n hashtableBean = new HashTableBean[5];\n position = 0;\n }","private void deleteBuckets(Vector<Vector<String>> index) {\n //deserialize bucket from each position\n for (int i = 0; i < index.size(); i++) {\n if (index.get(i) != null) {\n for (int j = 0; j < index.get(i).size(); j++) {\n Utilities.removeFromDisk(index.get(i).get(j));\n }\n\n }\n\n }\n //loop on entries and insert\n }","public void cleanUp() {\n if(ticker.skipCleanup()) {\n return;\n } \n \n // At this point cleanup is inevitable, so linked list traversal should\n // be performed. \n Entry<K, V> e = segment.head();\n Entry<K, V> end = segment.tail();\n \n int processed = 0;\n long createThreshold = ticker.nextTick() - createTTL;\n long accessThreshold = ticker.nextTick() - accessTTL;\n\n Object removeKey = null;\n while ((e = e.getNext()) != end && processed++ < REMOVE_DEPTH) {\n if (null != removeKey) {\n segment.remove(removeKey);\n removeKey = null;\n }\n\n // both, access and creation thresholds might trigger entry removal \n if (e.getCreationTime() <= createThreshold || e.getAccessTime() <= accessThreshold) {\n removeKey = e.getKey();\n }\n }\n\n if (null != removeKey) {\n segment.remove(removeKey);\n } \n ticker.markCleanup();\n }","@org.junit.Test\n public void remove() throws Exception {\n assertEquals(null, hashTable.remove(\"savon\"));\n assertEquals(\"Yuliya\", hashTable.remove(\"Savon\"));\n assertEquals(null, hashTable.remove(\"Savon\"));\n\n for (int i = 0; i < 2_000_000; i++) {\n hashTable.put(Integer.toString(i), Integer.toString(i));\n }\n\n for (int i = 0; i < 2_000_000; i++) {\n String curValue = hashTable.remove(Integer.toString(i));\n assertEquals(Integer.toString(i), curValue);\n }\n }","@Test\n public void testDropIdxOnClient() {\n GridCacheDynamicLoadOnClientTest.srvNode.getOrCreateCache(DEFAULT_CACHE_NAME).query(new SqlFieldsQuery(((\"CREATE INDEX IDX_TST ON \" + (GridCacheDynamicLoadOnClientTest.FULL_TABLE_NAME)) + \" (name desc)\"))).getAll();\n // Due to client receive created index asynchronously we need add the ugly sleep.\n doSleep(2000);\n getDefaultCacheOnClient().query(new SqlFieldsQuery(((\"DROP INDEX \" + (GridCacheDynamicLoadOnClientTest.PERSON_SCHEMA)) + \".IDX_TST\"))).getAll();\n }","@Override\n\tpublic void indexObject(ModelKey obj) throws ASException {\n\t\t\n\t}","@Override\n public void ensureCapacity(int index) {\n\n }","public synchronized void recreateIndex()\n throws InterruptedException, CancellationException, ExecutionException, IOException, IndexServiceException {\n // Clear index first\n clear();\n recreateService(IndexRecreateObject.Service.Groups);\n recreateService(IndexRecreateObject.Service.Acl);\n recreateService(IndexRecreateObject.Service.Themes);\n recreateService(IndexRecreateObject.Service.Series);\n recreateService(IndexRecreateObject.Service.Scheduler);\n recreateService(IndexRecreateObject.Service.Workflow);\n recreateService(IndexRecreateObject.Service.AssetManager);\n recreateService(IndexRecreateObject.Service.Comments);\n }","@Override\r\n\tpublic void cleanup() {\n\t\t\r\n\t}","protected int index(int hashvalue) {\r\n\t\tint hash=hashvalue& 0x7fffffff;\r\n\t\tint index = this.hashFunc1(hash) * FREE.length;////获取一个整型数值（正整数），用来定位一条数据存储\r\n\t\t// int stepSize = hashFunc2(hash);\r\n\t\tbyte[] cur = new byte[4];\r\n\t\tkeys.position(index);\r\n\t\tkeys.get(cur);\r\n\t\tint storehash=(cur[0] << 24)+ ((cur[1] & 0xFF) << 16)+ ((cur[2] & 0xFF) << 8)+ (cur[3] & 0xFF);\r\n\t\tif (storehash==hash) {\r\n\t\t\treturn index;\r\n\t\t}\r\n\t\tif (Arrays.equals(cur, FREE)) {\r\n\t\t\treturn -1;\r\n\t\t}\r\n\r\n\t\t// NOTE: here it has to be REMOVED or FULL (some user-given value)\r\n\t\tif (Arrays.equals(cur, REMOVED) || storehash!=hash) {\r\n\t\t\t// see Knuth, p. 529\r\n\t\t\tfinal int probe = (1 + (hash % (size - 2))) * FREE.length;\r\n\t\t\tint z = 0;\r\n\t\t\tdo {\r\n\t\t\t\tz++;\r\n\t\t\t\tindex += (probe); // add the step\r\n\t\t\t\tindex %= (size * FREE.length); // for wraparound\r\n\t\t\t\tcur = new byte[FREE.length];\r\n\t\t\t\tkeys.position(index);\r\n\t\t\t\tkeys.get(cur);\r\n\t\t\t\tif (z > size) {\r\n\t\t\t\t\tSDFSLogger.getLog().info(\r\n\t\t\t\t\t\t\t\"entries exhaused size=\" + this.size + \" entries=\"\r\n\t\t\t\t\t\t\t\t\t+ this.entries);\r\n\t\t\t\t\treturn -1;\r\n\t\t\t\t}\r\n\t\t\t} while (!Arrays.equals(cur, FREE)\r\n\t\t\t\t\t&& (Arrays.equals(cur, REMOVED) || storehash!=hash));\r\n\t\t}\r\n\r\n\t\treturn storehash!=hash ? -1 : index;\r\n\t}","private void remove(int index){\r\n \tkeys[index] = null;\r\n \tvals[index] = null;\r\n deleteCheck(index);\r\n }"],"string":"[\n \"@AfterClass\\n\\tpublic static void cleanIndex() {\\n\\t\\tEntityTest et = new EntityTest(id, \\\"EntityTest\\\");\\n\\t\\tRedisQuery.remove(et, id);\\n\\t}\",\n \"void indexReset();\",\n \"public void clear() {\\n index.clear();\\n }\",\n \"private Reindex() {}\",\n \"private Reindex() {}\",\n \"void clearAllIndexes();\",\n \"public H_index() {\\n\\t\\tsuper();\\n\\t}\",\n \"@Override\\n\\tpublic void clearIndex(String indexName) {\\n\\t\\t\\n\\t}\",\n \"public void onIndexReset();\",\n \"@Override\\n public void close()\\n {\\n notifyLegacyIndexOperationQueue();\\n\\n }\",\n \"@Override\\n\\tpublic void unIndexObject(ModelKey obj) throws ASException {\\n\\t\\t\\n\\t}\",\n \"public void truncate() {\\n\\t\\ttry {\\n\\t\\t\\t_reopenToken = _trackingIndexWriter.deleteAll();\\n\\t\\t\\tlog.warn(\\\"lucene index truncated\\\");\\n\\t\\t} catch(IOException ioEx) {\\n\\t\\t\\tlog.error(\\\"Error truncating lucene index: {}\\\",ioEx.getMessage(),\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t \\t\\t \\t ioEx);\\t\\t\\t\\n\\t\\t} finally {\\n\\t\\t\\ttry {\\n\\t\\t\\t\\t_indexWriter.commit(); \\n\\t\\t\\t} catch (IOException ioEx) {\\n\\t\\t\\t\\tlog.error(\\\"Error truncating lucene index: {}\\\",ioEx.getMessage(),\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t \\t\\t\\t ioEx);\\n\\t\\t\\t}\\n\\t\\t}\\n\\t}\",\n \"@Override\\n\\tpublic void unIndexObject(String indexName, String key) throws ASException {\\n\\t\\t\\n\\t}\",\n \"@Test\\n public void testIndexMaintenanceWithIndexOnMethodEntrySet() throws Exception {\\n Index i1 = qs.createIndex(\\\"indx1\\\", IndexType.FUNCTIONAL, \\\"entries.value.getID\\\",\\n SEPARATOR + \\\"portfolio.entrySet() entries\\\");\\n CacheUtils.getCache();\\n region = CacheUtils.getRegion(SEPARATOR + \\\"portfolio\\\");\\n region.put(\\\"4\\\", new Portfolio(4));\\n region.put(\\\"5\\\", new Portfolio(5));\\n CompactRangeIndex ri = (CompactRangeIndex) i1;\\n validateIndexForEntries(ri);\\n }\",\n \"@Test\\n public void testIndexMaintenanceWithIndexOnMethodKeys() throws Exception {\\n Index i1 = qs.createIndex(\\\"indx1\\\", IndexType.FUNCTIONAL, \\\"ks.toString\\\",\\n SEPARATOR + \\\"portfolio.keys() ks\\\");\\n CacheUtils.getCache();\\n region = CacheUtils.getRegion(SEPARATOR + \\\"portfolio\\\");\\n region.put(\\\"4\\\", new Portfolio(4));\\n region.put(\\\"5\\\", new Portfolio(5));\\n CompactRangeIndex ri = (CompactRangeIndex) i1;\\n validateIndexForKeys(ri);\\n }\",\n \"private void cleanUp() {\\n if (rehash()) {\\n // If we rehashed, we needn't clean up (clean up happens as\\n // a side effect).\\n return;\\n }\\n\\n if (size == 0) {\\n // No live entries == nothing to clean.\\n return;\\n }\\n\\n // Clean log(table.length) entries picking up where we left off\\n // last time.\\n int index = clean;\\n Object[] table = this.table;\\n for (int counter = table.length; counter > 0; counter >>= 1,\\n index = next(index)) {\\n Object k = table[index];\\n\\n if (k == TOMBSTONE || k == null) {\\n continue; // on to next entry\\n }\\n\\n // The table can only contain null, tombstones and references.\\n @SuppressWarnings(\\\"unchecked\\\")\\n Reference<ThreadLocal<?>> reference\\n = (Reference<ThreadLocal<?>>) k;\\n if (reference.get() == null) {\\n // This thread local was reclaimed by the garbage collector.\\n table[index] = TOMBSTONE;\\n table[index + 1] = null;\\n tombstones++;\\n size--;\\n }\\n }\\n\\n // Point cursor to next index.\\n clean = index;\\n }\",\n \"private void ensureHashingIndexExists() {\\n DB metadataDB = client.getDB(\\\"cacheManagerMetadata\\\");\\n if (!metadataDB.collectionExists(\\\"hashingIndex\\\")) {\\n DBCollection hashingIndex = metadataDB.getCollection(\\\"hashingIndex\\\");\\n hashingIndex.createIndex(new BasicDBObject(\\\"hashValue\\\", 1),\\n new BasicDBObject(\\\"unique\\\", 1));\\n }\\n }\",\n \"@Test\\n public void testIndexMaintenanceWithIndexOnMethodKeySet() throws Exception {\\n Index i1 =\\n qs.createIndex(\\\"indx1\\\", IndexType.FUNCTIONAL, \\\"ks.toString\\\",\\n SEPARATOR + \\\"portfolio.keySet() ks\\\");\\n CacheUtils.getCache();\\n region = CacheUtils.getRegion(SEPARATOR + \\\"portfolio\\\");\\n region.put(\\\"4\\\", new Portfolio(4));\\n region.put(\\\"5\\\", new Portfolio(5));\\n CompactRangeIndex ri = (CompactRangeIndex) i1;\\n validateIndexForKeys(ri);\\n }\",\n \"@Test\\n public void testIndexMaintenanceWithIndexOnMethodGetEntries() throws Exception {\\n Index i1 = qs.createIndex(\\\"indx1\\\", IndexType.FUNCTIONAL, \\\"entries.value.getID\\\",\\n SEPARATOR + \\\"portfolio.getEntries() entries\\\");\\n CacheUtils.getCache();\\n region = CacheUtils.getRegion(SEPARATOR + \\\"portfolio\\\");\\n region.put(\\\"4\\\", new Portfolio(4));\\n region.put(\\\"5\\\", new Portfolio(5));\\n CompactRangeIndex ri = (CompactRangeIndex) i1;\\n validateIndexForEntries(ri);\\n }\",\n \"@Override\\n\\tpublic void clearIndex(Class<? extends ModelKey> clazz) {\\n\\t\\t\\n\\t}\",\n \"public void close() throws IndexerException {\\n\\t\\t//TODO\\n\\t\\t\\n\\t}\",\n \"public abstract void deselectAllIndexes();\",\n \"@Override\\n public void beforeRerunningIndexCreationQuery() {\\n Thread th = new Thread(() -> {\\n // Assert that the size of region is now 0\\n assertTrue(region.size() == 0);\\n region.put(\\\"\\\" + 8, new Portfolio(8));\\n });\\n th.start();\\n ThreadUtils.join(th, 30 * 1000);\\n assertTrue(region.size() == 1);\\n }\",\n \"@Test\\n public void testIndexMaintenanceWithHeterogenousObjects() throws Exception {\\n DefaultQueryService.TEST_QUERY_HETEROGENEOUS_OBJECTS = true;\\n IndexManager.TEST_RANGEINDEX_ONLY = true;\\n Cache cache = CacheUtils.getCache();\\n qs = cache.getQueryService();\\n region = CacheUtils.createRegion(\\\"portfolio1\\\", null);\\n idSet.clear();\\n Portfolio p = new Portfolio(4);\\n region.put(\\\"4\\\", p);\\n idSet.add(\\\"\\\" + p.getID());\\n p = new Portfolio(5);\\n region.put(\\\"5\\\", p);\\n idSet.add(\\\"\\\" + p.getID());\\n region.put(\\\"6\\\", 6);\\n Index i1 =\\n qs.createIndex(\\\"indx1\\\", IndexType.FUNCTIONAL, \\\"pf.getID()\\\", SEPARATOR + \\\"portfolio1 pf\\\");\\n RangeIndex ri = (RangeIndex) i1;\\n assertEquals(2, ri.valueToEntriesMap.size());\\n Iterator itr = ri.valueToEntriesMap.values().iterator();\\n while (itr.hasNext()) {\\n RangeIndex.RegionEntryToValuesMap re2ValMap = (RangeIndex.RegionEntryToValuesMap) itr.next();\\n assertEquals(1, re2ValMap.map.size());\\n Object obj = re2ValMap.map.values().iterator().next();\\n assertFalse(obj instanceof Collection);\\n assertTrue(obj instanceof Portfolio);\\n Portfolio pf = (Portfolio) obj;\\n assertTrue(idSet.contains(String.valueOf(pf.getID())));\\n }\\n assertEquals(1, ri.undefinedMappedEntries.map.size());\\n Map.Entry entry = (Map.Entry) ri.undefinedMappedEntries.map.entrySet().iterator().next();\\n assertFalse(entry.getValue() instanceof Collection);\\n assertTrue(entry.getValue() instanceof Integer);\\n assertTrue(entry.getValue().equals(6));\\n\\n region.put(\\\"7\\\", 7);\\n idSet.add(7);\\n assertEquals(2, ri.undefinedMappedEntries.map.size());\\n itr = ri.undefinedMappedEntries.map.entrySet().iterator();\\n while (itr.hasNext()) {\\n entry = (Map.Entry) itr.next();\\n assertFalse(entry.getValue() instanceof Collection);\\n assertTrue(entry.getValue() instanceof Integer);\\n idSet.contains(entry.getValue());\\n }\\n\\n region.remove(\\\"7\\\");\\n idSet.remove(7);\\n Index i2 =\\n qs.createIndex(\\\"indx2\\\", IndexType.FUNCTIONAL, \\\"pf.pkid\\\", SEPARATOR + \\\"portfolio1 pf\\\");\\n ri = (RangeIndex) i2;\\n assertEquals(2, ri.valueToEntriesMap.size());\\n itr = ri.valueToEntriesMap.values().iterator();\\n while (itr.hasNext()) {\\n RangeIndex.RegionEntryToValuesMap re2ValMap = (RangeIndex.RegionEntryToValuesMap) itr.next();\\n assertEquals(1, re2ValMap.map.size());\\n Object obj = re2ValMap.map.values().iterator().next();\\n assertFalse(obj instanceof Collection);\\n assertTrue(obj instanceof Portfolio);\\n Portfolio pf = (Portfolio) obj;\\n assertTrue(idSet.contains(String.valueOf(pf.getID())));\\n }\\n assertEquals(1, ri.undefinedMappedEntries.map.size());\\n entry = (Map.Entry) ri.undefinedMappedEntries.map.entrySet().iterator().next();\\n assertFalse(entry.getValue() instanceof Collection);\\n assertTrue(entry.getValue() instanceof Integer);\\n assertTrue(entry.getValue().equals(6));\\n\\n region.put(\\\"7\\\", 7);\\n idSet.add(7);\\n assertEquals(2, ri.undefinedMappedEntries.map.size());\\n itr = ri.undefinedMappedEntries.map.entrySet().iterator();\\n while (itr.hasNext()) {\\n entry = (Map.Entry) itr.next();\\n assertFalse(entry.getValue() instanceof Collection);\\n assertTrue(entry.getValue() instanceof Integer);\\n idSet.contains(entry.getValue());\\n }\\n }\",\n \"@Override\\n @Secured(SecurityRoles.ADMINISTRATOR)\\n public void reindex() {\\n revisionDao.deleteAll();\\n // OK, launches a new indexation\\n indexFromLatest();\\n }\",\n \"@Test\\n @Ignore\\n public void testDelete_Index() throws Exception {\\n System.out.println(\\\"delete\\\");\\n Index entity = TestUtils.getTestIndex();\\n Identifier identifier = entity.getId();\\n instance.create(entity);\\n assertTrue(instance.exists(identifier));\\n instance.delete(entity);\\n assertFalse(instance.exists(identifier));\\n }\",\n \"public void flush() {\\n synchronized (getLock()) {\\n sIndexWritersCache.flush(this);\\n sIndexReadersCache.removeIndexReader(this);\\n }\\n }\",\n \"@Test\\n public void testIndexMaintenanceWithIndexOnMethodGetKeys() throws Exception {\\n Index i1 =\\n qs.createIndex(\\\"indx1\\\", IndexType.FUNCTIONAL, \\\"ks.toString\\\",\\n SEPARATOR + \\\"portfolio.getKeys() ks\\\");\\n CacheUtils.getCache();\\n region = CacheUtils.getRegion(SEPARATOR + \\\"portfolio\\\");\\n region.put(\\\"4\\\", new Portfolio(4));\\n region.put(\\\"5\\\", new Portfolio(5));\\n CompactRangeIndex ri = (CompactRangeIndex) i1;\\n validateIndexForKeys(ri);\\n }\",\n \"public void testCreIdx(){\\r\\n\\t \\r\\n\\t String dataDir = \\\"C:\\\\\\\\study\\\\\\\\Lucene\\\\\\\\Data\\\";\\r\\n\\t String idxDir = \\\"C:\\\\\\\\study\\\\\\\\Lucene\\\\\\\\Index\\\";\\r\\n\\t \\r\\n\\t LuceneUtils.delAll(idxDir);\\r\\n\\t \\r\\n\\t CreateIndex ci = new CreateIndex();\\r\\n\\t \\r\\n\\t ci.Indexer(new File(idxDir), new File(dataDir));\\r\\n\\t \\r\\n\\t\\t\\r\\n\\t}\",\n \"public ThreadSafeInvertedIndex() {\\n\\t\\tsuper();\\n\\t\\tthis.lock = new ReadWriteLock();\\n\\t}\",\n \"@Test\\n public void testCoh3733()\\n {\\n doSingleServerTest(\\\"IdxTestCoh3733\\\", new Runnable()\\n {\\n public void run()\\n {\\n NamedCache cache = getNamedCache(\\\"coh3733\\\");\\n\\n cache.addIndex(new IndexAwareExtractor()\\n {\\n public MapIndex createIndex(boolean fOrdered, Comparator comparator, Map mapIndex,\\n BackingMapContext ctx)\\n {\\n MapIndex index = new SimpleMapIndex(this, false, null, ctx)\\n {\\n protected void removeInverseMapping(Map mapIndex, Object oIxValue, Object oKey)\\n {\\n Set setKeys = (Set) mapIndex.get(oIxValue);\\n\\n assertTrue(\\\"Attempted to remove non-existent index entry\\\",\\n setKeys != null && setKeys.contains(oKey));\\n super.removeInverseMapping(mapIndex, oIxValue, oKey);\\n }\\n };\\n mapIndex.put(this, index);\\n return index;\\n }\\n\\n public MapIndex destroyIndex(Map mapIndex)\\n {\\n return (MapIndex) mapIndex.remove(this);\\n }\\n\\n public Object extract(Object oTarget)\\n {\\n return oTarget;\\n }\\n }, false, null);\\n cache.addMapListener(new MultiplexingMapListener()\\n {\\n protected void onMapEvent(MapEvent evt)\\n {\\n fail(\\\"Observed unexpected event: \\\" + evt);\\n }\\n });\\n\\n cache.remove(\\\"non-existent-key\\\");\\n\\n validateIndex(cache);\\n }\\n });\\n }\",\n \"@Test\\n public void testIndexMaintenanceWithIndexOnMethodtoArray() throws Exception {\\n Index i1 = qs.createIndex(\\\"indx1\\\", IndexType.FUNCTIONAL, \\\"pf.getID\\\",\\n SEPARATOR + \\\"portfolio.toArray() pf\\\");\\n assertTrue(i1 instanceof CompactRangeIndex);\\n Cache cache = CacheUtils.getCache();\\n region = CacheUtils.getRegion(SEPARATOR + \\\"portfolio\\\");\\n region.put(\\\"4\\\", new Portfolio(4));\\n region.put(\\\"5\\\", new Portfolio(5));\\n CompactRangeIndex ri = (CompactRangeIndex) i1;\\n validateIndexForValues(ri);\\n }\",\n \"void initiateRemoveIndexes(HarvestResultDTO harvestResult) throws DigitalAssetStoreException;\",\n \"private void close() throws CorruptIndexException, IOException {\\n\\n\\t\\tidxWriter.forceMerge(1);\\n\\t\\tidxWriter.commit();\\n\\t\\tidxWriter.close();\\n\\t}\",\n \"private void removeContentAfterIndexLink()\\r\\n \\t{\\r\\n \\t\\tdeleteNodes(XPath.AFTER_INDEX_LINK.query);\\r\\n \\t}\",\n \"@Test\\n public void testIndexMaintenanceWithIndexOnMethodValues() throws Exception {\\n Index i1 = qs.createIndex(\\\"indx1\\\", IndexType.FUNCTIONAL, \\\"pf.getID\\\",\\n SEPARATOR + \\\"portfolio.values() pf\\\");\\n assertTrue(i1 instanceof CompactRangeIndex);\\n Cache cache = CacheUtils.getCache();\\n region = CacheUtils.getRegion(SEPARATOR + \\\"portfolio\\\");\\n region.put(\\\"4\\\", new Portfolio(4));\\n region.put(\\\"5\\\", new Portfolio(5));\\n CompactRangeIndex ri = (CompactRangeIndex) i1;\\n validateIndexForValues(ri);\\n }\",\n \"public void clear()\\n\\t\\t{\\n\\t\\t\\tindices.clear();\\n\\t\\t}\",\n \"public void tIndex(IndexShort < O > index) throws Exception {\\n File query = new File(testProperties.getProperty(\\\"test.query.input\\\"));\\n File dbFolder = new File(testProperties.getProperty(\\\"test.db.path\\\"));\\n\\n int cx = 0;\\n\\n initIndex(index);\\n //search(index, (short) 3, (byte) 3);\\n //search(index, (short) 7, (byte) 1);\\n //search(index, (short) 12, (byte) 3);\\n \\n search(index, (short) 1000, (byte) 1);\\n\\n search(index, (short) 1000, (byte) 3);\\n\\n search(index, (short) 1000, (byte) 10);\\n \\n search(index, (short) 1000, (byte) 50);\\n \\n long i = 0;\\n // int realIndex = 0;\\n // test special methods that only apply to\\n // SynchronizableIndex\\n \\n\\n // now we delete elements from the DB\\n logger.info(\\\"Testing deletes\\\");\\n i = 0;\\n long max = index.databaseSize();\\n while (i < max) {\\n O x = index.getObject(i);\\n OperationStatus ex = index.exists(x);\\n assertTrue(ex.getStatus() == Status.EXISTS);\\n assertTrue(ex.getId() == i);\\n ex = index.delete(x);\\n assertTrue(\\\"Status is: \\\" + ex.getStatus() + \\\" i: \\\" + i , ex.getStatus() == Status.OK);\\n assertEquals(i, ex.getId());\\n ex = index.exists(x); \\n assertTrue( \\\"Exists after delete\\\" + ex.getStatus() + \\\" i \\\" + i, ex.getStatus() == Status.NOT_EXISTS);\\n i++;\\n }\\n index.close();\\n Directory.deleteDirectory(dbFolder);\\n }\",\n \"public void updateIndex() {\\n int i = this.index;\\n if (i == -1 || i > HashBiMap.this.size || !Objects.equal(HashBiMap.this.keys[this.index], this.key)) {\\n this.index = HashBiMap.this.findEntryByKey(this.key);\\n }\\n }\",\n \"public void clear() throws IOException {\\n\\t\\tindexWriter.deleteAll();\\n\\t\\tforceCommit();\\n\\t}\",\n \"public void onIndexUpdate();\",\n \"public void testIndexCosts() {\\n this.classHandler.applyIndexes();\\n }\",\n \"LuceneMemoryIndex createLuceneMemoryIndex();\",\n \"void stopIndexing();\",\n \"public long index() {\\n return manager.compactIndex();\\n }\",\n \"@Test\\n public void testIndexMaintenanceWithIndexOnMethodAsSet() throws Exception {\\n Index i1 = qs.createIndex(\\\"indx1\\\", IndexType.FUNCTIONAL, \\\"pf.getID\\\",\\n SEPARATOR + \\\"portfolio.asSet() pf\\\");\\n CacheUtils.getCache();\\n region = CacheUtils.getRegion(SEPARATOR + \\\"portfolio\\\");\\n region.put(\\\"4\\\", new Portfolio(4));\\n region.put(\\\"5\\\", new Portfolio(5));\\n CompactRangeIndex ri = (CompactRangeIndex) i1;\\n validateIndexForValues(ri);\\n }\",\n \"public void afterIndexCreated(IndexService indexService) {\\n\\n }\",\n \"@Override\\r\\n\\tpublic void delete(int r_idx) throws Exception {\\n\\r\\n\\t}\",\n \"public void deleteIndex() throws Exception {\\n\\n\\t\\tRetryingRunnable runnable = new RetryingRunnable() \\n\\t\\t{\\t\\n\\t\\t\\tpublic void run() throws Exception \\n\\t\\t\\t{\\n\\t\\t\\t\\tIndexWriter w = createIndexWriter(true); // open for writing and close (make empty)\\n\\t\\t\\t\\tw.deleteAll();\\n\\t\\t\\t\\tw.commit();\\n\\t\\t\\t\\tw.close(true);\\n\\t\\t\\t\\t\\n\\t\\t\\t\\tDirectory dir = getIndexDir();\\n\\t\\t\\t\\tfor(String file: dir.listAll())\\n\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\tif( dir.fileExists(file) ) // still exits\\n\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\tdir.sync(file);\\n\\t\\t\\t\\t\\t\\tdir.deleteFile(file);\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\tdir.close();\\n\\t\\t\\t}\\n\\t\\t\\t\\n\\t\\t\\tpublic boolean handleException(Throwable e) \\n\\t\\t\\t{\\n\\t\\t\\t\\treturn true;\\n\\t\\t\\t}\\n\\t\\t};\\n\\t\\t\\n\\t\\tchangeListener.onIndexReset(); // close searcher because index is deleted\\n\\t\\t\\n\\t\\trunRetryingRunnable(runnable); // delete index with retry\\n\\t}\",\n \"private void syncIndex(FundamentalData fd) throws Exception {\\n\\n List<MarketIndex> indexes = marketIndexService.findBySymbol(fd.getSymbol());\\n if(indexes.size()>1){\\n throw new Exception(\\\"Multiple instances (\\\"+indexes.size()+\\\") of symbol \\\"+fd.getSymbol()+\\\" present in the database.\\\");\\n }\\n\\n MarketIndex index;\\n if(indexes.size()==0){ // does not exist in db\\n index=new MarketIndex();\\n index.setSymbol(fd.getSymbol());\\n index.setName(fd.getName());\\n index.setCategory(fd.getType().getCode());\\n\\n }else{ // index exists in db\\n index = indexes.get(0);\\n if(fd.getName()!=null){\\n index.setName(fd.getName());\\n }\\n if(fd.getType()!=null){\\n index.setCategory(fd.getType().getCode());\\n }\\n\\n }\\n\\n updateIcon(index);\\n marketIndexService.update(index);\\n\\n }\",\n \"@Test\\n public void testIndexMaintenanceWithIndexOnMethodGetValues() throws Exception {\\n Index i1 =\\n qs.createIndex(\\\"indx1\\\", IndexType.FUNCTIONAL, \\\"pf.getID\\\",\\n SEPARATOR + \\\"portfolio.getValues() pf\\\");\\n assertTrue(i1 instanceof CompactRangeIndex);\\n Cache cache = CacheUtils.getCache();\\n region = CacheUtils.getRegion(SEPARATOR + \\\"portfolio\\\");\\n region.put(\\\"4\\\", new Portfolio(4));\\n region.put(\\\"5\\\", new Portfolio(5));\\n CompactRangeIndex ri = (CompactRangeIndex) i1;\\n validateIndexForValues(ri);\\n }\",\n \"@Test\\n public void testIndexMaintenanceOnCacheLoadedData() throws Exception {\\n IndexManager.TEST_RANGEINDEX_ONLY = true;\\n Cache cache = CacheUtils.getCache();\\n qs = cache.getQueryService();\\n region = CacheUtils.createRegion(\\\"portfolio1\\\", null);\\n AttributesMutator am = region.getAttributesMutator();\\n am.setCacheLoader(new CacheLoader() {\\n\\n @Override\\n public Object load(LoaderHelper helper) throws CacheLoaderException {\\n String key = (String) helper.getKey();\\n Portfolio p = new Portfolio(Integer.parseInt(key));\\n return p;\\n }\\n\\n @Override\\n public void close() {\\n // nothing\\n }\\n });\\n\\n Index i1 =\\n qs.createIndex(\\\"indx1\\\", IndexType.FUNCTIONAL, \\\"pf.getID()\\\", SEPARATOR + \\\"portfolio1 pf\\\");\\n List keys = new ArrayList();\\n keys.add(\\\"1\\\");\\n keys.add(\\\"2\\\");\\n keys.add(\\\"3\\\");\\n keys.add(\\\"4\\\");\\n\\n region.getAll(keys);\\n }\",\n \"private void flushCurrentIndexBlock() throws IOException {\\n if (currentMemoryIndex.documentsInIndex() < 1) {\\n return;\\n }\\n\\n logger.info(\\\"Flushing current memory Index. id = \\\" + indexBlockCount);\\n\\n final MemoryIndex flushingMemoryIndex = currentMemoryIndex;\\n final File shardFolder = getNextIndexShardFolder(1);\\n\\n try {\\n // reset the current index\\n // - this makes the flush operation thread safe while continuing to add new documents.\\n resetCurrentMemoryIndex();\\n } catch (Exception ex) {\\n throw new IOException(ex);\\n }\\n\\n try {\\n // first flush the index to disk\\n FlushToDisk.flushMemoryIndex(flushingMemoryIndex, shardFolder.getAbsolutePath(), false);\\n\\n // indicate that the flushing part of this thread is done\\n synchronized (geometricParts) {\\n // add flushed index to the set of bins -- needs to be a synconeous action\\n geometricParts.add(0, shardFolder.getAbsolutePath());\\n updateIndex();\\n flushingMemoryIndex.close();\\n }\\n\\n } catch (IOException e) {\\n logger.severe(e.toString());\\n }\\n }\",\n \"@Override\\n protected void cleanup(Context context) throws IOException, InterruptedException {\\n logger.info(\\\"Cleanup\\\");\\n super.cleanup(context);\\n for (java.util.Map.Entry<String, FullImageMetadata> entry : indexer.getEntries().entrySet()) {\\n String surt = entry.getKey();\\n context.write(new Text(surt), entry.getValue());\\n }\\n }\",\n \"public void close() {\\n\\t\\t\\n\\t\\ttry {\\n\\t\\t\\tindexWriter.optimize();\\n\\t\\t\\t\\n\\t\\t\\tindexWriter.close();\\n\\t\\t\\t\\n\\t\\t\\tIndexSearcher = new IndexSearcher(idx);\\n\\t\\t\\t\\n\\t\\t} catch (CorruptIndexException e) {\\n\\t\\t\\t// TODO Auto-generated catch block\\n\\t\\t\\te.printStackTrace();\\n\\t\\t} catch (IOException e) {\\n\\t\\t\\t// TODO Auto-generated catch block\\n\\t\\t\\te.printStackTrace();\\n\\t\\t}\\n\\t\\t\\n\\t\\t\\n\\t}\",\n \"@Test\\n public void testIndexMaintenanceOnPutAll() throws Exception {\\n IndexManager.TEST_RANGEINDEX_ONLY = true;\\n Cache cache = CacheUtils.getCache();\\n qs = cache.getQueryService();\\n region = CacheUtils.createRegion(\\\"portfolio1\\\", null);\\n region.put(\\\"1\\\", new Portfolio(1));\\n Index i1 = qs.createIndex(\\\"indx1\\\", IndexType.FUNCTIONAL, \\\"posvals.secId\\\",\\n SEPARATOR + \\\"portfolio1 pf, pf.positions.values posvals \\\");\\n Map data = new HashMap();\\n for (int i = 1; i < 11; ++i) {\\n data.put(\\\"\\\" + i, new Portfolio(i + 2));\\n }\\n\\n region.putAll(data);\\n }\",\n \"public void clear(long index);\",\n \"public Object migrateWords2index(String wordhash) throws IOException {\\n File db = plasmaWordIndexFile.wordHash2path(oldDatabaseRoot, wordhash);\\r\\n if (!(db.exists())) return \\\"not available\\\";\\r\\n plasmaWordIndexFile entity = null;\\r\\n try {\\r\\n entity = new plasmaWordIndexFile(oldDatabaseRoot, wordhash, true);\\r\\n int size = entity.size();\\r\\n indexContainer container = new indexContainer(wordhash, payloadrow(), useCollectionIndex);\\r\\n \\r\\n try {\\r\\n Iterator entries = entity.elements(true);\\r\\n indexRWIEntry entry;\\r\\n while (entries.hasNext()) {\\r\\n entry = (indexRWIEntry) entries.next();\\r\\n // System.out.println(\\\"ENTRY = \\\" + entry.getUrlHash());\\r\\n container.add(new indexRWIEntry[] { entry }, System.currentTimeMillis());\\r\\n }\\r\\n // we have read all elements, now delete the entity\\r\\n entity.deleteComplete();\\r\\n entity.close();\\r\\n entity = null;\\r\\n \\r\\n indexContainer feedback = collections.addEntries(container, container.updated(), false);\\r\\n if (feedback != null) return feedback;\\r\\n return new Integer(size);\\r\\n } catch (kelondroException e) {\\r\\n // database corrupted, we simply give up the database and delete it\\r\\n try { entity.close(); } catch (Exception ee) { }\\r\\n entity = null;\\r\\n try { db.delete(); } catch (Exception ee) { }\\r\\n return \\\"database corrupted; deleted\\\";\\r\\n }\\r\\n } finally {\\r\\n if (entity != null) try {entity.close();}catch(Exception e){}\\r\\n }\\r\\n }\",\n \"public abstract void updateIndex();\",\n \"public void close() throws IndexException {\\n }\",\n \"public void refresh() {\\n getIndexOperations().refresh();\\n }\",\n \"public interface FieldIndex<T> extends GenericIndex<T> \\r\\n{ \\r\\n /**\\r\\n * Put new object in the index. \\r\\n * @param obj object to be inserted in index. Object should contain indexed field. \\r\\n * Object can be not yet peristent, in this case\\r\\n * its forced to become persistent by assigning OID to it.\\r\\n * @return <code>true</code> if object is successfully inserted in the index, \\r\\n * <code>false</code> if index was declared as unique and there is already object with such value\\r\\n * of the key in the index. \\r\\n */\\r\\n public boolean put(T obj);\\r\\n\\r\\n /**\\r\\n * Associate new object with the key specified by object field value. \\r\\n * If there is already object with such key in the index, \\r\\n * then it will be removed from the index and new value associated with this key.\\r\\n * @param obj object to be inserted in index. Object should contain indexed field. \\r\\n * Object can be not yet peristent, in this case\\r\\n * its forced to become persistent by assigning OID to it.\\r\\n * @return object previously associated with this key, <code>null</code> if there was no such object\\r\\n */\\r\\n public T set(T obj);\\r\\n\\r\\n /**\\r\\n * Assign to the integer indexed field unique autoicremented value and \\r\\n * insert object in the index. \\r\\n * @param obj object to be inserted in index. Object should contain indexed field\\r\\n * of integer (<code>int</code> or <code>long</code>) type.\\r\\n * This field is assigned unique value (which will not be reused while \\r\\n * this index exists) and object is marked as modified.\\r\\n * Object can be not yet peristent, in this case\\r\\n * its forced to become persistent by assigning OID to it.\\r\\n * @exception StorageError(StorageError.INCOMPATIBLE_KEY_TYPE) when indexed field\\r\\n * has type other than <code>int</code> or <code>long</code>\\r\\n */\\r\\n public void append(T obj);\\r\\n\\r\\n /**\\r\\n * Remove object with specified key from the unique index\\r\\n * @param key value of removed key\\r\\n * @return removed object\\r\\n * @exception StorageError(StorageError.KEY_NOT_FOUND) exception if there is no such key in the index,\\r\\n * or StorageError(StorageError.KEY_NOT_UNIQUE) if index is not unique.\\r\\n */\\r\\n public T remove(Key key);\\r\\n\\r\\n /**\\r\\n * Remove object with specified key from the unique index\\r\\n * @param key value of removed key\\r\\n * @return removed object\\r\\n * @exception StorageError(StorageError.KEY_NOT_FOUND) exception if there is no such key in the index,\\r\\n * or StorageError(StorageError.KEY_NOT_UNIQUE) if index is not unique.\\r\\n */\\r\\n public T removeKey(Object key);\\r\\n\\r\\n /**\\r\\n * Check if index contains specified object instance.\\r\\n * @param obj object to be searched in the index. Object should contain indexed field. \\r\\n * @return <code>true</code> if object is present in the index, <code>false</code> otherwise\\r\\n */\\r\\n public boolean containsObject(T obj);\\r\\n\\r\\n /**\\r\\n * Locate objects with the same value of the key as specified object\\r\\n * @param obj object specifying search key value\\r\\n * @return selection iterator\\r\\n */\\r\\n public IterableIterator<T> queryByExample(T obj);\\r\\n\\r\\n /**\\r\\n * Get class obejct objects which can be inserted in this index\\r\\n * @return class specified in Storage.createFielIndex method\\r\\n */\\r\\n public Class getIndexedClass();\\r\\n\\r\\n /**\\r\\n * Get fields used as a key\\r\\n * @return array of index key fields\\r\\n */\\r\\n public Field[] getKeyFields();\\r\\n\\r\\n /**\\r\\n * Select members of the collection using search predicate\\r\\n * This iterator doesn't support remove() method.\\r\\n * To make it possible to update, remove or add members to the index \\r\\n * during iteration it is necessary to set \\\"perst.concurrent.iterator\\\"\\r\\n * property (by default it is not supported because it cause extra overhead during iteration)\\r\\n * @param predicate JSQL condition\\r\\n * @return iterator through members of the collection matching search condition\\r\\n */\\r\\n public IterableIterator<T> select(String predicate);\\r\\n\\r\\n /**\\r\\n * Check if field index is case insensitive\\r\\n * @return true if index ignore case of string keys\\r\\n */\\r\\n boolean isCaseInsensitive(); \\r\\n}\",\n \"public void finishedDirectIndexBuild()\\n\\t{\\n\\t\\tif(logger.isInfoEnabled()){\\n\\t\\t\\tlogger.info(\\\"flushing utf block lexicon to disk after the direct index completed\\\");\\n\\t\\t}\\n\\t\\t//only write a temporary lexicon if there are any items in it\\n\\t\\tif (TempLex.getNumberOfNodes() > 0)\\n\\t\\t\\twriteTemporaryLexicon();\\n\\n\\t\\t//merges the temporary lexicons\\n\\t\\tif (tempLexFiles.size() > 0)\\n\\t\\t{\\n\\t\\t\\ttry{\\n\\t\\t\\t\\tmerge(tempLexFiles);\\n\\t\\n\\t\\t\\t\\t//creates the offsets file\\n\\t\\t\\t\\tfinal String lexiconFilename = \\n\\t\\t\\t\\t\\tindexPath + ApplicationSetup.FILE_SEPARATOR + \\n\\t\\t\\t\\t\\tindexPrefix + ApplicationSetup.LEXICONSUFFIX;\\n\\t\\t\\t\\tLexiconInputStream lis = getLexInputStream(lexiconFilename);\\n\\t\\t\\t\\tcreateLexiconIndex(\\n\\t\\t\\t\\t\\tlis,\\n\\t\\t\\t\\t\\tlis.numberOfEntries(),\\n\\t\\t\\t\\t\\t/* after inverted index is built, the lexicon will be transformed into a\\n\\t\\t\\t\\t\\t * normal lexicon, without block frequency */\\n\\t\\t\\t\\t\\tUTFLexicon.lexiconEntryLength\\n\\t\\t\\t\\t\\t); \\n\\t\\t\\t\\tTermCount = lis.numberOfEntries();\\n\\t\\t\\t\\tif (index != null)\\n\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\tindex.addIndexStructure(\\\"lexicon\\\", \\\"uk.ac.gla.terrier.structures.UTFBlockLexicon\\\");\\n\\t\\t\\t\\t\\tindex.addIndexStructureInputStream(\\\"lexicon\\\", \\\"uk.ac.gla.terrier.structures.UTFBlockLexiconInputStream\\\");\\n\\t\\t\\t\\t\\tindex.setIndexProperty(\\\"num.Terms\\\", \\\"\\\"+lis.numberOfEntries());\\n\\t\\t\\t\\t\\tindex.setIndexProperty(\\\"num.Pointers\\\", \\\"\\\"+lis.getNumberOfPointersRead());\\n\\t\\t\\t\\t}\\n\\t\\t\\t} catch(IOException ioe){\\n\\t\\t\\t\\tlogger.error(\\\"Indexing failed to write a lexicon index file to disk\\\", ioe);\\n\\t\\t\\t}\\t\\n\\t\\t}\\n\\t\\telse\\n\\t\\t\\tlogger.warn(\\\"No temporary lexicons to merge, skipping\\\");\\n\\t\\t\\n\\t}\",\n \"private IndexingManager() {\\n Provider provider = new BouncyCastleProvider();\\n Security.addProvider(provider);\\n utility = Database_Utility.getInstance();\\n conn = utility.getConnection();\\n IMbuffer = IndexingManagerBuffer.getInstance();\\n\\n // This statement is to create purge table.\\n\\n boolean k = checkTable1(\\\"PurgeTable\\\");\\n if (!k) {\\n utility.createtable2(\\\"PurgeTable\\\");\\n }\\n boolean k1 = checkTable1(\\\"UserToCertMap\\\");\\n if (!k1) {\\n utility.createtable1();\\n }\\n\\n // This statement is to run maintenance thread on loading of class to purge entries whose timer has expired.\\n\\n //maintenancethread();\\n\\n // This statement is to run maintenance thread on loading of class to ascertain root nodes.\\n\\n // maintenancethread1();\\n\\n // This statement is to run maintenance thread on loading of class to delete entries from purge table.\\n\\n // maintenancethread2();\\n\\n }\",\n \"protected void removeFromIndex(SimpleFeature feature) {\\n\\t\\tif (feature==null) return;\\n\\t\\t\\n\\t\\t// ID Index\\n\\t\\tidIndex.remove( feature.getID() );\\n\\t\\t\\n\\t\\t// Type name index\\n\\t\\tName type = feature.getType().getName();\\n\\t\\tSet<SimpleFeature> prev = typeNameIndex.get(type);\\n\\t\\tif ( prev.remove( feature ) ) {\\n\\t\\t\\tif (prev.size()>0) {\\n\\t\\t\\t\\ttypeNameIndex.put(type,prev);\\n\\t\\t\\t} else {\\n\\t\\t\\t\\ttypeNameIndex.remove(type);\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\t\\n\\t\\t// Tile Index\\n\\t\\tif (feature.getID().matches(\\\".*-[0-9]+-[0-9]+-[0-9]+\\\")) {\\n\\t\\t\\tOSMTile tile = new OSMTile(feature.getID());\\n\\t\\t\\tprev = tileIndex.get( tile );\\n\\t\\t\\tif ( prev.remove( feature ) ) {\\n\\t\\t\\t\\tif (prev.size()>0) {\\n\\t\\t\\t\\t\\ttileIndex.put(tile, prev);\\n\\t\\t\\t\\t} else {\\n\\t\\t\\t\\t\\ttileIndex.remove(type);\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t} else {\\n\\t\\t\\t// Whatever for features\\n\\t\\t}\\n\\t}\",\n \"public void beforeIndexClosed(IndexService indexService) {\\n\\n }\",\n \"@Test\\n public void testIndexMaintenanceWithIndexOnMethodAsList() throws Exception {\\n Index i1 = qs.createIndex(\\\"indx1\\\", IndexType.FUNCTIONAL, \\\"pf.getID\\\",\\n SEPARATOR + \\\"portfolio.asList() pf\\\");\\n CacheUtils.getCache();\\n region = CacheUtils.getRegion(SEPARATOR + \\\"portfolio\\\");\\n region.put(\\\"4\\\", new Portfolio(4));\\n region.put(\\\"5\\\", new Portfolio(5));\\n CompactRangeIndex ri = (CompactRangeIndex) i1;\\n validateIndexForValues(ri);\\n }\",\n \"private void readIndex() throws IOException {\\n\\t\\t\\tif (this.keys != null)\\n\\t\\t\\t\\treturn;\\n\\t\\t\\tkeys = new HashMap<K, Long>(1024);\\n\\t\\t\\ttry {\\n\\t\\t\\t\\twhile (index.hasNext()) {\\n\\t\\t\\t\\t\\tPair<K, Long> pair;// = new Pair<K, Long>(index.getSchema());\\n\\t\\t\\t\\t\\tpair = index.next();\\n\\t\\t\\t\\t\\tkeys.put(pair.key(), pair.value());\\n\\t\\t\\t\\t\\tif (firstKey == null)\\n\\t\\t\\t\\t\\t\\tfirstKey = pair.key();\\n\\t\\t\\t\\t\\tfinalKey = pair.key();\\n\\t\\t\\t\\t\\tcount++;\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t}finally {\\n\\t\\t\\t\\tindexClosed = true;\\n\\t\\t\\t\\tindex.close();\\n\\t\\t\\t}\\n\\t\\t}\",\n \"@Override\\n public void reindexImpl()\\n {\\n List<StoreRef> storeRefs = nodeService.getStores();\\n int count = 0;\\n for (StoreRef storeRef : storeRefs)\\n {\\n // prompt the FTS reindexing\\n if (!ftsIndexerCalled)\\n {\\n ftsIndexer.requiresIndex(storeRef);\\n }\\n // reindex missing content\\n count += reindexMissingContent(storeRef);\\n // check if we have to break out\\n if (isShuttingDown())\\n {\\n break;\\n }\\n }\\n \\n // The FTS indexer only needs to be prompted once\\n ftsIndexerCalled = true;\\n\\n // done\\n if (logger.isDebugEnabled())\\n {\\n logger.debug(\\\"Missing content indexing touched \\\" + count + \\\" content nodes\\\");\\n }\\n }\",\n \"@Override\\n public void close() throws IOException {\\n flushCurrentIndexBlock();\\n\\n // logger.info(\\\"Performing final merge\\\");\\n // try {\\n //Bin finalMergeBin = geometricParts.getAllShards();\\n //doMerge(finalMergeBin, getNextIndexShardFolder(finalMergeBin.size + 1));\\n // check point is updated by the merge op.\\n\\n // } catch (IOException ex) {\\n // Logger.getLogger(GeometricRetrieval.class.getName()).log(Level.SEVERE, null, ex);\\n //}\\n\\n }\",\n \"public interface IndexBuilder {\\n\\n /**\\n * Rebuilds the index only when the existing index is not populated.\\n */\\n void rebuildIfNecessary();\\n\\n}\",\n \"@Override\\n protected boolean preserveIndicesUponCompletion() {\\n return true;\\n }\",\n \"private static void deleteTest() throws SailException{\\n\\n\\t\\tString dir2 = \\\"repo-temp\\\";\\n\\t\\tSail sail2 = new NativeStore(new File(dir2));\\n\\t\\tsail2 = new IndexingSail(sail2, IndexManager.getInstance());\\n\\t\\t\\n//\\t\\tsail.initialize();\\n\\t\\tsail2.initialize();\\n\\t\\t\\n//\\t\\tValueFactory factory = sail2.getValueFactory();\\n//\\t\\tCloseableIteration<? extends Statement, SailException> statements = sail2\\n//\\t\\t\\t\\t.getConnection().getStatements(null, null, null, false);\\n\\n\\t\\tSailConnection connection = sail2.getConnection();\\n\\n\\t\\tint cachesize = 1000;\\n\\t\\tint cached = 0;\\n\\t\\tlong count = 0;\\n\\t\\tconnection.removeStatements(null, null, null, null);\\n//\\t\\tconnection.commit();\\n\\t}\",\n \"public Object preparePut(Object object)\\r\\n {\\n FullUniqueIndex perThreadAddedIndex = new FullUniqueIndex(this.hashStrategy);\\r\\n perThreadAddedIndex.setUnderlyingObjectGetter(transactionalUnderlyingObjectGetter);\\r\\n perThreadAddedIndex.putUsingUnderlying(object, ((MithraTransactionalObject) object).zGetNonTxData());\\r\\n synchronized (this.preparedIndices)\\r\\n {\\r\\n this.preparedIndices.add(perThreadAddedIndex);\\r\\n }\\r\\n return perThreadAddedIndex;\\r\\n }\",\n \"public void destroy() {\\n //Write hit count to DB!!\\n }\",\n \"private void resetCurrentMemoryIndex() throws Exception {\\n // by using the globalParameters, the memory index can startup counters etc.\\n // we set the documentCount to ensure all documents are given a unique number.\\n tupleFlowParameters.getJSON().set(\\\"documentNumberOffset\\\", this.globalDocumentCount);\\n currentMemoryIndex = new MemoryIndex(tupleFlowParameters);\\n }\",\n \"@Test\\n public void testIndexCreationThreshold() throws Exception {\\n SchemaModel sm;\\n //\\n // sm = Util.loadSchemaModel2(\\\"resources/performance2/B.xsd\\\"); // NOI18N\\n sm = Util.loadSchemaModel2(\\\"resources/performance2.zip\\\", \\\"B.xsd\\\"); // NOI18N\\n //\\n assertTrue(sm.getState() == State.VALID);\\n //\\n assertTrue(sm instanceof SchemaModelImpl);\\n SchemaModelImpl smImpl = SchemaModelImpl.class.cast(sm);\\n GlobalComponentsIndexSupport indexSupport = smImpl.getGlobalComponentsIndexSupport();\\n assertNotNull(indexSupport);\\n GlobalComponentsIndexSupport.JUnitTestSupport testSupport =\\n indexSupport.getJUnitTestSupport();\\n assertNotNull(testSupport);\\n //\\n // Initiate index building\\n GlobalElement found = sm.findByNameAndType(\\\"B000\\\", GlobalElement.class);\\n assertNotNull(found);\\n Thread.sleep(500); // Wait the index is build\\n //\\n assertTrue(testSupport.isSupportIndex());\\n int indexSise = testSupport.getIndexSize();\\n assertEquals(indexSise, 90);\\n //\\n UndoManager um = new javax.swing.undo.UndoManager();\\n AbstractDocumentModel.class.cast(sm).addUndoableEditListener(um);\\n //\\n sm.startTransaction();\\n try {\\n Schema schema = sm.getSchema();\\n java.util.List<SchemaComponent> gChildren = schema.getChildren();\\n int counter = 0;\\n for (SchemaComponent child : gChildren) {\\n //\\n assertTrue(child instanceof GlobalElement);\\n GlobalElement gElem = GlobalElement.class.cast(child);\\n schema.removeElement(gElem);\\n //\\n counter++;\\n if (counter >= 50) {\\n break;\\n }\\n }\\n } finally {\\n sm.endTransaction();\\n }\\n //\\n int childrenCount = sm.getSchema().getChildren().size();\\n assertEquals(childrenCount, 40);\\n assertFalse(testSupport.isSupportIndex());\\n //\\n //\\n um.undo();\\n //\\n // Initiate index building again\\n found = sm.findByNameAndType(\\\"B000\\\", GlobalElement.class);\\n assertNotNull(found);\\n Thread.sleep(500); // Wait the index is build\\n //\\n assertTrue(testSupport.isSupportIndex());\\n indexSise = testSupport.getIndexSize();\\n assertEquals(indexSise, 90);\\n //\\n System.out.println(\\\"=============================\\\"); // NOI18N\\n System.out.println(\\\" testIndexCreationThreshold \\\"); // NOI18N\\n System.out.println(\\\"=============LOG=============\\\"); // NOI18N\\n String log = testSupport.printLog();\\n System.out.print(log);\\n System.out.println(\\\"=============================\\\"); // NOI18N\\n //\\n }\",\n \"abstract void onIndexDisrupted(String caseId);\",\n \"@Override\\n public void cleanup() {\\n \\n }\",\n \"@Override\\n public void cleanup() {\\n \\n }\",\n \"private void updateIndex() throws IOException {\\n // maintain the document store (corpus) - if there is one\\n if (currentMemoryIndex.containsPart(\\\"corpus\\\")) {\\n // get all corpora + shove into document store\\n ArrayList<DocumentReader> readers = new ArrayList<>();\\n readers.add((DocumentReader) currentMemoryIndex.getIndexPart(\\\"corpus\\\"));\\n for (String path : geometricParts.getAllShards().getBinPaths()) {\\n String corpus = path + File.separator + \\\"corpus\\\";\\n readers.add(new CorpusReader(corpus));\\n }\\n }\\n // finally write new checkpointing data (checkpoints the disk indexes)\\n Parameters checkpoint = createCheckpoint();\\n this.checkpointer.saveCheckpoint(checkpoint);\\n }\",\n \"@Override\\n public void visit(Index node) {\\n }\",\n \"@Override\\r\\n public ParaMap index(ParaMap inMap) throws Exception {\\n return null;\\r\\n }\",\n \"void commit() throws IndexTransactionException;\",\n \"void remove(ThreadLocal<?> key) {\\n cleanUp();\\n\\n for (int index = key.hash & mask;; index = next(index)) {\\n Object reference = table[index];\\n\\n if (reference == key.reference) {\\n // Success!\\n table[index] = TOMBSTONE;\\n table[index + 1] = null;\\n tombstones++;\\n size--;\\n return;\\n }\\n\\n if (reference == null) {\\n // No entry found.\\n return;\\n }\\n }\\n }\",\n \"public void beforeIndexCreated(Index index) {\\n\\n }\",\n \"@Override\\n\\tpublic void clear() {\\n\\t\\tsuper.clear();\\n\\t\\tidIndex = new HashMap<String, SimpleFeature>();\\n\\t\\ttypeNameIndex = new HashMap<Name, Set<SimpleFeature>>();\\n\\t\\ttileIndex = new HashMap<OSMTile, Set<SimpleFeature>>();\\n\\t}\",\n \"public void unIndex(final Term idTerm) {\\n\\t\\ttry {\\n\\t\\t\\t_reopenToken = _trackingIndexWriter.deleteDocuments(idTerm);\\n\\t\\t\\tlog.debug(\\\"{}={} term matching records un-indexed from lucene\\\",idTerm.field(),\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t idTerm.text());\\n\\t\\t} catch(IOException ioEx) {\\n\\t\\t\\tlog.error(\\\"Error in un-index lucene operation: {}\\\",ioEx.getMessage(),\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t \\t\\t \\t\\t ioEx);\\t\\t\\t\\n\\t\\t} finally {\\n\\t\\t\\ttry {\\n\\t\\t\\t\\t_indexWriter.commit(); \\n\\t\\t\\t} catch (IOException ioEx) {\\n\\t\\t\\t\\tlog.error(\\\"Error while commiting changes to Lucene index: {}\\\",ioEx.getMessage(),\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t \\t\\t \\t\\t\\t\\t\\t ioEx);\\n\\t\\t\\t}\\n\\t\\t}\\n\\t}\",\n \"public void clear(){\\n\\t\\tcontenido = getName() + ':';\\n\\t\\tindices.clear();\\n\\t\\tindices.add(0);\\n\\t}\",\n \"@Override\\n public void clear() {\\n hashtableBean = null;\\n\\n hashtableBean = new HashTableBean[5];\\n position = 0;\\n }\",\n \"private void deleteBuckets(Vector<Vector<String>> index) {\\n //deserialize bucket from each position\\n for (int i = 0; i < index.size(); i++) {\\n if (index.get(i) != null) {\\n for (int j = 0; j < index.get(i).size(); j++) {\\n Utilities.removeFromDisk(index.get(i).get(j));\\n }\\n\\n }\\n\\n }\\n //loop on entries and insert\\n }\",\n \"public void cleanUp() {\\n if(ticker.skipCleanup()) {\\n return;\\n } \\n \\n // At this point cleanup is inevitable, so linked list traversal should\\n // be performed. \\n Entry<K, V> e = segment.head();\\n Entry<K, V> end = segment.tail();\\n \\n int processed = 0;\\n long createThreshold = ticker.nextTick() - createTTL;\\n long accessThreshold = ticker.nextTick() - accessTTL;\\n\\n Object removeKey = null;\\n while ((e = e.getNext()) != end && processed++ < REMOVE_DEPTH) {\\n if (null != removeKey) {\\n segment.remove(removeKey);\\n removeKey = null;\\n }\\n\\n // both, access and creation thresholds might trigger entry removal \\n if (e.getCreationTime() <= createThreshold || e.getAccessTime() <= accessThreshold) {\\n removeKey = e.getKey();\\n }\\n }\\n\\n if (null != removeKey) {\\n segment.remove(removeKey);\\n } \\n ticker.markCleanup();\\n }\",\n \"@org.junit.Test\\n public void remove() throws Exception {\\n assertEquals(null, hashTable.remove(\\\"savon\\\"));\\n assertEquals(\\\"Yuliya\\\", hashTable.remove(\\\"Savon\\\"));\\n assertEquals(null, hashTable.remove(\\\"Savon\\\"));\\n\\n for (int i = 0; i < 2_000_000; i++) {\\n hashTable.put(Integer.toString(i), Integer.toString(i));\\n }\\n\\n for (int i = 0; i < 2_000_000; i++) {\\n String curValue = hashTable.remove(Integer.toString(i));\\n assertEquals(Integer.toString(i), curValue);\\n }\\n }\",\n \"@Test\\n public void testDropIdxOnClient() {\\n GridCacheDynamicLoadOnClientTest.srvNode.getOrCreateCache(DEFAULT_CACHE_NAME).query(new SqlFieldsQuery(((\\\"CREATE INDEX IDX_TST ON \\\" + (GridCacheDynamicLoadOnClientTest.FULL_TABLE_NAME)) + \\\" (name desc)\\\"))).getAll();\\n // Due to client receive created index asynchronously we need add the ugly sleep.\\n doSleep(2000);\\n getDefaultCacheOnClient().query(new SqlFieldsQuery(((\\\"DROP INDEX \\\" + (GridCacheDynamicLoadOnClientTest.PERSON_SCHEMA)) + \\\".IDX_TST\\\"))).getAll();\\n }\",\n \"@Override\\n\\tpublic void indexObject(ModelKey obj) throws ASException {\\n\\t\\t\\n\\t}\",\n \"@Override\\n public void ensureCapacity(int index) {\\n\\n }\",\n \"public synchronized void recreateIndex()\\n throws InterruptedException, CancellationException, ExecutionException, IOException, IndexServiceException {\\n // Clear index first\\n clear();\\n recreateService(IndexRecreateObject.Service.Groups);\\n recreateService(IndexRecreateObject.Service.Acl);\\n recreateService(IndexRecreateObject.Service.Themes);\\n recreateService(IndexRecreateObject.Service.Series);\\n recreateService(IndexRecreateObject.Service.Scheduler);\\n recreateService(IndexRecreateObject.Service.Workflow);\\n recreateService(IndexRecreateObject.Service.AssetManager);\\n recreateService(IndexRecreateObject.Service.Comments);\\n }\",\n \"@Override\\r\\n\\tpublic void cleanup() {\\n\\t\\t\\r\\n\\t}\",\n \"protected int index(int hashvalue) {\\r\\n\\t\\tint hash=hashvalue& 0x7fffffff;\\r\\n\\t\\tint index = this.hashFunc1(hash) * FREE.length;////获取一个整型数值（正整数），用来定位一条数据存储\\r\\n\\t\\t// int stepSize = hashFunc2(hash);\\r\\n\\t\\tbyte[] cur = new byte[4];\\r\\n\\t\\tkeys.position(index);\\r\\n\\t\\tkeys.get(cur);\\r\\n\\t\\tint storehash=(cur[0] << 24)+ ((cur[1] & 0xFF) << 16)+ ((cur[2] & 0xFF) << 8)+ (cur[3] & 0xFF);\\r\\n\\t\\tif (storehash==hash) {\\r\\n\\t\\t\\treturn index;\\r\\n\\t\\t}\\r\\n\\t\\tif (Arrays.equals(cur, FREE)) {\\r\\n\\t\\t\\treturn -1;\\r\\n\\t\\t}\\r\\n\\r\\n\\t\\t// NOTE: here it has to be REMOVED or FULL (some user-given value)\\r\\n\\t\\tif (Arrays.equals(cur, REMOVED) || storehash!=hash) {\\r\\n\\t\\t\\t// see Knuth, p. 529\\r\\n\\t\\t\\tfinal int probe = (1 + (hash % (size - 2))) * FREE.length;\\r\\n\\t\\t\\tint z = 0;\\r\\n\\t\\t\\tdo {\\r\\n\\t\\t\\t\\tz++;\\r\\n\\t\\t\\t\\tindex += (probe); // add the step\\r\\n\\t\\t\\t\\tindex %= (size * FREE.length); // for wraparound\\r\\n\\t\\t\\t\\tcur = new byte[FREE.length];\\r\\n\\t\\t\\t\\tkeys.position(index);\\r\\n\\t\\t\\t\\tkeys.get(cur);\\r\\n\\t\\t\\t\\tif (z > size) {\\r\\n\\t\\t\\t\\t\\tSDFSLogger.getLog().info(\\r\\n\\t\\t\\t\\t\\t\\t\\t\\\"entries exhaused size=\\\" + this.size + \\\" entries=\\\"\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t+ this.entries);\\r\\n\\t\\t\\t\\t\\treturn -1;\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t} while (!Arrays.equals(cur, FREE)\\r\\n\\t\\t\\t\\t\\t&& (Arrays.equals(cur, REMOVED) || storehash!=hash));\\r\\n\\t\\t}\\r\\n\\r\\n\\t\\treturn storehash!=hash ? -1 : index;\\r\\n\\t}\",\n \"private void remove(int index){\\r\\n \\tkeys[index] = null;\\r\\n \\tvals[index] = null;\\r\\n deleteCheck(index);\\r\\n }\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6721599","0.6681743","0.66589624","0.65445966","0.65445966","0.6508383","0.63637435","0.6360245","0.63154876","0.62771064","0.62437534","0.6216059","0.6196626","0.61939406","0.61733735","0.61713153","0.6138556","0.61282516","0.61186033","0.6097255","0.60916597","0.6064276","0.60636556","0.60311574","0.60201687","0.59836733","0.59775645","0.5968548","0.5936951","0.5935982","0.59297764","0.5928079","0.591542","0.5915161","0.5897357","0.5894298","0.5888599","0.5876485","0.58757263","0.5874803","0.5867999","0.58547026","0.5853894","0.583781","0.582098","0.58162874","0.5809275","0.58071107","0.5774035","0.5769674","0.57693124","0.57682914","0.5766046","0.5762575","0.5762243","0.57544374","0.57512045","0.57316995","0.5731581","0.5728489","0.5723132","0.5716007","0.56763524","0.5671989","0.5665374","0.5664316","0.56315935","0.56250036","0.5624256","0.56185883","0.56136805","0.5613507","0.5609511","0.5594688","0.5584218","0.557975","0.55759895","0.5575217","0.55751175","0.55751175","0.55672604","0.5561553","0.5543655","0.55317926","0.5528704","0.5528623","0.55217016","0.5510281","0.5504107","0.5496991","0.5494953","0.54836965","0.5483436","0.5483425","0.54728717","0.54720855","0.54545945","0.5448113","0.54410535","0.54342276"],"string":"[\n \"0.6721599\",\n \"0.6681743\",\n \"0.66589624\",\n \"0.65445966\",\n \"0.65445966\",\n \"0.6508383\",\n \"0.63637435\",\n \"0.6360245\",\n \"0.63154876\",\n \"0.62771064\",\n \"0.62437534\",\n \"0.6216059\",\n \"0.6196626\",\n \"0.61939406\",\n \"0.61733735\",\n \"0.61713153\",\n \"0.6138556\",\n \"0.61282516\",\n \"0.61186033\",\n \"0.6097255\",\n \"0.60916597\",\n \"0.6064276\",\n \"0.60636556\",\n \"0.60311574\",\n \"0.60201687\",\n \"0.59836733\",\n \"0.59775645\",\n \"0.5968548\",\n \"0.5936951\",\n \"0.5935982\",\n \"0.59297764\",\n \"0.5928079\",\n \"0.591542\",\n \"0.5915161\",\n \"0.5897357\",\n \"0.5894298\",\n \"0.5888599\",\n \"0.5876485\",\n \"0.58757263\",\n \"0.5874803\",\n \"0.5867999\",\n \"0.58547026\",\n \"0.5853894\",\n \"0.583781\",\n \"0.582098\",\n \"0.58162874\",\n \"0.5809275\",\n \"0.58071107\",\n \"0.5774035\",\n \"0.5769674\",\n \"0.57693124\",\n \"0.57682914\",\n \"0.5766046\",\n \"0.5762575\",\n \"0.5762243\",\n \"0.57544374\",\n \"0.57512045\",\n \"0.57316995\",\n \"0.5731581\",\n \"0.5728489\",\n \"0.5723132\",\n \"0.5716007\",\n \"0.56763524\",\n \"0.5671989\",\n \"0.5665374\",\n \"0.5664316\",\n \"0.56315935\",\n \"0.56250036\",\n \"0.5624256\",\n \"0.56185883\",\n \"0.56136805\",\n \"0.5613507\",\n \"0.5609511\",\n \"0.5594688\",\n \"0.5584218\",\n \"0.557975\",\n \"0.55759895\",\n \"0.5575217\",\n \"0.55751175\",\n \"0.55751175\",\n \"0.55672604\",\n \"0.5561553\",\n \"0.5543655\",\n \"0.55317926\",\n \"0.5528704\",\n \"0.5528623\",\n \"0.55217016\",\n \"0.5510281\",\n \"0.5504107\",\n \"0.5496991\",\n \"0.5494953\",\n \"0.54836965\",\n \"0.5483436\",\n \"0.5483425\",\n \"0.54728717\",\n \"0.54720855\",\n \"0.54545945\",\n \"0.5448113\",\n \"0.54410535\",\n \"0.54342276\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.6162504"},"document_rank":{"kind":"string","value":"16"}}},{"rowIdx":13886,"cells":{"query":{"kind":"string","value":"SEARCH MANAGEMENT (USER) [MODIFIED] Returns the postings for a specific term, or null if the term is not in the index."},"document":{"kind":"string","value":"public PostingsList getPostings( String token ) {\n PostingsList post = new PostingsList();\n if(this.index.containsKey(token))\n post = (this.index.get(token)).clone();\n /*System.err.println(\"start search...\");\n // Read JSON file associated to token and return it as a postingslist\n String filename = \"postings/t\"+hash(token)+\".json\";\n PostingsList post = new PostingsList();\n try(Reader reader = new FileReader(filename)){\n post = (new Gson()).fromJson(reader, PostingsList.class);\n } catch (IOException e) {\n e.printStackTrace();\n }*/\n return post;\n }"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["@Override\r\n\tpublic List<Post> searchInfResult(String word) {\n\t\tpostDao=new PostDaoImpl(TransactionManager.connection);\r\n\t\treturn postDao.selectPosts(word);\r\n\t}","private void termQuerySearch(String[] terms) {\n for (String term : terms) {\n LinkedList<TermPositions> postingLists = indexMap.get(analyzeTerm(term));\n if (postingLists != null) {\n for (TermPositions matches : postingLists) {\n double score = (double) 1 + Math.log((double) matches.getPositionList().size()) *\n Math.log((double) N / (double) postingLists.size());\n resultsCollector.add(new DocCollector(matches.getDocId(), score));\n }\n }\n }\n }","List<DataTerm> search(String searchTerm);","public void search(Indexer indexer, CityIndexer cityIndexer, Ranker ranker, String query, boolean withSemantic, ArrayList<String> chosenCities, ObservableList<String> citiesByTag, boolean withStemming, String saveInPath, String queryId, String queryDescription) {\n String[] originalQueryTerms = query.split(\" \");\n String originQuery = query;\n docsResults = new HashMap<>();\n parser = new Parse(withStemming, saveInPath, saveInPath);\n HashSet<String> docsOfChosenCities = new HashSet<>();\n query = \"\" + query + queryDescription;\n HashMap<String, Integer> queryTerms = parser.parseQuery(query);\n HashMap<String, ArrayList<Integer>> dictionary = indexer.getDictionary();\n if (!withStemming){\n setDocsInfo(saveInPath + \"\\\\docsInformation.txt\");\n }\n else{\n setDocsInfo(saveInPath + \"\\\\docsInformation_stemming.txt\");\n }\n\n\n //add semantic words of each term in query to 'queryTerms'\n if(withSemantic) {\n HashMap<String,ArrayList<String>> semanticWords = ws.connectToApi(originQuery);\n }\n\n //give an ID to query if it's a regular query (not queries file)\n if(queryId.equals(\"\")){\n queryId = \"\" + Searcher.queryID;\n Searcher.queryID++;\n }\n\n String postingDir;\n if (!withStemming) {\n postingDir = \"\\\\indexResults\\\\postingFiles\";\n } else {\n postingDir = \"\\\\indexResults\\\\postingFiles_Stemming\";\n }\n int pointer = 0;\n\n //find docs that contain the terms in the query in their text\n HashMap<String, Integer> queryTermsIgnoreCase = new HashMap<>();\n for (String term : queryTerms.keySet()) {\n String originTerm = term;\n if (!dictionary.containsKey(term.toUpperCase()) && !dictionary.containsKey(term.toLowerCase())) {\n continue;\n }\n if(dictionary.containsKey(term.toLowerCase())){\n term = term.toLowerCase();\n }\n else {\n term = term.toUpperCase();\n }\n queryTermsIgnoreCase.put(term,queryTerms.get(originTerm));\n pointer = dictionary.get(term).get(2);\n String chunk = (\"\" + term.charAt(0)).toUpperCase();\n\n //get the relevant line from posting file\n BufferedReader br = null;\n try {\n br = new BufferedReader(new FileReader(new File(saveInPath + postingDir + \"\\\\posting_\" + chunk + \".txt\")));\n String line = \"\";\n int i = 1;\n while ((line = (br.readLine())) != null) {\n if (i == pointer) {\n break;\n }\n i++;\n }\n br.close();\n\n //get docs from posting line and add them to the data structure 'docsResults'\n if(line != null) {\n findDocsFromLine(line, term);\n }\n\n } catch (IOException e) {\n e.printStackTrace();\n }\n }\n\n //find docs that contain the chosen cities in their text\n for (String cityTerm : chosenCities) {\n if (!dictionary.containsKey(cityTerm) && !dictionary.containsKey(cityTerm.toLowerCase())) {\n continue;\n }\n if(dictionary.containsKey(cityTerm.toLowerCase())){\n cityTerm = cityTerm.toLowerCase();\n }\n pointer = dictionary.get(cityTerm).get(2);\n // char chunk = indexer.classifyToPosting(term).charAt(0);\n String chunk = (\"\" + cityTerm.charAt(0)).toUpperCase();\n\n //get the relevant line from posting file\n BufferedReader br = null;\n try {\n br = new BufferedReader(new FileReader(new File(saveInPath + postingDir + \"\\\\posting_\" + chunk + \".txt\")));\n String line = \"\";\n int i = 1;\n while ((line = (br.readLine())) != null) {\n if (i == pointer) {\n break;\n }\n i++;\n }\n br.close();\n\n //get docs from posting line and add them to the data structure 'docsOfChosenCities'\n String docs = line.substring(0, line.indexOf(\"[\") - 1); //get 'docsListStr'\n String[] docsArr = docs.split(\";\");\n for (String docInfo : docsArr) {\n String doc = docInfo.substring(0, docInfo.indexOf(\": \"));\n while(doc.charAt(0) == ' '){\n doc = doc.substring(1);\n }\n docsOfChosenCities.add(doc);\n }\n } catch (IOException e) {\n e.printStackTrace();\n }\n }\n\n //find docs that contain the chosen cities in their city tag\n if(!chosenCities.isEmpty()){\n for (String cityDicRec: chosenCities) {\n //get pointer to posting from cityDictionary\n try {\n pointer = cityIndexer.getCitiesDictionary().get(cityDicRec);\n } catch (NumberFormatException e) {\n e.printStackTrace();\n }\n //get the relevant line from posting file\n BufferedReader br = null;\n try {\n br = new BufferedReader(new FileReader(new File(saveInPath + \"\\\\cityIndexResults\" + \"\\\\posting_city\" + \".txt\")));\n String line = \"\";\n int i = 1;\n while ((line = (br.readLine())) != null) {\n if (i == pointer) {\n break;\n }\n i++;\n }\n br.close();\n\n //get docs from posting line and add them to the data structure 'docsOfChosenCities'\n String docs = line.substring(line.indexOf(\"[\") + 1, line.indexOf(\"]\")); //get 'docsListStr'\n String[] docsArr = docs.split(\"; \");\n for (String doc : docsArr) {\n docsOfChosenCities.add(doc);\n }\n } catch (IOException e) {\n e.printStackTrace();\n }\n }\n }\n\n\n ranker.rank(docsResults, docsOfChosenCities, queryTermsIgnoreCase, dictionary, docsInfo,entities, queryId);\n }","@Override\n public int getIndexByTerm(String term) {\n return 0;\n }","@Override\n\tprotected void executeSearch(String term) {\n\t\t\n\t}","@Override\n \tpublic ArrayList<Object> searchPostByName(String search) {\n\t\t\n\t\tSystem.out.println(\"i am in service search looking for cool posts\" + search);\n\t\t\n\t\tif(search == null){\n\t\t\treturn null;\n\t\t}\n\t\t\n\t\tArrayList<Object> list = null; //postRepository.findPostByName(search); ****Nick set this to null; otherwise it failed. Needs corrected in future\n\t\t\n\t\t//System.out.println(Arrays.toString(list));\n\t\treturn list;\n\t}","public org.apache.xmlbeans.XmlAnySimpleType getSearchTerms()\n {\n synchronized (monitor())\n {\n check_orphaned();\n org.apache.xmlbeans.XmlAnySimpleType target = null;\n target = (org.apache.xmlbeans.XmlAnySimpleType)get_store().find_attribute_user(SEARCHTERMS$6);\n if (target == null)\n {\n return null;\n }\n return target;\n }\n }","public PostingsList search( Query query, int queryType, int rankingType, int structureType ) {\r\n switch(queryType){\r\n case Index.INTERSECTION_QUERY : \r\n return searchIntersection( query, rankingType, structureType);\r\n\r\n case Index.PHRASE_QUERY :\r\n return searchPhrase( query, rankingType, structureType);\r\n default:\r\n break;\r\n }\r\n\r\n return null;\r\n }","public static void searchJobs(String searchTerm) {\n\n for (int i = 0; i > PostJob.allJobs.size(); i++) {\n\n\n if (PostJob.allJobs.contains(searchTerm)) {\n int itemIndx = PostJob.allJobs.indexOf(searchTerm);\n String output = PostJob.allJobs.get(itemIndx);\n System.out.print(\"Available jobs within your search terms\" + output);\n\n }\n }\n }","public void onSearchResults(String term, List<WikiPage> results);","public int getTermIndex() {return termIndex;}","public MagicSearch createMagicSearch();","public interface DocumentRelatedTermsSearcher {\n List<ScoredTerm> getDocumentRelatedTerms(int docId, String term) throws SearchException;\n}","public void SearchPhrase(Object_Ord temp) {\n\tif (!Doneloading) {\r\n\t return;\r\n\t}\r\n\tif (temp == null) {\r\n\t return;\r\n\t} else if (temp.Ordet.equals(\"\")) {\r\n\t return;\r\n\t}\r\n\ttemp.Set_Searched();\r\n\t//PrintAction( this.getClass().toString() + \" Searching for phrase \" + temp.Ordet );\r\n\tThread thread = new Thread_PhraseSearcher(this, temp);\r\n\tThreadsRunning++;\r\n\tThreadsStarted++;\r\n }","public String search(String term, String location) {\n\t\t\t String limit = \"6\";\n\t\t OAuthRequest request = new OAuthRequest(Verb.GET, \"http://api.yelp.com/v2/search\");\n\t\t request.addQuerystringParameter(\"term\", term);\n\t\t request.addQuerystringParameter(\"location\", location);\n\t\t request.addQuerystringParameter(\"limit\", limit);\n\t\t this.service.signRequest(this.accessToken, request);\n\t\t Response response = request.send();\n\t\t return response.getBody();\n\t\t }","public void onSearchSubmit(String queryTerm);","public String getTerm(){\n return this.term;\n }","public PostingsList getPostings( String token ) {\r\n PostingsList element = index.get(token) ;\r\n if (element != null)\r\n {\r\n return element;\r\n }\r\n return null;\r\n }","List<User> searchUsers(String searchTerm) {\n return null;\n }","@Override\n public List<SearchResult> search(String queryString, int k) {\n // TODO: YOUR CODE HERE\n\n // Tokenize the query and put it into a Set\n HashSet<String> tokenSet = new HashSet<>(Searcher.tokenize(queryString));\n\n /*\n * Section 1: FETCHING termId, termFreq and relevant docId from the Query\n */\n\n // Init a set to store Relevant Document Id\n HashSet<Integer> relevantDocIdSet = new HashSet<>();\n for (String token : tokenSet) { // Iterates thru all query tokens\n int termId;\n try {\n termId = indexer.getTermDict().get(token);\n } catch (NullPointerException e) { // In case current token is not in the termDict\n continue; // Skip this one\n }\n // Get the Posting associate to the termId\n HashSet<Integer> posting = indexer.getPostingLists().get(termId);\n relevantDocIdSet.addAll(posting); // Add them all to the Relevant Document Id set\n }\n\n /*\n * Section 2: Calculate Jaccard Coefficient between the Query and all POTENTIAL DOCUMENTS\n */\n\n // ArrayList for the Final Result\n ArrayList<SearchResult> searchResults = new ArrayList<>();\n for (Document doc : documents) { // Iterates thru all documents\n if (!relevantDocIdSet.contains(doc.getId())) { // If the document is relevant\n searchResults.add(new SearchResult(doc, 0)); // Add the document as a SearchResult with zero score\n } else {\n HashSet<String> termIdSet = new HashSet<>(doc.getTokens()); // Get the token set from the document\n\n // Calculate Jaccard Coefficient of the document\n double jaccardScore = JaccardMathHelper.calculateJaccardSimilarity(tokenSet, termIdSet);\n\n // Add the SearchResult with the computed Jaccard Score\n searchResults.add(new SearchResult(doc, jaccardScore));\n }\n }\n\n return TFIDFSearcher.finalizeSearchResult(searchResults, k);\n }","@RequestMapping(method=RequestMethod.POST,value = \"/search\")\n public ArrayList<Results> searchMentors(@RequestBody SearchForm s) {\n return resultsRepository.findMentors(s.getFrom(),s.getCourse(),s.getTimeslot());\n }","@Override\n public SearchResult search_hunter(String keyword, int page, int rows ,int search_type) throws Exception{\n\n return null;\n }","public PostingsList search( Query query, int queryType, int rankingType,\n int structureType ) {\n double idf_threshold = new Double(0);\n double index_elimination = new Double(0.008);\n // System.err.println(pageRank[docNumber.get(\"121\")]);\n\n if (query.size()>0){\n switch (queryType){\n case Index.INTERSECTION_QUERY:\n System.err.println(\"Intersection query\");\n return intersect(query);\n case Index.PHRASE_QUERY:\n System.err.println(\"Phrase query\");\n return phrase_query(query);\n case Index.RANKED_QUERY:\n System.err.println(\"Ranked query\");\n switch(rankingType){\n case Index.TF_IDF: return ranked_query(query, 1, idf_threshold);\n case Index.PAGERANK: return ranked_query(query, 0, idf_threshold);//ranked_query(query, 0, idf_threshold);//ranked_query2(query, 0);\n case Index.COMBINATION: return ranked_query(query, index_elimination, idf_threshold);\n }\n default:\n System.out.println(\"not valid query\");\n return null;\n }\n }\n else\n // Query was empty\n return null;\n }","public PostingsList phrase_query(Query query){\n\n LinkedList<PostingsList> listQueriedPostings = new LinkedList<PostingsList>();\n // List with postings corresponding to the queries\n for (int i = 0; i<query.size(); i++){\n // If any query has zero matches, return 0 results\n //if(!(new File(\"postings/t\"+hash(query.terms.get(i))+\".json\")).exists()){\n if (!this.index.containsKey(query.terms.get(i))){\n return null;\n }\n // Otherwise store postings in the list\n listQueriedPostings.add(this.getPostings(query.terms.get(i)));\n }\n\n PostingsList result = new PostingsList();\n result = listQueriedPostings.get(0);\n\n // In case only one word is queried\n if (listQueriedPostings.size() == 1){\n return result;\n }\n\n // Apply algorithm as many times as words in the query\n for(int i = 1; i < listQueriedPostings.size(); i++){\n result = phrase_query(result, listQueriedPostings.get(i));\n if (result.isEmpty()){\n return null;\n }\n }\n return result;\n }","Search getSearch();","public void search() {\r\n \t\r\n }","SearchResult<TimelineMeta> search(SearchParameter searchParameter);","com.google.ads.googleads.v6.resources.SearchTermView getSearchTermView();","SearchResult<TimelineMeta> search(SearchQuery searchQuery);","public void search() {\n String q = this.query.getText();\n String cat = this.category.getValue();\n if(cat.equals(\"Book\")) {\n searchBook(q);\n } else {\n searchCharacter(q);\n }\n }","public Post[] wallSearch(String text) {\n return null;\n }","private static String handleNonPhraseToken(String stringPart) {\r\n // Set of final terms to be used (no empty elements, right syntax of index fields)\r\n ArrayList <String> terms = new ArrayList <String> ();\r\n \r\n /** Case Index field **/\r\n if(stringPart.contains(\"[\") | stringPart.contains(\"[\")){ // at least an Index field contained here\r\n //separate brackets for term with one space (extra spaces dont matter, trim() is used later)\r\n stringPart = stringPart.replace(\"[\", \" [\");\r\n stringPart = stringPart.replace(\"]\", \"] \");\r\n }\r\n\r\n /** Case Bag of terms **/\r\n //replace space with AND (change default operator to match pubMed's)\r\n // No need for this if setDefaultOperator(QueryParser.Operator.AND) is used\r\n \r\n String[] tokens = stringPart.split(\"\\\\s\");\r\n if(tokens.length > 0){ \r\n for(int i = 1 ; i < tokens.length ; i++){\r\n tokens[i] = tokens[i].trim();\r\n /* Case index field [fieldName] */\r\n if(tokens[i].startsWith(\"[\") & tokens[i].endsWith(\"]\")){\r\n tokens[i] = tokens[i].replace(\"[\",\"\");// clean field name from brackets\r\n tokens[i] = tokens[i].replace(\"]\",\"\");// clean field name from brackets\r\n //Add index field as prefix to previus (not empty) term (as opening index fields handled separately, this index field should not be the first term of string part)\r\n int tmp = i-1;\r\n boolean perviusTermFound = false;\r\n while(!perviusTermFound & tmp >= 0){\r\n if(!tokens[tmp].equals(\"\")){\r\n perviusTermFound = true;\r\n //TO DO : handle wrong syntax (e.g. ... AND [ArticleTitle])\r\n String luceneField = supportedIndexFields.get(tokens[i]);\r\n if(luceneField != null){\r\n tokens[tmp] = luceneField + \":\" + tokens[tmp];\r\n } // else : Lucene counterpart not found, unsupported field - do nothing\r\n } else {\r\n tmp--;\r\n }\r\n }\r\n //Empty field to not be added as a search term in query\r\n tokens[i] = \"\";\r\n } \r\n \r\n /*\r\n \r\n else if(!tokens[i].equals(\"AND\") & !tokens[i].equals(\"\")) {\r\n terms.add(tokens[i]);\r\n }\r\n */\r\n }\r\n }\r\n \r\n String luceneQueryPart = \"\";\r\n boolean notWaiting = false;\r\n boolean orWaiting = false;\r\n for(int i = 0 ; i < tokens.length ; i++){\r\n\r\n if(!tokens[i].equals(\"AND\") & !tokens[i].equals(\"\")){\r\n //in case of AND nothing should happen, it is the default operator\r\n //empty elements are also ignored as useless\r\n \r\n if(!tokens[i].equals(\"NOT\") & !tokens[i].equals(\"OR\") ){ // it's not an operator, it's a term\r\n \r\n if(!luceneQueryPart.endsWith(\" OR \") & !luceneQueryPart.endsWith(\" -\") ) { \r\n luceneQueryPart += \" +\"; \r\n } \r\n luceneQueryPart += tokens[i];\r\n } else {\r\n if(tokens[i].equals(\"NOT\")) {\r\n luceneQueryPart += \" -\";\r\n }\r\n if(tokens[i].equals(\"OR\")){\r\n luceneQueryPart += \" OR \";\r\n }\r\n \r\n } \r\n } \r\n }\r\n \r\n return luceneQueryPart;\r\n }","private void searchWord()\n {\n String inputWord = searchField.getText();\n \n if(inputWord.isEmpty())\n queryResult = null;\n \n else\n {\n char firstLetter = inputWord.toUpperCase().charAt(0);\n \n for(int i = 0 ; i < lexiNodeTrees.size() ; i++)\n {\n if(lexiNodeTrees.get(i).getCurrentCharacter() == firstLetter)\n {\n queryResult = lexiNodeTrees.get(i).searchWord(inputWord, false);\n i = lexiNodeTrees.size(); // escape the loop\n }\n }\n }\n \n // update the list on the GUI\n if(queryResult != null)\n {\n ArrayList<String> words = new ArrayList<>();\n for(WordDefinition word : queryResult)\n {\n words.add(word.getWord());\n }\n \n // sort the list of words alphabetically \n Collections.sort(words);\n \n // display the list of wordsin the UI\n DefaultListModel model = new DefaultListModel();\n for(String word : words)\n {\n model.addElement(word);\n }\n\n this.getSearchSuggestionList().setModel(model);\n }\n \n else\n this.getSearchSuggestionList().setModel( new DefaultListModel() );\n }","public void search() {\n }","@Override\r\n\tpublic String searchPoster(String searchPoster) throws Exception {\n\t\treturn null;\r\n\t}","void search();","void search();","@Override\r\n\t\t\tpublic List<ScoredDocument> search(Query query) {\n\t\t\t\treturn null;\r\n\t\t\t}","@Action\r\n public String search() {\n ServiceFunctions.clearCache();\r\n\r\n if (isAdmin()) {\r\n return adminSearch();\r\n }\r\n\r\n return publicSearch();\r\n }","@Override\n public String getTermByIndex(int index) {\n return null;\n }","public String getTerm() {\n return term;\n }","@Override\r\n\t\t\tpublic boolean containsTerm(Document document, String term) {\n\t\t\t\treturn false;\r\n\t\t\t}","public org.apache.xmlbeans.XmlAnySimpleType addNewSearchTerms()\n {\n synchronized (monitor())\n {\n check_orphaned();\n org.apache.xmlbeans.XmlAnySimpleType target = null;\n target = (org.apache.xmlbeans.XmlAnySimpleType)get_store().add_attribute_user(SEARCHTERMS$6);\n return target;\n }\n }","@RequestMapping(\"/\")\n public String index(@RequestParam(value = \"searchTerm\", required = false, defaultValue = \"None\") String searchTerm, Model model) {\n List<Review> reviews = this.reviewService.fetchAll();\n if (!searchTerm.equals(\"None\")) {\n List<Review> filteredReviews = new ArrayList<>();\n for (Review review : reviews)\n if (review.getPlaceId().equals(searchTerm))\n filteredReviews.add(review);\n reviews = filteredReviews;\n }\n System.out.println(reviews);\n model.addAttribute(reviews);\n return \"index\";\n }","public PostingsList ranked_query(Query query, double w, double idf_threshold){\n long startTime = System.nanoTime();\n PostingsList result = new PostingsList();\n\n // Obtain union of terms above idf threshold if indexElimination is true\n // (Set idf_threshold to zero to disable this feature)\n Set<String> termsToConsider = this.queryTermsConsidered(query, idf_threshold);\n result = this.union_query(query, termsToConsider);\n //System.err.println(\"Size of result is \" + result.size());\n\n long estimatedTime = (System.nanoTime() - startTime)/1000000;\n System.err.println(\"* Union took: \" + estimatedTime);\n\n\n /*\n * 2) Iterate over PostingsEntries and build the solution\n */\n startTime = System.nanoTime();\n // Required when iterating over a PostingsList\n PostingsEntry postEnt = new PostingsEntry();\n // Number of documents in the collection\n double nDocs = this.docIDs.size();\n // Weight of a query vector coefficient\n double w_query_term;\n // Document tf-idf variables\n double termFrequency_doc, documentFrequency_doc, w_doc_term;\n\n for(String term : termsToConsider){\n // Obtain idf of the term\n documentFrequency_doc = Math.log(nDocs/new Double(this.idfMap.get(term)));\n\n // Obtain weight of the term\n w_query_term = query.weights.get(term);\n // Iterate over all documents containing the term and update the score(q,d)\n Iterator<PostingsEntry> it_d = result.iterator();\n while(it_d.hasNext()){\n postEnt = it_d.next();\n if (this.tfMap.get(postEnt.docID).containsKey(term)){\n termFrequency_doc = this.tfMap.get(postEnt.docID).get(term);\n w_doc_term = documentFrequency_doc*termFrequency_doc;\n postEnt.score += w_query_term*w_doc_term;\n }\n }\n }\n estimatedTime = (System.nanoTime() - startTime)/1000000;\n System.err.println(\"* Building solution took: \" + estimatedTime);\n\n /*\n * 3) Normalize the scores\n */\n startTime = System.nanoTime();\n Iterator<PostingsEntry> it = result.iterator();\n while(it.hasNext()){\n postEnt = it.next();\n postEnt.score /= (new Double(this.docLengths.get(\"\"+postEnt.docID)));//(Math.sqrt(postEnt.norm2));\n postEnt.score = w * postEnt.score + (1-w) * quality(postEnt.docID);\n }\n estimatedTime = (System.nanoTime() - startTime)/1000000;\n System.err.println(\"* Normalizing took: \" + estimatedTime);\n\n /*\n * 4) Sort the resulting solution\n */\n startTime = System.nanoTime();\n result.sort();\n estimatedTime = (System.nanoTime() - startTime)/1000000;\n System.err.println(\"* Sorting took: \" + estimatedTime);\n\n return result;\n }","ReagentSearch getReagentSearch();","SpellResponse spellQuery(SearchRequest request, Map<SearchParam, String> params);","@Override\n\tpublic List<Literature> searchKeywords() {\n\t\treturn null;\n\t}","List<PilotContainer> Search(String cas, String word);","abstract public void search();","public IndexedList<Task> search() {\n\t\treturn null;\n\t}","public ArrayList<ArrayList> simpleQuery(String word)\n {\n ArrayList<ArrayList> data = new ArrayList();\n\n IndexObject obj = myIndex.get(word.hashCode());\n if(obj == null)\n {\n errorMsg();\n return null;\n }\n data.add(new ArrayList<Document>(obj.getDocuments()));\n data.add(new ArrayList<Double>(obj.getRelevance()));\n data.add(new ArrayList<Integer>(obj.getOccurrence()));\n data.add(new ArrayList<Integer>(obj.getPopularity()));\n return data;\n }","@Override\n public Data3DPlastic search() {\n return super.search();\n }","public abstract HashMap search(String keyword);","com.google.ads.googleads.v6.resources.SearchTermViewOrBuilder getSearchTermViewOrBuilder();","public List<Recipe> search(String queryText, Category category, CookingMethod cookingMethod);","@Override\n\tpublic void search() {\n\t}","List<Block> search(String searchTerm);","public HashMap<String, Double> search(String query) {\n // ===================================================\n // 1. Fetch all inverted lists corresponding to terms\n // in the query.\n // ===================================================\n String[] terms = query.split(\" \");\n HashMap<String, Integer> qf = new HashMap<String, Integer>();\n // Calculate term frequencies in the query\n for (String term : terms) {\n if (qf.containsKey(term))\n qf.put(term, qf.get(term) + 1);\n else\n qf.put(term, 1);\n }\n HashMap<String, Double> docScore = new HashMap<String, Double>();\n for (Entry<String, Integer> termEntry : qf.entrySet()) {\n String term = termEntry.getKey();\n int qfi = termEntry.getValue();\n\n // ===================================================\n // 2. Compute BM25 scores for documents in the lists.\n // Make a score list for documents in the inverted\n // lists. Assume that no relevance information is \n // available. For parameters, use k1=1.2, b=0.75, \n // k2=100.\n // ===================================================\n double k1 = 1.2;\n double b = 0.75;\n double k2 = 100;\n int ni = invIndex.get(term).size();\n\n\n for (Entry<String, IndexEntry> invListEntry : invIndex.get(term).entrySet()) {\n String docID = invListEntry.getKey();\n double bm25Score;\n if (docScore.containsKey(docID))\n bm25Score = docScore.get(docID);\n else\n bm25Score = 0;\n\n // length of the document\n int dl = docStat.get(docID);\n // frequency of the term in the document\n int fi = invListEntry.getValue().getTf();\n double K = k1 * ((1 - b) + b * ((double) dl / avdl));\n\n // ===================================================\n // 3. Accumulate scores for each term in a query\n // on the score list.\n // ===================================================\n bm25Score += Math.log((N - ni + 0.5) / (ni + 0.5))\n * (((k1 + 1) * fi * (k2 + 1) * qfi) / ((K + fi) * (k2 + qfi)));\n docScore.put(docID, bm25Score);\n }\n }\n\n return docScore;\n }","List<SearchResult> search(SearchQuery searchQuery);","public List<Post> search(PostCriteria criteria, int page, int size);","private static List<SearchData> booleanSearchWord(Query query, Indexer si) {\n Tokenizer tkn = new SimpleTokenizer();\n tkn.tokenize(query.getStr(), \"[a-zA-Z]{3,}\", true, true);\n List<SearchData> searchList = new ArrayList<>();\n LinkedList<Token> wordsList = tkn.getTokens();\n Iterator<Token> wordsIt = wordsList.iterator();\n HashMap<String, LinkedList<Posting>> indexer = si.getIndexer();\n int idx;\n SearchData searched_doc;\n\n while (wordsIt.hasNext()) {\n String word = wordsIt.next().getSequence();\n if (indexer.containsKey(word)) {\n\n LinkedList<Posting> posting = indexer.get(word);\n\n for (Posting pst : posting) {\n\n SearchData sd = new SearchData(query, pst.getDocId());\n\n if (!searchList.contains(sd)) {\n sd.setScore(1);\n searchList.add(sd);\n } else {\n idx = searchList.indexOf(sd);\n searched_doc = searchList.get(idx);\n searched_doc.setScore(searched_doc.getScore() + 1);\n }\n }\n\n }\n\n\n }\n\n Collections.sort(searchList);\n\n return searchList;\n }","public abstract int search(String[] words, String wordToFind) throws ItemNotFoundException;","public static void searchSimillar(String keyword,int numberofResults,PreSearch ps) {\t\t\r\n\t\tHashMap<String,Integer> sortedDistance = sortByEditDistance(keyword,ps);\r\n\t\tIterator<Entry<String, Integer>> iterator2 = sortedDistance.entrySet().iterator(); \r\n\t\twhile(iterator2.hasNext()) \r\n\t\t{ \t\t\t\r\n\t\t\tMap.Entry<String, Integer> me = (Map.Entry<String, Integer>)iterator2.next();\r\n\t\t\tString word = me.getKey().toString();\t\t\t\r\n\t\t\tSystem.out.println(\"Instead showing results for : \"+word);\r\n\t\t\t\r\n\t\t\t//Searching for the word with lowest distance.\r\n\t\t\tMap<String,Integer> sortedMap;\r\n\t\t\tArrayList<String> as = ps.find(word);\r\n\t\t\tString phrase = word.toLowerCase();\r\n\t\t\t\r\n\t\t\tsortedMap = SortResultsByRank.sortByRank(as, phrase);\t\t\t\r\n\t\t\tSearch.printResult(sortedMap,numberofResults);\r\n\t\t\tbreak;\r\n\t\t}\r\n\t\t\r\n\t}","@RequestMapping(value={\"/search\"}, method={RequestMethod.GET})\n \tpublic ModelAndView handleSearch(@RequestParam(required=false) String q, @RequestParam(required=false,defaultValue=\"1\") Integer page){\n \t\tMap<String,Object> model = new HashMap<String,Object>();\n \t\t\n \t HashMap<String,Object> search = new HashMap<String,Object>();\n \t search.put(\"term\", \"\");\n \t search.put(\"total\",0);\n \n \t List<Map<String,String>> searchResult = new ArrayList<Map<String,String>>();\n \t if(StringUtils.isNotBlank(q)){\n \t \tsearch.put(\"term\", q);\n \t \tLimitedResult<List<NameConceptModelIF>> nameConceptModelList = null;\n \t \tint pageIndex = (page <= 0)?0:(page-1);\n \t \t//use page index +1 to avoid returning a bad page number\n \t\tsearch.put(\"pageNumber\", (pageIndex+1));\n \t\tsearch.put(\"pageSize\", searchService.getPageSize());\n \t\t//check if we want another page than the first one\n \t \tif(pageIndex > 0){\n \t \t\tnameConceptModelList = searchService.searchName(q,pageIndex);\n \t \t}\n \t \telse{\n \t \t\tnameConceptModelList = searchService.searchName(q);\n \t \t}\n \n \t\t search.put(\"total\",nameConceptModelList.getTotal_rows());\n \t\t List<Map<String,String>> searchResults = new ArrayList<Map<String,String>>();\n \t\t Map<String,String> searchRow = null;\n \t\t //TODO use objects directly instead of map\n \t\t for(NameConceptModelIF currNameConceptModel : nameConceptModelList.getRows()){\n \t\t \tif(currNameConceptModel.getClass().equals(NameConceptTaxonModel.class)){\n \t\t \t\tsearchRow = new HashMap<String,String>();\n \t\t \t\tsearchRow.put(\"type\",\"taxon\");\n \t\t \t\tsearchRow.put(\"name\", currNameConceptModel.getName());\n \t\t \t\tsearchRow.put(\"id\", currNameConceptModel.getTaxonId().toString());\n \t\t \t\tsearchRow.put(\"status\", currNameConceptModel.getStatus());\n \t\t \t\tsearchRow.put(\"namehtml\",((NameConceptTaxonModel)currNameConceptModel).getNamehtml());\n \t\t \t\tsearchRow.put(\"namehtmlauthor\",((NameConceptTaxonModel)currNameConceptModel).getNamehtmlauthor());\n \t\t \t\tsearchRow.put(\"rankname\",((NameConceptTaxonModel)currNameConceptModel).getRankname());\n \t\t \t\tsearchRow.put(\"parentid\",((NameConceptTaxonModel)currNameConceptModel).getParentid().toString());\n \t\t \t\tsearchRow.put(\"parentnamehtml\",((NameConceptTaxonModel)currNameConceptModel).getParentnamehtml());\n \t\t \t\tsearchResult.add(searchRow);\n \t\t \t}\n \t\t \telse if(currNameConceptModel.getClass().equals(NameConceptVernacularNameModel.class)){\n \t\t \t\tsearchRow = new HashMap<String, String>();\n \t\t \t\tsearchRow.put(\"type\",\"vernacular\");\n \t\t \t\tsearchRow.put(\"name\", currNameConceptModel.getName());\n \t\t \t\tsearchRow.put(\"id\", Integer.toString(((NameConceptVernacularNameModel)currNameConceptModel).getId()));\n \t\t \t\tsearchRow.put(\"status\", currNameConceptModel.getStatus());\n \t\t \t\tsearchRow.put(\"lang\",((NameConceptVernacularNameModel)currNameConceptModel).getLang());\n \t\t \t\tsearchRow.put(\"taxonid\",currNameConceptModel.getTaxonId().toString());\n \t\t \t\tsearchRow.put(\"taxonnamehtml\",((NameConceptVernacularNameModel)currNameConceptModel).getTaxonnamehtml());\n \t\t \t\tsearchResult.add(searchRow);\n \t\t \t}\n \t\t \telse{\n \t\t \t\t//logger\n \t\t \t\tsearchRow = null;\n \t\t \t}\n \t\t \tsearchResults.add(searchRow);\n \t\t }\n \t\t model.put(\"results\",searchResults);\n \t }\n \t \n \t model.put(\"search\",search);\n \t return new ModelAndView(\"search\", model);\n \t}","@Override\n public List<KBHandle> searchItems(KnowledgeBase aKB, String aQuery)\n {\n return disambiguate(aKB, null, ConceptFeatureValueType.ANY_OBJECT, aQuery, null, 0, null);\n }","public abstract S getSearch();","public void searchIndexWithTermQueryByBody(final String toSearch) throws IOException, ParseException {\n searchIndexWithTermQuery(toSearch, \"body\", DEFAULT_LIMIT);\n }","Boolean getSearchObjective();","@Override\r\n\tpublic void search() {\n\r\n\t}","private void performSearch() {\n String text = txtSearch.getText();\n String haystack = field.getText();\n \n // Is this case sensitive?\n if (!chkMatchCase.isSelected()) {\n text = text.toLowerCase();\n haystack = haystack.toLowerCase();\n }\n \n // Check if it is a new string that the user is searching for.\n if (!text.equals(needle)) {\n needle = text;\n curr_index = 0;\n }\n \n // Grab the list of places where we found it.\n populateFoundList(haystack);\n \n // Nothing was found.\n if (found.isEmpty()) {\n Debug.println(\"FINDING\", \"No occurrences of \" + needle + \" found.\");\n JOptionPane.showMessageDialog(null, \"No occurrences of \" + needle + \" found.\",\n \"Nothing found\", JOptionPane.INFORMATION_MESSAGE);\n \n return;\n }\n \n // Loop back the indexes if we have reached the end.\n if (curr_index == found.size()) {\n curr_index = 0;\n }\n \n // Go through the findings one at a time.\n int indexes[] = found.get(curr_index);\n field.select(indexes[0], indexes[1]);\n curr_index++;\n }","public Map<String, String> directQuoteSearch (String q, String contentOrTitle) throws IOException, ParseException{\n\n\t\t\n\t\tif (contentOrTitle.equals(\"content\")){\n\t\t\tcontentOrTitle=field;\n\t\t} else if (contentOrTitle.equals(\"title\")){\n\t\t\tcontentOrTitle=title;\n\t\t}\n\t\t\n\t\tIndexReader reader = DirectoryReader.open(FSDirectory.open(Paths.get(index)));\n\t\tIndexSearcher searcher = new IndexSearcher(reader);\n\t\tboolean raw = false;\n\t\tint repeat = 0;\n\n\t\tfinal List<String> stopWords = Arrays.asList();\n\t\tfinal CharArraySet stopSet = new CharArraySet(stopWords, true);\n\n\t\tAnalyzer analyzer = new StandardAnalyzer(stopSet);\n\t\tAnalyzingQueryParser parser = new AnalyzingQueryParser(contentOrTitle, analyzer);\n\t\t\n\n\t\t\n\t\tString[] items = q.split(\" \");\n\t\tList<String> itemList = Arrays.asList(items);\n\t\tQuery query=null;\n\t\t\n\t\t\n\t\tif (q.equals(\"\")){\n\t\t\tSystem.out.println(\"no input\");\n\t\t\t\n\t\t} else {\n\t\t\tquery = parser.parse(q);\n\n\t\t}\n\n\t\t\n\t\t\n\t\tBufferedReader in = null;\n\t\tin = new BufferedReader(new InputStreamReader(System.in, StandardCharsets.UTF_8));\n\n\t\tif (repeat > 0) { // repeat & time as benchmark\n\t\t\tDate start = new Date();\n\t\t\tfor (int i = 0; i < repeat; i++) {\n\t\t\t\tsearcher.search(query, 100);\n\t\t\t}\n\t\t\tDate end = new Date();\n\t\t\tSystem.out.println(\"Time: \"+(end.getTime()-start.getTime())+\"ms\");\n\t\t}\n\n\t\treturn doPagingSearch(in, searcher, query, hitsPerPage, raw, true);\n\t}","abstract public boolean performSearch();","@Override\n\tpublic void searchMembers(String keyword) {\n\t}","public HashMap<String, int[]> documentsContaining(String word) {\n return index.get(word);\n }","@Override\n public String doSearchResult() {\n return null;\n }","public byte filter(Manager m, SearchRequest q, ResultSet rs, int DocAtNumber, int DocNo)\n\t{\t\t\n\t\tString originalQuery = q.getOriginalQuery();\n\t\t//highlight query terms only for the queries, \n\t\t//which are not about finding related documents\n\t\t//this check may be removed, because the preparation of the \n\t\t//query terms for highlighting takes into account\n\t\t//the related: operator\n\t\tboolean highlightQueryTerms = true;\n\t\tif (originalQuery.matches(\"\\\\brelated:\\\\d+\\\\b\") || //check if the query uses the related: operator \n\t\t\t!enableQueryTermsHighlight || //check if the highlighting of terms is enabled\n\t\t\thighlight.pattern().equals(\"(\\\\b)()(\\\\b)\")) //check if there are no query terms to highlight\n\t\t\thighlightQueryTerms = false;\n\t\t\n\t\tString[] qTerms = q.getOriginalQuery().replaceAll(\" \\\\w+\\\\p{Punct}\\\\w+ \",\" \").toLowerCase().split(\" \");\n\t\t\n\t\tString[] metadata = null;\n\t\tint tmpSentence;\n\t\tdouble tmpScore;\n\t\tsynchronized(metaCache) {\n\t\t\ttry {\n\t\t\t\tInteger DocNoObject = new Integer(DocNo);\n\t\t\t\tif (metaCache.containsKey(DocNoObject))\n\t\t\t\t\t\tmetadata = (String[]) metaCache.get(DocNoObject);\n\t\t\t\telse {\n\t\t\t\t\tmetadata = metaIndex.getItems(keys, DocNo);\n\t\t\t\t\tmetaCache.put(DocNoObject,metadata);\n\t\t\t\t}\n\t\t\t} catch(IOException ioe) {} \n\t\t}\n\t\n\t\tif (show_snippet)\n\t\t{\n\t\t\tString extract = metadata[1];\n\t\t\tString[] sentences = sentencePattern.split(extract, 50); //use 50 sentences at most\n\t\t\tdouble[] sentenceScores = new double[sentences.length]; \n\t\t\tint frsSentence = -1;\n\t\t\tint sndSentence = -1;\n\t\t\tint top1Sentence = 0;\n\t\t\tint top2Sentence = 0;\n\t\t\tdouble max1Score = -1;\n\t\t\tdouble max2Score = 0;\n\t\t\tfinal int qTermsLength = qTerms.length;\n\t\t\tfor (int i=0; i<qTermsLength; i++) {\n\t\t\t\tqTerms[i] = removeEndings.matcher(qTerms[i]).replaceAll(\"\");\n\t\t\t}\n\t\t\tString lowerCaseSentence;\n\t\t\tint sentenceLength;\n\t\t\tfinal int sentencesLength = sentences.length;\n\n\t\t\tfor (int i=0; i<sentencesLength; i++) {\n\t\t\t\t\n\t\t\t\tlowerCaseSentence = sentences[i].toLowerCase();\n\t\t\t\tsentenceLength=sentences[i].length();\n\t\t\t\tif (sentenceLength < 20 || sentenceLength > 250) {\n\t\t\t\t\tfor (int j=0; j<qTermsLength; j++) {\n\t\t\t\t\t\tif (lowerCaseSentence.indexOf(qTerms[j])>=0) {\n\t\t\t\t\t\t\tsentenceScores[i]+=1.0d + sentenceLength / (20.0d + sentenceLength);\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\n\t\t\t\t\t\n\t\t\t\t} else {\n\t\t\t\t\tfor (int j=0; j<qTermsLength; j++) {\n\t\t\t\t\t\tif (lowerCaseSentence.indexOf(qTerms[j])>=0) {\n\t\t\t\t\t\t\tsentenceScores[i]+=qTerms[j].length() + sentenceLength / (1.0d + sentenceLength);\n\t\t\t\t\t\t}\n\t\t\t\t\t}\t\t\t\t\t\n\t\t\t\t}\n\t\t\t\t\t\t\t\t\n\t\t\t\t//do your best to get at least a second sentence for the snippet, \n\t\t\t\t//after having found the first one\n\t\t\t\tif (frsSentence > -1 && sndSentence == -1 && sentenceLength > 5) {\n\t\t\t\t\tsndSentence = i;\n\t\t\t\t}\n\n\t\t\t\t//do your best to get at least one sentence for the snippet\n\t\t\t\tif (frsSentence == -1 && sentenceLength > 5) { \n\t\t\t\t\tfrsSentence = i;\n\t\t\t\t}\n\n\t\t\t\tif (max2Score < sentenceScores[i]) {\n\t\t\t\t\tmax2Score = sentenceScores[i];\n\t\t\t\t\ttop2Sentence = i;\n\t\t\t\t\t//logger.debug(\"top 2 sentence is \" + i);\n\t\t\t\t\tif (max2Score > max1Score) {\n\t\t\t\t\t\ttmpScore = max1Score; max1Score = max2Score; max2Score = tmpScore;\n\t\t\t\t\t\ttmpSentence = top1Sentence; top1Sentence = top2Sentence; top2Sentence = tmpSentence;\n\t\t\t\t\t}\n\t\t\t\t}\n\n\t\t\t}\n\t\t\tint lastIndexOfSpace = -1;\n\t\t\tString sentence=\"\";\n\t\t\tString secondSentence=\"\";\n\t\t\tString snippet = \"\";\n\t\t\tif (max1Score == -1) {\n\t\t\t\tif (frsSentence>=0) {\n\t\t\t\t\tsentence = sentences[frsSentence];\n\t\t\t\t\tif (sentence.length() > 100) {\n\t\t\t\t\t\tlastIndexOfSpace = sentence.substring(0, 100).lastIndexOf(\" \");\n\t\t\t\t\t\tsentence = sentence.substring(0, lastIndexOfSpace > 0 ? lastIndexOfSpace : 100);\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t\t\n\t\t\t\tif (sndSentence>=0) {\n\t\t\t\t\tsecondSentence = sentences[sndSentence];\n\t\t\t\t\tif (secondSentence.length() > 100) {\n\t\t\t\t\t\tlastIndexOfSpace = secondSentence.substring(0, 100).lastIndexOf(\" \");\n\t\t\t\t\t\tsecondSentence = secondSentence.substring(0, lastIndexOfSpace>0 ? lastIndexOfSpace : 100);\n\t\t\t\t\t}\t\t\t\t\t\n\t\t\t\t}\n\t\t\t\t\n\t\t\t\tif (frsSentence >=0 && sndSentence >= 0) \n\t\t\t\t\tsnippet = sentence.trim() + \"...\" + secondSentence.trim();\n\t\t\t\telse if (frsSentence >= 0 && sndSentence<0) \n\t\t\t\t\tsnippet = sentence.trim();\n\t\t\t\t\n\t\t\t} else if (sentences[top1Sentence].length()<100 && top1Sentence!=top2Sentence) {\n\t\t\t\tsentence = sentences[top1Sentence];\n\t\t\t\tif (sentence.length() > 100) {\n\t\t\t\t\tlastIndexOfSpace = sentence.substring(0, 100).lastIndexOf(\" \");\n\t\t\t\t\tsentence = sentence.substring(0, lastIndexOfSpace > 0 ? lastIndexOfSpace : 100);\n\t\t\t\t}\n\t\t\t\t\t\t\t\t\n\t\t\t\tsecondSentence = sentences[top2Sentence];\n\t\t\t\tif (secondSentence.length() > 100) {\n\t\t\t\t\tlastIndexOfSpace = secondSentence.substring(0, 100).lastIndexOf(\" \");\n\t\t\t\t\tsecondSentence = secondSentence.substring(0, lastIndexOfSpace>0 ? lastIndexOfSpace : 100);\n\t\t\t\t}\n\t\t\t\tsnippet = sentence.trim() + \"...\" + secondSentence.trim();\n\t\t\t} else {\n\t\t\t\tsentence = sentences[top1Sentence];\n\t\t\t\tif (sentence.length()>200) {\n\t\t\t\t\tlastIndexOfSpace = sentence.substring(0, 200).lastIndexOf(\" \");\n\t\t\t\t\tsentence = sentence.substring(0, lastIndexOfSpace > 0 ? lastIndexOfSpace : 200);\n\t\t\t\t}\n\t\t\t\tsnippet = sentence.trim();\n\t\t\t}\n\t\t\t\n\t\t\t//checking and removing any control characters\n\t\t\tcontrolNonVisibleCharactersMatcher.reset(snippet);\n\t\t\tsnippet = controlNonVisibleCharactersMatcher.replaceAll(\"\");\n\t\t\t\n\t\t\t//String escapedSnippet = StringEscapeUtils.escapeHtml(snippet);\n\t\t\t//if (highlightQueryTerms)\n\t\t\t//\tescapedSnippet = highlight.matcher(escapedSnippet).replaceAll(\"$1<b>$2</b>$3\");\n\t\t\tif (highlightQueryTerms)\n\t\t\t\tsnippet = highlight.matcher(snippet).replaceAll(\"$1<b>$2</b>$3\");\n\t\t\t//else \n\t\t\t//\tsnippet = StringEscapeUtils.escapeHtml(snippet);\n\t\t\t\n\t\t\t//change by Vassilis, 20/09/2006\n\t\t\t//disabling the xml escaping in order to move the data into ![CDATA[ ]]\n\t\t\t//the code was:\n\t\t\t//rs.addMetaItem(\"snippet\", DocAtNumber, StringEscapeUtils.escapeXml(snippet));\n\t\t\t//and now it is:\n\t\t\t//snippet.replaceAll(\"[^\\\\u0009\\\\u000A\\\\u000D\\\\u0020-\\\\uD7FF\\\\uE000-\\\\uFFFD\\\\u10000-\\\\u10FFFF]\",\"\");\n\t\t\trs.addMetaItem(\"snippet\", DocAtNumber, snippet);\n\t\t\t\n\t\t}\n\t\tif (show_title)\n\t\t{\n\t\t\tString title = metadata[2];\n\t\t\t\n\t\t\t//checking and removing any control characters\n\t\t\tcontrolNonVisibleCharactersMatcher.reset(title);\n\t\t\ttitle = controlNonVisibleCharactersMatcher.replaceAll(\"\");\n\t\t\ttitle = (highlightQueryTerms)\n\t\t\t\t ? highlight.matcher(metadata[2]).replaceAll(\"$1<b>$2</b>$3\") \n\t\t\t\t : metadata[2];\n\t\t\t\n\t\t\t\n\t\t\t//String escapedTitle = StringEscapeUtils.escapeHtml(metadata[2]);\n\t\t\t//String title = (highlightQueryTerms)\n\t\t\t//\t\t\t ? highlight.matcher(escapedTitle).replaceAll(\"$1<b>$2</b>$3\") \n\t\t\t//\t\t\t : escapedTitle;\n\t\t\t//String title = (highlightQueryTerms) \n\t\t\t//\t\t? highlight.matcher(metadata[2]).replaceAll(\"$1<b>$2</b>$3\") \n\t\t\t//\t\t: metadata[2];\n\n\t\t\t//change by Vassilis, 20/09/2006\n\t\t\t//disabling the xml escaping in order to move the data into ![CDATA[ ]]\n\t\t\t//the code was:\n\t\t\t//rs.addMetaItem(\"title\", DocAtNumber, StringEscapeUtils.escapeXml(title));\n\t\t\t//and now is:\n\t\t\t//title.replaceAll(\"[^\\\\u0009\\\\u000A\\\\u000D\\\\u0020-\\\\uD7FF\\\\uE000-\\\\uFFFD\\\\u10000-\\\\u10FFFF]\",\"\");\n\t\t\trs.addMetaItem(\"title\", DocAtNumber, title);\n\t\t\t\n\t\t}\n\t\tif (!show_docid_early && show_docid)\n\t\t{\n\t\t\trs.addMetaItem(\"docid\", DocAtNumber, docIndex.getDocumentNumber(DocNo));\n\t\t}\n\t\tif (!show_url_early && show_url)\n\t\t{\n\n\t\t\trs.addMetaItem(\"url\", DocAtNumber, StringEscapeUtils.escapeXml(metadata[0]));\n\t\t}\n\t\t\n\t\treturn FILTER_OK;\n\t}","public void set_graph() throws ParseException, IOException {\n \tg = new WeightedUndirectedGraph(words.length);\n //g = new WeightedUndirectedGraph(most_important_terms.size());\n \n Directory dir = new SimpleFSDirectory(new File(\".\\\\data\\\\lucene_index_r_r\"));\n Analyzer analyzer = new StandardAnalyzer(LUCENE_41);\n \n // creat a map that stores, for each word (in the cluster), a set of all the documents that contain that word\n HashMap<String,HashSet<Integer>> word_to_docs_map = new HashMap<String,HashSet<Integer>>();\n int n_strings = words.length; \n \n // for each word...\n for (int idx = 0; idx < n_strings; idx++) {\n // query the index with that given word and retrieve all the documents that contains that word\n String query = words[idx]; \n QueryParser parser = new QueryParser(Version.LUCENE_41, \"text\", analyzer); \n Query q = parser.parse(query); \n\n IndexReader reader = DirectoryReader.open(dir);\n IndexSearcher searcher = new IndexSearcher(reader);\n TopDocs docs = searcher.search(q, reader.numDocs());\n ScoreDoc[] hits = docs.scoreDocs;\n \n // update map from word to docs it appears in \n //HashSet<Integer> tmp = null;\n // tmp is the set of all the document ids in which the current word is contained\n HashSet<Integer> tmp = new HashSet<>();\n //word_to_docs_map.put(query, tmp);\n \n // for each document, retrieved from the query\n for(Integer i=0;i<hits.length;i++) {\n Integer docId = hits[i].doc;\n // tmp = word_to_docs_map.get(query); \n // if the document is a document written by an user of interest \n if(indices.contains(docId)) {\n tmp.add(docId);\n }\n //word_to_docs_map.put(query, tmp); \n }\n word_to_docs_map.put(query, tmp);\n\t }\n\t \n\t // add edges: iterate over possible term pairs ...\n\t for(int idx_1 = 0; idx_1 < n_strings - 1; idx_1++) {\n\t \n\t for(int idx_2 = idx_1 + 1 ; idx_2 < n_strings ; idx_2 ++ ) {\n\t \n\t // extract document sets associated with the considered terms \n\t HashSet<Integer> set_a = word_to_docs_map.get(words[idx_1]); \n\t HashSet<Integer> set_b = word_to_docs_map.get(words[idx_2]); \n\t \n\t // compute set intersection \n\t int n = intersectionSize(set_a, set_b);\n\t \n\t // if the terms appear in at least one common document\n\t if(n>0) {\n\t // add edge \n\t g.testAndAdd(idx_1, idx_2 , n); \n\t }\n\t } \n\t }\n\t}","protected final void searchForText() {\n Logger.debug(\" - search for text\");\n final String searchText = theSearchEdit.getText().toString();\n\n MultiDaoSearchTask task = new MultiDaoSearchTask() {\n @Override\n protected void onSearchCompleted(List<Object> results) {\n adapter.setData(results);\n }\n\n @Override\n protected int getMinSearchTextLength() {\n return 0;\n }\n };\n task.readDaos.add(crDao);\n task.readDaos.add(monsterDao);\n task.readDaos.add(customMonsterDao);\n task.execute(searchText.toUpperCase());\n }","@Override\r\n\tpublic Set<Article> search(String keyworkds) {\n\t\treturn null;\r\n\t}","protected Query newTermQuery(Term term, float boost) {\n Query q = new TermQuery(term);\n if (boost == DEFAULT_BOOST) {\n return q;\n }\n return new BoostQuery(q, boost);\n }","public abstract Search defaultSearch(StringBuilder sb);","@Override\n protected void doPost(HttpServletRequest request, HttpServletResponse response)\n throws ServletException, IOException {\n\n // Item searched\n String term = request.getParameter(\"term\");\n int type, pricefilter, order;\n try {\n // 0 Restaurant, 1 City, 2 Region\n type = Integer.parseInt(request.getParameter(\"type\"));\n // 0 All, 1 €, 2 €€, 3 €€€\n pricefilter = Integer.parseInt(request.getParameter(\"pricefilter\"));\n // 1 Raking, 2 Alphabetical, 3 Price\n order = Integer.parseInt(request.getParameter(\"order\"));\n } catch (NumberFormatException e){\n response.sendRedirect(\"index.jsp\");\n return;\n }\n\n // If null is searched, redirects\n if(term == null){\n response.sendRedirect(\"index.jsp\");\n return;\n }\n\n // Term searched must be at least 3 characters long\n if(term.length() < 3){\n // Input too short\n response.sendRedirect(\"index.jsp?alert=1\");\n return;\n }\n\n // Character which must not be searched\n if(term.toLowerCase().contains(\"%\") || term.toLowerCase().contains(\"[\") || term.toLowerCase().contains(\"]\") ||\n term.toLowerCase().contains(\"^\")){\n response.sendRedirect(\"index.jsp\");\n return;\n }\n\n // List of results depending on the filtering\n ArrayList<SearchResult> results = null;\n switch (type){\n case 0:\n results = dbmanager.getRestaurants(term, pricefilter, order);\n break;\n case 1:\n results = dbmanager.getRestaurantsByCity(term, pricefilter, order);\n break;\n case 2:\n results = dbmanager.getRestaurantsByRegion(term, pricefilter, order);\n break;\n default:\n }\n\n if(results == null){\n response.sendRedirect(\"index.jsp\");\n }else{\n request.setAttribute(\"results\", results);\n request.setAttribute(\"type\", type);\n request.setAttribute(\"term\", term);\n request.setAttribute(\"pricefilter\", pricefilter);\n request.setAttribute(\"order\", order);\n getServletContext().getRequestDispatcher(\"/searchResults.jsp\").forward(request, response);\n }\n\n }","@Override\n\tpublic NodeIterator search(String queryString) throws Exception {\n\t\treturn null;\n\t}","public SuggestedTerm(String term, int editDistance){\n this.term = term;\n this.editDistance = editDistance;\n }","public Vector mapTerm(String term) throws TermNotFoundException {\n int i = termIndex.get(term);\n\n if (i == -1) {\n throw new TermNotFoundException(term);\n }\n\n return new DenseVector(Uk[i]);\n }","private void search()\n {\n JTextField searchField = (currentSearchView.equals(SEARCH_PANE_VIEW))? searchBar : resultsSearchBar;\n String searchTerm = searchField.getText();\n \n showTransition(2000);\n \n currentPage = 1;\n showResultsView(true);\n paginate(1, getResultsPerPage());\n\n if(searchWeb) showResultsTableView(WEB_RESULTS_PANE);\n else showResultsTableView(IMAGE_RESULTS_PANE);\n\n \n showSearchView(RESULTS_PANE_VIEW);\n resultsSearchBar.setText(searchTerm);\n }","public List<TermSpanRecord> getResults()\n {\n String whereClause = \"owner = ?\";\n List<TermSpanRecord> results = TermSpanRecord.find(TermSpanRecord.class, whereClause, new String[]{String.valueOf(getId())});\n return results;\n }","private static void RankedQueryMode(DiskIndexWriter diskWriter, DiskPositionalIndex disk_posIndex) throws IOException, ClassNotFoundException, InstantiationException, IllegalAccessException {\n\n if (query.equals(\"q\")) {\n\n System.exit(0);\n }\n\n List<String> word = new ArrayList();\n String[] query_array = query.split(\"\\\\s+\");\n TokenProcessor processor = new NewTokenProcessor();\n\n for (int i = 0; i < query_array.length; i++) {\n word.add(processor.processToken(query_array[i]).get(0));\n }\n\n StrategyFactory sf = new StrategyFactory();\n StrategyInterface strategy = sf.execute(rankedOption);\n\n //maps postings to accumulator value\n HashMap<Integer, Doc_accum> postingMap = new HashMap<Integer, Doc_accum>();\n\n PriorityQueue<Doc_accum> queue = new PriorityQueue<>(Collections.reverseOrder());\n\n List<Posting> postings = new ArrayList<>();\n List<Doc_accum> results = new ArrayList<>();\n\n for (String term : word) {\n\n postings = disk_posIndex.getPosting_noPos(term);\n for (Posting p : postings) { //for each document in the postings list\n double t_fd = p.getT_fd();\n double d_ft = p.getD_ft();\n double w_qt = strategy.calculate_wqt(N, d_ft);\n double accum = 0;\n double w_dt = strategy.get_wdt(t_fd, disk_posIndex, p.getDocumentId());\n\n //pairs (Ranked_posting, accumulator factor)\n if (postingMap.containsKey(p.getDocumentId())) {\n accum = postingMap.get(p.getDocumentId()).getAccumulator();\n accum += (w_qt * w_dt);\n postingMap.replace(p.getDocumentId(), new Doc_accum(p, accum)); //replaces old accum value\n\n } else {\n accum += (w_qt * w_dt);\n postingMap.put(p.getDocumentId(), new Doc_accum(p, accum));\n }\n }\n\n }\n\n for (Integer p : postingMap.keySet()) {\n Doc_accum doc_temp = postingMap.get(p);\n double accum = doc_temp.getAccumulator(); //gets accum associated with doc\n\n if (accum > 0) {\n //search for each p's Ld factor in docWeights.bin\n double l_d = strategy.calculate_Ld(disk_posIndex, doc_temp.getPosting().getDocumentId());\n\n accum /= l_d;\n doc_temp.setAccumulator(accum);\n }\n\n queue.add(postingMap.get(p));\n\n }\n\n //returns top K=10 results \n int topK = 50;\n\n while ((results.size() < topK) && queue.size() > 0) {\n\n results.add(queue.poll()); //gets the posting acc pair and returns only posting\n\n }\n\n display_RankedResults(results);\n\n }","List<ShipmentInfoPODDTO> search(String query);","@Override\n public SearchResult search_item(String keyword, int page, int rows , int search_type) throws Exception{\n return null;\n }","private List<SearchWord> getSearchWords(Long lastUpdateTime) {\n return new ArrayList<>();\n }","@Test\n public void term() throws AtlasBaseException {\n SearchParameters params = new SearchParameters();\n params.setTermName(SALES_TERM+\"@\"+SALES_GLOSSARY);\n\n List<AtlasEntityHeader> entityHeaders = discoveryService.searchWithParameters(params).getEntities();\n\n Assert.assertTrue(CollectionUtils.isNotEmpty(entityHeaders));\n assertEquals(entityHeaders.size(), 10);\n }","public void SearchTutor() {\n\t\t\n\t}","public String search() {\n return \"manage\";\n }","public T caseMOMoTSearch(MOMoTSearch object)\r\n {\r\n return null;\r\n }","@Override\n\tpublic List<BoardVO> admin_search(String type, String keyword) {\n\t\treturn null;\n\t}","private void searchFunction() {\n\t\t\r\n\t}","@Override\n\tpublic List<T> searchInfo(String flag, String token) {\n\t\treturn trendsDao.searchInfo(flag, token);\n\t}"],"string":"[\n \"@Override\\r\\n\\tpublic List<Post> searchInfResult(String word) {\\n\\t\\tpostDao=new PostDaoImpl(TransactionManager.connection);\\r\\n\\t\\treturn postDao.selectPosts(word);\\r\\n\\t}\",\n \"private void termQuerySearch(String[] terms) {\\n for (String term : terms) {\\n LinkedList<TermPositions> postingLists = indexMap.get(analyzeTerm(term));\\n if (postingLists != null) {\\n for (TermPositions matches : postingLists) {\\n double score = (double) 1 + Math.log((double) matches.getPositionList().size()) *\\n Math.log((double) N / (double) postingLists.size());\\n resultsCollector.add(new DocCollector(matches.getDocId(), score));\\n }\\n }\\n }\\n }\",\n \"List<DataTerm> search(String searchTerm);\",\n \"public void search(Indexer indexer, CityIndexer cityIndexer, Ranker ranker, String query, boolean withSemantic, ArrayList<String> chosenCities, ObservableList<String> citiesByTag, boolean withStemming, String saveInPath, String queryId, String queryDescription) {\\n String[] originalQueryTerms = query.split(\\\" \\\");\\n String originQuery = query;\\n docsResults = new HashMap<>();\\n parser = new Parse(withStemming, saveInPath, saveInPath);\\n HashSet<String> docsOfChosenCities = new HashSet<>();\\n query = \\\"\\\" + query + queryDescription;\\n HashMap<String, Integer> queryTerms = parser.parseQuery(query);\\n HashMap<String, ArrayList<Integer>> dictionary = indexer.getDictionary();\\n if (!withStemming){\\n setDocsInfo(saveInPath + \\\"\\\\\\\\docsInformation.txt\\\");\\n }\\n else{\\n setDocsInfo(saveInPath + \\\"\\\\\\\\docsInformation_stemming.txt\\\");\\n }\\n\\n\\n //add semantic words of each term in query to 'queryTerms'\\n if(withSemantic) {\\n HashMap<String,ArrayList<String>> semanticWords = ws.connectToApi(originQuery);\\n }\\n\\n //give an ID to query if it's a regular query (not queries file)\\n if(queryId.equals(\\\"\\\")){\\n queryId = \\\"\\\" + Searcher.queryID;\\n Searcher.queryID++;\\n }\\n\\n String postingDir;\\n if (!withStemming) {\\n postingDir = \\\"\\\\\\\\indexResults\\\\\\\\postingFiles\\\";\\n } else {\\n postingDir = \\\"\\\\\\\\indexResults\\\\\\\\postingFiles_Stemming\\\";\\n }\\n int pointer = 0;\\n\\n //find docs that contain the terms in the query in their text\\n HashMap<String, Integer> queryTermsIgnoreCase = new HashMap<>();\\n for (String term : queryTerms.keySet()) {\\n String originTerm = term;\\n if (!dictionary.containsKey(term.toUpperCase()) && !dictionary.containsKey(term.toLowerCase())) {\\n continue;\\n }\\n if(dictionary.containsKey(term.toLowerCase())){\\n term = term.toLowerCase();\\n }\\n else {\\n term = term.toUpperCase();\\n }\\n queryTermsIgnoreCase.put(term,queryTerms.get(originTerm));\\n pointer = dictionary.get(term).get(2);\\n String chunk = (\\\"\\\" + term.charAt(0)).toUpperCase();\\n\\n //get the relevant line from posting file\\n BufferedReader br = null;\\n try {\\n br = new BufferedReader(new FileReader(new File(saveInPath + postingDir + \\\"\\\\\\\\posting_\\\" + chunk + \\\".txt\\\")));\\n String line = \\\"\\\";\\n int i = 1;\\n while ((line = (br.readLine())) != null) {\\n if (i == pointer) {\\n break;\\n }\\n i++;\\n }\\n br.close();\\n\\n //get docs from posting line and add them to the data structure 'docsResults'\\n if(line != null) {\\n findDocsFromLine(line, term);\\n }\\n\\n } catch (IOException e) {\\n e.printStackTrace();\\n }\\n }\\n\\n //find docs that contain the chosen cities in their text\\n for (String cityTerm : chosenCities) {\\n if (!dictionary.containsKey(cityTerm) && !dictionary.containsKey(cityTerm.toLowerCase())) {\\n continue;\\n }\\n if(dictionary.containsKey(cityTerm.toLowerCase())){\\n cityTerm = cityTerm.toLowerCase();\\n }\\n pointer = dictionary.get(cityTerm).get(2);\\n // char chunk = indexer.classifyToPosting(term).charAt(0);\\n String chunk = (\\\"\\\" + cityTerm.charAt(0)).toUpperCase();\\n\\n //get the relevant line from posting file\\n BufferedReader br = null;\\n try {\\n br = new BufferedReader(new FileReader(new File(saveInPath + postingDir + \\\"\\\\\\\\posting_\\\" + chunk + \\\".txt\\\")));\\n String line = \\\"\\\";\\n int i = 1;\\n while ((line = (br.readLine())) != null) {\\n if (i == pointer) {\\n break;\\n }\\n i++;\\n }\\n br.close();\\n\\n //get docs from posting line and add them to the data structure 'docsOfChosenCities'\\n String docs = line.substring(0, line.indexOf(\\\"[\\\") - 1); //get 'docsListStr'\\n String[] docsArr = docs.split(\\\";\\\");\\n for (String docInfo : docsArr) {\\n String doc = docInfo.substring(0, docInfo.indexOf(\\\": \\\"));\\n while(doc.charAt(0) == ' '){\\n doc = doc.substring(1);\\n }\\n docsOfChosenCities.add(doc);\\n }\\n } catch (IOException e) {\\n e.printStackTrace();\\n }\\n }\\n\\n //find docs that contain the chosen cities in their city tag\\n if(!chosenCities.isEmpty()){\\n for (String cityDicRec: chosenCities) {\\n //get pointer to posting from cityDictionary\\n try {\\n pointer = cityIndexer.getCitiesDictionary().get(cityDicRec);\\n } catch (NumberFormatException e) {\\n e.printStackTrace();\\n }\\n //get the relevant line from posting file\\n BufferedReader br = null;\\n try {\\n br = new BufferedReader(new FileReader(new File(saveInPath + \\\"\\\\\\\\cityIndexResults\\\" + \\\"\\\\\\\\posting_city\\\" + \\\".txt\\\")));\\n String line = \\\"\\\";\\n int i = 1;\\n while ((line = (br.readLine())) != null) {\\n if (i == pointer) {\\n break;\\n }\\n i++;\\n }\\n br.close();\\n\\n //get docs from posting line and add them to the data structure 'docsOfChosenCities'\\n String docs = line.substring(line.indexOf(\\\"[\\\") + 1, line.indexOf(\\\"]\\\")); //get 'docsListStr'\\n String[] docsArr = docs.split(\\\"; \\\");\\n for (String doc : docsArr) {\\n docsOfChosenCities.add(doc);\\n }\\n } catch (IOException e) {\\n e.printStackTrace();\\n }\\n }\\n }\\n\\n\\n ranker.rank(docsResults, docsOfChosenCities, queryTermsIgnoreCase, dictionary, docsInfo,entities, queryId);\\n }\",\n \"@Override\\n public int getIndexByTerm(String term) {\\n return 0;\\n }\",\n \"@Override\\n\\tprotected void executeSearch(String term) {\\n\\t\\t\\n\\t}\",\n \"@Override\\n \\tpublic ArrayList<Object> searchPostByName(String search) {\\n\\t\\t\\n\\t\\tSystem.out.println(\\\"i am in service search looking for cool posts\\\" + search);\\n\\t\\t\\n\\t\\tif(search == null){\\n\\t\\t\\treturn null;\\n\\t\\t}\\n\\t\\t\\n\\t\\tArrayList<Object> list = null; //postRepository.findPostByName(search); ****Nick set this to null; otherwise it failed. Needs corrected in future\\n\\t\\t\\n\\t\\t//System.out.println(Arrays.toString(list));\\n\\t\\treturn list;\\n\\t}\",\n \"public org.apache.xmlbeans.XmlAnySimpleType getSearchTerms()\\n {\\n synchronized (monitor())\\n {\\n check_orphaned();\\n org.apache.xmlbeans.XmlAnySimpleType target = null;\\n target = (org.apache.xmlbeans.XmlAnySimpleType)get_store().find_attribute_user(SEARCHTERMS$6);\\n if (target == null)\\n {\\n return null;\\n }\\n return target;\\n }\\n }\",\n \"public PostingsList search( Query query, int queryType, int rankingType, int structureType ) {\\r\\n switch(queryType){\\r\\n case Index.INTERSECTION_QUERY : \\r\\n return searchIntersection( query, rankingType, structureType);\\r\\n\\r\\n case Index.PHRASE_QUERY :\\r\\n return searchPhrase( query, rankingType, structureType);\\r\\n default:\\r\\n break;\\r\\n }\\r\\n\\r\\n return null;\\r\\n }\",\n \"public static void searchJobs(String searchTerm) {\\n\\n for (int i = 0; i > PostJob.allJobs.size(); i++) {\\n\\n\\n if (PostJob.allJobs.contains(searchTerm)) {\\n int itemIndx = PostJob.allJobs.indexOf(searchTerm);\\n String output = PostJob.allJobs.get(itemIndx);\\n System.out.print(\\\"Available jobs within your search terms\\\" + output);\\n\\n }\\n }\\n }\",\n \"public void onSearchResults(String term, List<WikiPage> results);\",\n \"public int getTermIndex() {return termIndex;}\",\n \"public MagicSearch createMagicSearch();\",\n \"public interface DocumentRelatedTermsSearcher {\\n List<ScoredTerm> getDocumentRelatedTerms(int docId, String term) throws SearchException;\\n}\",\n \"public void SearchPhrase(Object_Ord temp) {\\n\\tif (!Doneloading) {\\r\\n\\t return;\\r\\n\\t}\\r\\n\\tif (temp == null) {\\r\\n\\t return;\\r\\n\\t} else if (temp.Ordet.equals(\\\"\\\")) {\\r\\n\\t return;\\r\\n\\t}\\r\\n\\ttemp.Set_Searched();\\r\\n\\t//PrintAction( this.getClass().toString() + \\\" Searching for phrase \\\" + temp.Ordet );\\r\\n\\tThread thread = new Thread_PhraseSearcher(this, temp);\\r\\n\\tThreadsRunning++;\\r\\n\\tThreadsStarted++;\\r\\n }\",\n \"public String search(String term, String location) {\\n\\t\\t\\t String limit = \\\"6\\\";\\n\\t\\t OAuthRequest request = new OAuthRequest(Verb.GET, \\\"http://api.yelp.com/v2/search\\\");\\n\\t\\t request.addQuerystringParameter(\\\"term\\\", term);\\n\\t\\t request.addQuerystringParameter(\\\"location\\\", location);\\n\\t\\t request.addQuerystringParameter(\\\"limit\\\", limit);\\n\\t\\t this.service.signRequest(this.accessToken, request);\\n\\t\\t Response response = request.send();\\n\\t\\t return response.getBody();\\n\\t\\t }\",\n \"public void onSearchSubmit(String queryTerm);\",\n \"public String getTerm(){\\n return this.term;\\n }\",\n \"public PostingsList getPostings( String token ) {\\r\\n PostingsList element = index.get(token) ;\\r\\n if (element != null)\\r\\n {\\r\\n return element;\\r\\n }\\r\\n return null;\\r\\n }\",\n \"List<User> searchUsers(String searchTerm) {\\n return null;\\n }\",\n \"@Override\\n public List<SearchResult> search(String queryString, int k) {\\n // TODO: YOUR CODE HERE\\n\\n // Tokenize the query and put it into a Set\\n HashSet<String> tokenSet = new HashSet<>(Searcher.tokenize(queryString));\\n\\n /*\\n * Section 1: FETCHING termId, termFreq and relevant docId from the Query\\n */\\n\\n // Init a set to store Relevant Document Id\\n HashSet<Integer> relevantDocIdSet = new HashSet<>();\\n for (String token : tokenSet) { // Iterates thru all query tokens\\n int termId;\\n try {\\n termId = indexer.getTermDict().get(token);\\n } catch (NullPointerException e) { // In case current token is not in the termDict\\n continue; // Skip this one\\n }\\n // Get the Posting associate to the termId\\n HashSet<Integer> posting = indexer.getPostingLists().get(termId);\\n relevantDocIdSet.addAll(posting); // Add them all to the Relevant Document Id set\\n }\\n\\n /*\\n * Section 2: Calculate Jaccard Coefficient between the Query and all POTENTIAL DOCUMENTS\\n */\\n\\n // ArrayList for the Final Result\\n ArrayList<SearchResult> searchResults = new ArrayList<>();\\n for (Document doc : documents) { // Iterates thru all documents\\n if (!relevantDocIdSet.contains(doc.getId())) { // If the document is relevant\\n searchResults.add(new SearchResult(doc, 0)); // Add the document as a SearchResult with zero score\\n } else {\\n HashSet<String> termIdSet = new HashSet<>(doc.getTokens()); // Get the token set from the document\\n\\n // Calculate Jaccard Coefficient of the document\\n double jaccardScore = JaccardMathHelper.calculateJaccardSimilarity(tokenSet, termIdSet);\\n\\n // Add the SearchResult with the computed Jaccard Score\\n searchResults.add(new SearchResult(doc, jaccardScore));\\n }\\n }\\n\\n return TFIDFSearcher.finalizeSearchResult(searchResults, k);\\n }\",\n \"@RequestMapping(method=RequestMethod.POST,value = \\\"/search\\\")\\n public ArrayList<Results> searchMentors(@RequestBody SearchForm s) {\\n return resultsRepository.findMentors(s.getFrom(),s.getCourse(),s.getTimeslot());\\n }\",\n \"@Override\\n public SearchResult search_hunter(String keyword, int page, int rows ,int search_type) throws Exception{\\n\\n return null;\\n }\",\n \"public PostingsList search( Query query, int queryType, int rankingType,\\n int structureType ) {\\n double idf_threshold = new Double(0);\\n double index_elimination = new Double(0.008);\\n // System.err.println(pageRank[docNumber.get(\\\"121\\\")]);\\n\\n if (query.size()>0){\\n switch (queryType){\\n case Index.INTERSECTION_QUERY:\\n System.err.println(\\\"Intersection query\\\");\\n return intersect(query);\\n case Index.PHRASE_QUERY:\\n System.err.println(\\\"Phrase query\\\");\\n return phrase_query(query);\\n case Index.RANKED_QUERY:\\n System.err.println(\\\"Ranked query\\\");\\n switch(rankingType){\\n case Index.TF_IDF: return ranked_query(query, 1, idf_threshold);\\n case Index.PAGERANK: return ranked_query(query, 0, idf_threshold);//ranked_query(query, 0, idf_threshold);//ranked_query2(query, 0);\\n case Index.COMBINATION: return ranked_query(query, index_elimination, idf_threshold);\\n }\\n default:\\n System.out.println(\\\"not valid query\\\");\\n return null;\\n }\\n }\\n else\\n // Query was empty\\n return null;\\n }\",\n \"public PostingsList phrase_query(Query query){\\n\\n LinkedList<PostingsList> listQueriedPostings = new LinkedList<PostingsList>();\\n // List with postings corresponding to the queries\\n for (int i = 0; i<query.size(); i++){\\n // If any query has zero matches, return 0 results\\n //if(!(new File(\\\"postings/t\\\"+hash(query.terms.get(i))+\\\".json\\\")).exists()){\\n if (!this.index.containsKey(query.terms.get(i))){\\n return null;\\n }\\n // Otherwise store postings in the list\\n listQueriedPostings.add(this.getPostings(query.terms.get(i)));\\n }\\n\\n PostingsList result = new PostingsList();\\n result = listQueriedPostings.get(0);\\n\\n // In case only one word is queried\\n if (listQueriedPostings.size() == 1){\\n return result;\\n }\\n\\n // Apply algorithm as many times as words in the query\\n for(int i = 1; i < listQueriedPostings.size(); i++){\\n result = phrase_query(result, listQueriedPostings.get(i));\\n if (result.isEmpty()){\\n return null;\\n }\\n }\\n return result;\\n }\",\n \"Search getSearch();\",\n \"public void search() {\\r\\n \\t\\r\\n }\",\n \"SearchResult<TimelineMeta> search(SearchParameter searchParameter);\",\n \"com.google.ads.googleads.v6.resources.SearchTermView getSearchTermView();\",\n \"SearchResult<TimelineMeta> search(SearchQuery searchQuery);\",\n \"public void search() {\\n String q = this.query.getText();\\n String cat = this.category.getValue();\\n if(cat.equals(\\\"Book\\\")) {\\n searchBook(q);\\n } else {\\n searchCharacter(q);\\n }\\n }\",\n \"public Post[] wallSearch(String text) {\\n return null;\\n }\",\n \"private static String handleNonPhraseToken(String stringPart) {\\r\\n // Set of final terms to be used (no empty elements, right syntax of index fields)\\r\\n ArrayList <String> terms = new ArrayList <String> ();\\r\\n \\r\\n /** Case Index field **/\\r\\n if(stringPart.contains(\\\"[\\\") | stringPart.contains(\\\"[\\\")){ // at least an Index field contained here\\r\\n //separate brackets for term with one space (extra spaces dont matter, trim() is used later)\\r\\n stringPart = stringPart.replace(\\\"[\\\", \\\" [\\\");\\r\\n stringPart = stringPart.replace(\\\"]\\\", \\\"] \\\");\\r\\n }\\r\\n\\r\\n /** Case Bag of terms **/\\r\\n //replace space with AND (change default operator to match pubMed's)\\r\\n // No need for this if setDefaultOperator(QueryParser.Operator.AND) is used\\r\\n \\r\\n String[] tokens = stringPart.split(\\\"\\\\\\\\s\\\");\\r\\n if(tokens.length > 0){ \\r\\n for(int i = 1 ; i < tokens.length ; i++){\\r\\n tokens[i] = tokens[i].trim();\\r\\n /* Case index field [fieldName] */\\r\\n if(tokens[i].startsWith(\\\"[\\\") & tokens[i].endsWith(\\\"]\\\")){\\r\\n tokens[i] = tokens[i].replace(\\\"[\\\",\\\"\\\");// clean field name from brackets\\r\\n tokens[i] = tokens[i].replace(\\\"]\\\",\\\"\\\");// clean field name from brackets\\r\\n //Add index field as prefix to previus (not empty) term (as opening index fields handled separately, this index field should not be the first term of string part)\\r\\n int tmp = i-1;\\r\\n boolean perviusTermFound = false;\\r\\n while(!perviusTermFound & tmp >= 0){\\r\\n if(!tokens[tmp].equals(\\\"\\\")){\\r\\n perviusTermFound = true;\\r\\n //TO DO : handle wrong syntax (e.g. ... AND [ArticleTitle])\\r\\n String luceneField = supportedIndexFields.get(tokens[i]);\\r\\n if(luceneField != null){\\r\\n tokens[tmp] = luceneField + \\\":\\\" + tokens[tmp];\\r\\n } // else : Lucene counterpart not found, unsupported field - do nothing\\r\\n } else {\\r\\n tmp--;\\r\\n }\\r\\n }\\r\\n //Empty field to not be added as a search term in query\\r\\n tokens[i] = \\\"\\\";\\r\\n } \\r\\n \\r\\n /*\\r\\n \\r\\n else if(!tokens[i].equals(\\\"AND\\\") & !tokens[i].equals(\\\"\\\")) {\\r\\n terms.add(tokens[i]);\\r\\n }\\r\\n */\\r\\n }\\r\\n }\\r\\n \\r\\n String luceneQueryPart = \\\"\\\";\\r\\n boolean notWaiting = false;\\r\\n boolean orWaiting = false;\\r\\n for(int i = 0 ; i < tokens.length ; i++){\\r\\n\\r\\n if(!tokens[i].equals(\\\"AND\\\") & !tokens[i].equals(\\\"\\\")){\\r\\n //in case of AND nothing should happen, it is the default operator\\r\\n //empty elements are also ignored as useless\\r\\n \\r\\n if(!tokens[i].equals(\\\"NOT\\\") & !tokens[i].equals(\\\"OR\\\") ){ // it's not an operator, it's a term\\r\\n \\r\\n if(!luceneQueryPart.endsWith(\\\" OR \\\") & !luceneQueryPart.endsWith(\\\" -\\\") ) { \\r\\n luceneQueryPart += \\\" +\\\"; \\r\\n } \\r\\n luceneQueryPart += tokens[i];\\r\\n } else {\\r\\n if(tokens[i].equals(\\\"NOT\\\")) {\\r\\n luceneQueryPart += \\\" -\\\";\\r\\n }\\r\\n if(tokens[i].equals(\\\"OR\\\")){\\r\\n luceneQueryPart += \\\" OR \\\";\\r\\n }\\r\\n \\r\\n } \\r\\n } \\r\\n }\\r\\n \\r\\n return luceneQueryPart;\\r\\n }\",\n \"private void searchWord()\\n {\\n String inputWord = searchField.getText();\\n \\n if(inputWord.isEmpty())\\n queryResult = null;\\n \\n else\\n {\\n char firstLetter = inputWord.toUpperCase().charAt(0);\\n \\n for(int i = 0 ; i < lexiNodeTrees.size() ; i++)\\n {\\n if(lexiNodeTrees.get(i).getCurrentCharacter() == firstLetter)\\n {\\n queryResult = lexiNodeTrees.get(i).searchWord(inputWord, false);\\n i = lexiNodeTrees.size(); // escape the loop\\n }\\n }\\n }\\n \\n // update the list on the GUI\\n if(queryResult != null)\\n {\\n ArrayList<String> words = new ArrayList<>();\\n for(WordDefinition word : queryResult)\\n {\\n words.add(word.getWord());\\n }\\n \\n // sort the list of words alphabetically \\n Collections.sort(words);\\n \\n // display the list of wordsin the UI\\n DefaultListModel model = new DefaultListModel();\\n for(String word : words)\\n {\\n model.addElement(word);\\n }\\n\\n this.getSearchSuggestionList().setModel(model);\\n }\\n \\n else\\n this.getSearchSuggestionList().setModel( new DefaultListModel() );\\n }\",\n \"public void search() {\\n }\",\n \"@Override\\r\\n\\tpublic String searchPoster(String searchPoster) throws Exception {\\n\\t\\treturn null;\\r\\n\\t}\",\n \"void search();\",\n \"void search();\",\n \"@Override\\r\\n\\t\\t\\tpublic List<ScoredDocument> search(Query query) {\\n\\t\\t\\t\\treturn null;\\r\\n\\t\\t\\t}\",\n \"@Action\\r\\n public String search() {\\n ServiceFunctions.clearCache();\\r\\n\\r\\n if (isAdmin()) {\\r\\n return adminSearch();\\r\\n }\\r\\n\\r\\n return publicSearch();\\r\\n }\",\n \"@Override\\n public String getTermByIndex(int index) {\\n return null;\\n }\",\n \"public String getTerm() {\\n return term;\\n }\",\n \"@Override\\r\\n\\t\\t\\tpublic boolean containsTerm(Document document, String term) {\\n\\t\\t\\t\\treturn false;\\r\\n\\t\\t\\t}\",\n \"public org.apache.xmlbeans.XmlAnySimpleType addNewSearchTerms()\\n {\\n synchronized (monitor())\\n {\\n check_orphaned();\\n org.apache.xmlbeans.XmlAnySimpleType target = null;\\n target = (org.apache.xmlbeans.XmlAnySimpleType)get_store().add_attribute_user(SEARCHTERMS$6);\\n return target;\\n }\\n }\",\n \"@RequestMapping(\\\"/\\\")\\n public String index(@RequestParam(value = \\\"searchTerm\\\", required = false, defaultValue = \\\"None\\\") String searchTerm, Model model) {\\n List<Review> reviews = this.reviewService.fetchAll();\\n if (!searchTerm.equals(\\\"None\\\")) {\\n List<Review> filteredReviews = new ArrayList<>();\\n for (Review review : reviews)\\n if (review.getPlaceId().equals(searchTerm))\\n filteredReviews.add(review);\\n reviews = filteredReviews;\\n }\\n System.out.println(reviews);\\n model.addAttribute(reviews);\\n return \\\"index\\\";\\n }\",\n \"public PostingsList ranked_query(Query query, double w, double idf_threshold){\\n long startTime = System.nanoTime();\\n PostingsList result = new PostingsList();\\n\\n // Obtain union of terms above idf threshold if indexElimination is true\\n // (Set idf_threshold to zero to disable this feature)\\n Set<String> termsToConsider = this.queryTermsConsidered(query, idf_threshold);\\n result = this.union_query(query, termsToConsider);\\n //System.err.println(\\\"Size of result is \\\" + result.size());\\n\\n long estimatedTime = (System.nanoTime() - startTime)/1000000;\\n System.err.println(\\\"* Union took: \\\" + estimatedTime);\\n\\n\\n /*\\n * 2) Iterate over PostingsEntries and build the solution\\n */\\n startTime = System.nanoTime();\\n // Required when iterating over a PostingsList\\n PostingsEntry postEnt = new PostingsEntry();\\n // Number of documents in the collection\\n double nDocs = this.docIDs.size();\\n // Weight of a query vector coefficient\\n double w_query_term;\\n // Document tf-idf variables\\n double termFrequency_doc, documentFrequency_doc, w_doc_term;\\n\\n for(String term : termsToConsider){\\n // Obtain idf of the term\\n documentFrequency_doc = Math.log(nDocs/new Double(this.idfMap.get(term)));\\n\\n // Obtain weight of the term\\n w_query_term = query.weights.get(term);\\n // Iterate over all documents containing the term and update the score(q,d)\\n Iterator<PostingsEntry> it_d = result.iterator();\\n while(it_d.hasNext()){\\n postEnt = it_d.next();\\n if (this.tfMap.get(postEnt.docID).containsKey(term)){\\n termFrequency_doc = this.tfMap.get(postEnt.docID).get(term);\\n w_doc_term = documentFrequency_doc*termFrequency_doc;\\n postEnt.score += w_query_term*w_doc_term;\\n }\\n }\\n }\\n estimatedTime = (System.nanoTime() - startTime)/1000000;\\n System.err.println(\\\"* Building solution took: \\\" + estimatedTime);\\n\\n /*\\n * 3) Normalize the scores\\n */\\n startTime = System.nanoTime();\\n Iterator<PostingsEntry> it = result.iterator();\\n while(it.hasNext()){\\n postEnt = it.next();\\n postEnt.score /= (new Double(this.docLengths.get(\\\"\\\"+postEnt.docID)));//(Math.sqrt(postEnt.norm2));\\n postEnt.score = w * postEnt.score + (1-w) * quality(postEnt.docID);\\n }\\n estimatedTime = (System.nanoTime() - startTime)/1000000;\\n System.err.println(\\\"* Normalizing took: \\\" + estimatedTime);\\n\\n /*\\n * 4) Sort the resulting solution\\n */\\n startTime = System.nanoTime();\\n result.sort();\\n estimatedTime = (System.nanoTime() - startTime)/1000000;\\n System.err.println(\\\"* Sorting took: \\\" + estimatedTime);\\n\\n return result;\\n }\",\n \"ReagentSearch getReagentSearch();\",\n \"SpellResponse spellQuery(SearchRequest request, Map<SearchParam, String> params);\",\n \"@Override\\n\\tpublic List<Literature> searchKeywords() {\\n\\t\\treturn null;\\n\\t}\",\n \"List<PilotContainer> Search(String cas, String word);\",\n \"abstract public void search();\",\n \"public IndexedList<Task> search() {\\n\\t\\treturn null;\\n\\t}\",\n \"public ArrayList<ArrayList> simpleQuery(String word)\\n {\\n ArrayList<ArrayList> data = new ArrayList();\\n\\n IndexObject obj = myIndex.get(word.hashCode());\\n if(obj == null)\\n {\\n errorMsg();\\n return null;\\n }\\n data.add(new ArrayList<Document>(obj.getDocuments()));\\n data.add(new ArrayList<Double>(obj.getRelevance()));\\n data.add(new ArrayList<Integer>(obj.getOccurrence()));\\n data.add(new ArrayList<Integer>(obj.getPopularity()));\\n return data;\\n }\",\n \"@Override\\n public Data3DPlastic search() {\\n return super.search();\\n }\",\n \"public abstract HashMap search(String keyword);\",\n \"com.google.ads.googleads.v6.resources.SearchTermViewOrBuilder getSearchTermViewOrBuilder();\",\n \"public List<Recipe> search(String queryText, Category category, CookingMethod cookingMethod);\",\n \"@Override\\n\\tpublic void search() {\\n\\t}\",\n \"List<Block> search(String searchTerm);\",\n \"public HashMap<String, Double> search(String query) {\\n // ===================================================\\n // 1. Fetch all inverted lists corresponding to terms\\n // in the query.\\n // ===================================================\\n String[] terms = query.split(\\\" \\\");\\n HashMap<String, Integer> qf = new HashMap<String, Integer>();\\n // Calculate term frequencies in the query\\n for (String term : terms) {\\n if (qf.containsKey(term))\\n qf.put(term, qf.get(term) + 1);\\n else\\n qf.put(term, 1);\\n }\\n HashMap<String, Double> docScore = new HashMap<String, Double>();\\n for (Entry<String, Integer> termEntry : qf.entrySet()) {\\n String term = termEntry.getKey();\\n int qfi = termEntry.getValue();\\n\\n // ===================================================\\n // 2. Compute BM25 scores for documents in the lists.\\n // Make a score list for documents in the inverted\\n // lists. Assume that no relevance information is \\n // available. For parameters, use k1=1.2, b=0.75, \\n // k2=100.\\n // ===================================================\\n double k1 = 1.2;\\n double b = 0.75;\\n double k2 = 100;\\n int ni = invIndex.get(term).size();\\n\\n\\n for (Entry<String, IndexEntry> invListEntry : invIndex.get(term).entrySet()) {\\n String docID = invListEntry.getKey();\\n double bm25Score;\\n if (docScore.containsKey(docID))\\n bm25Score = docScore.get(docID);\\n else\\n bm25Score = 0;\\n\\n // length of the document\\n int dl = docStat.get(docID);\\n // frequency of the term in the document\\n int fi = invListEntry.getValue().getTf();\\n double K = k1 * ((1 - b) + b * ((double) dl / avdl));\\n\\n // ===================================================\\n // 3. Accumulate scores for each term in a query\\n // on the score list.\\n // ===================================================\\n bm25Score += Math.log((N - ni + 0.5) / (ni + 0.5))\\n * (((k1 + 1) * fi * (k2 + 1) * qfi) / ((K + fi) * (k2 + qfi)));\\n docScore.put(docID, bm25Score);\\n }\\n }\\n\\n return docScore;\\n }\",\n \"List<SearchResult> search(SearchQuery searchQuery);\",\n \"public List<Post> search(PostCriteria criteria, int page, int size);\",\n \"private static List<SearchData> booleanSearchWord(Query query, Indexer si) {\\n Tokenizer tkn = new SimpleTokenizer();\\n tkn.tokenize(query.getStr(), \\\"[a-zA-Z]{3,}\\\", true, true);\\n List<SearchData> searchList = new ArrayList<>();\\n LinkedList<Token> wordsList = tkn.getTokens();\\n Iterator<Token> wordsIt = wordsList.iterator();\\n HashMap<String, LinkedList<Posting>> indexer = si.getIndexer();\\n int idx;\\n SearchData searched_doc;\\n\\n while (wordsIt.hasNext()) {\\n String word = wordsIt.next().getSequence();\\n if (indexer.containsKey(word)) {\\n\\n LinkedList<Posting> posting = indexer.get(word);\\n\\n for (Posting pst : posting) {\\n\\n SearchData sd = new SearchData(query, pst.getDocId());\\n\\n if (!searchList.contains(sd)) {\\n sd.setScore(1);\\n searchList.add(sd);\\n } else {\\n idx = searchList.indexOf(sd);\\n searched_doc = searchList.get(idx);\\n searched_doc.setScore(searched_doc.getScore() + 1);\\n }\\n }\\n\\n }\\n\\n\\n }\\n\\n Collections.sort(searchList);\\n\\n return searchList;\\n }\",\n \"public abstract int search(String[] words, String wordToFind) throws ItemNotFoundException;\",\n \"public static void searchSimillar(String keyword,int numberofResults,PreSearch ps) {\\t\\t\\r\\n\\t\\tHashMap<String,Integer> sortedDistance = sortByEditDistance(keyword,ps);\\r\\n\\t\\tIterator<Entry<String, Integer>> iterator2 = sortedDistance.entrySet().iterator(); \\r\\n\\t\\twhile(iterator2.hasNext()) \\r\\n\\t\\t{ \\t\\t\\t\\r\\n\\t\\t\\tMap.Entry<String, Integer> me = (Map.Entry<String, Integer>)iterator2.next();\\r\\n\\t\\t\\tString word = me.getKey().toString();\\t\\t\\t\\r\\n\\t\\t\\tSystem.out.println(\\\"Instead showing results for : \\\"+word);\\r\\n\\t\\t\\t\\r\\n\\t\\t\\t//Searching for the word with lowest distance.\\r\\n\\t\\t\\tMap<String,Integer> sortedMap;\\r\\n\\t\\t\\tArrayList<String> as = ps.find(word);\\r\\n\\t\\t\\tString phrase = word.toLowerCase();\\r\\n\\t\\t\\t\\r\\n\\t\\t\\tsortedMap = SortResultsByRank.sortByRank(as, phrase);\\t\\t\\t\\r\\n\\t\\t\\tSearch.printResult(sortedMap,numberofResults);\\r\\n\\t\\t\\tbreak;\\r\\n\\t\\t}\\r\\n\\t\\t\\r\\n\\t}\",\n \"@RequestMapping(value={\\\"/search\\\"}, method={RequestMethod.GET})\\n \\tpublic ModelAndView handleSearch(@RequestParam(required=false) String q, @RequestParam(required=false,defaultValue=\\\"1\\\") Integer page){\\n \\t\\tMap<String,Object> model = new HashMap<String,Object>();\\n \\t\\t\\n \\t HashMap<String,Object> search = new HashMap<String,Object>();\\n \\t search.put(\\\"term\\\", \\\"\\\");\\n \\t search.put(\\\"total\\\",0);\\n \\n \\t List<Map<String,String>> searchResult = new ArrayList<Map<String,String>>();\\n \\t if(StringUtils.isNotBlank(q)){\\n \\t \\tsearch.put(\\\"term\\\", q);\\n \\t \\tLimitedResult<List<NameConceptModelIF>> nameConceptModelList = null;\\n \\t \\tint pageIndex = (page <= 0)?0:(page-1);\\n \\t \\t//use page index +1 to avoid returning a bad page number\\n \\t\\tsearch.put(\\\"pageNumber\\\", (pageIndex+1));\\n \\t\\tsearch.put(\\\"pageSize\\\", searchService.getPageSize());\\n \\t\\t//check if we want another page than the first one\\n \\t \\tif(pageIndex > 0){\\n \\t \\t\\tnameConceptModelList = searchService.searchName(q,pageIndex);\\n \\t \\t}\\n \\t \\telse{\\n \\t \\t\\tnameConceptModelList = searchService.searchName(q);\\n \\t \\t}\\n \\n \\t\\t search.put(\\\"total\\\",nameConceptModelList.getTotal_rows());\\n \\t\\t List<Map<String,String>> searchResults = new ArrayList<Map<String,String>>();\\n \\t\\t Map<String,String> searchRow = null;\\n \\t\\t //TODO use objects directly instead of map\\n \\t\\t for(NameConceptModelIF currNameConceptModel : nameConceptModelList.getRows()){\\n \\t\\t \\tif(currNameConceptModel.getClass().equals(NameConceptTaxonModel.class)){\\n \\t\\t \\t\\tsearchRow = new HashMap<String,String>();\\n \\t\\t \\t\\tsearchRow.put(\\\"type\\\",\\\"taxon\\\");\\n \\t\\t \\t\\tsearchRow.put(\\\"name\\\", currNameConceptModel.getName());\\n \\t\\t \\t\\tsearchRow.put(\\\"id\\\", currNameConceptModel.getTaxonId().toString());\\n \\t\\t \\t\\tsearchRow.put(\\\"status\\\", currNameConceptModel.getStatus());\\n \\t\\t \\t\\tsearchRow.put(\\\"namehtml\\\",((NameConceptTaxonModel)currNameConceptModel).getNamehtml());\\n \\t\\t \\t\\tsearchRow.put(\\\"namehtmlauthor\\\",((NameConceptTaxonModel)currNameConceptModel).getNamehtmlauthor());\\n \\t\\t \\t\\tsearchRow.put(\\\"rankname\\\",((NameConceptTaxonModel)currNameConceptModel).getRankname());\\n \\t\\t \\t\\tsearchRow.put(\\\"parentid\\\",((NameConceptTaxonModel)currNameConceptModel).getParentid().toString());\\n \\t\\t \\t\\tsearchRow.put(\\\"parentnamehtml\\\",((NameConceptTaxonModel)currNameConceptModel).getParentnamehtml());\\n \\t\\t \\t\\tsearchResult.add(searchRow);\\n \\t\\t \\t}\\n \\t\\t \\telse if(currNameConceptModel.getClass().equals(NameConceptVernacularNameModel.class)){\\n \\t\\t \\t\\tsearchRow = new HashMap<String, String>();\\n \\t\\t \\t\\tsearchRow.put(\\\"type\\\",\\\"vernacular\\\");\\n \\t\\t \\t\\tsearchRow.put(\\\"name\\\", currNameConceptModel.getName());\\n \\t\\t \\t\\tsearchRow.put(\\\"id\\\", Integer.toString(((NameConceptVernacularNameModel)currNameConceptModel).getId()));\\n \\t\\t \\t\\tsearchRow.put(\\\"status\\\", currNameConceptModel.getStatus());\\n \\t\\t \\t\\tsearchRow.put(\\\"lang\\\",((NameConceptVernacularNameModel)currNameConceptModel).getLang());\\n \\t\\t \\t\\tsearchRow.put(\\\"taxonid\\\",currNameConceptModel.getTaxonId().toString());\\n \\t\\t \\t\\tsearchRow.put(\\\"taxonnamehtml\\\",((NameConceptVernacularNameModel)currNameConceptModel).getTaxonnamehtml());\\n \\t\\t \\t\\tsearchResult.add(searchRow);\\n \\t\\t \\t}\\n \\t\\t \\telse{\\n \\t\\t \\t\\t//logger\\n \\t\\t \\t\\tsearchRow = null;\\n \\t\\t \\t}\\n \\t\\t \\tsearchResults.add(searchRow);\\n \\t\\t }\\n \\t\\t model.put(\\\"results\\\",searchResults);\\n \\t }\\n \\t \\n \\t model.put(\\\"search\\\",search);\\n \\t return new ModelAndView(\\\"search\\\", model);\\n \\t}\",\n \"@Override\\n public List<KBHandle> searchItems(KnowledgeBase aKB, String aQuery)\\n {\\n return disambiguate(aKB, null, ConceptFeatureValueType.ANY_OBJECT, aQuery, null, 0, null);\\n }\",\n \"public abstract S getSearch();\",\n \"public void searchIndexWithTermQueryByBody(final String toSearch) throws IOException, ParseException {\\n searchIndexWithTermQuery(toSearch, \\\"body\\\", DEFAULT_LIMIT);\\n }\",\n \"Boolean getSearchObjective();\",\n \"@Override\\r\\n\\tpublic void search() {\\n\\r\\n\\t}\",\n \"private void performSearch() {\\n String text = txtSearch.getText();\\n String haystack = field.getText();\\n \\n // Is this case sensitive?\\n if (!chkMatchCase.isSelected()) {\\n text = text.toLowerCase();\\n haystack = haystack.toLowerCase();\\n }\\n \\n // Check if it is a new string that the user is searching for.\\n if (!text.equals(needle)) {\\n needle = text;\\n curr_index = 0;\\n }\\n \\n // Grab the list of places where we found it.\\n populateFoundList(haystack);\\n \\n // Nothing was found.\\n if (found.isEmpty()) {\\n Debug.println(\\\"FINDING\\\", \\\"No occurrences of \\\" + needle + \\\" found.\\\");\\n JOptionPane.showMessageDialog(null, \\\"No occurrences of \\\" + needle + \\\" found.\\\",\\n \\\"Nothing found\\\", JOptionPane.INFORMATION_MESSAGE);\\n \\n return;\\n }\\n \\n // Loop back the indexes if we have reached the end.\\n if (curr_index == found.size()) {\\n curr_index = 0;\\n }\\n \\n // Go through the findings one at a time.\\n int indexes[] = found.get(curr_index);\\n field.select(indexes[0], indexes[1]);\\n curr_index++;\\n }\",\n \"public Map<String, String> directQuoteSearch (String q, String contentOrTitle) throws IOException, ParseException{\\n\\n\\t\\t\\n\\t\\tif (contentOrTitle.equals(\\\"content\\\")){\\n\\t\\t\\tcontentOrTitle=field;\\n\\t\\t} else if (contentOrTitle.equals(\\\"title\\\")){\\n\\t\\t\\tcontentOrTitle=title;\\n\\t\\t}\\n\\t\\t\\n\\t\\tIndexReader reader = DirectoryReader.open(FSDirectory.open(Paths.get(index)));\\n\\t\\tIndexSearcher searcher = new IndexSearcher(reader);\\n\\t\\tboolean raw = false;\\n\\t\\tint repeat = 0;\\n\\n\\t\\tfinal List<String> stopWords = Arrays.asList();\\n\\t\\tfinal CharArraySet stopSet = new CharArraySet(stopWords, true);\\n\\n\\t\\tAnalyzer analyzer = new StandardAnalyzer(stopSet);\\n\\t\\tAnalyzingQueryParser parser = new AnalyzingQueryParser(contentOrTitle, analyzer);\\n\\t\\t\\n\\n\\t\\t\\n\\t\\tString[] items = q.split(\\\" \\\");\\n\\t\\tList<String> itemList = Arrays.asList(items);\\n\\t\\tQuery query=null;\\n\\t\\t\\n\\t\\t\\n\\t\\tif (q.equals(\\\"\\\")){\\n\\t\\t\\tSystem.out.println(\\\"no input\\\");\\n\\t\\t\\t\\n\\t\\t} else {\\n\\t\\t\\tquery = parser.parse(q);\\n\\n\\t\\t}\\n\\n\\t\\t\\n\\t\\t\\n\\t\\tBufferedReader in = null;\\n\\t\\tin = new BufferedReader(new InputStreamReader(System.in, StandardCharsets.UTF_8));\\n\\n\\t\\tif (repeat > 0) { // repeat & time as benchmark\\n\\t\\t\\tDate start = new Date();\\n\\t\\t\\tfor (int i = 0; i < repeat; i++) {\\n\\t\\t\\t\\tsearcher.search(query, 100);\\n\\t\\t\\t}\\n\\t\\t\\tDate end = new Date();\\n\\t\\t\\tSystem.out.println(\\\"Time: \\\"+(end.getTime()-start.getTime())+\\\"ms\\\");\\n\\t\\t}\\n\\n\\t\\treturn doPagingSearch(in, searcher, query, hitsPerPage, raw, true);\\n\\t}\",\n \"abstract public boolean performSearch();\",\n \"@Override\\n\\tpublic void searchMembers(String keyword) {\\n\\t}\",\n \"public HashMap<String, int[]> documentsContaining(String word) {\\n return index.get(word);\\n }\",\n \"@Override\\n public String doSearchResult() {\\n return null;\\n }\",\n \"public byte filter(Manager m, SearchRequest q, ResultSet rs, int DocAtNumber, int DocNo)\\n\\t{\\t\\t\\n\\t\\tString originalQuery = q.getOriginalQuery();\\n\\t\\t//highlight query terms only for the queries, \\n\\t\\t//which are not about finding related documents\\n\\t\\t//this check may be removed, because the preparation of the \\n\\t\\t//query terms for highlighting takes into account\\n\\t\\t//the related: operator\\n\\t\\tboolean highlightQueryTerms = true;\\n\\t\\tif (originalQuery.matches(\\\"\\\\\\\\brelated:\\\\\\\\d+\\\\\\\\b\\\") || //check if the query uses the related: operator \\n\\t\\t\\t!enableQueryTermsHighlight || //check if the highlighting of terms is enabled\\n\\t\\t\\thighlight.pattern().equals(\\\"(\\\\\\\\b)()(\\\\\\\\b)\\\")) //check if there are no query terms to highlight\\n\\t\\t\\thighlightQueryTerms = false;\\n\\t\\t\\n\\t\\tString[] qTerms = q.getOriginalQuery().replaceAll(\\\" \\\\\\\\w+\\\\\\\\p{Punct}\\\\\\\\w+ \\\",\\\" \\\").toLowerCase().split(\\\" \\\");\\n\\t\\t\\n\\t\\tString[] metadata = null;\\n\\t\\tint tmpSentence;\\n\\t\\tdouble tmpScore;\\n\\t\\tsynchronized(metaCache) {\\n\\t\\t\\ttry {\\n\\t\\t\\t\\tInteger DocNoObject = new Integer(DocNo);\\n\\t\\t\\t\\tif (metaCache.containsKey(DocNoObject))\\n\\t\\t\\t\\t\\t\\tmetadata = (String[]) metaCache.get(DocNoObject);\\n\\t\\t\\t\\telse {\\n\\t\\t\\t\\t\\tmetadata = metaIndex.getItems(keys, DocNo);\\n\\t\\t\\t\\t\\tmetaCache.put(DocNoObject,metadata);\\n\\t\\t\\t\\t}\\n\\t\\t\\t} catch(IOException ioe) {} \\n\\t\\t}\\n\\t\\n\\t\\tif (show_snippet)\\n\\t\\t{\\n\\t\\t\\tString extract = metadata[1];\\n\\t\\t\\tString[] sentences = sentencePattern.split(extract, 50); //use 50 sentences at most\\n\\t\\t\\tdouble[] sentenceScores = new double[sentences.length]; \\n\\t\\t\\tint frsSentence = -1;\\n\\t\\t\\tint sndSentence = -1;\\n\\t\\t\\tint top1Sentence = 0;\\n\\t\\t\\tint top2Sentence = 0;\\n\\t\\t\\tdouble max1Score = -1;\\n\\t\\t\\tdouble max2Score = 0;\\n\\t\\t\\tfinal int qTermsLength = qTerms.length;\\n\\t\\t\\tfor (int i=0; i<qTermsLength; i++) {\\n\\t\\t\\t\\tqTerms[i] = removeEndings.matcher(qTerms[i]).replaceAll(\\\"\\\");\\n\\t\\t\\t}\\n\\t\\t\\tString lowerCaseSentence;\\n\\t\\t\\tint sentenceLength;\\n\\t\\t\\tfinal int sentencesLength = sentences.length;\\n\\n\\t\\t\\tfor (int i=0; i<sentencesLength; i++) {\\n\\t\\t\\t\\t\\n\\t\\t\\t\\tlowerCaseSentence = sentences[i].toLowerCase();\\n\\t\\t\\t\\tsentenceLength=sentences[i].length();\\n\\t\\t\\t\\tif (sentenceLength < 20 || sentenceLength > 250) {\\n\\t\\t\\t\\t\\tfor (int j=0; j<qTermsLength; j++) {\\n\\t\\t\\t\\t\\t\\tif (lowerCaseSentence.indexOf(qTerms[j])>=0) {\\n\\t\\t\\t\\t\\t\\t\\tsentenceScores[i]+=1.0d + sentenceLength / (20.0d + sentenceLength);\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t} else {\\n\\t\\t\\t\\t\\tfor (int j=0; j<qTermsLength; j++) {\\n\\t\\t\\t\\t\\t\\tif (lowerCaseSentence.indexOf(qTerms[j])>=0) {\\n\\t\\t\\t\\t\\t\\t\\tsentenceScores[i]+=qTerms[j].length() + sentenceLength / (1.0d + sentenceLength);\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t}\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t//do your best to get at least a second sentence for the snippet, \\n\\t\\t\\t\\t//after having found the first one\\n\\t\\t\\t\\tif (frsSentence > -1 && sndSentence == -1 && sentenceLength > 5) {\\n\\t\\t\\t\\t\\tsndSentence = i;\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\t//do your best to get at least one sentence for the snippet\\n\\t\\t\\t\\tif (frsSentence == -1 && sentenceLength > 5) { \\n\\t\\t\\t\\t\\tfrsSentence = i;\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\tif (max2Score < sentenceScores[i]) {\\n\\t\\t\\t\\t\\tmax2Score = sentenceScores[i];\\n\\t\\t\\t\\t\\ttop2Sentence = i;\\n\\t\\t\\t\\t\\t//logger.debug(\\\"top 2 sentence is \\\" + i);\\n\\t\\t\\t\\t\\tif (max2Score > max1Score) {\\n\\t\\t\\t\\t\\t\\ttmpScore = max1Score; max1Score = max2Score; max2Score = tmpScore;\\n\\t\\t\\t\\t\\t\\ttmpSentence = top1Sentence; top1Sentence = top2Sentence; top2Sentence = tmpSentence;\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t}\\n\\t\\t\\tint lastIndexOfSpace = -1;\\n\\t\\t\\tString sentence=\\\"\\\";\\n\\t\\t\\tString secondSentence=\\\"\\\";\\n\\t\\t\\tString snippet = \\\"\\\";\\n\\t\\t\\tif (max1Score == -1) {\\n\\t\\t\\t\\tif (frsSentence>=0) {\\n\\t\\t\\t\\t\\tsentence = sentences[frsSentence];\\n\\t\\t\\t\\t\\tif (sentence.length() > 100) {\\n\\t\\t\\t\\t\\t\\tlastIndexOfSpace = sentence.substring(0, 100).lastIndexOf(\\\" \\\");\\n\\t\\t\\t\\t\\t\\tsentence = sentence.substring(0, lastIndexOfSpace > 0 ? lastIndexOfSpace : 100);\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\n\\t\\t\\t\\tif (sndSentence>=0) {\\n\\t\\t\\t\\t\\tsecondSentence = sentences[sndSentence];\\n\\t\\t\\t\\t\\tif (secondSentence.length() > 100) {\\n\\t\\t\\t\\t\\t\\tlastIndexOfSpace = secondSentence.substring(0, 100).lastIndexOf(\\\" \\\");\\n\\t\\t\\t\\t\\t\\tsecondSentence = secondSentence.substring(0, lastIndexOfSpace>0 ? lastIndexOfSpace : 100);\\n\\t\\t\\t\\t\\t}\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\n\\t\\t\\t\\tif (frsSentence >=0 && sndSentence >= 0) \\n\\t\\t\\t\\t\\tsnippet = sentence.trim() + \\\"...\\\" + secondSentence.trim();\\n\\t\\t\\t\\telse if (frsSentence >= 0 && sndSentence<0) \\n\\t\\t\\t\\t\\tsnippet = sentence.trim();\\n\\t\\t\\t\\t\\n\\t\\t\\t} else if (sentences[top1Sentence].length()<100 && top1Sentence!=top2Sentence) {\\n\\t\\t\\t\\tsentence = sentences[top1Sentence];\\n\\t\\t\\t\\tif (sentence.length() > 100) {\\n\\t\\t\\t\\t\\tlastIndexOfSpace = sentence.substring(0, 100).lastIndexOf(\\\" \\\");\\n\\t\\t\\t\\t\\tsentence = sentence.substring(0, lastIndexOfSpace > 0 ? lastIndexOfSpace : 100);\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\tsecondSentence = sentences[top2Sentence];\\n\\t\\t\\t\\tif (secondSentence.length() > 100) {\\n\\t\\t\\t\\t\\tlastIndexOfSpace = secondSentence.substring(0, 100).lastIndexOf(\\\" \\\");\\n\\t\\t\\t\\t\\tsecondSentence = secondSentence.substring(0, lastIndexOfSpace>0 ? lastIndexOfSpace : 100);\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\tsnippet = sentence.trim() + \\\"...\\\" + secondSentence.trim();\\n\\t\\t\\t} else {\\n\\t\\t\\t\\tsentence = sentences[top1Sentence];\\n\\t\\t\\t\\tif (sentence.length()>200) {\\n\\t\\t\\t\\t\\tlastIndexOfSpace = sentence.substring(0, 200).lastIndexOf(\\\" \\\");\\n\\t\\t\\t\\t\\tsentence = sentence.substring(0, lastIndexOfSpace > 0 ? lastIndexOfSpace : 200);\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\tsnippet = sentence.trim();\\n\\t\\t\\t}\\n\\t\\t\\t\\n\\t\\t\\t//checking and removing any control characters\\n\\t\\t\\tcontrolNonVisibleCharactersMatcher.reset(snippet);\\n\\t\\t\\tsnippet = controlNonVisibleCharactersMatcher.replaceAll(\\\"\\\");\\n\\t\\t\\t\\n\\t\\t\\t//String escapedSnippet = StringEscapeUtils.escapeHtml(snippet);\\n\\t\\t\\t//if (highlightQueryTerms)\\n\\t\\t\\t//\\tescapedSnippet = highlight.matcher(escapedSnippet).replaceAll(\\\"$1<b>$2</b>$3\\\");\\n\\t\\t\\tif (highlightQueryTerms)\\n\\t\\t\\t\\tsnippet = highlight.matcher(snippet).replaceAll(\\\"$1<b>$2</b>$3\\\");\\n\\t\\t\\t//else \\n\\t\\t\\t//\\tsnippet = StringEscapeUtils.escapeHtml(snippet);\\n\\t\\t\\t\\n\\t\\t\\t//change by Vassilis, 20/09/2006\\n\\t\\t\\t//disabling the xml escaping in order to move the data into ![CDATA[ ]]\\n\\t\\t\\t//the code was:\\n\\t\\t\\t//rs.addMetaItem(\\\"snippet\\\", DocAtNumber, StringEscapeUtils.escapeXml(snippet));\\n\\t\\t\\t//and now it is:\\n\\t\\t\\t//snippet.replaceAll(\\\"[^\\\\\\\\u0009\\\\\\\\u000A\\\\\\\\u000D\\\\\\\\u0020-\\\\\\\\uD7FF\\\\\\\\uE000-\\\\\\\\uFFFD\\\\\\\\u10000-\\\\\\\\u10FFFF]\\\",\\\"\\\");\\n\\t\\t\\trs.addMetaItem(\\\"snippet\\\", DocAtNumber, snippet);\\n\\t\\t\\t\\n\\t\\t}\\n\\t\\tif (show_title)\\n\\t\\t{\\n\\t\\t\\tString title = metadata[2];\\n\\t\\t\\t\\n\\t\\t\\t//checking and removing any control characters\\n\\t\\t\\tcontrolNonVisibleCharactersMatcher.reset(title);\\n\\t\\t\\ttitle = controlNonVisibleCharactersMatcher.replaceAll(\\\"\\\");\\n\\t\\t\\ttitle = (highlightQueryTerms)\\n\\t\\t\\t\\t ? highlight.matcher(metadata[2]).replaceAll(\\\"$1<b>$2</b>$3\\\") \\n\\t\\t\\t\\t : metadata[2];\\n\\t\\t\\t\\n\\t\\t\\t\\n\\t\\t\\t//String escapedTitle = StringEscapeUtils.escapeHtml(metadata[2]);\\n\\t\\t\\t//String title = (highlightQueryTerms)\\n\\t\\t\\t//\\t\\t\\t ? highlight.matcher(escapedTitle).replaceAll(\\\"$1<b>$2</b>$3\\\") \\n\\t\\t\\t//\\t\\t\\t : escapedTitle;\\n\\t\\t\\t//String title = (highlightQueryTerms) \\n\\t\\t\\t//\\t\\t? highlight.matcher(metadata[2]).replaceAll(\\\"$1<b>$2</b>$3\\\") \\n\\t\\t\\t//\\t\\t: metadata[2];\\n\\n\\t\\t\\t//change by Vassilis, 20/09/2006\\n\\t\\t\\t//disabling the xml escaping in order to move the data into ![CDATA[ ]]\\n\\t\\t\\t//the code was:\\n\\t\\t\\t//rs.addMetaItem(\\\"title\\\", DocAtNumber, StringEscapeUtils.escapeXml(title));\\n\\t\\t\\t//and now is:\\n\\t\\t\\t//title.replaceAll(\\\"[^\\\\\\\\u0009\\\\\\\\u000A\\\\\\\\u000D\\\\\\\\u0020-\\\\\\\\uD7FF\\\\\\\\uE000-\\\\\\\\uFFFD\\\\\\\\u10000-\\\\\\\\u10FFFF]\\\",\\\"\\\");\\n\\t\\t\\trs.addMetaItem(\\\"title\\\", DocAtNumber, title);\\n\\t\\t\\t\\n\\t\\t}\\n\\t\\tif (!show_docid_early && show_docid)\\n\\t\\t{\\n\\t\\t\\trs.addMetaItem(\\\"docid\\\", DocAtNumber, docIndex.getDocumentNumber(DocNo));\\n\\t\\t}\\n\\t\\tif (!show_url_early && show_url)\\n\\t\\t{\\n\\n\\t\\t\\trs.addMetaItem(\\\"url\\\", DocAtNumber, StringEscapeUtils.escapeXml(metadata[0]));\\n\\t\\t}\\n\\t\\t\\n\\t\\treturn FILTER_OK;\\n\\t}\",\n \"public void set_graph() throws ParseException, IOException {\\n \\tg = new WeightedUndirectedGraph(words.length);\\n //g = new WeightedUndirectedGraph(most_important_terms.size());\\n \\n Directory dir = new SimpleFSDirectory(new File(\\\".\\\\\\\\data\\\\\\\\lucene_index_r_r\\\"));\\n Analyzer analyzer = new StandardAnalyzer(LUCENE_41);\\n \\n // creat a map that stores, for each word (in the cluster), a set of all the documents that contain that word\\n HashMap<String,HashSet<Integer>> word_to_docs_map = new HashMap<String,HashSet<Integer>>();\\n int n_strings = words.length; \\n \\n // for each word...\\n for (int idx = 0; idx < n_strings; idx++) {\\n // query the index with that given word and retrieve all the documents that contains that word\\n String query = words[idx]; \\n QueryParser parser = new QueryParser(Version.LUCENE_41, \\\"text\\\", analyzer); \\n Query q = parser.parse(query); \\n\\n IndexReader reader = DirectoryReader.open(dir);\\n IndexSearcher searcher = new IndexSearcher(reader);\\n TopDocs docs = searcher.search(q, reader.numDocs());\\n ScoreDoc[] hits = docs.scoreDocs;\\n \\n // update map from word to docs it appears in \\n //HashSet<Integer> tmp = null;\\n // tmp is the set of all the document ids in which the current word is contained\\n HashSet<Integer> tmp = new HashSet<>();\\n //word_to_docs_map.put(query, tmp);\\n \\n // for each document, retrieved from the query\\n for(Integer i=0;i<hits.length;i++) {\\n Integer docId = hits[i].doc;\\n // tmp = word_to_docs_map.get(query); \\n // if the document is a document written by an user of interest \\n if(indices.contains(docId)) {\\n tmp.add(docId);\\n }\\n //word_to_docs_map.put(query, tmp); \\n }\\n word_to_docs_map.put(query, tmp);\\n\\t }\\n\\t \\n\\t // add edges: iterate over possible term pairs ...\\n\\t for(int idx_1 = 0; idx_1 < n_strings - 1; idx_1++) {\\n\\t \\n\\t for(int idx_2 = idx_1 + 1 ; idx_2 < n_strings ; idx_2 ++ ) {\\n\\t \\n\\t // extract document sets associated with the considered terms \\n\\t HashSet<Integer> set_a = word_to_docs_map.get(words[idx_1]); \\n\\t HashSet<Integer> set_b = word_to_docs_map.get(words[idx_2]); \\n\\t \\n\\t // compute set intersection \\n\\t int n = intersectionSize(set_a, set_b);\\n\\t \\n\\t // if the terms appear in at least one common document\\n\\t if(n>0) {\\n\\t // add edge \\n\\t g.testAndAdd(idx_1, idx_2 , n); \\n\\t }\\n\\t } \\n\\t }\\n\\t}\",\n \"protected final void searchForText() {\\n Logger.debug(\\\" - search for text\\\");\\n final String searchText = theSearchEdit.getText().toString();\\n\\n MultiDaoSearchTask task = new MultiDaoSearchTask() {\\n @Override\\n protected void onSearchCompleted(List<Object> results) {\\n adapter.setData(results);\\n }\\n\\n @Override\\n protected int getMinSearchTextLength() {\\n return 0;\\n }\\n };\\n task.readDaos.add(crDao);\\n task.readDaos.add(monsterDao);\\n task.readDaos.add(customMonsterDao);\\n task.execute(searchText.toUpperCase());\\n }\",\n \"@Override\\r\\n\\tpublic Set<Article> search(String keyworkds) {\\n\\t\\treturn null;\\r\\n\\t}\",\n \"protected Query newTermQuery(Term term, float boost) {\\n Query q = new TermQuery(term);\\n if (boost == DEFAULT_BOOST) {\\n return q;\\n }\\n return new BoostQuery(q, boost);\\n }\",\n \"public abstract Search defaultSearch(StringBuilder sb);\",\n \"@Override\\n protected void doPost(HttpServletRequest request, HttpServletResponse response)\\n throws ServletException, IOException {\\n\\n // Item searched\\n String term = request.getParameter(\\\"term\\\");\\n int type, pricefilter, order;\\n try {\\n // 0 Restaurant, 1 City, 2 Region\\n type = Integer.parseInt(request.getParameter(\\\"type\\\"));\\n // 0 All, 1 €, 2 €€, 3 €€€\\n pricefilter = Integer.parseInt(request.getParameter(\\\"pricefilter\\\"));\\n // 1 Raking, 2 Alphabetical, 3 Price\\n order = Integer.parseInt(request.getParameter(\\\"order\\\"));\\n } catch (NumberFormatException e){\\n response.sendRedirect(\\\"index.jsp\\\");\\n return;\\n }\\n\\n // If null is searched, redirects\\n if(term == null){\\n response.sendRedirect(\\\"index.jsp\\\");\\n return;\\n }\\n\\n // Term searched must be at least 3 characters long\\n if(term.length() < 3){\\n // Input too short\\n response.sendRedirect(\\\"index.jsp?alert=1\\\");\\n return;\\n }\\n\\n // Character which must not be searched\\n if(term.toLowerCase().contains(\\\"%\\\") || term.toLowerCase().contains(\\\"[\\\") || term.toLowerCase().contains(\\\"]\\\") ||\\n term.toLowerCase().contains(\\\"^\\\")){\\n response.sendRedirect(\\\"index.jsp\\\");\\n return;\\n }\\n\\n // List of results depending on the filtering\\n ArrayList<SearchResult> results = null;\\n switch (type){\\n case 0:\\n results = dbmanager.getRestaurants(term, pricefilter, order);\\n break;\\n case 1:\\n results = dbmanager.getRestaurantsByCity(term, pricefilter, order);\\n break;\\n case 2:\\n results = dbmanager.getRestaurantsByRegion(term, pricefilter, order);\\n break;\\n default:\\n }\\n\\n if(results == null){\\n response.sendRedirect(\\\"index.jsp\\\");\\n }else{\\n request.setAttribute(\\\"results\\\", results);\\n request.setAttribute(\\\"type\\\", type);\\n request.setAttribute(\\\"term\\\", term);\\n request.setAttribute(\\\"pricefilter\\\", pricefilter);\\n request.setAttribute(\\\"order\\\", order);\\n getServletContext().getRequestDispatcher(\\\"/searchResults.jsp\\\").forward(request, response);\\n }\\n\\n }\",\n \"@Override\\n\\tpublic NodeIterator search(String queryString) throws Exception {\\n\\t\\treturn null;\\n\\t}\",\n \"public SuggestedTerm(String term, int editDistance){\\n this.term = term;\\n this.editDistance = editDistance;\\n }\",\n \"public Vector mapTerm(String term) throws TermNotFoundException {\\n int i = termIndex.get(term);\\n\\n if (i == -1) {\\n throw new TermNotFoundException(term);\\n }\\n\\n return new DenseVector(Uk[i]);\\n }\",\n \"private void search()\\n {\\n JTextField searchField = (currentSearchView.equals(SEARCH_PANE_VIEW))? searchBar : resultsSearchBar;\\n String searchTerm = searchField.getText();\\n \\n showTransition(2000);\\n \\n currentPage = 1;\\n showResultsView(true);\\n paginate(1, getResultsPerPage());\\n\\n if(searchWeb) showResultsTableView(WEB_RESULTS_PANE);\\n else showResultsTableView(IMAGE_RESULTS_PANE);\\n\\n \\n showSearchView(RESULTS_PANE_VIEW);\\n resultsSearchBar.setText(searchTerm);\\n }\",\n \"public List<TermSpanRecord> getResults()\\n {\\n String whereClause = \\\"owner = ?\\\";\\n List<TermSpanRecord> results = TermSpanRecord.find(TermSpanRecord.class, whereClause, new String[]{String.valueOf(getId())});\\n return results;\\n }\",\n \"private static void RankedQueryMode(DiskIndexWriter diskWriter, DiskPositionalIndex disk_posIndex) throws IOException, ClassNotFoundException, InstantiationException, IllegalAccessException {\\n\\n if (query.equals(\\\"q\\\")) {\\n\\n System.exit(0);\\n }\\n\\n List<String> word = new ArrayList();\\n String[] query_array = query.split(\\\"\\\\\\\\s+\\\");\\n TokenProcessor processor = new NewTokenProcessor();\\n\\n for (int i = 0; i < query_array.length; i++) {\\n word.add(processor.processToken(query_array[i]).get(0));\\n }\\n\\n StrategyFactory sf = new StrategyFactory();\\n StrategyInterface strategy = sf.execute(rankedOption);\\n\\n //maps postings to accumulator value\\n HashMap<Integer, Doc_accum> postingMap = new HashMap<Integer, Doc_accum>();\\n\\n PriorityQueue<Doc_accum> queue = new PriorityQueue<>(Collections.reverseOrder());\\n\\n List<Posting> postings = new ArrayList<>();\\n List<Doc_accum> results = new ArrayList<>();\\n\\n for (String term : word) {\\n\\n postings = disk_posIndex.getPosting_noPos(term);\\n for (Posting p : postings) { //for each document in the postings list\\n double t_fd = p.getT_fd();\\n double d_ft = p.getD_ft();\\n double w_qt = strategy.calculate_wqt(N, d_ft);\\n double accum = 0;\\n double w_dt = strategy.get_wdt(t_fd, disk_posIndex, p.getDocumentId());\\n\\n //pairs (Ranked_posting, accumulator factor)\\n if (postingMap.containsKey(p.getDocumentId())) {\\n accum = postingMap.get(p.getDocumentId()).getAccumulator();\\n accum += (w_qt * w_dt);\\n postingMap.replace(p.getDocumentId(), new Doc_accum(p, accum)); //replaces old accum value\\n\\n } else {\\n accum += (w_qt * w_dt);\\n postingMap.put(p.getDocumentId(), new Doc_accum(p, accum));\\n }\\n }\\n\\n }\\n\\n for (Integer p : postingMap.keySet()) {\\n Doc_accum doc_temp = postingMap.get(p);\\n double accum = doc_temp.getAccumulator(); //gets accum associated with doc\\n\\n if (accum > 0) {\\n //search for each p's Ld factor in docWeights.bin\\n double l_d = strategy.calculate_Ld(disk_posIndex, doc_temp.getPosting().getDocumentId());\\n\\n accum /= l_d;\\n doc_temp.setAccumulator(accum);\\n }\\n\\n queue.add(postingMap.get(p));\\n\\n }\\n\\n //returns top K=10 results \\n int topK = 50;\\n\\n while ((results.size() < topK) && queue.size() > 0) {\\n\\n results.add(queue.poll()); //gets the posting acc pair and returns only posting\\n\\n }\\n\\n display_RankedResults(results);\\n\\n }\",\n \"List<ShipmentInfoPODDTO> search(String query);\",\n \"@Override\\n public SearchResult search_item(String keyword, int page, int rows , int search_type) throws Exception{\\n return null;\\n }\",\n \"private List<SearchWord> getSearchWords(Long lastUpdateTime) {\\n return new ArrayList<>();\\n }\",\n \"@Test\\n public void term() throws AtlasBaseException {\\n SearchParameters params = new SearchParameters();\\n params.setTermName(SALES_TERM+\\\"@\\\"+SALES_GLOSSARY);\\n\\n List<AtlasEntityHeader> entityHeaders = discoveryService.searchWithParameters(params).getEntities();\\n\\n Assert.assertTrue(CollectionUtils.isNotEmpty(entityHeaders));\\n assertEquals(entityHeaders.size(), 10);\\n }\",\n \"public void SearchTutor() {\\n\\t\\t\\n\\t}\",\n \"public String search() {\\n return \\\"manage\\\";\\n }\",\n \"public T caseMOMoTSearch(MOMoTSearch object)\\r\\n {\\r\\n return null;\\r\\n }\",\n \"@Override\\n\\tpublic List<BoardVO> admin_search(String type, String keyword) {\\n\\t\\treturn null;\\n\\t}\",\n \"private void searchFunction() {\\n\\t\\t\\r\\n\\t}\",\n \"@Override\\n\\tpublic List<T> searchInfo(String flag, String token) {\\n\\t\\treturn trendsDao.searchInfo(flag, token);\\n\\t}\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.5979783","0.59439623","0.5828963","0.5720514","0.5714142","0.56416255","0.563343","0.5438755","0.5398442","0.53896147","0.5354768","0.5341725","0.531625","0.5312132","0.53009015","0.5274076","0.5270938","0.52231854","0.5207723","0.5195788","0.51900214","0.517766","0.5164126","0.5151208","0.51464766","0.5142497","0.5137106","0.51017445","0.5099717","0.50917554","0.5079044","0.5075073","0.5054392","0.5036259","0.50294185","0.5025743","0.50068676","0.50068676","0.5006172","0.5000156","0.49979353","0.49956673","0.4993676","0.49903253","0.49836314","0.49783412","0.49492773","0.49317592","0.49252412","0.49241686","0.49234182","0.4918374","0.49110228","0.49009204","0.4898666","0.4888007","0.48824668","0.48801196","0.48797354","0.4878633","0.48693866","0.4867728","0.4862818","0.48504704","0.48445645","0.48416302","0.48408225","0.48406625","0.48364678","0.48089686","0.48073113","0.4793018","0.4792933","0.47901827","0.47889656","0.4785059","0.47815242","0.47809443","0.47706783","0.4764043","0.4758914","0.4758263","0.4756697","0.47483584","0.47413394","0.47406664","0.47361144","0.47340208","0.47337246","0.47324923","0.47299927","0.47282842","0.4728135","0.47242323","0.47198763","0.47167513","0.4715453","0.47089347","0.4707816","0.47020838"],"string":"[\n \"0.5979783\",\n \"0.59439623\",\n \"0.5828963\",\n \"0.5720514\",\n \"0.5714142\",\n \"0.56416255\",\n \"0.563343\",\n \"0.5438755\",\n \"0.5398442\",\n \"0.53896147\",\n \"0.5354768\",\n \"0.5341725\",\n \"0.531625\",\n \"0.5312132\",\n \"0.53009015\",\n \"0.5274076\",\n \"0.5270938\",\n \"0.52231854\",\n \"0.5207723\",\n \"0.5195788\",\n \"0.51900214\",\n \"0.517766\",\n \"0.5164126\",\n \"0.5151208\",\n \"0.51464766\",\n \"0.5142497\",\n \"0.5137106\",\n \"0.51017445\",\n \"0.5099717\",\n \"0.50917554\",\n \"0.5079044\",\n \"0.5075073\",\n \"0.5054392\",\n \"0.5036259\",\n \"0.50294185\",\n \"0.5025743\",\n \"0.50068676\",\n \"0.50068676\",\n \"0.5006172\",\n \"0.5000156\",\n \"0.49979353\",\n \"0.49956673\",\n \"0.4993676\",\n \"0.49903253\",\n \"0.49836314\",\n \"0.49783412\",\n \"0.49492773\",\n \"0.49317592\",\n \"0.49252412\",\n \"0.49241686\",\n \"0.49234182\",\n \"0.4918374\",\n \"0.49110228\",\n \"0.49009204\",\n \"0.4898666\",\n \"0.4888007\",\n \"0.48824668\",\n \"0.48801196\",\n \"0.48797354\",\n \"0.4878633\",\n \"0.48693866\",\n \"0.4867728\",\n \"0.4862818\",\n \"0.48504704\",\n \"0.48445645\",\n \"0.48416302\",\n \"0.48408225\",\n \"0.48406625\",\n \"0.48364678\",\n \"0.48089686\",\n \"0.48073113\",\n \"0.4793018\",\n \"0.4792933\",\n \"0.47901827\",\n \"0.47889656\",\n \"0.4785059\",\n \"0.47815242\",\n \"0.47809443\",\n \"0.47706783\",\n \"0.4764043\",\n \"0.4758914\",\n \"0.4758263\",\n \"0.4756697\",\n \"0.47483584\",\n \"0.47413394\",\n \"0.47406664\",\n \"0.47361144\",\n \"0.47340208\",\n \"0.47337246\",\n \"0.47324923\",\n \"0.47299927\",\n \"0.47282842\",\n \"0.4728135\",\n \"0.47242323\",\n \"0.47198763\",\n \"0.47167513\",\n \"0.4715453\",\n \"0.47089347\",\n \"0.4707816\",\n \"0.47020838\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.5259476"},"document_rank":{"kind":"string","value":"17"}}},{"rowIdx":13887,"cells":{"query":{"kind":"string","value":"QUERIES MANAGEMENT Searches the index for postings matching the query."},"document":{"kind":"string","value":"public PostingsList search( Query query, int queryType, int rankingType,\n int structureType ) {\n double idf_threshold = new Double(0);\n double index_elimination = new Double(0.008);\n // System.err.println(pageRank[docNumber.get(\"121\")]);\n\n if (query.size()>0){\n switch (queryType){\n case Index.INTERSECTION_QUERY:\n System.err.println(\"Intersection query\");\n return intersect(query);\n case Index.PHRASE_QUERY:\n System.err.println(\"Phrase query\");\n return phrase_query(query);\n case Index.RANKED_QUERY:\n System.err.println(\"Ranked query\");\n switch(rankingType){\n case Index.TF_IDF: return ranked_query(query, 1, idf_threshold);\n case Index.PAGERANK: return ranked_query(query, 0, idf_threshold);//ranked_query(query, 0, idf_threshold);//ranked_query2(query, 0);\n case Index.COMBINATION: return ranked_query(query, index_elimination, idf_threshold);\n }\n default:\n System.out.println(\"not valid query\");\n return null;\n }\n }\n else\n // Query was empty\n return null;\n }"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["private void queryPosts() {\n ParseQuery<OutfitPost> query = ParseQuery.getQuery(OutfitPost.class);\n // only include data referred by user key\n query.include(OutfitPost.KEY_USER);\n query.whereEqualTo(OutfitPost.KEY_USER, ParseUser.getCurrentUser());\n // limit query to latest 20 items\n query.setLimit(20);\n // order posts by creation date (newest first)\n query.addDescendingOrder(OutfitPost.KEY_CREATED_KEY);\n // start an asynchronous call for posts\n query.findInBackground(new FindCallback<OutfitPost>() {\n @Override\n public void done(List<OutfitPost> posts, ParseException e) {\n // check for errors\n if (e != null) {\n Log.e(TAG, \"Issue with getting posts\", e);\n return;\n }\n // Save oldest post in query for loading more posts\n if (posts.size() > 0) {\n oldestPost = posts.get(posts.size() - 1).getCreatedAt();\n }\n // update adapter with posts list\n adapter.clear();\n adapter.addAll(posts);\n }\n });\n }","private void termQuerySearch(String[] terms) {\n for (String term : terms) {\n LinkedList<TermPositions> postingLists = indexMap.get(analyzeTerm(term));\n if (postingLists != null) {\n for (TermPositions matches : postingLists) {\n double score = (double) 1 + Math.log((double) matches.getPositionList().size()) *\n Math.log((double) N / (double) postingLists.size());\n resultsCollector.add(new DocCollector(matches.getDocId(), score));\n }\n }\n }\n }","CampusSearchQuery generateQuery();","WorldUps.UQuery getQueries(int index);","@Override\n public boolean onQueryTextSubmit(String query) {\n prepareBooks(engine.search(query.toLowerCase(),filter));\n return false;\n }","public PostingsList ranked_query(Query query, double w, double idf_threshold){\n long startTime = System.nanoTime();\n PostingsList result = new PostingsList();\n\n // Obtain union of terms above idf threshold if indexElimination is true\n // (Set idf_threshold to zero to disable this feature)\n Set<String> termsToConsider = this.queryTermsConsidered(query, idf_threshold);\n result = this.union_query(query, termsToConsider);\n //System.err.println(\"Size of result is \" + result.size());\n\n long estimatedTime = (System.nanoTime() - startTime)/1000000;\n System.err.println(\"* Union took: \" + estimatedTime);\n\n\n /*\n * 2) Iterate over PostingsEntries and build the solution\n */\n startTime = System.nanoTime();\n // Required when iterating over a PostingsList\n PostingsEntry postEnt = new PostingsEntry();\n // Number of documents in the collection\n double nDocs = this.docIDs.size();\n // Weight of a query vector coefficient\n double w_query_term;\n // Document tf-idf variables\n double termFrequency_doc, documentFrequency_doc, w_doc_term;\n\n for(String term : termsToConsider){\n // Obtain idf of the term\n documentFrequency_doc = Math.log(nDocs/new Double(this.idfMap.get(term)));\n\n // Obtain weight of the term\n w_query_term = query.weights.get(term);\n // Iterate over all documents containing the term and update the score(q,d)\n Iterator<PostingsEntry> it_d = result.iterator();\n while(it_d.hasNext()){\n postEnt = it_d.next();\n if (this.tfMap.get(postEnt.docID).containsKey(term)){\n termFrequency_doc = this.tfMap.get(postEnt.docID).get(term);\n w_doc_term = documentFrequency_doc*termFrequency_doc;\n postEnt.score += w_query_term*w_doc_term;\n }\n }\n }\n estimatedTime = (System.nanoTime() - startTime)/1000000;\n System.err.println(\"* Building solution took: \" + estimatedTime);\n\n /*\n * 3) Normalize the scores\n */\n startTime = System.nanoTime();\n Iterator<PostingsEntry> it = result.iterator();\n while(it.hasNext()){\n postEnt = it.next();\n postEnt.score /= (new Double(this.docLengths.get(\"\"+postEnt.docID)));//(Math.sqrt(postEnt.norm2));\n postEnt.score = w * postEnt.score + (1-w) * quality(postEnt.docID);\n }\n estimatedTime = (System.nanoTime() - startTime)/1000000;\n System.err.println(\"* Normalizing took: \" + estimatedTime);\n\n /*\n * 4) Sort the resulting solution\n */\n startTime = System.nanoTime();\n result.sort();\n estimatedTime = (System.nanoTime() - startTime)/1000000;\n System.err.println(\"* Sorting took: \" + estimatedTime);\n\n return result;\n }","public List<Post> search(PostCriteria criteria, int page, int size);","public void search(Indexer indexer, CityIndexer cityIndexer, Ranker ranker, String query, boolean withSemantic, ArrayList<String> chosenCities, ObservableList<String> citiesByTag, boolean withStemming, String saveInPath, String queryId, String queryDescription) {\n String[] originalQueryTerms = query.split(\" \");\n String originQuery = query;\n docsResults = new HashMap<>();\n parser = new Parse(withStemming, saveInPath, saveInPath);\n HashSet<String> docsOfChosenCities = new HashSet<>();\n query = \"\" + query + queryDescription;\n HashMap<String, Integer> queryTerms = parser.parseQuery(query);\n HashMap<String, ArrayList<Integer>> dictionary = indexer.getDictionary();\n if (!withStemming){\n setDocsInfo(saveInPath + \"\\\\docsInformation.txt\");\n }\n else{\n setDocsInfo(saveInPath + \"\\\\docsInformation_stemming.txt\");\n }\n\n\n //add semantic words of each term in query to 'queryTerms'\n if(withSemantic) {\n HashMap<String,ArrayList<String>> semanticWords = ws.connectToApi(originQuery);\n }\n\n //give an ID to query if it's a regular query (not queries file)\n if(queryId.equals(\"\")){\n queryId = \"\" + Searcher.queryID;\n Searcher.queryID++;\n }\n\n String postingDir;\n if (!withStemming) {\n postingDir = \"\\\\indexResults\\\\postingFiles\";\n } else {\n postingDir = \"\\\\indexResults\\\\postingFiles_Stemming\";\n }\n int pointer = 0;\n\n //find docs that contain the terms in the query in their text\n HashMap<String, Integer> queryTermsIgnoreCase = new HashMap<>();\n for (String term : queryTerms.keySet()) {\n String originTerm = term;\n if (!dictionary.containsKey(term.toUpperCase()) && !dictionary.containsKey(term.toLowerCase())) {\n continue;\n }\n if(dictionary.containsKey(term.toLowerCase())){\n term = term.toLowerCase();\n }\n else {\n term = term.toUpperCase();\n }\n queryTermsIgnoreCase.put(term,queryTerms.get(originTerm));\n pointer = dictionary.get(term).get(2);\n String chunk = (\"\" + term.charAt(0)).toUpperCase();\n\n //get the relevant line from posting file\n BufferedReader br = null;\n try {\n br = new BufferedReader(new FileReader(new File(saveInPath + postingDir + \"\\\\posting_\" + chunk + \".txt\")));\n String line = \"\";\n int i = 1;\n while ((line = (br.readLine())) != null) {\n if (i == pointer) {\n break;\n }\n i++;\n }\n br.close();\n\n //get docs from posting line and add them to the data structure 'docsResults'\n if(line != null) {\n findDocsFromLine(line, term);\n }\n\n } catch (IOException e) {\n e.printStackTrace();\n }\n }\n\n //find docs that contain the chosen cities in their text\n for (String cityTerm : chosenCities) {\n if (!dictionary.containsKey(cityTerm) && !dictionary.containsKey(cityTerm.toLowerCase())) {\n continue;\n }\n if(dictionary.containsKey(cityTerm.toLowerCase())){\n cityTerm = cityTerm.toLowerCase();\n }\n pointer = dictionary.get(cityTerm).get(2);\n // char chunk = indexer.classifyToPosting(term).charAt(0);\n String chunk = (\"\" + cityTerm.charAt(0)).toUpperCase();\n\n //get the relevant line from posting file\n BufferedReader br = null;\n try {\n br = new BufferedReader(new FileReader(new File(saveInPath + postingDir + \"\\\\posting_\" + chunk + \".txt\")));\n String line = \"\";\n int i = 1;\n while ((line = (br.readLine())) != null) {\n if (i == pointer) {\n break;\n }\n i++;\n }\n br.close();\n\n //get docs from posting line and add them to the data structure 'docsOfChosenCities'\n String docs = line.substring(0, line.indexOf(\"[\") - 1); //get 'docsListStr'\n String[] docsArr = docs.split(\";\");\n for (String docInfo : docsArr) {\n String doc = docInfo.substring(0, docInfo.indexOf(\": \"));\n while(doc.charAt(0) == ' '){\n doc = doc.substring(1);\n }\n docsOfChosenCities.add(doc);\n }\n } catch (IOException e) {\n e.printStackTrace();\n }\n }\n\n //find docs that contain the chosen cities in their city tag\n if(!chosenCities.isEmpty()){\n for (String cityDicRec: chosenCities) {\n //get pointer to posting from cityDictionary\n try {\n pointer = cityIndexer.getCitiesDictionary().get(cityDicRec);\n } catch (NumberFormatException e) {\n e.printStackTrace();\n }\n //get the relevant line from posting file\n BufferedReader br = null;\n try {\n br = new BufferedReader(new FileReader(new File(saveInPath + \"\\\\cityIndexResults\" + \"\\\\posting_city\" + \".txt\")));\n String line = \"\";\n int i = 1;\n while ((line = (br.readLine())) != null) {\n if (i == pointer) {\n break;\n }\n i++;\n }\n br.close();\n\n //get docs from posting line and add them to the data structure 'docsOfChosenCities'\n String docs = line.substring(line.indexOf(\"[\") + 1, line.indexOf(\"]\")); //get 'docsListStr'\n String[] docsArr = docs.split(\"; \");\n for (String doc : docsArr) {\n docsOfChosenCities.add(doc);\n }\n } catch (IOException e) {\n e.printStackTrace();\n }\n }\n }\n\n\n ranker.rank(docsResults, docsOfChosenCities, queryTermsIgnoreCase, dictionary, docsInfo,entities, queryId);\n }","private static void RankedQueryMode(DiskIndexWriter diskWriter, DiskPositionalIndex disk_posIndex) throws IOException, ClassNotFoundException, InstantiationException, IllegalAccessException {\n\n if (query.equals(\"q\")) {\n\n System.exit(0);\n }\n\n List<String> word = new ArrayList();\n String[] query_array = query.split(\"\\\\s+\");\n TokenProcessor processor = new NewTokenProcessor();\n\n for (int i = 0; i < query_array.length; i++) {\n word.add(processor.processToken(query_array[i]).get(0));\n }\n\n StrategyFactory sf = new StrategyFactory();\n StrategyInterface strategy = sf.execute(rankedOption);\n\n //maps postings to accumulator value\n HashMap<Integer, Doc_accum> postingMap = new HashMap<Integer, Doc_accum>();\n\n PriorityQueue<Doc_accum> queue = new PriorityQueue<>(Collections.reverseOrder());\n\n List<Posting> postings = new ArrayList<>();\n List<Doc_accum> results = new ArrayList<>();\n\n for (String term : word) {\n\n postings = disk_posIndex.getPosting_noPos(term);\n for (Posting p : postings) { //for each document in the postings list\n double t_fd = p.getT_fd();\n double d_ft = p.getD_ft();\n double w_qt = strategy.calculate_wqt(N, d_ft);\n double accum = 0;\n double w_dt = strategy.get_wdt(t_fd, disk_posIndex, p.getDocumentId());\n\n //pairs (Ranked_posting, accumulator factor)\n if (postingMap.containsKey(p.getDocumentId())) {\n accum = postingMap.get(p.getDocumentId()).getAccumulator();\n accum += (w_qt * w_dt);\n postingMap.replace(p.getDocumentId(), new Doc_accum(p, accum)); //replaces old accum value\n\n } else {\n accum += (w_qt * w_dt);\n postingMap.put(p.getDocumentId(), new Doc_accum(p, accum));\n }\n }\n\n }\n\n for (Integer p : postingMap.keySet()) {\n Doc_accum doc_temp = postingMap.get(p);\n double accum = doc_temp.getAccumulator(); //gets accum associated with doc\n\n if (accum > 0) {\n //search for each p's Ld factor in docWeights.bin\n double l_d = strategy.calculate_Ld(disk_posIndex, doc_temp.getPosting().getDocumentId());\n\n accum /= l_d;\n doc_temp.setAccumulator(accum);\n }\n\n queue.add(postingMap.get(p));\n\n }\n\n //returns top K=10 results \n int topK = 50;\n\n while ((results.size() < topK) && queue.size() > 0) {\n\n results.add(queue.poll()); //gets the posting acc pair and returns only posting\n\n }\n\n display_RankedResults(results);\n\n }","public interface SearchQuerySet extends QuerySet\n{\n\n // for AbstractSearch\n public static final int STAT_MODELS = 1;\n public static final int STAT_CLUSTERS = 2;\n public static final int STAT_GENOMES = 4;\n public static final int STAT_MODEL_CLUSTERS = 8;\n\n public String getStatsById(Collection data);\n public String getStatsByQuery(String query);\n public String getStatsById(Collection data,int stats);\n public String getStatsByQuery(String query,int stats);\n \n // for BlastSearch\n public String getBlastSearchQuery(Collection dbNames, Collection keys, KeyTypeUser.KeyType keyType);\n \n //for ClusterIDSearch\n public String getClusterIDSearchQuery(Collection input, int limit, int[] DBs, KeyTypeUser.KeyType keyType);\n \n // for ClusterNameSearch\n public String getClusterNameSearchQuery(Collection input, int limit, int[] DBs, KeyTypeUser.KeyType keyType);\n \n // for DescriptionSearch\n public String getDescriptionSearchQuery(Collection input, int limit, int[] DBs, KeyTypeUser.KeyType keyType);\n \n // for GoSearch \n public String getGoSearchQuery(Collection input, int limit, KeyTypeUser.KeyType keyType);\n \n // for GoTextSearch\n public String getGoTextSearchQuery(Collection input, int limit, KeyTypeUser.KeyType keyType);\n \n // for IdSearch\n public String getIdSearchQuery(Collection input, int limit, int[] DBs, KeyTypeUser.KeyType keyType);\n \n // for QueryCompSearch\n public String getQueryCompSearchQuery(String comp_id, String status, KeyTypeUser.KeyType keyType);\n \n // for QuerySearch\n public String getQuerySearchQuery(String queries_id, KeyTypeUser.KeyType keyType); \n \n // for SeqModelSearch\n public String getSeqModelSearchQuery(Collection model_ids, KeyTypeUser.KeyType keyType);\n \n // for UnknowclusterIdSearch\n public String getUnknownClusterIdSearchQuery(int cluster_id, KeyTypeUser.KeyType keyType);\n \n // for ProbeSetSearch\n public String getProbeSetSearchQuery(Collection input, int limit, KeyTypeUser.KeyType keyType);\n \n // for ProbeSetKeySearch\n public String getProbeSetKeySearchQuery(Collection input, int limit, KeyTypeUser.KeyType keyType);\n \n // for QueryTestSearch\n public String getQueryTestSearchQuery(String query_id, String version, String genome_id);\n \n // for QueryStatsSearch\n public String getQueryStatsSearchQuery(List query_ids,List DBs);\n \n // for PskClusterSearch\n public String getPskClusterSearchQuery(int cluster_id,KeyTypeUser.KeyType keyType);\n \n // for ClusterCorrSearch\n public String getClusterCorrSearchQuery(int cluster_id, int psk_id, KeyTypeUser.KeyType keyType);\n \n // for UnknownGenesSearch\n public String getUnknownGenesSearchQuery(Collection sources, KeyTypeUser.KeyType keyType);\n \n}","public Query( String queryString ) {\r\n\tStringTokenizer tok = new StringTokenizer( queryString );\r\n\twhile ( tok.hasMoreTokens() ) {\r\n\t terms.add( tok.nextToken() );\r\n\t weights.add( new Double(1) );\r\n\t} \r\n }","Query query();","public PageList query(String squadName, String axiser, String cubers, String followers,\n String investors, String status, Date gmtCreate, Date gmtModify,\n int pageSize, int pageNum) throws DataAccessException;","public CheckOutQ() {\r\n\t\tq = new LinkedList<Person>();\r\n\t\tmaxQ = 0;\r\n\t}","public PostingsList phrase_query(Query query){\n\n LinkedList<PostingsList> listQueriedPostings = new LinkedList<PostingsList>();\n // List with postings corresponding to the queries\n for (int i = 0; i<query.size(); i++){\n // If any query has zero matches, return 0 results\n //if(!(new File(\"postings/t\"+hash(query.terms.get(i))+\".json\")).exists()){\n if (!this.index.containsKey(query.terms.get(i))){\n return null;\n }\n // Otherwise store postings in the list\n listQueriedPostings.add(this.getPostings(query.terms.get(i)));\n }\n\n PostingsList result = new PostingsList();\n result = listQueriedPostings.get(0);\n\n // In case only one word is queried\n if (listQueriedPostings.size() == 1){\n return result;\n }\n\n // Apply algorithm as many times as words in the query\n for(int i = 1; i < listQueriedPostings.size(); i++){\n result = phrase_query(result, listQueriedPostings.get(i));\n if (result.isEmpty()){\n return null;\n }\n }\n return result;\n }","private static void BooleanQueryMode(DiskIndexWriter diskWriter, DiskPositionalIndex disk_posIndex) throws ClassNotFoundException, InstantiationException, IllegalAccessException {\n if (!specialQueries(query)) {\n //newCorpus = false; \n BooleanQueryParser bParser = new BooleanQueryParser();\n QueryComponent qComponent = bParser.parseQuery(query);\n postings = qComponent.getPostings(disk_posIndex);\n\n if (postings.isEmpty()) {\n GUI.JListModel.clear();\n GUI.ResultsLabel.setText(\"\");\n clickList = false;\n\n String notFound = \"Your search '\" + query + \"' is not found in any documents\";\n GUI.ResultsLabel.setText(notFound);\n\n } else {\n clickList = true;\n\n //clears list and repopulates it \n String docInfo;\n\n GUI.JListModel.clear();\n GUI.ResultsLabel.setText(\"\");\n\n for (Posting p : postings) {\n if (queryMode) {\n corpus.getDocument(p.getDocumentId()).getContent();\n }\n docInfo = corpus.getDocument(p.getDocumentId()).getTitle();\n //docInfo = corpus.getDocument(p.getDocumentId()).getFileName().toString();\n GUI.JListModel.addElement(docInfo);\n\n }\n GUI.ResultsLabel.setText(\"Total Documents Found: \" + postings.size());\n }\n\n }\n\n //GUI.SearchBarTextField.setText(\"Enter a new search or 'q' to exit\");\n GUI.SearchBarTextField.selectAll();\n\n }","public void search() {\n String q = this.query.getText();\n String cat = this.category.getValue();\n if(cat.equals(\"Book\")) {\n searchBook(q);\n } else {\n searchCharacter(q);\n }\n }","private void queryIndex() {\n if (predicate == TruePredicate.INSTANCE) {\n return;\n }\n\n // get indexes\n MapService mapService = nodeEngine.getService(SERVICE_NAME);\n MapServiceContext mapServiceContext = mapService.getMapServiceContext();\n Indexes indexes = mapServiceContext.getMapContainer(name).getIndexes();\n // optimize predicate\n QueryOptimizer queryOptimizer = mapServiceContext.getQueryOptimizer();\n predicate = queryOptimizer.optimize(predicate, indexes);\n\n Set<QueryableEntry> querySet = indexes.query(predicate);\n if (querySet == null) {\n return;\n }\n\n List<Data> keys = null;\n for (QueryableEntry e : querySet) {\n if (keys == null) {\n keys = new ArrayList<Data>(querySet.size());\n }\n keys.add(e.getKeyData());\n }\n\n hasIndex = true;\n keySet = keys == null ? Collections.<Data>emptySet() : InflatableSet.newBuilder(keys).build();\n }","private void executeQuery1(PersistenceManager pm) {\n Query query = pm.newQuery(Book.class, \"pages > 300\");\n Collection results = (Collection)query.execute();\n printCollection(\"Books with more than 300 pages:\", results.iterator());\n query.closeAll();\n }","private void montaQuery(Publicacao object, Query q) {\t\t\n\t}","protected void queryPosts() {\n ParseQuery<Post> query = ParseQuery.getQuery(Post.class);\n //get all the post objects from the database\n query.include(Post.KEY_USER);\n //set the limit to 20 posts being retrieved\n query.setLimit(POSTS_QUERY_LIMIT);\n\n query.addDescendingOrder(Post.KEY_CREATED_KEY);\n\n query.findInBackground(new FindCallback<Post>() {\n @Override\n public void done(List<Post> posts, ParseException e) {\n // e == null if success\n if (e != null) {\n Log.e(TAG, \"Issue with getting posts\", e);\n return;\n }\n\n for (Post post : posts) {\n Log.i(TAG, \"Post: \" + post.getDescription() + \", username: \" + post.getUser().getUsername());\n }\n adapter.clear();\n allPosts.addAll(posts);\n adapter.notifyDataSetChanged();\n }\n });\n }","public void testAdvancedQuery() {\n\t\t//manager.advancedQuery(ElasticIndex.analyzed, \"metropolitan areas\", \"sports clubs\");\n\t\t//manager.advancedQuery(ElasticIndex.analyzed, \"\", \"Award\");\n\n\t//manager.advancedQuery(ElasticIndex.analyzed,\"american actor\", \"list of movies starring Sean Connery\");\n//\tmanager.categorySearch(\"Sportspeople\", \"tennis\",ElasticIndex.analyzed,30);\n\t//manager.advancedQuery(ElasticIndex.analyzed,\"Broadway musicals\", \"Grammy Award\");\n\t//manager.advancedQuery(ElasticIndex.analyzed,\"musical movies\", \"Tony Award\");\n\t//manager.advancedQuery(ElasticIndex.analyzed,\"Top level football leagues\", \"teams\");\n\t//manager.advancedQuery(ElasticIndex.analyzed,\"american movies\", \"directed by Woody Allen\");\n\t//manager.advancedQuery(ElasticIndex.analyzed,\"United states\", \"professional sports teams\");\n\t\t//manager.advancedQuery(\"musical movies\", \"tony award\");\n\t\t//manager.advancedQuery(\"grammy\", \"best album in 2012\"); \n\t\t//manager.advancedQuery(\"american movies\", \"directed by Woody Allen\"); \n\t\t//Canceled manager.advancedQuery(\"tennis\", \"international players\"); \n\t\t// canceled manager.advancedQuery(\"tennis\", \"french open\"); \n\t\t// canceled manager.advancedQuery(\"film movie\", \"1933\"); \n//\t\tmanager.advancedQuery(\"United states\", \"professional sports teams \");\n//\t\t manager.advancedQuery(\"computer games\", \"developed by Ubisoft\");\n//\t\tmanager.advancedQuery(\"movies\", \"academy award nominations\");\n //manager.advancedQuery(\"movies\", \"starring Dustin Hoffman\");\n // manager.advancedQuery(\"movies\", \"best costume design\");\n // manager.advancedQuery(\"concert tours\", \"england\");\n // manager.advancedQuery(\"sport\", \"Francesco\");\n\t\t//System.out.println(\"******* advanced query *******\");\n\t\t//manager.advancedQuery(\"sportspeople\", \"tennis\");\n//\t\tmanager.advancedQuery(ElasticIndex.analyzed, \"Broadway musicals\", \"Grammy Award\");\n //System.out.println(\"*****************************\");\n\n\n\t\t\n\t\t//manager.advancedQuery(\"football\", \"italian championship\");\n\t\t//manager.advancedQuery(\"american basketball\", \"team\");\n\t\t //manager.advancedQuery(\"Goya Award\", \"Winner and nominees from FRA\");\n\t\t//manager.advancedQuery(\"films\", \"american comedy \");\n\t\t//manager.advancedQuery(\"films\", \"american Adventure directed by James P. Hogan\");\n\t\t//manager.advancedQuery(\"NCAA Division\", \"american universities in Arkansas\");\n\t\t//manager.advancedQuery(\"Academy award\", \"winners and nominees in acting in 2011\");\n\t\t//manager.advancedQuery(\"canadian soccer\", \"Alain Rochat position \");\n\n\t}","public void Query() {\n }","protected boolean query() {\r\n\t\tqueryStr = new String(processQueryTitle(queryBk.getTitle()) + processQueryAuthor(queryBk.getCreator())\r\n\t\t\t\t+ processQueryPublisher(queryBk.getPublisher()));\r\n\t\tSystem.out.println(queryStr);\r\n\t\t// if edition is 'lastest' (coded '0'), no query is performed; and\r\n\t\t// return false.\r\n\t\tif (queryBk.parseEdition() == 0) {\r\n\t\t\treturn false;\r\n\t\t} // end if\r\n\r\n\t\t/*\r\n\t\t * The following section adds edition info to the query string if edition no. is\r\n\t\t * greater than one. By cataloging practice, for the first edition, probably\r\n\t\t * there is NO input on the associated MARC field. Considering this, edition\r\n\t\t * query string to Primo is NOT added if querying for the first edition or no\r\n\t\t * edition is specified.\r\n\t\t */\r\n\t\tif (queryBk.parseEdition() > 1) {\r\n\t\t\tqueryStr += processQueryEdition(queryBk.parseEdition());\r\n\t\t} // end if\r\n\r\n\t\t/*\r\n\t\t * Querying the Primo X-service; and invoking the matching processes (all done\r\n\t\t * by remoteQuery()).\r\n\t\t */\r\n\t\tif (strHandle.hasSomething(queryBk.getPublisher())) {\r\n\t\t\tif (remoteQuery(queryStr)) {\r\n\t\t\t\tmatch = true;\r\n\t\t\t\tsetBookInfo();\r\n\t\t\t\tcheckAVA(queryBk.parseVolume());\r\n\t\t\t\treturn true;\r\n\t\t\t} else {\r\n\t\t\t\tmatch = false;\r\n\t\t\t} // end if\r\n\t\t} // end if\r\n\r\n\t\t/*\r\n\t\t * For various reasons, there are possibilities that the first query fails while\r\n\t\t * a match should be found. The follow work as remedy queries to ensure the\r\n\t\t * accuracy.\r\n\t\t */\r\n\r\n\t\tif (!match && strHandle.hasSomething(queryBk.getPublisher())) {\r\n\t\t\tqueryStr = new String(\r\n\t\t\t\t\tprocessQueryPublisher(queryBk.getPublisher()) + processQueryAuthor(queryBk.getCreator()));\r\n\t\t\tif (remoteQuery(queryStr)) {\r\n\t\t\t\tmatch = true;\r\n\t\t\t\tsetBookInfo();\r\n\t\t\t\tcheckAVA(queryBk.parseVolume());\r\n\t\t\t\treturn true;\r\n\t\t\t} else {\r\n\t\t\t\tmatch = false;\r\n\t\t\t} // end if\r\n\t\t} // end if\r\n\r\n\t\tif (!match) {\r\n\t\t\tqueryStr = new String(processQueryTitle(queryBk.getTitle()) + processQueryAuthor(queryBk.getCreator()));\r\n\t\t\tif (remoteQuery(queryStr)) {\r\n\t\t\t\tmatch = true;\r\n\t\t\t\tsetBookInfo();\r\n\t\t\t\tcheckAVA(queryBk.parseVolume());\r\n\t\t\t\treturn true;\r\n\t\t\t} else {\r\n\t\t\t\tmatch = false;\r\n\t\t\t} // end if\r\n\t\t} // end if\r\n\r\n\t\tif (!match) {\r\n\t\t\tqueryStr = new String(processQueryTitle(queryBk.getTitle()));\r\n\t\t\tif (remoteQuery(queryStr)) {\r\n\t\t\t\tmatch = true;\r\n\t\t\t\tsetBookInfo();\r\n\t\t\t\tcheckAVA(queryBk.parseVolume());\r\n\t\t\t\treturn true;\r\n\t\t\t} else {\r\n\t\t\t\tmatch = false;\r\n\t\t\t} // end if\r\n\t\t} // end if\r\n\r\n\t\tif (!match && strHandle.hasSomething(queryBk.getPublishYear())) {\r\n\t\t\tqueryStr = new String(\r\n\t\t\t\t\tprocessQueryAuthor(queryBk.getCreator()) + processQueryYear(queryBk.getPublishYear()));\r\n\r\n\t\t\tif (remoteQuery(queryStr)) {\r\n\t\t\t\tmatch = true;\r\n\t\t\t\tsetBookInfo();\r\n\t\t\t\tcheckAVA(queryBk.parseVolume());\r\n\t\t\t\treturn true;\r\n\t\t\t} else {\r\n\t\t\t\tmatch = false;\r\n\t\t\t} // end if\r\n\t\t} // end if\r\n\r\n\t\tif (!match) {\r\n\t\t\tqueryStr = new String(\r\n\t\t\t\t\tprocessQueryAuthor(queryBk.getCreator()) + processQueryTitleShort(queryBk.getTitle()));\r\n\t\t\tif (remoteQuery(queryStr)) {\r\n\t\t\t\tmatch = true;\r\n\t\t\t\tsetBookInfo();\r\n\t\t\t\tcheckAVA(queryBk.parseVolume());\r\n\t\t\t\treturn true;\r\n\t\t\t} else {\r\n\t\t\t\tmatch = false;\r\n\t\t\t} // end if\r\n\t\t} // end if\r\n\r\n\t\t// Additional query for Chinese titles\r\n\r\n\t\tif (!match && (CJKStringHandling.isCJKString(queryBk.getTitle())\r\n\t\t\t\t|| CJKStringHandling.isCJKString(queryBk.getCreator())\r\n\t\t\t\t|| CJKStringHandling.isCJKString(queryBk.getPublisher()))) {\r\n\r\n\t\t\tqueryStr = new String(processQueryTitle(queryBk.getTitle()));\r\n\t\t\tif (remoteQuery(queryStr)) {\r\n\t\t\t\tmatch = true;\r\n\t\t\t\tsetBookInfo();\r\n\t\t\t\tcheckAVA(queryBk.parseVolume());\r\n\t\t\t\treturn true;\r\n\t\t\t} else {\r\n\t\t\t\tmatch = false;\r\n\t\t\t} // end if\r\n\r\n\t\t\tif (!match && queryBk.parseEdition() != -1) {\r\n\t\t\t\tqueryStr = new String(\r\n\t\t\t\t\t\tprocessQueryTitle(queryBk.getTitle()) + processQueryEdition2(queryBk.parseEdition()));\r\n\t\t\t\tif (remoteQuery(queryStr)) {\r\n\t\t\t\t\tmatch = true;\r\n\t\t\t\t\tsetBookInfo();\r\n\t\t\t\t\tcheckAVA(queryBk.parseVolume());\r\n\t\t\t\t\treturn true;\r\n\t\t\t\t} else {\r\n\t\t\t\t\tmatch = false;\r\n\t\t\t\t} // end if\r\n\r\n\t\t\t\tif (!match && queryBk.parseEdition() != -1) {\r\n\t\t\t\t\tqueryStr = new String(\r\n\t\t\t\t\t\t\tprocessQueryTitle(queryBk.getTitle()) + processQueryEdition3(queryBk.parseEdition()));\r\n\t\t\t\t\tif (remoteQuery(queryStr)) {\r\n\t\t\t\t\t\tmatch = true;\r\n\t\t\t\t\t\tsetBookInfo();\r\n\t\t\t\t\t\tcheckAVA(queryBk.parseVolume());\r\n\t\t\t\t\t\treturn true;\r\n\t\t\t\t\t} else {\r\n\t\t\t\t\t\tmatch = false;\r\n\t\t\t\t\t} // end if\r\n\t\t\t\t} // end if\r\n\t\t\t} // end if\r\n\t\t} // end if\r\n\r\n\t\t// Additional check for ISO Document number in <search> <genernal> PNX\r\n\t\t// tag\r\n\t\tif (!match && !CJKStringHandling.isCJKString(queryBk.getTitle())) {\r\n\t\t\tqueryStr = new String(processQueryTitleISODoc(queryBk.getTitle()));\r\n\t\t\tif (remoteQuery(queryStr)) {\r\n\t\t\t\tmatch = true;\r\n\t\t\t\tsetBookInfo();\r\n\t\t\t\tcheckAVA(queryBk.parseVolume());\r\n\t\t\t\treturn true;\r\n\t\t\t} else {\r\n\t\t\t\tmatch = false;\r\n\t\t\t\terrMsg += \"Query: No record found on Primo.\" + Config.QUERY_SETTING;\r\n\t\t\t} // end if\r\n\t\t} // end if\r\n\t\treturn false;\r\n\t}","private void queryList (String query) {\n\t\tmemoListAdapter.query(query);\n\t}","Term getQ();","private static void prMode(DiskIndexWriter diskWriter, DiskPositionalIndex disk_posIndex) throws ClassNotFoundException, InstantiationException, IllegalAccessException, FileNotFoundException {\n long time = 0;\n GUI.JListModel.clear();\n\n if (query.equals(\"q\")) {\n\n System.exit(0);\n }\n MAP mean_ap = new MAP(path);\n //returns qRel.keyset() i.e. queries \n Set<String> queries = mean_ap.getQueries();\n List<Long> time_per_query = new ArrayList<>();\n //run ranked retrival for each query\n for (String q : queries) {\n time = 0;\n List<String> word = new ArrayList();\n\n query = q;\n long start = System.currentTimeMillis();\n\n String[] query_array = query.split(\"\\\\s+\");\n TokenProcessor processor = new NewTokenProcessor();\n\n for (int i = 0; i < query_array.length; i++) {\n word.add(processor.processToken(query_array[i]).get(0));\n }\n long t1 = System.currentTimeMillis();\n time = t1 - start; //time to parse\n StrategyFactory sf = new StrategyFactory();\n StrategyInterface strategy = sf.execute(rankedOption);\n\n //maps postings to accumulator value\n HashMap<Integer, Doc_accum> postingMap = new HashMap<Integer, Doc_accum>();\n\n PriorityQueue<Doc_accum> queue = new PriorityQueue<>(Collections.reverseOrder());\n\n List<Posting> postings = new ArrayList<>();\n List<Doc_accum> results = new ArrayList<>();\n\n for (String term : word) {\n long t2 = System.currentTimeMillis();\n\n if (term.equals(\"\")) {\n continue;\n } else {\n\n postings = disk_posIndex.getPosting_noPos(term);\n long t3 = System.currentTimeMillis();\n time = time + (t3 - t2);\n\n for (Posting p : postings) { //for each document in the postings list\n double t_fd = p.getT_fd();\n double d_ft = p.getD_ft();\n double w_qt = strategy.calculate_wqt(N, d_ft);\n double accum = 0;\n double w_dt = strategy.get_wdt(t_fd, disk_posIndex, p.getDocumentId());\n\n //pairs (Ranked_posting, accumulator factor)\n if (postingMap.containsKey(p.getDocumentId())) {\n accum = postingMap.get(p.getDocumentId()).getAccumulator();\n accum += (w_qt * w_dt);\n postingMap.replace(p.getDocumentId(), new Doc_accum(p, accum)); //replaces old accum value\n\n } else {\n accum += (w_qt * w_dt);\n postingMap.put(p.getDocumentId(), new Doc_accum(p, accum));\n }\n }\n\n }\n }\n for (Integer p : postingMap.keySet()) {\n Doc_accum doc_temp = postingMap.get(p);\n double accum = doc_temp.getAccumulator(); //gets accum associated with doc\n\n if (accum > 0) {\n //search for each p's Ld factor in docWeights.bin\n double l_d = strategy.calculate_Ld(disk_posIndex, doc_temp.getPosting().getDocumentId());\n\n accum /= l_d;\n doc_temp.setAccumulator(accum);\n }\n\n queue.add(postingMap.get(p));\n\n }\n\n //returns top K=10 results \n int topK = 50;\n\n while ((results.size() < topK) && queue.size() > 0) {\n\n results.add(queue.poll()); //gets the posting acc pair and returns only posting\n\n }\n time_per_query.add(time);\n List<String> filenames = get_RankedResults(results);\n\n mean_ap.add_poseRel(q, filenames);\n\n }\n\n double map_result = mean_ap.mean_ap();\n String mapDisplay = \"Mean average precision: \" + map_result;\n GUI.JListModel.addElement(mapDisplay);\n System.out.println(\"\\n\" + mapDisplay);\n\n double throughput_result = mean_ap.calculate_throughput(time_per_query);\n String throughput_Display = \"Throughput of the system is: \" + throughput_result;\n GUI.JListModel.addElement(throughput_Display);\n System.out.println(throughput_Display);\n\n double mrt_result = mean_ap.calculae_mean_response_time(time_per_query);\n String mrt_Display = \"Mean Response Time of the system is: \" + mrt_result;\n GUI.JListModel.addElement(mrt_Display);\n System.out.println(mrt_Display);\n\n }","public void run(){\n\t\tif(searchHow==0){\n\t\t\tint isbnCount = 0;\n\t\t\tfor(int i=0; i<db.size(); i++){\n\t\t\t\t\tSearchRequest requestIsbn = new SearchRequest(db, searchForThis, isbnCount, db.size());\n\t\t\t\t\tdb.searchByISBN(requestIsbn);\n\t\t\t\t\tisbnCount = requestIsbn.foundPos;\n\t\t\t\t\tif (requestIsbn.foundPos >= 0) {\n\t\t\t\t\t\tisbnCount++;\n\t\t\t\t\t\tString formatThis = \"Matched ISBN at position: \" + requestIsbn.foundPos;\n\t\t\t\t\t\tSystem.out.printf(\"%-35s || Title: \"+db.getBook(requestIsbn.foundPos)+\"\\n\",formatThis);\n\t\t\t\t\t}\n\t\t\t\t\telse\n\t\t\t\t\t\ti=db.size();\n\t\t\t}\n\t\t}\n\t\tif(searchHow==1){\n\t\t\tint titleCount = 0;\n\t\t\tfor(int i=0; i<db.size(); i++){\n\t\t\t\t\tSearchRequest requestTitle = new SearchRequest(db, searchForThis, titleCount, db.size());\n\t\t\t\t\tdb.searchByTitle(requestTitle);\n\t\t\t\t\ttitleCount = requestTitle.foundPos;\n\t\t\t\t\tif (requestTitle.foundPos >= 0) {\n\t\t\t\t\t\ttitleCount++;\n\t\t\t\t\t\tString formatThis = \"Matched title at position: \" + requestTitle.foundPos;\n\t\t\t\t\t\tSystem.out.printf(\"%-35s || Title: \"+db.getBook(requestTitle.foundPos)+\"\\n\",formatThis);\n\t\t\t\t\t}\n\t\t\t\t\telse\n\t\t\t\t\t\ti=db.size();\n\t\t\t}\n\t\t}\n\t\tif(searchHow==2){\n\t\t\tint authorCount = 0;\n\t\t\tfor(int i=0; i<db.size(); i++){\n\t\t\t\t\tSearchRequest requestAuthor = new SearchRequest(db, searchForThis, authorCount, db.size());\n\t\t\t\t\tdb.searchByAuthor(requestAuthor);\n\t\t\t\t\tauthorCount = requestAuthor.foundPos;\n\t\t\t\t\tif (requestAuthor.foundPos >= 0) {\n\t\t\t\t\t\tauthorCount++;\n\t\t\t\t\t\tString formatThis = \"Matched author at position: \" + requestAuthor.foundPos;\n\t\t\t\t\t\tSystem.out.printf(\"%-35s || Title: \"+db.getBook(requestAuthor.foundPos)+\"\\n\",formatThis);\n\t\t\t\t\t}\n\t\t\t\t\telse\n\t\t\t\t\t\ti=db.size();\n\t\t\t}\n\t\t}\n\t\tif(searchHow==3){\n\t\t\tint pageCount = 0;\n\t\t\tfor(int i=0; i<db.size(); i++){\n\t\t\t\t\tSearchRequest requestPage = new SearchRequest(db, searchForThis, pageCount, db.size());\n\t\t\t\t\tdb.searchByNumPages(requestPage);\n\t\t\t\t\tpageCount = requestPage.foundPos;\n\t\t\t\t\tif (requestPage.foundPos >= 0) {\n\t\t\t\t\t\tpageCount++;\n\t\t\t\t\t\tString formatThis = \"Matched pages at position: \" + requestPage.foundPos;\n\t\t\t\t\t\tSystem.out.printf(\"%-35s || Title: \"+db.getBook(requestPage.foundPos)+\"\\n\",formatThis);\n\t\t\t\t\t}\n\t\t\t\t\telse\n\t\t\t\t\t\ti=db.size();\n\t\t\t}\n\t\t}\n\t\tif(searchHow==4){\n\t\t\tint yearCount = 0;\n\t\t\tfor(int i=0; i<db.size(); i++){\n\t\t\t\t\tSearchRequest requestYear = new SearchRequest(db, searchForThis, yearCount, db.size());\n\t\t\t\t\tdb.searchByYear(requestYear);\n\t\t\t\t\tyearCount = requestYear.foundPos;\n\t\t\t\t\tif (requestYear.foundPos >= 0) {\n\t\t\t\t\t\tyearCount++;\n\t\t\t\t\t\tString formatThis = \"Matched year at position: \" + requestYear.foundPos;\n\t\t\t\t\t\tSystem.out.printf(\"%-35s || Title: \"+db.getBook(requestYear.foundPos)+\"\\n\",formatThis);\n\t\t\t\t\t}\n\t\t\t\t\telse\n\t\t\t\t\t\ti=db.size();\n\t\t\t}\n\t\t}\n\t}","@Override\n public boolean onQueryTextSubmit(String query) {\n topStories = false;\n filter.setQuery(query);\n gvResults.clearOnScrollListeners();\n setUpRecycler();\n findViewById(R.id.relativeLayout).setVisibility(View.GONE);\n findViewById(R.id.tvHeading).setVisibility(View.GONE);\n fetchArticles(0,true);\n searchView.clearFocus();\n return true;\n }","public void query()\n\t{\n\t\tJSONObject queryInfo = new JSONObject();\n\t\t\n\t\ttry\n\t\t{\n\t\t\tqueryInfo.put(\"type\", \"query\");\n\t\t\t\n\t\t\tos.println(queryInfo.toString());\n\t\t\tos.flush();\n\t\t\t\n\t\t\tSystem.out.println(\"send query request : \" + queryInfo.toString());\n\t\t}\n\t\tcatch (JSONException e)\n\t\t{\n\t\t\te.printStackTrace();\n\t\t}\n\t}","protected void queryPosts()\n {\n ParseQuery<Post> query = ParseQuery.getQuery(Post.class);\n query.include(Post.KEY_USER);\n query.whereEqualTo(Post.KEY_USER, ParseUser.getCurrentUser());\n query.setLimit(20);\n query.addDescendingOrder(Post.KEY_CREATED_AT);\n query.findInBackground(new FindCallback<Post>() {\n @Override\n public void done(List<Post> posts, ParseException e)\n {\n if(e != null)\n {\n Log.e(TAG, \"Issue with getting posts\", e);\n }\n for(Post post : posts)\n {\n Log.i(TAG, \"Post: \" + post.getDescription() + \", username\" + post.getUser().getUsername());\n }\n adapter.clear();\n allPosts.addAll(posts);\n swipeContainer.setRefreshing(false);\n adapter.notifyDataSetChanged();\n\n }\n });\n }","public void search(IndexShort < O > index, short range, short k)\n throws Exception {\n // assertEquals(index.aDB.count(), index.bDB.count());\n // assertEquals(index.aDB.count(), index.bDB.count());\n // index.stats();\n index.resetStats();\n // it is time to Search\n int querySize = 1000; // amount of elements to read from the query\n String re = null;\n logger.info(\"Matching begins...\");\n File query = new File(testProperties.getProperty(\"test.query.input\"));\n File dbFolder = new File(testProperties.getProperty(\"test.db.path\"));\n BufferedReader r = new BufferedReader(new FileReader(query));\n List < OBPriorityQueueShort < O >> result = new LinkedList < OBPriorityQueueShort < O >>();\n re = r.readLine();\n int i = 0;\n long realIndex = index.databaseSize();\n\n while (re != null) {\n String line = parseLine(re);\n if (line != null) {\n OBPriorityQueueShort < O > x = new OBPriorityQueueShort < O >(\n k);\n if (i % 100 == 0) {\n logger.info(\"Matching \" + i);\n }\n\n O s = factory.create(line);\n if (factory.shouldProcess(s)) {\n if(i == 279){\n System.out.println(\"hey\");\n }\n index.searchOB(s, range, x);\n result.add(x);\n i++;\n }\n }\n if (i == querySize) {\n logger.warn(\"Finishing test at i : \" + i);\n break;\n }\n re = r.readLine();\n }\n \n logger.info(index.getStats().toString());\n \n int maxQuery = i;\n // logger.info(\"Matching ends... Stats follow:\");\n // index.stats();\n\n // now we compare the results we got with the sequential search\n Iterator < OBPriorityQueueShort < O >> it = result.iterator();\n r.close();\n r = new BufferedReader(new FileReader(query));\n re = r.readLine();\n i = 0;\n while (re != null) {\n String line = parseLine(re);\n if (line != null) {\n if (i % 300 == 0) {\n logger.info(\"Matching \" + i + \" of \" + maxQuery);\n }\n O s = factory.create(line);\n if (factory.shouldProcess(s)) {\n OBPriorityQueueShort < O > x2 = new OBPriorityQueueShort < O >(\n k);\n searchSequential(realIndex, s, x2, index, range);\n OBPriorityQueueShort < O > x1 = it.next();\n //assertEquals(\"Error in query line: \" + i + \" slice: \"\n // + line, x2, x1); \n \n assertEquals(\"Error in query line: \" + i + \" \" + index.debug(s) + \"\\n slice: \"\n + line + \" \" + debug(x2,index ) + \"\\n\" + debug(x1,index), x2, x1);\n\n i++;\n }\n \n }\n if (i == querySize) {\n logger.warn(\"Finishing test at i : \" + i);\n break;\n }\n re = r.readLine();\n }\n r.close();\n logger.info(\"Finished matching validation.\");\n assertFalse(it.hasNext());\n }","@Override\n protected void queryPosts() {\n ParseQuery<Post> query = ParseQuery.getQuery(Post.class);\n query.include(Post.KEY_USER);\n query.whereEqualTo(Post.KEY_USER, ParseUser.getCurrentUser());\n Log.d(TAG, \"ParseUser\" + ParseUser.getCurrentUser().toString());\n query.setLimit(20);\n query.addDescendingOrder(Post.KEY_CREATED_AT);\n query.findInBackground(new FindCallback<Post>() {\n @Override\n public void done(List<Post> posts, ParseException e) {\n if (e != null){\n Log.e(TAG, \"Issue with getting posts\", e);\n return;\n }\n for (Post post: posts){\n Log.i(TAG, \"Post: \" + post.getDescription() + \", username: \" + post.getUser().getUsername());\n }\n allPosts.addAll(posts);\n adapter.notifyDataSetChanged();\n }\n });\n }","private void queryPost() {\n tv_search.setText(\"Recently Added Posts:\");\n ParseQuery<Post> query = ParseQuery.getQuery(Post.class);\n query.include(Post.KEY_USER);\n query.setLimit(15);\n query.addDescendingOrder(Post.KEY_CREATED);\n query.findInBackground(new FindCallback<Post>() {\n @Override\n public void done(List<Post> posts, ParseException e) {\n if(e!= null){\n Log.e(tag, \"Issue with getting post\", e);\n return;\n }\n adaptor.clear();\n adaptor.addAll(posts);\n //allPost.addAll(posts);\n //adaptor.notifyDataSetChanged();\n //swipeRefreshLayout.setRefreshing(false);\n\n //user just created a post\n if (isJustCreatedNewPost == true)\n {\n //reset bool\n isJustCreatedNewPost = false;\n// //subscribe user to their new post channel\n// String postChannel = \"POST_\"+posts.get(0).getObjectId();\n// ParsePush.subscribeInBackground(postChannel);\n\n }\n }\n });\n }","public Qs() {\n this(\"qs\", null);\n }","public void search() {\n try {\n for(int i = 0; i < this.queries.size(); i++){\n search(i);\n // in case of error stop\n if(!this.searchOK(i)){\n System.out.println(\"\\t\" + new Date().toString() + \" \" + db + \" Search for rest queries cancelled, because failed for query \" + i + \" : \" + this.queries.get(i));\n break;\n }\n }\n } catch (UnsupportedEncodingException ex) {\n Logger.getLogger(EntrezSearcher.class.getName()).log(Level.SEVERE, null, ex);\n }\n }","public static void searchJobs(String searchTerm) {\n\n for (int i = 0; i > PostJob.allJobs.size(); i++) {\n\n\n if (PostJob.allJobs.contains(searchTerm)) {\n int itemIndx = PostJob.allJobs.indexOf(searchTerm);\n String output = PostJob.allJobs.get(itemIndx);\n System.out.print(\"Available jobs within your search terms\" + output);\n\n }\n }\n }","public void performQuack(){\n qb.quack();\n }","SearchResponse query(SearchRequest request, Map<SearchParam, String> params);","List<Revenue> search(String query);","public static void query(String q) throws TwitterException, SQLException, ClassNotFoundException {\n\n\t\t//the search object returns a list of all the tweets from the query string q\n\t\tSearch newQuery = new Search(q);\n\t\t\n\t\tClass.forName(\"org.h2.Driver\");\n\t\tConnection conn = DriverManager.getConnection(DB, user, pass);\n\t\t\n\t\t//authentication allows a user to have up to 350 requests per hour over the normal 150\n\t\tTwitter a = OAuth.authenticate();\n\n\t\ttry {\n\t\t\tArrayList<Long> sid = new ArrayList<Long>();\n\t\t\tfor (Tweet tweets : newQuery.statusList) {\n\t\t\t\tlong statusID = tweets.getId();\n\t\t\t\t//this checks for redudant statuses then inserts new ones into the DB\n\t\t\t\tif (!(DB_Interface.exist_Status(statusID, conn))) {\n\t\t\t\t\tSystem.out.println(\"Preparin new insert of status \"\n\t\t\t\t\t\t\t+ statusID);\n\t\t\t\t\tsid.add(statusID);\n\t\t\t\t\t\n\t\t\t\t\t/* a.showStatus transforms a query tweet into a normal status this takes up a rate limit\n\t\t\t\t\t * this is a difficult problem to address because scraped tweets and streamed tweets are\n\t\t\t\t\t * formatted as a normal status, but only queried tweets are structured this way\n\t\t\t\t\t */\n\t\t\t\t\tDB_Interface.insertTweet(conn, a.showStatus(statusID));\n\t\t\t\t} else {\n\t\t\t\t\tSystem.out.println(\"Status Already exists!!!!\");\n\t\t\t\t}\n\t\t\t}\n\t\t} catch (JdbcSQLException e) {\n\t\t\te.printStackTrace();\n\t\t}\n\t\t\n\t\tconn.close();\n\n\t}","public void performSearch() {\n final String url = String.format(BING_SEARCH_URL, Words.getRandomWord(), Words.getRandomWord());\n\n //open page with custom data\n openWebPage(url, \"Search url: \" + url);\n }","@Override\r\n public boolean onQueryTextSubmit(String query) {\n searchAdapter.setSearchResults(DataCache.getInstance().getSearchResults(query));\r\n return false;\r\n }","@Override\n public boolean onQueryTextSubmit(String query) {\n if(!TextUtils.isEmpty(query)){\n //seach\n seachHispost(query);\n }else {\n loadHisPosts();\n }\n return false;\n }","List<Cemetery> search(String query);","SearchResponse search(Pageable pageable, QueryBuilder query, Collection<AggregationBuilder> aggregations);","void runQueries();","private static void executeQuery4(PersistenceManager pm) {\n Query query = pm.newQuery(Category.class);\n query.declareParameters(\"int length\");\n query.declareVariables(\"Item item\");\n query.setFilter(\n \"elements.contains(item) && item.name.length() <= length\");\n Collection results = (Collection)query.execute(new Integer(10));\n printCollection(\"Categories containing an item with a short name: \",\n results.iterator());\n query.closeAll();\n }","List<Job> findAllByLocation(String query);","public IndexSearcher longQueryExpansion(String indexDir, String queriesFile, PrintWriter outputWriter, Debug debug, String similarity, Analyzer analyzer) throws IOException, ParseException {\t\t\n\t\t\n\t\t//Welcome to shortQueries\n\t\tSystem.out.println(\"Set requests to LONG QUERIES EXPANSION\");\n\t\t\n\t\t//Create IndexReader and Searcher\n\t\tIndexReader reader = DirectoryReader.open(FSDirectory.open( new File(indexDir).toPath()));\t\t//Creating an index reader\n\t\tIndexSearcher searcher = new IndexSearcher(reader);\t\t\t\t\t\t\t\t\t\t\t\t//Create an index searcher\n\t\t\n\t\t//Set similarity measure\n\t\tsearcher = new SetSimilarity().SetSimilaritySearcher(searcher, similarity);\n\t\t\n\t\t//Read queries from file\n\t\t\tString[] queries = Search.readQueriesFile(queriesFile);\n\t\t\t\n\t\t\tfor (int i=0; i < queries.length; i++ ){ //for all queries\n\t\t\t\t\n\t\t\t\ttry {\n\t\t\t\t\t//Parse Multiple fields Query\t\t\t\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\n\t\t\t\t\tString str = queries[i];\t\t\t\t//take all queries\n\t\t\t\t\tString[] parts = str.split(\"#\", 3);\t\t//split them in three\n\t\t\t\t\t//String num = parts[0];\t\t\t\t\t//part 1 is number\n\t\t\t\t\tString title = parts[1];\t\t\t\t//part 2 is title\n\t\t\t\t\tString desc = parts[2];\t\t\t\t\t//part 3 is description\n\t\t\t\t\tString num = Integer.toString(i + 1);\t//(part 1 is number ) other option for queyrid\n\t\t\t\t\tSystem.out.println(\"Query number: \" + num);\n\t\t\t\t\tSystem.out.println(\"Title of query: \" + title); \n\t\t\t\t\tSystem.out.println(\"Description of query: \" + desc);\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t//Title query\n\t\t\t\t\tQueryParser titleQP = new QueryParser(\"contents\", analyzer);\t\t\t\t//Built QueryParser\n\t\t\t\t\t\n\t\t\t\t\tString newTitle = title.substring(3, title.length());\t//Strip numbers from title\n\t\t\t\t\tQuery titleQuery = titleQP.parse(newTitle); \t\t\t\t\t\t\t\t\t//Parse titles\n\t\t\t\t\t//Desc query\n\t\t\t\t\tQueryParser descQP = new QueryParser (\"contents\", analyzer);\t\t\t\t//Build QueryParser\n\t\t\t\t\tQuery descQuery = descQP.parse(desc);\t\t\t\t\t\t\t\t\t\t//Parse descriptions\t\n\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t//Final Query\n\t\t\t\t\tBuilder booleanQuery = new BooleanQuery.Builder();\n\t\t\t\t\tbooleanQuery.add(titleQuery, BooleanClause.Occur.SHOULD);\n\t\t\t\t\tbooleanQuery.add(descQuery, BooleanClause.Occur.SHOULD);\n\t\t\t\t\tQuery q = booleanQuery.build();\n\t\t\t\t\tSearch.displayQuery(q);\n\t\t\t\t\t\n\t\t\t\t\t//Search\n\t\t\t\t\tTopScoreDocCollector collector = TopScoreDocCollector.create(1000);\t\t\t\t\t\t\t\t//Create a TopScore Collector\n\t\t\t\t\tsearcher.search(q, collector);\t\n\t\t\t\t\t\n\t\t\t\t\t//Print results\n\t\t\t\t\t//displayResults(searcher, collector);\n\t\t\t\t\t\n\t\t\t\t\t//Output results to file\n\t\t\t\t\tSearch.outputResults(searcher, collector, outputWriter, num);\n\t\t\t\t\t\n\t\t\t\t}//end try\n\t\t\t\tcatch (Exception e) {\n\t\t\t\t\tSystem.out.println(\"Parse exception in query #\" + i);\n\t\t\t\t\te.printStackTrace();\n\t\t\t\t}//end catch\n\t\t\t\n\t\t}//end for\n\t\t\t//Close index reader\n\t\t\toutputWriter.close();\n\t\t\treader.close();\n\t\t\treturn searcher;\n\t\t\t\n\t}","public void onSearchSubmit(String queryTerm);","public static void QueryVector() {\n for(Entry<String, List<Double>> entry: wtgMap.entrySet()){\n List<Double> queryValue = new ArrayList();\n queryValue = entry.getValue();\n double temp = queryValue.get(totaldocument);\n\n query.add(temp);\n }\n }","private void createAdapters() {\n // Available quests for a Neutral hero\n adapterAvailableNeutral = new QuestAdapter(this, new ParseQueryAdapter.QueryFactory<ParseObject>(){\n @Override\n public ParseQuery create() {\n ParseQuery query = new ParseQuery(QuestApp.QUEST_DATABASE);\n query.whereEqualTo(QuestApp.COMPLETED_KEY, false);\n query.whereDoesNotMatchKeyInQuery(QuestApp.ACCEPTEDBY_KEY, QuestApp.OBJECTID_KEY, ParseUser.getQuery());\n return query;\n }\n });\n\n // Available quests for a Good hero\n adapterAvailableGood = new QuestAdapter(this, new ParseQueryAdapter.QueryFactory<ParseObject>(){\n @Override\n public ParseQuery create() {\n ParseQuery query = new ParseQuery(QuestApp.QUEST_DATABASE);\n query.whereEqualTo(QuestApp.COMPLETED_KEY, false);\n query.whereEqualTo(QuestApp.ALIGNMENT_KEY, 0);\n query.whereDoesNotMatchKeyInQuery(QuestApp.ACCEPTEDBY_KEY, QuestApp.OBJECTID_KEY, ParseUser.getQuery());\n return query;\n }\n });\n\n // Available quests for an Evil hero\n adapterAvailableEvil = new QuestAdapter(this, new ParseQueryAdapter.QueryFactory<ParseObject>(){\n @Override\n public ParseQuery create() {\n ParseQuery query = new ParseQuery(QuestApp.QUEST_DATABASE);\n query.whereEqualTo(QuestApp.COMPLETED_KEY, false);\n query.whereEqualTo(QuestApp.ALIGNMENT_KEY, 2);\n query.whereDoesNotMatchKeyInQuery(QuestApp.ACCEPTEDBY_KEY, QuestApp.OBJECTID_KEY, ParseUser.getQuery());\n return query;\n }\n });\n\n // Quests accepted by user\n adapterAccepted = new QuestAdapter(this, new ParseQueryAdapter.QueryFactory<ParseObject>(){\n @Override\n public ParseQuery create() {\n ParseQuery query = new ParseQuery(QuestApp.QUEST_DATABASE);\n query.whereEqualTo(QuestApp.COMPLETED_KEY, false);\n query.whereEqualTo(QuestApp.ACCEPTEDBY_KEY, user);\n return query;\n }\n });\n\n // Quests completed by user\n adapterCompleted = new QuestAdapter(this, new ParseQueryAdapter.QueryFactory<ParseObject>(){\n @Override\n public ParseQuery create() {\n ParseQuery query = new ParseQuery(QuestApp.QUEST_DATABASE);\n query.whereEqualTo(QuestApp.COMPLETED_KEY, true);\n query.whereEqualTo(QuestApp.ACCEPTEDBY_KEY, user);\n return query;\n }\n });\n }","private void addQueries(String query){\n ArrayList <String> idsFullSet = new ArrayList <String>(searchIDs);\n while(idsFullSet.size() > 0){\n ArrayList <String> idsSmallSet = new ArrayList <String>(); \n if(debugMode) {\n System.out.println(\"\\t Pmids not used in query available : \" + idsFullSet.size());\n }\n idsSmallSet.addAll(idsFullSet.subList(0,Math.min(getSearchIdsLimit(), idsFullSet.size())));\n idsFullSet.removeAll(idsSmallSet);\n String idsConstrain =\"\";\n idsConstrain = idsConstrain(idsSmallSet);\n addQuery(query,idsConstrain);\n }\n }","public static void search(){\n\t\tfor (Page p:heap){\n\t\t\tfor(Building b:p.buildings){\n\t\t\t\t\n\t\t\t\t//System.out.println(b.buildingName);\n\t\t\t\tif(b.getBuildingName()!=null) {\n\t\t\t\t\tif(b.getBuildingName().contains(searchQuery)){\n\t\t\t\t\t\tSystem.out.println(\"======================================================\");\n\t\t\t\t\t\tSystem.out.println(\"Building Name: \" + b.getBuildingName());\n\t\t\t\t\t\tSystem.out.println(\"Property ID: \" + b.getPropID());\n\t\t\t\t\t\tSystem.out.println(\"Census year: \" + b.getCensusYear());\n\t\t\t\t\t\tSystem.out.println(\"======================================================\");\n\t\t\t\t\t\tSystem.out.println();\n\t\t\t\t\t\tbuildingsFound++;\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t\tpagesSearched++;\n\t\t}\n\t}","public void index(List<ParsedDocument> pdocs,int qid) {\n\t\ttry {\n\t\t\tint count = iw.maxDoc()+1;\n\t\t\tDocument doc = null;\n\t\t\tIndexDocument iDoc=null;\n\t\t\tfor (ParsedDocument pdoc : pdocs) {\n\t\t\t\t\n\t\t\t\tiDoc=parseDocument(pdoc);\n\t\t\t\tif(iDoc==null){\n\t\t\t\t\tcontinue;\n\t\t\t\t}\n\t\t\t\tField queryField = new Field(\"qid\", qid+\"\", Store.YES,\n\t\t\t\t\t\tIndex.NOT_ANALYZED);\n\t\t\t\tField uniqueField = new Field(\"id\", count + \"\", Store.YES,\n\t\t\t\t\t\tIndex.NOT_ANALYZED);\n\t\t\t\tField titleField = new Field(\"title\", iDoc.getTitle(),\n\t\t\t\t\t\tStore.YES, Index.ANALYZED, TermVector.YES);\n\t\t\t\tField bodyField = new Field(\"body\", iDoc.getBody(), Store.YES,\n\t\t\t\t\t\tIndex.ANALYZED, TermVector.YES);\n\t\t\t\tField urlField = new Field(\"url\", iDoc.getUrl(), Store.YES,\n\t\t\t\t\t\tIndex.NOT_ANALYZED);\n\t\t\t\tField anchorField = new Field(\"anchor\", iDoc.getAnchor(), Store.YES,\n\t\t\t\t\t\tIndex.ANALYZED, TermVector.YES);\n\n\t\t\t\tdoc = new Document();\n\t\t\t\tdoc.add(uniqueField);//标示不同的document\n\t\t\t\tdoc.add(queryField);//标示不同的query\n\t\t\t\tdoc.add(titleField);\n\t\t\t\tdoc.add(bodyField);\n\t\t\t\tdoc.add(urlField);\n\t\t\t\tdoc.add(anchorField);\n\t\t\t\t\n\t\t\t\tiw.addDocument(doc);\n\t\t\t\tcount++;\n\t\t\t}\n\t\t\tiw.commit();\n\t\t\t\n\t\t} catch (IOException e) {\n\t\t\te.printStackTrace();\n\t\t} \n\t}","public static void main(String[] args) {\n\t\tSession s2=util.getSession();\r\n\t\tQuery qry=s2.getNamedQuery(\"q2\");\r\n\t\t//Query qry=s2.getNamedQuery(\"q3\");\r\n\t\t//qry.setInteger(0, 50);\r\n\t\tList<Object[]> lust=qry.list();\r\n\t\tfor(Object[] row:lust) {\r\n\t\t\tSystem.out.println(Arrays.toString(row));\r\n\t\t}\r\n\t\tSystem.out.println(\"Completed\");\r\n\t}","public List<T> query(QueryObject qo) {\n\t\treturn null;\n\t}","private static String addQueryEntry(String query) throws IOException {\n\t\t\t\t\n\t\tString submittedQuery=null;\n\t\tString queryParts[]=query.split(\"&\"); // get parameters from query\t\t\n\t\tboolean isNextPage=false;\n\t\tString key=null;\n\t\tInteger value=null;\n\t\tboolean docsProcessed=false; // identifies if 'docs' occurs more than once in the query\t\t\n\t\tboolean termsProcessed=false; // identifies if 'terms' occurs more than once in the query\n\t\t\n\t\t// identify if it is a next page\n\t\tfor (int i=0;i<queryParts.length;i++) { // verifies if it is a next page\n\t\t\tString queryPartsFields[]=queryParts[i].split(\"=\",2);\t\t\t\n\t\t\tqueryPartsFields[0]=queryPartsFields[0].trim();\n\t\t\tif (queryPartsFields.length>1) {\n\t\t\t\tqueryPartsFields[1]=queryPartsFields[1].trim();\n\t\t\t}\n\t\t\t\n\t\t\tif (queryPartsFields[0].equals(DOCS_KEY) && queryPartsFields.length>1 && !queryPartsFields[1].equals(\"\")) {\t\t\t\n\t\t\t\tint ipage;\n\t\t\t\ttry {\n\t\t\t\t\tipage=Integer.parseInt(queryPartsFields[1]);\n\t\t\t\t}\n\t\t\t\tcatch (NumberFormatException e) {\n\t\t\t\t\tipage=0;\n\t\t\t\t}\n\t\t\t\t\n\t\t\t\tif (ipage!=0) { // regist only pages>0 \t\t\t\t\t\t\t\n\t\t\t\t\tisNextPage=true;\t\t\t\n\t\t\t\t\tif (ipage%RESULTS_PER_PAGE!=0) {\n\t\t\t\t\t\tSystem.err.println(\"Page results not multiple of \"+RESULTS_PER_PAGE+\": \"+ipage);\n\t\t\t\t\t\tipage+=ipage%RESULTS_PER_PAGE;\n\t\t\t\t\t}\n\t\t\t\t\tif (!docsProcessed) {\n\t\t\t\t\t\tint index=ipage/RESULTS_PER_PAGE>pagesViewedDistAux.length-1 ? pagesViewedDistAux.length-1 : ipage/RESULTS_PER_PAGE;\t\t\t\n\t\t\t\t\t\tif (index==0) { // sanity check\n\t\t\t\t\t\t throw new IOException(\"Error of index=0 on a next page. ipage:\"+ipage);\n\t\t\t\t\t\t}\n\t\t\t\t\t\tpagesViewedDistAux[index]++;\n\t\t\t\t\t}\n\t\t\t\t\tdocsProcessed=true;\t\t\t\t\n\t\t\t\t}\t\t\t\t\t\t\n\t\t\t}\n\t\t\telse if (queryPartsFields[0].equals(QUERY_KEY)) {\n\t\t\t\ttermsProcessed=true;\n\t\t\t}\n\t\t}\n\t\t// check wrong entries\n\t\tif (docsProcessed && !termsProcessed) {\n\t\t\tSystem.err.println(\"Error of query with docs without terms: \"+query);\n\t\t\treturn null;\n\t\t}\t\t\t\t\n\t\tif (isNextPage) {\n\t\t\treturn null;\n\t\t}\n\t\t\n\t\t// count only first page\n\t\tdocsProcessed=false;\n\t\tfor (int i=0;i<queryParts.length;i++) {\t\t\t\t\t\t\t\t\t\n\t\t\tString queryPartsFields[]=queryParts[i].split(\"=\",2);\t\t\t\n\t\t\tqueryPartsFields[0]=queryPartsFields[0].trim();\n\t\t\t\n\t\t\tif (!queryPartsFields[0].equals(QUERY_KEY) || queryPartsFields.length!=2) {\n\t\t\t\tcontinue;\n\t\t\t}\n\t\t\t\n\t\t\t// normalize query\t\t\t\n\t\t\ttry {\n\t\t\t\tqueryPartsFields[1]=decodeStrings(decodeNCR(java.net.URLDecoder.decode(queryPartsFields[1],\"ISO8859-1\").toLowerCase()));\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t}\n\t\t\tcatch(IllegalArgumentException e) {\n\t\t\t\tqueryPartsFields[1]=decodeStrings(decodeNCR(queryPartsFields[1].toLowerCase()));\n\t\t\t}\n\t\t\t// remove spaces\n\t\t\tString terms[]=queryPartsFields[1].split(\"\\\\s\");\n\t\t\tqueryPartsFields[1]=\"\";\n\t\t\tfor (int j=0,k=0;j<terms.length;j++) {\t\t\t\t\t\n\t\t\t\tif (terms[j].equals(\"\")) {\n\t\t\t\t\tcontinue;\n\t\t\t\t}\t\t\t\t\t\n\t\t\t\tif (k>0) {\n\t\t\t\t\tqueryPartsFields[1]+=\" \";\t\n\t\t\t\t}\n\t\t\t\tqueryPartsFields[1]+=terms[j];\t\t\t\t\t\n\t\t\t\tk++;\n\t\t\t}\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t// filter queries\t\t\t\t\t\n\t\t\tif (queryFiltersMap.containsKey(queryPartsFields[1]) || queryPartsFields[1].startsWith(\"cache%3\") || queryPartsFields[1].equals(\"\")) {\t\t\t\t\n\t\t\t\tcontinue;\n\t\t\t}\t\t\t\t\t\t\t\t\n\t\t\t// set first page viewed\n\t\t\tif (!docsProcessed) {\n\t\t\t\tpagesViewedDistAux[0]++;\n\t\t\t\tdocsProcessed=true;\t\t\t\t\t\t\n\t\t\t}\n\t\t\t\n\t\t\t//key=queryPartsFields[0]+\" \"+queryPartsFields[1];\n\t\t\tkey=NEW_QUERY_KEY+\" \"+queryPartsFields[1];\t\t\t\n\t\t\tif ((value=queryPartsMap.get(key))==null) {\n\t\t\t\tqueryPartsMap.put(key,1);\n\t\t\t}\n\t\t\telse {\n\t\t\t\tqueryPartsMap.put(key,value+1);\n\t\t\t}\n\t\t\t\n\t\t\t// set submitted query\n\t\t\tif (submittedQuery!=null) { // sanity check\n\t\t\t\tthrow new IOException(\"Submitted query already set.\");\n\t\t\t}\n\t\t\tsubmittedQuery=queryPartsFields[1];\n\t\t\t\t\n\t\t\t// count queries per session\t\n\t\t\tnQueriesSession++;\n\t\t}\n\t\treturn submittedQuery;\n\t}","public void parseQueryStringAndSearch(String searchString) {\n char[] chars = searchString.toCharArray();\n for (int i = 0; i < chars.length; i++) {\n Queue<Character> queue;\n int k;\n if (Character.isDigit(chars[i])) {\n k = Integer.parseInt(String.valueOf(chars[i]));\n i++;\n queue = new LinkedList<>();\n while (i < chars.length && chars[i] != ')') {\n queue.add(chars[i]);\n i++;\n }\n i++;\n String query = queryToString(queue);\n String[] terms = query.split(\" \");\n //System.out.println(query + \" and k: \" + k);\n positionIntersects(indexMap.get(analyzeTerm(terms[0])), indexMap.get(analyzeTerm(terms[1])), k);\n } else {\n queue = new LinkedList<>();\n while (i < chars.length && !Character.isDigit(chars[i])) {\n queue.add(chars[i]);\n i++;\n }\n i--;\n String query = queryToString(queue);\n String[] terms = query.trim().split(\" \");\n termQuerySearch(terms);\n }\n\n }\n\n }","@ActionTrigger(action=\"KEY-ENTQRY\", function=KeyFunction.SEARCH)\n\t\tpublic void spriden_Search()\n\t\t{\n\t\t\t\n\t\t\t\texecuteAction(\"QUERY\");\n\t\t\t\tgetTask().getGoqrpls().gCheckFailure();\n\t\t\t}","List<E> queryAll(String namedQuery);","private SeqIter query(final int db, final int qu) throws Exception {\r\n final int size = qressizes[db * nqueries + qu];\r\n final double qtime = qt[db * nqueries + qu];\r\n \r\n if(size == 0) return new SeqIter();\r\n \r\n // query and cache result\r\n final String que = XQM + \"for $i score $s in \" +\r\n queries.get(qu) + \" order by $s descending \" +\r\n \"return (basex:sum-path($i), $s, base-uri($i))\";\r\n \r\n final Process proc = new XQuery(que);\r\n final CachedOutput res = new CachedOutput();\r\n if(session.execute(proc)) session.output(res);\r\n \r\n final SeqIter sq = new SeqIter();\r\n final StringTokenizer st = new StringTokenizer(res.toString(), \" \");\r\n String lp = \"\";\r\n int z = 0;\r\n while(st.hasMoreTokens() && z < size) {\r\n qtimes[qu] += qtime;\r\n final String p = st.nextToken();\r\n if(!st.hasMoreTokens()) break;\r\n final String s = st.nextToken();\r\n if(!st.hasMoreTokens()) break;\r\n String uri = st.nextToken();\r\n //while(uri.indexOf(\".xml\") == -1) uri = st.nextToken();\r\n uri = uri.substring(uri.lastIndexOf('/') + 1);\r\n final String tmp = uri + \";\" + p;\r\n if(!lp.equals(tmp)) {\r\n final Str str = Str.get(token(uri + \";\" + p));\r\n str.score(Double.parseDouble(s));\r\n sq.add(str);\r\n lp = tmp;\r\n }\r\n z++;\r\n }\r\n \r\n Main.outln(\"Query % on %: %\", qu + 1, databases.get(db), qtime);\r\n return sq;\r\n }","public QueryController(String[] args){\n // Parse Args\n QueryArgs queryArgs = new QueryArgs();\n try {\n queryArgs.parseArgs(args);\n } catch (FileNotFoundException e) {\n //e.printStackTrace();\n System.err.println(\"Invalid Arguments received. Please check your arguments passed to ./search\");\n return;\n }\n\n // Run the Term Normaliser\n TermNormalizer normalizer = new TermNormalizer();\n String[] queryTerms = normalizer.transformedStringToTerms(queryArgs.queryString);\n\n //create the model\n Model model = new Model();\n model.loadCollectionFromMap(queryArgs.mapPath);\n model.loadLexicon(queryArgs.lexiconPath);\n model.loadInvertedList(queryArgs.invlistPath);\n if(queryArgs.stopListEnabled)\n {\n model.loadStopList(queryArgs.stopListPath);\n }\n if(queryArgs.printSummary && queryArgs.collectionPath != \"\")\n {\n model.setPathToCollection(queryArgs.collectionPath);\n }\n\n\n //fetch the top results from the query module\n QueryModule queryModule = new QueryModule();\n queryModule.doQuery(queryTerms, model, queryArgs.bm25Enabled);\n List<QueryResult> topResults = queryModule.getTopResult(queryArgs.maxResults);\n\n\n\n ResultsView resultsView = new ResultsView();\n if(queryArgs.printSummary)\n {\n\n DocSummary docSummary = new DocSummary();\n for(QueryResult result:topResults)\n {\n // retrieve the actualy text from the document collection\n result.setDoc(model.getDocumentCollection().getDocumentByIndex(result.getDoc().getIndex(), true));\n\n //set the summary on the result object by fetching it from the docSummary object\n result.setSummaryNQB(docSummary.getNonQueryBiasedSummary(result.getDoc(), model.getStopListModule()));\n result.setSummaryQB(docSummary.getQueryBiasedSummary(result.getDoc(), model.getStopListModule(), Arrays.asList(queryTerms)));\n }\n resultsView.printResultsWithSummary(topResults,queryArgs.queryLabel);\n }else\n {\n resultsView.printResults(topResults,queryArgs.queryLabel);\n }\n\n }","@Test\n\tpublic void testKeywordQuery(){\n\t\t//manager.getResponse(\"american football \"); //match multiple keywords\n//\t\tmanager.getResponse(\"list of Bond 007 movies\");\n//\tmanager.getResponse(\"Disney movies\");\n\t\t//manager.keywordQuery(\"Paul Brown Stadium location\");\n\t\t//manager.keywordQuery(\"0Francesco\");\n System.out.println(\"******* keyword query *******\");\n\t\t//manager.keywordQuery(\"sportspeople in tennis\");\n\t\t//manager.keywordSearch(\"list of movies starring Sean Connery\",ElasticIndex.analyzed,100 );\n//\t\tmanager.keywordSearch(\"movies starring Sean Connery\",ElasticIndex.notStemmed,100 );\n// manager.keywordSearch(\"musical movies tony award\",ElasticIndex.analyzed,100 );\n// manager.keywordSearch(\"movies directed by Woody Allen\",ElasticIndex.analyzed,100 );\n// manager.keywordSearch(\"United states professional sports teams\",ElasticIndex.analyzed,100 );\n// manager.keywordSearch(\"computer games developed by Ubisoft\",ElasticIndex.analyzed,100 );\n// manager.keywordSearch(\"computer games developed by Ubisoft\",ElasticIndex.notStemmed,100 );\n// manager.keywordSearch(\"movies academy award nominations\",ElasticIndex.notStemmed,100 );\n System.out.println(SearchResultUtil.toSummary(manager.keywordSearch(\"movies directed by Woody Allen\",ElasticIndex.notLowercased,20 )));\n //manager.keywordSearch(\"grammy best album in 2012\",ElasticIndex.notAnalyzed,100 );\n //(better than analyzed) manager.keywordSearch(\"grammy best album in 2012\",ElasticIndex.notStemmed,100 );\n System.out.println(\"*****************************\");\n\n\t\t//manager.keywordQuery(\"Disney movies\");\n\t}","public Query advancedQuery() \n {\n return null;\n }","@Override\n public List<SearchResult> search(String queryString, int k) {\n // TODO: YOUR CODE HERE\n\n // Tokenize the query and put it into a Set\n HashSet<String> tokenSet = new HashSet<>(Searcher.tokenize(queryString));\n\n /*\n * Section 1: FETCHING termId, termFreq and relevant docId from the Query\n */\n\n // Init a set to store Relevant Document Id\n HashSet<Integer> relevantDocIdSet = new HashSet<>();\n for (String token : tokenSet) { // Iterates thru all query tokens\n int termId;\n try {\n termId = indexer.getTermDict().get(token);\n } catch (NullPointerException e) { // In case current token is not in the termDict\n continue; // Skip this one\n }\n // Get the Posting associate to the termId\n HashSet<Integer> posting = indexer.getPostingLists().get(termId);\n relevantDocIdSet.addAll(posting); // Add them all to the Relevant Document Id set\n }\n\n /*\n * Section 2: Calculate Jaccard Coefficient between the Query and all POTENTIAL DOCUMENTS\n */\n\n // ArrayList for the Final Result\n ArrayList<SearchResult> searchResults = new ArrayList<>();\n for (Document doc : documents) { // Iterates thru all documents\n if (!relevantDocIdSet.contains(doc.getId())) { // If the document is relevant\n searchResults.add(new SearchResult(doc, 0)); // Add the document as a SearchResult with zero score\n } else {\n HashSet<String> termIdSet = new HashSet<>(doc.getTokens()); // Get the token set from the document\n\n // Calculate Jaccard Coefficient of the document\n double jaccardScore = JaccardMathHelper.calculateJaccardSimilarity(tokenSet, termIdSet);\n\n // Add the SearchResult with the computed Jaccard Score\n searchResults.add(new SearchResult(doc, jaccardScore));\n }\n }\n\n return TFIDFSearcher.finalizeSearchResult(searchResults, k);\n }","public Query getQuery ()\n {\n\n\treturn this.q;\n\n }","QueryResponse query(SolrParams solrParams) throws SolrServerException;","@Override\n public Data3DPlastic search() {\n return super.search();\n }","public SearchResponse prepareSearchScrollRequest() {\n GetSettingsResponse getSettingsResponse = client.admin().indices().getSettings(new GetSettingsRequest().indices(dataPointer.getIndexName())).actionGet();\n int numShards = 0, numIndices = 0;\n for(ObjectCursor<Settings> settings : getSettingsResponse.getIndexToSettings().values()) {\n numShards += settings.value.getAsInt(\"index.number_of_shards\", 0);\n numIndices++;\n }\n\n int sizePerShard = (int)Math.ceil((double)SCROLL_SHARD_LIMIT/numShards);\n logger.info(\"Found \" + numIndices + \" indices and \" + numShards + \" shards matching the index-pattern, thus setting the sizePerShard to \" + sizePerShard);\n\n SearchRequestBuilder searchRequestBuilder = client.prepareSearch(dataPointer.getIndexName())\n .setTypes(dataPointer.getTypeName())\n .setSearchType(SearchType.SCAN)\n .addFields(\"_ttl\", \"_source\")\n .setScroll(new TimeValue(SCROLL_TIME_LIMIT))\n .setSize(sizePerShard);\n\n if (!Strings.isNullOrEmpty(query.getQuery())) {\n searchRequestBuilder.setQuery(query.getQuery());\n }\n if (!Strings.isNullOrEmpty(query.getSortField())) {\n searchRequestBuilder.addSort(new FieldSortBuilder(query.getSortField()).order(query.getSortOrder()));\n }\n\n bound.map(resolvedBound -> boundedFilterFactory.createBoundedFilter(segmentationField.get(), resolvedBound))\n .ifPresent(searchRequestBuilder::setQuery);\n\n return searchRequestBuilder.execute().actionGet();\n }","private void compute(IndexSearcher searcher, int size) throws IOException {\n Bucket<Term> bucket = new Bucket<Term>(size);\n DocumentCounter counter = new DocumentCounter();\n for (TermQuery q : this._queries) {\n searcher.search(q, counter);\n bucket.add(q.getTerm(), counter.getCount());\n counter.reset();\n }\n this._bucket = bucket;\n }","@Override\n\tprotected void executeSearch(String term) {\n\t\t\n\t}","@Override\r\n\t\t\tpublic List<ScoredDocument> search(Query query) {\n\t\t\t\treturn null;\r\n\t\t\t}","public void setQ(int q) {\n this.q = q;\n }","private void search()\n {\n JTextField searchField = (currentSearchView.equals(SEARCH_PANE_VIEW))? searchBar : resultsSearchBar;\n String searchTerm = searchField.getText();\n \n showTransition(2000);\n \n currentPage = 1;\n showResultsView(true);\n paginate(1, getResultsPerPage());\n\n if(searchWeb) showResultsTableView(WEB_RESULTS_PANE);\n else showResultsTableView(IMAGE_RESULTS_PANE);\n\n \n showSearchView(RESULTS_PANE_VIEW);\n resultsSearchBar.setText(searchTerm);\n }","public interface Query {\n\n\t/**\n\t * @return ID of the given query\n\t */\n\tint queryID();\n\t\n\t/**\n\t * @return given query\n\t */\n\tString query();\n\t\n\t/**\n\t * @return list of relevant documents to the corresponding query\n\t */\n\tList<RelevanceInfo> listOfRelevantDocuments();\n\t\n\t/**\n\t * @return list of results to the corresponding query after running one of the retrieval models\n\t */\n\tList<Result> resultList();\n\t\n\t/**\n\t * @param resultList\n\t * @Effects adds results to the result list of the corresponding query\n\t */\n\tvoid putResultList(List<Result> resultList);\n}","public void performSearch() {\n OASelect<QueryInfo> sel = getQueryInfoSearch().getSelect();\n sel.setSearchHub(getSearchFromHub());\n sel.setFinder(getFinder());\n getHub().select(sel);\n }","public void testSearchRules() throws Exception {\n Project project = new Project();\r\n \r\n DateFormatSymbols symbols = new DateFormatSymbols(Locale.US);\r\n \r\n for (int i = 0; i < 12; i++) {\r\n \r\n String month = symbols.getMonths()[i];\r\n String shortMonth = symbols.getShortMonths()[i];\r\n \r\n // Basic project info\r\n project.setId(i);\r\n project.setCategoryId(1);\r\n project.setAllowGuests(true);\r\n project.setMembershipRequired(false);\r\n project.setApproved(true);\r\n project.setClosed(false);\r\n project.setPortal(false);\r\n \r\n // Unique Title\r\n project.setTitle(month + \" test project\");\r\n project.setShortDescription(month + \" description word\");\r\n project.setKeywords(shortMonth);\r\n \r\n // Unique Location\r\n project.setCity(\"Virginia Beach\");\r\n project.setState(\"VA\");\r\n project.setPostalCode(\"234\" + String.valueOf(50 + i));\r\n \r\n // Random Rating for now\r\n project.setRatingCount(i + 1);\r\n project.setRatingValue(project.getRatingCount() * StringUtils.rand(1, 5));\r\n project.setRatingAverage(project.getRatingValue() / project.getRatingCount());\r\n \r\n // Index it\r\n ProjectIndexer indexer = new ProjectIndexer();\r\n indexer.add(snowballWriter, project, true);\r\n }\r\n \r\n QueryParser parser = new QueryParser(\"contents\", snowballAnalyzer);\r\n \r\n {\r\n // Make sure a single matching term yields a single hit\r\n SearchBean search = new SearchBean();\r\n search.setQuery(symbols.getMonths()[0]);\r\n search.setLocation(\"Virginia Beach\");\r\n assertNotNull(search.getQuery());\r\n assertNotNull(search.getLocation());\r\n search.parseQuery();\r\n assertTrue(search.isValid());\r\n \r\n String queryString = SearchUtils.generateProjectQueryString(search, UserUtils.createGuestUser().getId(), -1, null);\r\n assertNotNull(queryString);\r\n \r\n // (approved:1)\r\n // AND (guests:1)\r\n // AND (closed:0)\r\n // AND (website:0)\r\n // AND (\"january\"^20 OR january^15 OR january*^4) AND (location:(\"virginia beach\"^30))\r\n \r\n Query query = parser.parse(queryString);\r\n Hits hits = getSnowballSearcher().search(query);\r\n assertTrue(hits.length() == 1);\r\n }\r\n \r\n {\r\n // Make sure a single matching term stem yields a single hit\r\n SearchBean search = new SearchBean();\r\n search.setQuery(symbols.getMonths()[0] + \"'s\");\r\n search.setLocation(\"Virginia Beach\");\r\n assertNotNull(search.getQuery());\r\n assertNotNull(search.getLocation());\r\n search.parseQuery();\r\n assertTrue(search.isValid());\r\n \r\n String queryString = SearchUtils.generateProjectQueryString(search, UserUtils.createGuestUser().getId(), -1, null);\r\n assertNotNull(queryString);\r\n \r\n // (approved:1)\r\n // AND (guests:1)\r\n // AND (closed:0)\r\n // AND (website:0)\r\n // AND (\"january's\"^20 OR january's^15 OR january's*^4) AND (location:(\"virginia beach\"^30))\r\n \r\n Query query = parser.parse(queryString);\r\n Hits hits = getSnowballSearcher().search(query);\r\n assertTrue(hits.length() == 1);\r\n }\r\n \r\n {\r\n // Make sure multiple matching words yield two hits\r\n SearchBean search = new SearchBean();\r\n search.setQuery(symbols.getMonths()[0] + \" \" + symbols.getMonths()[1]);\r\n search.setLocation(\"Virginia Beach\");\r\n search.parseQuery();\r\n assertTrue(search.isValid());\r\n \r\n String queryString = SearchUtils.generateProjectQueryString(search, UserUtils.createGuestUser().getId(), -1, null);\r\n assertNotNull(queryString);\r\n \r\n // (approved:1)\r\n // AND (guests:1)\r\n // AND (closed:0)\r\n // AND (website:0)\r\n // AND (\"january february\"^20 OR january^15 OR february^14 OR january*^4 OR february*^3) AND (location:(\"virginia beach\"^30))\r\n \r\n Query query = parser.parse(queryString);\r\n Hits hits = getSnowballSearcher().search(query);\r\n assertTrue(hits.length() == 2);\r\n }\r\n \r\n {\r\n // Make sure wilcards yield multiple hits\r\n SearchBean search = new SearchBean();\r\n search.setQuery(\"j\");\r\n search.setLocation(\"Virginia Beach\");\r\n search.parseQuery();\r\n assertTrue(search.isValid());\r\n \r\n // Look for data with a \"j\" for comparison\r\n int jCount = 0;\r\n for (int i = 0; i < symbols.getMonths().length; i++) {\r\n if (symbols.getMonths()[i].toLowerCase().indexOf(\"j\") > -1 ||\r\n symbols.getShortMonths()[i].toLowerCase().indexOf(\"j\") > -1) {\r\n ++jCount;\r\n }\r\n }\r\n assertTrue(jCount > 0);\r\n \r\n String queryString = SearchUtils.generateProjectQueryString(search, UserUtils.createGuestUser().getId(), -1, null);\r\n assertNotNull(queryString);\r\n \r\n // (approved:1)\r\n // AND (guests:1)\r\n // AND (closed:0)\r\n // AND (website:0)\r\n // AND (\"j\"^20 OR j^15 OR j*^4) AND (location:(\"virginia beach\"^30))\r\n \r\n Query query = parser.parse(queryString);\r\n Hits hits = getSnowballSearcher().search(query);\r\n assertTrue(hits.length() == jCount);\r\n }\r\n \r\n {\r\n // Make sure alternate locations do not yield any hits\r\n SearchBean search = new SearchBean();\r\n search.setQuery(symbols.getMonths()[0]);\r\n search.setLocation(\"Norfolk\");\r\n search.parseQuery();\r\n \r\n String queryString = SearchUtils.generateProjectQueryString(search, UserUtils.createGuestUser().getId(), -1, null);\r\n \r\n Query query = parser.parse(queryString);\r\n Hits hits = getSnowballSearcher().search(query);\r\n assertTrue(hits.length() == 0);\r\n }\r\n \r\n {\r\n // Make sure locations as query terms do not yield any hits\r\n SearchBean search = new SearchBean();\r\n search.setQuery(\"Virginia Beach\");\r\n search.setLocation(\"Virginia Beach\");\r\n search.parseQuery();\r\n \r\n String queryString = SearchUtils.generateProjectQueryString(search, UserUtils.createGuestUser().getId(), -1, null);\r\n \r\n Query query = parser.parse(queryString);\r\n Hits hits = getSnowballSearcher().search(query);\r\n assertTrue(hits.length() == 0);\r\n }\r\n }","public WorldUps.UQuery getQueries(int index) {\n return queries_.get(index);\n }","private void performNewQuery(){\n\n // update the label of the Activity\n setLabelForActivity();\n // reset the page number that is being used in queries\n pageNumberBeingQueried = 1;\n // clear the ArrayList of Movie objects\n cachedMovieData.clear();\n // notify our MovieAdapter about this\n movieAdapter.notifyDataSetChanged();\n // reset endless scroll listener when performing a new search\n recyclerViewScrollListener.resetState();\n\n /*\n * Loader call - case 3 of 3\n * We call loader methods as we have just performed reset of the data set\n * */\n // initiate a new query\n manageLoaders();\n\n }","private void searchforResults() {\n\n List<String> queryList = new SavePreferences(this).getStringSetPref();\n if(queryList != null && queryList.size() > 0){\n Log.i(TAG, \"Searching for results \" + queryList.get(0));\n Intent searchIntent = new Intent(Intent.ACTION_WEB_SEARCH);\n searchIntent.addFlags(Intent.FLAG_ACTIVITY_NEW_TASK);\n searchIntent.putExtra(SearchManager.QUERY, queryList.get(0));\n this.startActivity(searchIntent);\n }\n }","public void actionPerformed(ActionEvent e) {\n displayInfoText(\" \");\n // Turn the search string into a Query\n String queryString = queryWindow.getText().toLowerCase().trim();\n query = new Query(queryString);\n // Take relevance feedback from the user into account (assignment 3)\n // Check which documents the user has marked as relevant.\n if (box != null) {\n boolean[] relevant = new boolean[box.length];\n for (int i = 0; i < box.length; i++) {\n if (box[i] != null)\n relevant[i] = box[i].isSelected();\n }\n query.relevanceFeedback(results, relevant, engine);\n }\n // Search and print results. Access to the index is synchronized since\n // we don't want to search at the same time we're indexing new files\n // (this might corrupt the index).\n long startTime = System.currentTimeMillis();\n synchronized (engine.indexLock) {\n results = engine.searcher.search(query, queryType, rankingType);\n }\n long elapsedTime = System.currentTimeMillis() - startTime;\n // Display the first few results + a button to see all results.\n //\n // We don't want to show all results directly since the displaying itself\n // might take a long time, if there are many results.\n if (results != null) {\n displayResults(MAX_RESULTS, elapsedTime / 1000.0);\n } else {\n displayInfoText(\"Found 0 matching document(s)\");\n\n if (engine.speller != null) {\n startTime = System.currentTimeMillis();\n SpellingOptionsDialog dialog = new SpellingOptionsDialog(50);\n String[] corrections = engine.speller.check(query, 10);\n elapsedTime = System.currentTimeMillis() - startTime;\n System.err.println(\"It took \" + elapsedTime / 1000.0 + \"s to check spelling\");\n if (corrections != null && corrections.length > 0) {\n String choice = dialog.show(corrections, corrections[0]);\n if (choice != null) {\n queryWindow.setText(choice);\n queryWindow.grabFocus();\n\n this.actionPerformed(e);\n }\n }\n }\n }\n }","public List<Recipe> search(String queryText, Category category, CookingMethod cookingMethod);","private void search(SearchRequest request) {\r\n\t\tif(request == null)return;\r\n\t\tList<Record> results = handler.search(request);\r\n\t\tlist.show(results);\r\n\t\tpanInfo.setNumRec(results.size());\r\n\t\tpanInfo.setTotalAmt(Record.sumBalance(results));\r\n\t}","public void testUsingQueriesFromQueryManger(){\n\t\tSet<String> names = testDataMap.keySet();\n\t\tUtils.prtObMess(this.getClass(), \"atm query\");\n\t\tDseInputQuery<BigDecimal> atmq = \n\t\t\t\tqm.getQuery(new AtmDiot());\n\t\tMap<String, ComplexQueryResult<BigDecimal>> bdResult = \n\t\t\t\tatmq.get(names, 1, TimeUnit.SECONDS);\n\t\tCollectionsStaticMethods.prtMapItems(bdResult);\n\n\t\tUtils.prtObMess(this.getClass(), \"vol query\");\n\t\tDseInputQuery<BigDecimal> volq = \n\t\t\t\tqm.getQuery(new VolDiotForTest());\n\t\tMap<String, ComplexQueryResult<BigDecimal>> dbResult = \n\t\t\t\tvolq.get(names, 1, TimeUnit.SECONDS);\n\t\tCollectionsStaticMethods.prtMapItems(dbResult);\n\t\n\t\tUtils.prtObMess(this.getClass(), \"integer query\");\n\t\tDseInputQuery<BigDecimal> strikeq = \n\t\t\t\tqm.getQuery(new StrikeDiotForTest());\n\t\tMap<String, ComplexQueryResult<BigDecimal>> strikeResult = \n\t\t\t\tstrikeq.get(names, 1, TimeUnit.SECONDS);\n\t\tCollectionsStaticMethods.prtMapItems(strikeResult);\n\t\n\t}","PaginatedSearchResponseModel findAllPostsForUser(Party partyBean, Pageable page);","@Override\r\n\t\t\tpublic double matchingItems(Query query) {\n\t\t\t\treturn 0;\r\n\t\t\t}","List<ShipmentInfoPODDTO> search(String query);","@Override\n\t\t\tpublic void run() {\n\n\t\t\t\tpostParameters[0] = new PostParameter(\"keyword\", searchKeyword);\n\t\t\t\tpostParameters[1] = new PostParameter(\"university\", university);\n\t\t\t\tpostParameters[2] = new PostParameter(\"page\", Integer.toString(requestTime));\n\t\t\t\t\n\t\t\t\tjsonString = HttpUtil.httpRequest(HttpUtil.USER_SEARCHBOOKS, postParameters, HttpUtil.POST);\n\t\t\t\tif (jsonString != null) {\t\t\t\t\t\n\t\t\t\t\tMessage msg = handler.obtainMessage();\n\t\t\t\t\tmsg.what = what;\n\t\t\t\t\thandler.sendMessage(msg);\t\t\t\t\t\n\t\t\t\t}\n\t\t\t\telse{\n\t\t\t\t\thandler.sendEmptyMessage(-1);\n\t\t\t\t}\n\t\t\t}","default List<SearchResult> search(String tvShowName, int season, int episode, Quality quality) {\n return search(new SearchQuery(tvShowName, season, episode, quality));\n }","public void searchAndWriteQueryResultsToOutput() {\n\n List<String> queryList = fu.textFileToList(QUERY_FILE_PATH);\n\n for (int queryID = 0; queryID < queryList.size(); queryID++) {\n String query = queryList.get(queryID);\n // ===================================================\n // 4. Sort the documents by the BM25 scores.\n // ===================================================\n HashMap<String, Double> docScore = search(query);\n List<Map.Entry<String, Double>> rankedDocList =\n new LinkedList<Map.Entry<String, Double>>(docScore.entrySet());\n Collections.sort(rankedDocList, new MapComparatorByValues());\n\n // ===================================================\n // 5. Write Query Results to output\n // =================================================== \n String outputFilePath =\n RANKING_RESULTS_PATH + \"queryID_\" + (queryID + 1) + \".txt\";\n StringBuilder toOutput = new StringBuilder();\n // display results in console\n System.out.println(\"Found \" + docScore.size() + \" hits.\");\n int i = 0;\n for (Entry<String, Double> scoreEntry : rankedDocList) {\n if (i >= NUM_OF_RESULTS_TO_RETURN)\n break;\n String docId = scoreEntry.getKey();\n Double score = scoreEntry.getValue();\n String resultLine =\n (queryID + 1) + \" Q0 \" + docId + \" \" + (i + 1) + \" \" + score + \" BM25\";\n toOutput.append(resultLine);\n toOutput.append(System.getProperty(\"line.separator\"));\n System.out.println(resultLine);\n i++;\n }\n fu.writeStringToFile(toOutput.toString(), outputFilePath);\n }\n }","private Collection<Record> handleRequest(SearchRequest request) {\n\t\tCollection<Record> resultSet = getResults(request.getQuery());\n\t\treturn resultSet;\n\t}","TSearchQuery prepareSearchQuery(SearchQueryDefinitionAPI searchQueryDefinition);","public Map<String, String> directQuoteSearch (String q, String contentOrTitle) throws IOException, ParseException{\n\n\t\t\n\t\tif (contentOrTitle.equals(\"content\")){\n\t\t\tcontentOrTitle=field;\n\t\t} else if (contentOrTitle.equals(\"title\")){\n\t\t\tcontentOrTitle=title;\n\t\t}\n\t\t\n\t\tIndexReader reader = DirectoryReader.open(FSDirectory.open(Paths.get(index)));\n\t\tIndexSearcher searcher = new IndexSearcher(reader);\n\t\tboolean raw = false;\n\t\tint repeat = 0;\n\n\t\tfinal List<String> stopWords = Arrays.asList();\n\t\tfinal CharArraySet stopSet = new CharArraySet(stopWords, true);\n\n\t\tAnalyzer analyzer = new StandardAnalyzer(stopSet);\n\t\tAnalyzingQueryParser parser = new AnalyzingQueryParser(contentOrTitle, analyzer);\n\t\t\n\n\t\t\n\t\tString[] items = q.split(\" \");\n\t\tList<String> itemList = Arrays.asList(items);\n\t\tQuery query=null;\n\t\t\n\t\t\n\t\tif (q.equals(\"\")){\n\t\t\tSystem.out.println(\"no input\");\n\t\t\t\n\t\t} else {\n\t\t\tquery = parser.parse(q);\n\n\t\t}\n\n\t\t\n\t\t\n\t\tBufferedReader in = null;\n\t\tin = new BufferedReader(new InputStreamReader(System.in, StandardCharsets.UTF_8));\n\n\t\tif (repeat > 0) { // repeat & time as benchmark\n\t\t\tDate start = new Date();\n\t\t\tfor (int i = 0; i < repeat; i++) {\n\t\t\t\tsearcher.search(query, 100);\n\t\t\t}\n\t\t\tDate end = new Date();\n\t\t\tSystem.out.println(\"Time: \"+(end.getTime()-start.getTime())+\"ms\");\n\t\t}\n\n\t\treturn doPagingSearch(in, searcher, query, hitsPerPage, raw, true);\n\t}","public Map<String, DataModel> getQuery() {\n if (queries == null) {\n queries = FxSharedUtils.getMappedFunction(new FxSharedUtils.ParameterMapper<String, DataModel>() {\n @Override\n public DataModel get(Object key) {\n try {\n final FxResultSet result = EJBLookup.getSearchEngine().search((String) key, 0, -1, null);\n return new FxResultSetDataModel(result);\n } catch (FxApplicationException e) {\n throw e.asRuntimeException();\n }\n }\n }, true);\n }\n return queries;\n }","public PostingsList getPostings( String token ) {\n PostingsList post = new PostingsList();\n if(this.index.containsKey(token))\n post = (this.index.get(token)).clone();\n /*System.err.println(\"start search...\");\n // Read JSON file associated to token and return it as a postingslist\n String filename = \"postings/t\"+hash(token)+\".json\";\n PostingsList post = new PostingsList();\n try(Reader reader = new FileReader(filename)){\n post = (new Gson()).fromJson(reader, PostingsList.class);\n } catch (IOException e) {\n e.printStackTrace();\n }*/\n return post;\n }","public static void main(String[] args) throws Exception {\n\n IndexManager indexManager = new IndexManager();\n Query query = new TermQuery(new Term(\"name\", \"求职\"));\n indexManager.excQuery(query);\n\n }","public void doSearch(String query)\n \t{\n \t\tlistener.onQueryTextSubmit(query);\n \t}","@Override\n public Set<Restaurant> getMatches(String queryString) {\n\n /* Setup grammar listener */\n CharStream stream = new ANTLRInputStream(queryString);\n QueryLexer lexer = new QueryLexer(stream);\n TokenStream tokens = new CommonTokenStream(lexer);\n QueryParser parser = new QueryParser(tokens);\n ParseTree tree = parser.root();\n ParseTreeWalker walker = new ParseTreeWalker();\n\n // Setup custom walker\n QueryCreator creator = new QueryCreator();\n walker.walk(creator, tree);\n\n Set<Restaurant> matches = new HashSet<Restaurant>();\n RestaurantHandle rH = creator.getHandle();\n Expression expTree = creator.getExpression();\n\n // Look through every restaurant, if one matches query add it to the set\n for (Restaurant r : this.restaurantMap.values()) {\n rH.setRestaurant(r);\n if (expTree.eval()) {\n matches.add(r);\n }\n }\n\n return matches;\n }"],"string":"[\n \"private void queryPosts() {\\n ParseQuery<OutfitPost> query = ParseQuery.getQuery(OutfitPost.class);\\n // only include data referred by user key\\n query.include(OutfitPost.KEY_USER);\\n query.whereEqualTo(OutfitPost.KEY_USER, ParseUser.getCurrentUser());\\n // limit query to latest 20 items\\n query.setLimit(20);\\n // order posts by creation date (newest first)\\n query.addDescendingOrder(OutfitPost.KEY_CREATED_KEY);\\n // start an asynchronous call for posts\\n query.findInBackground(new FindCallback<OutfitPost>() {\\n @Override\\n public void done(List<OutfitPost> posts, ParseException e) {\\n // check for errors\\n if (e != null) {\\n Log.e(TAG, \\\"Issue with getting posts\\\", e);\\n return;\\n }\\n // Save oldest post in query for loading more posts\\n if (posts.size() > 0) {\\n oldestPost = posts.get(posts.size() - 1).getCreatedAt();\\n }\\n // update adapter with posts list\\n adapter.clear();\\n adapter.addAll(posts);\\n }\\n });\\n }\",\n \"private void termQuerySearch(String[] terms) {\\n for (String term : terms) {\\n LinkedList<TermPositions> postingLists = indexMap.get(analyzeTerm(term));\\n if (postingLists != null) {\\n for (TermPositions matches : postingLists) {\\n double score = (double) 1 + Math.log((double) matches.getPositionList().size()) *\\n Math.log((double) N / (double) postingLists.size());\\n resultsCollector.add(new DocCollector(matches.getDocId(), score));\\n }\\n }\\n }\\n }\",\n \"CampusSearchQuery generateQuery();\",\n \"WorldUps.UQuery getQueries(int index);\",\n \"@Override\\n public boolean onQueryTextSubmit(String query) {\\n prepareBooks(engine.search(query.toLowerCase(),filter));\\n return false;\\n }\",\n \"public PostingsList ranked_query(Query query, double w, double idf_threshold){\\n long startTime = System.nanoTime();\\n PostingsList result = new PostingsList();\\n\\n // Obtain union of terms above idf threshold if indexElimination is true\\n // (Set idf_threshold to zero to disable this feature)\\n Set<String> termsToConsider = this.queryTermsConsidered(query, idf_threshold);\\n result = this.union_query(query, termsToConsider);\\n //System.err.println(\\\"Size of result is \\\" + result.size());\\n\\n long estimatedTime = (System.nanoTime() - startTime)/1000000;\\n System.err.println(\\\"* Union took: \\\" + estimatedTime);\\n\\n\\n /*\\n * 2) Iterate over PostingsEntries and build the solution\\n */\\n startTime = System.nanoTime();\\n // Required when iterating over a PostingsList\\n PostingsEntry postEnt = new PostingsEntry();\\n // Number of documents in the collection\\n double nDocs = this.docIDs.size();\\n // Weight of a query vector coefficient\\n double w_query_term;\\n // Document tf-idf variables\\n double termFrequency_doc, documentFrequency_doc, w_doc_term;\\n\\n for(String term : termsToConsider){\\n // Obtain idf of the term\\n documentFrequency_doc = Math.log(nDocs/new Double(this.idfMap.get(term)));\\n\\n // Obtain weight of the term\\n w_query_term = query.weights.get(term);\\n // Iterate over all documents containing the term and update the score(q,d)\\n Iterator<PostingsEntry> it_d = result.iterator();\\n while(it_d.hasNext()){\\n postEnt = it_d.next();\\n if (this.tfMap.get(postEnt.docID).containsKey(term)){\\n termFrequency_doc = this.tfMap.get(postEnt.docID).get(term);\\n w_doc_term = documentFrequency_doc*termFrequency_doc;\\n postEnt.score += w_query_term*w_doc_term;\\n }\\n }\\n }\\n estimatedTime = (System.nanoTime() - startTime)/1000000;\\n System.err.println(\\\"* Building solution took: \\\" + estimatedTime);\\n\\n /*\\n * 3) Normalize the scores\\n */\\n startTime = System.nanoTime();\\n Iterator<PostingsEntry> it = result.iterator();\\n while(it.hasNext()){\\n postEnt = it.next();\\n postEnt.score /= (new Double(this.docLengths.get(\\\"\\\"+postEnt.docID)));//(Math.sqrt(postEnt.norm2));\\n postEnt.score = w * postEnt.score + (1-w) * quality(postEnt.docID);\\n }\\n estimatedTime = (System.nanoTime() - startTime)/1000000;\\n System.err.println(\\\"* Normalizing took: \\\" + estimatedTime);\\n\\n /*\\n * 4) Sort the resulting solution\\n */\\n startTime = System.nanoTime();\\n result.sort();\\n estimatedTime = (System.nanoTime() - startTime)/1000000;\\n System.err.println(\\\"* Sorting took: \\\" + estimatedTime);\\n\\n return result;\\n }\",\n \"public List<Post> search(PostCriteria criteria, int page, int size);\",\n \"public void search(Indexer indexer, CityIndexer cityIndexer, Ranker ranker, String query, boolean withSemantic, ArrayList<String> chosenCities, ObservableList<String> citiesByTag, boolean withStemming, String saveInPath, String queryId, String queryDescription) {\\n String[] originalQueryTerms = query.split(\\\" \\\");\\n String originQuery = query;\\n docsResults = new HashMap<>();\\n parser = new Parse(withStemming, saveInPath, saveInPath);\\n HashSet<String> docsOfChosenCities = new HashSet<>();\\n query = \\\"\\\" + query + queryDescription;\\n HashMap<String, Integer> queryTerms = parser.parseQuery(query);\\n HashMap<String, ArrayList<Integer>> dictionary = indexer.getDictionary();\\n if (!withStemming){\\n setDocsInfo(saveInPath + \\\"\\\\\\\\docsInformation.txt\\\");\\n }\\n else{\\n setDocsInfo(saveInPath + \\\"\\\\\\\\docsInformation_stemming.txt\\\");\\n }\\n\\n\\n //add semantic words of each term in query to 'queryTerms'\\n if(withSemantic) {\\n HashMap<String,ArrayList<String>> semanticWords = ws.connectToApi(originQuery);\\n }\\n\\n //give an ID to query if it's a regular query (not queries file)\\n if(queryId.equals(\\\"\\\")){\\n queryId = \\\"\\\" + Searcher.queryID;\\n Searcher.queryID++;\\n }\\n\\n String postingDir;\\n if (!withStemming) {\\n postingDir = \\\"\\\\\\\\indexResults\\\\\\\\postingFiles\\\";\\n } else {\\n postingDir = \\\"\\\\\\\\indexResults\\\\\\\\postingFiles_Stemming\\\";\\n }\\n int pointer = 0;\\n\\n //find docs that contain the terms in the query in their text\\n HashMap<String, Integer> queryTermsIgnoreCase = new HashMap<>();\\n for (String term : queryTerms.keySet()) {\\n String originTerm = term;\\n if (!dictionary.containsKey(term.toUpperCase()) && !dictionary.containsKey(term.toLowerCase())) {\\n continue;\\n }\\n if(dictionary.containsKey(term.toLowerCase())){\\n term = term.toLowerCase();\\n }\\n else {\\n term = term.toUpperCase();\\n }\\n queryTermsIgnoreCase.put(term,queryTerms.get(originTerm));\\n pointer = dictionary.get(term).get(2);\\n String chunk = (\\\"\\\" + term.charAt(0)).toUpperCase();\\n\\n //get the relevant line from posting file\\n BufferedReader br = null;\\n try {\\n br = new BufferedReader(new FileReader(new File(saveInPath + postingDir + \\\"\\\\\\\\posting_\\\" + chunk + \\\".txt\\\")));\\n String line = \\\"\\\";\\n int i = 1;\\n while ((line = (br.readLine())) != null) {\\n if (i == pointer) {\\n break;\\n }\\n i++;\\n }\\n br.close();\\n\\n //get docs from posting line and add them to the data structure 'docsResults'\\n if(line != null) {\\n findDocsFromLine(line, term);\\n }\\n\\n } catch (IOException e) {\\n e.printStackTrace();\\n }\\n }\\n\\n //find docs that contain the chosen cities in their text\\n for (String cityTerm : chosenCities) {\\n if (!dictionary.containsKey(cityTerm) && !dictionary.containsKey(cityTerm.toLowerCase())) {\\n continue;\\n }\\n if(dictionary.containsKey(cityTerm.toLowerCase())){\\n cityTerm = cityTerm.toLowerCase();\\n }\\n pointer = dictionary.get(cityTerm).get(2);\\n // char chunk = indexer.classifyToPosting(term).charAt(0);\\n String chunk = (\\\"\\\" + cityTerm.charAt(0)).toUpperCase();\\n\\n //get the relevant line from posting file\\n BufferedReader br = null;\\n try {\\n br = new BufferedReader(new FileReader(new File(saveInPath + postingDir + \\\"\\\\\\\\posting_\\\" + chunk + \\\".txt\\\")));\\n String line = \\\"\\\";\\n int i = 1;\\n while ((line = (br.readLine())) != null) {\\n if (i == pointer) {\\n break;\\n }\\n i++;\\n }\\n br.close();\\n\\n //get docs from posting line and add them to the data structure 'docsOfChosenCities'\\n String docs = line.substring(0, line.indexOf(\\\"[\\\") - 1); //get 'docsListStr'\\n String[] docsArr = docs.split(\\\";\\\");\\n for (String docInfo : docsArr) {\\n String doc = docInfo.substring(0, docInfo.indexOf(\\\": \\\"));\\n while(doc.charAt(0) == ' '){\\n doc = doc.substring(1);\\n }\\n docsOfChosenCities.add(doc);\\n }\\n } catch (IOException e) {\\n e.printStackTrace();\\n }\\n }\\n\\n //find docs that contain the chosen cities in their city tag\\n if(!chosenCities.isEmpty()){\\n for (String cityDicRec: chosenCities) {\\n //get pointer to posting from cityDictionary\\n try {\\n pointer = cityIndexer.getCitiesDictionary().get(cityDicRec);\\n } catch (NumberFormatException e) {\\n e.printStackTrace();\\n }\\n //get the relevant line from posting file\\n BufferedReader br = null;\\n try {\\n br = new BufferedReader(new FileReader(new File(saveInPath + \\\"\\\\\\\\cityIndexResults\\\" + \\\"\\\\\\\\posting_city\\\" + \\\".txt\\\")));\\n String line = \\\"\\\";\\n int i = 1;\\n while ((line = (br.readLine())) != null) {\\n if (i == pointer) {\\n break;\\n }\\n i++;\\n }\\n br.close();\\n\\n //get docs from posting line and add them to the data structure 'docsOfChosenCities'\\n String docs = line.substring(line.indexOf(\\\"[\\\") + 1, line.indexOf(\\\"]\\\")); //get 'docsListStr'\\n String[] docsArr = docs.split(\\\"; \\\");\\n for (String doc : docsArr) {\\n docsOfChosenCities.add(doc);\\n }\\n } catch (IOException e) {\\n e.printStackTrace();\\n }\\n }\\n }\\n\\n\\n ranker.rank(docsResults, docsOfChosenCities, queryTermsIgnoreCase, dictionary, docsInfo,entities, queryId);\\n }\",\n \"private static void RankedQueryMode(DiskIndexWriter diskWriter, DiskPositionalIndex disk_posIndex) throws IOException, ClassNotFoundException, InstantiationException, IllegalAccessException {\\n\\n if (query.equals(\\\"q\\\")) {\\n\\n System.exit(0);\\n }\\n\\n List<String> word = new ArrayList();\\n String[] query_array = query.split(\\\"\\\\\\\\s+\\\");\\n TokenProcessor processor = new NewTokenProcessor();\\n\\n for (int i = 0; i < query_array.length; i++) {\\n word.add(processor.processToken(query_array[i]).get(0));\\n }\\n\\n StrategyFactory sf = new StrategyFactory();\\n StrategyInterface strategy = sf.execute(rankedOption);\\n\\n //maps postings to accumulator value\\n HashMap<Integer, Doc_accum> postingMap = new HashMap<Integer, Doc_accum>();\\n\\n PriorityQueue<Doc_accum> queue = new PriorityQueue<>(Collections.reverseOrder());\\n\\n List<Posting> postings = new ArrayList<>();\\n List<Doc_accum> results = new ArrayList<>();\\n\\n for (String term : word) {\\n\\n postings = disk_posIndex.getPosting_noPos(term);\\n for (Posting p : postings) { //for each document in the postings list\\n double t_fd = p.getT_fd();\\n double d_ft = p.getD_ft();\\n double w_qt = strategy.calculate_wqt(N, d_ft);\\n double accum = 0;\\n double w_dt = strategy.get_wdt(t_fd, disk_posIndex, p.getDocumentId());\\n\\n //pairs (Ranked_posting, accumulator factor)\\n if (postingMap.containsKey(p.getDocumentId())) {\\n accum = postingMap.get(p.getDocumentId()).getAccumulator();\\n accum += (w_qt * w_dt);\\n postingMap.replace(p.getDocumentId(), new Doc_accum(p, accum)); //replaces old accum value\\n\\n } else {\\n accum += (w_qt * w_dt);\\n postingMap.put(p.getDocumentId(), new Doc_accum(p, accum));\\n }\\n }\\n\\n }\\n\\n for (Integer p : postingMap.keySet()) {\\n Doc_accum doc_temp = postingMap.get(p);\\n double accum = doc_temp.getAccumulator(); //gets accum associated with doc\\n\\n if (accum > 0) {\\n //search for each p's Ld factor in docWeights.bin\\n double l_d = strategy.calculate_Ld(disk_posIndex, doc_temp.getPosting().getDocumentId());\\n\\n accum /= l_d;\\n doc_temp.setAccumulator(accum);\\n }\\n\\n queue.add(postingMap.get(p));\\n\\n }\\n\\n //returns top K=10 results \\n int topK = 50;\\n\\n while ((results.size() < topK) && queue.size() > 0) {\\n\\n results.add(queue.poll()); //gets the posting acc pair and returns only posting\\n\\n }\\n\\n display_RankedResults(results);\\n\\n }\",\n \"public interface SearchQuerySet extends QuerySet\\n{\\n\\n // for AbstractSearch\\n public static final int STAT_MODELS = 1;\\n public static final int STAT_CLUSTERS = 2;\\n public static final int STAT_GENOMES = 4;\\n public static final int STAT_MODEL_CLUSTERS = 8;\\n\\n public String getStatsById(Collection data);\\n public String getStatsByQuery(String query);\\n public String getStatsById(Collection data,int stats);\\n public String getStatsByQuery(String query,int stats);\\n \\n // for BlastSearch\\n public String getBlastSearchQuery(Collection dbNames, Collection keys, KeyTypeUser.KeyType keyType);\\n \\n //for ClusterIDSearch\\n public String getClusterIDSearchQuery(Collection input, int limit, int[] DBs, KeyTypeUser.KeyType keyType);\\n \\n // for ClusterNameSearch\\n public String getClusterNameSearchQuery(Collection input, int limit, int[] DBs, KeyTypeUser.KeyType keyType);\\n \\n // for DescriptionSearch\\n public String getDescriptionSearchQuery(Collection input, int limit, int[] DBs, KeyTypeUser.KeyType keyType);\\n \\n // for GoSearch \\n public String getGoSearchQuery(Collection input, int limit, KeyTypeUser.KeyType keyType);\\n \\n // for GoTextSearch\\n public String getGoTextSearchQuery(Collection input, int limit, KeyTypeUser.KeyType keyType);\\n \\n // for IdSearch\\n public String getIdSearchQuery(Collection input, int limit, int[] DBs, KeyTypeUser.KeyType keyType);\\n \\n // for QueryCompSearch\\n public String getQueryCompSearchQuery(String comp_id, String status, KeyTypeUser.KeyType keyType);\\n \\n // for QuerySearch\\n public String getQuerySearchQuery(String queries_id, KeyTypeUser.KeyType keyType); \\n \\n // for SeqModelSearch\\n public String getSeqModelSearchQuery(Collection model_ids, KeyTypeUser.KeyType keyType);\\n \\n // for UnknowclusterIdSearch\\n public String getUnknownClusterIdSearchQuery(int cluster_id, KeyTypeUser.KeyType keyType);\\n \\n // for ProbeSetSearch\\n public String getProbeSetSearchQuery(Collection input, int limit, KeyTypeUser.KeyType keyType);\\n \\n // for ProbeSetKeySearch\\n public String getProbeSetKeySearchQuery(Collection input, int limit, KeyTypeUser.KeyType keyType);\\n \\n // for QueryTestSearch\\n public String getQueryTestSearchQuery(String query_id, String version, String genome_id);\\n \\n // for QueryStatsSearch\\n public String getQueryStatsSearchQuery(List query_ids,List DBs);\\n \\n // for PskClusterSearch\\n public String getPskClusterSearchQuery(int cluster_id,KeyTypeUser.KeyType keyType);\\n \\n // for ClusterCorrSearch\\n public String getClusterCorrSearchQuery(int cluster_id, int psk_id, KeyTypeUser.KeyType keyType);\\n \\n // for UnknownGenesSearch\\n public String getUnknownGenesSearchQuery(Collection sources, KeyTypeUser.KeyType keyType);\\n \\n}\",\n \"public Query( String queryString ) {\\r\\n\\tStringTokenizer tok = new StringTokenizer( queryString );\\r\\n\\twhile ( tok.hasMoreTokens() ) {\\r\\n\\t terms.add( tok.nextToken() );\\r\\n\\t weights.add( new Double(1) );\\r\\n\\t} \\r\\n }\",\n \"Query query();\",\n \"public PageList query(String squadName, String axiser, String cubers, String followers,\\n String investors, String status, Date gmtCreate, Date gmtModify,\\n int pageSize, int pageNum) throws DataAccessException;\",\n \"public CheckOutQ() {\\r\\n\\t\\tq = new LinkedList<Person>();\\r\\n\\t\\tmaxQ = 0;\\r\\n\\t}\",\n \"public PostingsList phrase_query(Query query){\\n\\n LinkedList<PostingsList> listQueriedPostings = new LinkedList<PostingsList>();\\n // List with postings corresponding to the queries\\n for (int i = 0; i<query.size(); i++){\\n // If any query has zero matches, return 0 results\\n //if(!(new File(\\\"postings/t\\\"+hash(query.terms.get(i))+\\\".json\\\")).exists()){\\n if (!this.index.containsKey(query.terms.get(i))){\\n return null;\\n }\\n // Otherwise store postings in the list\\n listQueriedPostings.add(this.getPostings(query.terms.get(i)));\\n }\\n\\n PostingsList result = new PostingsList();\\n result = listQueriedPostings.get(0);\\n\\n // In case only one word is queried\\n if (listQueriedPostings.size() == 1){\\n return result;\\n }\\n\\n // Apply algorithm as many times as words in the query\\n for(int i = 1; i < listQueriedPostings.size(); i++){\\n result = phrase_query(result, listQueriedPostings.get(i));\\n if (result.isEmpty()){\\n return null;\\n }\\n }\\n return result;\\n }\",\n \"private static void BooleanQueryMode(DiskIndexWriter diskWriter, DiskPositionalIndex disk_posIndex) throws ClassNotFoundException, InstantiationException, IllegalAccessException {\\n if (!specialQueries(query)) {\\n //newCorpus = false; \\n BooleanQueryParser bParser = new BooleanQueryParser();\\n QueryComponent qComponent = bParser.parseQuery(query);\\n postings = qComponent.getPostings(disk_posIndex);\\n\\n if (postings.isEmpty()) {\\n GUI.JListModel.clear();\\n GUI.ResultsLabel.setText(\\\"\\\");\\n clickList = false;\\n\\n String notFound = \\\"Your search '\\\" + query + \\\"' is not found in any documents\\\";\\n GUI.ResultsLabel.setText(notFound);\\n\\n } else {\\n clickList = true;\\n\\n //clears list and repopulates it \\n String docInfo;\\n\\n GUI.JListModel.clear();\\n GUI.ResultsLabel.setText(\\\"\\\");\\n\\n for (Posting p : postings) {\\n if (queryMode) {\\n corpus.getDocument(p.getDocumentId()).getContent();\\n }\\n docInfo = corpus.getDocument(p.getDocumentId()).getTitle();\\n //docInfo = corpus.getDocument(p.getDocumentId()).getFileName().toString();\\n GUI.JListModel.addElement(docInfo);\\n\\n }\\n GUI.ResultsLabel.setText(\\\"Total Documents Found: \\\" + postings.size());\\n }\\n\\n }\\n\\n //GUI.SearchBarTextField.setText(\\\"Enter a new search or 'q' to exit\\\");\\n GUI.SearchBarTextField.selectAll();\\n\\n }\",\n \"public void search() {\\n String q = this.query.getText();\\n String cat = this.category.getValue();\\n if(cat.equals(\\\"Book\\\")) {\\n searchBook(q);\\n } else {\\n searchCharacter(q);\\n }\\n }\",\n \"private void queryIndex() {\\n if (predicate == TruePredicate.INSTANCE) {\\n return;\\n }\\n\\n // get indexes\\n MapService mapService = nodeEngine.getService(SERVICE_NAME);\\n MapServiceContext mapServiceContext = mapService.getMapServiceContext();\\n Indexes indexes = mapServiceContext.getMapContainer(name).getIndexes();\\n // optimize predicate\\n QueryOptimizer queryOptimizer = mapServiceContext.getQueryOptimizer();\\n predicate = queryOptimizer.optimize(predicate, indexes);\\n\\n Set<QueryableEntry> querySet = indexes.query(predicate);\\n if (querySet == null) {\\n return;\\n }\\n\\n List<Data> keys = null;\\n for (QueryableEntry e : querySet) {\\n if (keys == null) {\\n keys = new ArrayList<Data>(querySet.size());\\n }\\n keys.add(e.getKeyData());\\n }\\n\\n hasIndex = true;\\n keySet = keys == null ? Collections.<Data>emptySet() : InflatableSet.newBuilder(keys).build();\\n }\",\n \"private void executeQuery1(PersistenceManager pm) {\\n Query query = pm.newQuery(Book.class, \\\"pages > 300\\\");\\n Collection results = (Collection)query.execute();\\n printCollection(\\\"Books with more than 300 pages:\\\", results.iterator());\\n query.closeAll();\\n }\",\n \"private void montaQuery(Publicacao object, Query q) {\\t\\t\\n\\t}\",\n \"protected void queryPosts() {\\n ParseQuery<Post> query = ParseQuery.getQuery(Post.class);\\n //get all the post objects from the database\\n query.include(Post.KEY_USER);\\n //set the limit to 20 posts being retrieved\\n query.setLimit(POSTS_QUERY_LIMIT);\\n\\n query.addDescendingOrder(Post.KEY_CREATED_KEY);\\n\\n query.findInBackground(new FindCallback<Post>() {\\n @Override\\n public void done(List<Post> posts, ParseException e) {\\n // e == null if success\\n if (e != null) {\\n Log.e(TAG, \\\"Issue with getting posts\\\", e);\\n return;\\n }\\n\\n for (Post post : posts) {\\n Log.i(TAG, \\\"Post: \\\" + post.getDescription() + \\\", username: \\\" + post.getUser().getUsername());\\n }\\n adapter.clear();\\n allPosts.addAll(posts);\\n adapter.notifyDataSetChanged();\\n }\\n });\\n }\",\n \"public void testAdvancedQuery() {\\n\\t\\t//manager.advancedQuery(ElasticIndex.analyzed, \\\"metropolitan areas\\\", \\\"sports clubs\\\");\\n\\t\\t//manager.advancedQuery(ElasticIndex.analyzed, \\\"\\\", \\\"Award\\\");\\n\\n\\t//manager.advancedQuery(ElasticIndex.analyzed,\\\"american actor\\\", \\\"list of movies starring Sean Connery\\\");\\n//\\tmanager.categorySearch(\\\"Sportspeople\\\", \\\"tennis\\\",ElasticIndex.analyzed,30);\\n\\t//manager.advancedQuery(ElasticIndex.analyzed,\\\"Broadway musicals\\\", \\\"Grammy Award\\\");\\n\\t//manager.advancedQuery(ElasticIndex.analyzed,\\\"musical movies\\\", \\\"Tony Award\\\");\\n\\t//manager.advancedQuery(ElasticIndex.analyzed,\\\"Top level football leagues\\\", \\\"teams\\\");\\n\\t//manager.advancedQuery(ElasticIndex.analyzed,\\\"american movies\\\", \\\"directed by Woody Allen\\\");\\n\\t//manager.advancedQuery(ElasticIndex.analyzed,\\\"United states\\\", \\\"professional sports teams\\\");\\n\\t\\t//manager.advancedQuery(\\\"musical movies\\\", \\\"tony award\\\");\\n\\t\\t//manager.advancedQuery(\\\"grammy\\\", \\\"best album in 2012\\\"); \\n\\t\\t//manager.advancedQuery(\\\"american movies\\\", \\\"directed by Woody Allen\\\"); \\n\\t\\t//Canceled manager.advancedQuery(\\\"tennis\\\", \\\"international players\\\"); \\n\\t\\t// canceled manager.advancedQuery(\\\"tennis\\\", \\\"french open\\\"); \\n\\t\\t// canceled manager.advancedQuery(\\\"film movie\\\", \\\"1933\\\"); \\n//\\t\\tmanager.advancedQuery(\\\"United states\\\", \\\"professional sports teams \\\");\\n//\\t\\t manager.advancedQuery(\\\"computer games\\\", \\\"developed by Ubisoft\\\");\\n//\\t\\tmanager.advancedQuery(\\\"movies\\\", \\\"academy award nominations\\\");\\n //manager.advancedQuery(\\\"movies\\\", \\\"starring Dustin Hoffman\\\");\\n // manager.advancedQuery(\\\"movies\\\", \\\"best costume design\\\");\\n // manager.advancedQuery(\\\"concert tours\\\", \\\"england\\\");\\n // manager.advancedQuery(\\\"sport\\\", \\\"Francesco\\\");\\n\\t\\t//System.out.println(\\\"******* advanced query *******\\\");\\n\\t\\t//manager.advancedQuery(\\\"sportspeople\\\", \\\"tennis\\\");\\n//\\t\\tmanager.advancedQuery(ElasticIndex.analyzed, \\\"Broadway musicals\\\", \\\"Grammy Award\\\");\\n //System.out.println(\\\"*****************************\\\");\\n\\n\\n\\t\\t\\n\\t\\t//manager.advancedQuery(\\\"football\\\", \\\"italian championship\\\");\\n\\t\\t//manager.advancedQuery(\\\"american basketball\\\", \\\"team\\\");\\n\\t\\t //manager.advancedQuery(\\\"Goya Award\\\", \\\"Winner and nominees from FRA\\\");\\n\\t\\t//manager.advancedQuery(\\\"films\\\", \\\"american comedy \\\");\\n\\t\\t//manager.advancedQuery(\\\"films\\\", \\\"american Adventure directed by James P. Hogan\\\");\\n\\t\\t//manager.advancedQuery(\\\"NCAA Division\\\", \\\"american universities in Arkansas\\\");\\n\\t\\t//manager.advancedQuery(\\\"Academy award\\\", \\\"winners and nominees in acting in 2011\\\");\\n\\t\\t//manager.advancedQuery(\\\"canadian soccer\\\", \\\"Alain Rochat position \\\");\\n\\n\\t}\",\n \"public void Query() {\\n }\",\n \"protected boolean query() {\\r\\n\\t\\tqueryStr = new String(processQueryTitle(queryBk.getTitle()) + processQueryAuthor(queryBk.getCreator())\\r\\n\\t\\t\\t\\t+ processQueryPublisher(queryBk.getPublisher()));\\r\\n\\t\\tSystem.out.println(queryStr);\\r\\n\\t\\t// if edition is 'lastest' (coded '0'), no query is performed; and\\r\\n\\t\\t// return false.\\r\\n\\t\\tif (queryBk.parseEdition() == 0) {\\r\\n\\t\\t\\treturn false;\\r\\n\\t\\t} // end if\\r\\n\\r\\n\\t\\t/*\\r\\n\\t\\t * The following section adds edition info to the query string if edition no. is\\r\\n\\t\\t * greater than one. By cataloging practice, for the first edition, probably\\r\\n\\t\\t * there is NO input on the associated MARC field. Considering this, edition\\r\\n\\t\\t * query string to Primo is NOT added if querying for the first edition or no\\r\\n\\t\\t * edition is specified.\\r\\n\\t\\t */\\r\\n\\t\\tif (queryBk.parseEdition() > 1) {\\r\\n\\t\\t\\tqueryStr += processQueryEdition(queryBk.parseEdition());\\r\\n\\t\\t} // end if\\r\\n\\r\\n\\t\\t/*\\r\\n\\t\\t * Querying the Primo X-service; and invoking the matching processes (all done\\r\\n\\t\\t * by remoteQuery()).\\r\\n\\t\\t */\\r\\n\\t\\tif (strHandle.hasSomething(queryBk.getPublisher())) {\\r\\n\\t\\t\\tif (remoteQuery(queryStr)) {\\r\\n\\t\\t\\t\\tmatch = true;\\r\\n\\t\\t\\t\\tsetBookInfo();\\r\\n\\t\\t\\t\\tcheckAVA(queryBk.parseVolume());\\r\\n\\t\\t\\t\\treturn true;\\r\\n\\t\\t\\t} else {\\r\\n\\t\\t\\t\\tmatch = false;\\r\\n\\t\\t\\t} // end if\\r\\n\\t\\t} // end if\\r\\n\\r\\n\\t\\t/*\\r\\n\\t\\t * For various reasons, there are possibilities that the first query fails while\\r\\n\\t\\t * a match should be found. The follow work as remedy queries to ensure the\\r\\n\\t\\t * accuracy.\\r\\n\\t\\t */\\r\\n\\r\\n\\t\\tif (!match && strHandle.hasSomething(queryBk.getPublisher())) {\\r\\n\\t\\t\\tqueryStr = new String(\\r\\n\\t\\t\\t\\t\\tprocessQueryPublisher(queryBk.getPublisher()) + processQueryAuthor(queryBk.getCreator()));\\r\\n\\t\\t\\tif (remoteQuery(queryStr)) {\\r\\n\\t\\t\\t\\tmatch = true;\\r\\n\\t\\t\\t\\tsetBookInfo();\\r\\n\\t\\t\\t\\tcheckAVA(queryBk.parseVolume());\\r\\n\\t\\t\\t\\treturn true;\\r\\n\\t\\t\\t} else {\\r\\n\\t\\t\\t\\tmatch = false;\\r\\n\\t\\t\\t} // end if\\r\\n\\t\\t} // end if\\r\\n\\r\\n\\t\\tif (!match) {\\r\\n\\t\\t\\tqueryStr = new String(processQueryTitle(queryBk.getTitle()) + processQueryAuthor(queryBk.getCreator()));\\r\\n\\t\\t\\tif (remoteQuery(queryStr)) {\\r\\n\\t\\t\\t\\tmatch = true;\\r\\n\\t\\t\\t\\tsetBookInfo();\\r\\n\\t\\t\\t\\tcheckAVA(queryBk.parseVolume());\\r\\n\\t\\t\\t\\treturn true;\\r\\n\\t\\t\\t} else {\\r\\n\\t\\t\\t\\tmatch = false;\\r\\n\\t\\t\\t} // end if\\r\\n\\t\\t} // end if\\r\\n\\r\\n\\t\\tif (!match) {\\r\\n\\t\\t\\tqueryStr = new String(processQueryTitle(queryBk.getTitle()));\\r\\n\\t\\t\\tif (remoteQuery(queryStr)) {\\r\\n\\t\\t\\t\\tmatch = true;\\r\\n\\t\\t\\t\\tsetBookInfo();\\r\\n\\t\\t\\t\\tcheckAVA(queryBk.parseVolume());\\r\\n\\t\\t\\t\\treturn true;\\r\\n\\t\\t\\t} else {\\r\\n\\t\\t\\t\\tmatch = false;\\r\\n\\t\\t\\t} // end if\\r\\n\\t\\t} // end if\\r\\n\\r\\n\\t\\tif (!match && strHandle.hasSomething(queryBk.getPublishYear())) {\\r\\n\\t\\t\\tqueryStr = new String(\\r\\n\\t\\t\\t\\t\\tprocessQueryAuthor(queryBk.getCreator()) + processQueryYear(queryBk.getPublishYear()));\\r\\n\\r\\n\\t\\t\\tif (remoteQuery(queryStr)) {\\r\\n\\t\\t\\t\\tmatch = true;\\r\\n\\t\\t\\t\\tsetBookInfo();\\r\\n\\t\\t\\t\\tcheckAVA(queryBk.parseVolume());\\r\\n\\t\\t\\t\\treturn true;\\r\\n\\t\\t\\t} else {\\r\\n\\t\\t\\t\\tmatch = false;\\r\\n\\t\\t\\t} // end if\\r\\n\\t\\t} // end if\\r\\n\\r\\n\\t\\tif (!match) {\\r\\n\\t\\t\\tqueryStr = new String(\\r\\n\\t\\t\\t\\t\\tprocessQueryAuthor(queryBk.getCreator()) + processQueryTitleShort(queryBk.getTitle()));\\r\\n\\t\\t\\tif (remoteQuery(queryStr)) {\\r\\n\\t\\t\\t\\tmatch = true;\\r\\n\\t\\t\\t\\tsetBookInfo();\\r\\n\\t\\t\\t\\tcheckAVA(queryBk.parseVolume());\\r\\n\\t\\t\\t\\treturn true;\\r\\n\\t\\t\\t} else {\\r\\n\\t\\t\\t\\tmatch = false;\\r\\n\\t\\t\\t} // end if\\r\\n\\t\\t} // end if\\r\\n\\r\\n\\t\\t// Additional query for Chinese titles\\r\\n\\r\\n\\t\\tif (!match && (CJKStringHandling.isCJKString(queryBk.getTitle())\\r\\n\\t\\t\\t\\t|| CJKStringHandling.isCJKString(queryBk.getCreator())\\r\\n\\t\\t\\t\\t|| CJKStringHandling.isCJKString(queryBk.getPublisher()))) {\\r\\n\\r\\n\\t\\t\\tqueryStr = new String(processQueryTitle(queryBk.getTitle()));\\r\\n\\t\\t\\tif (remoteQuery(queryStr)) {\\r\\n\\t\\t\\t\\tmatch = true;\\r\\n\\t\\t\\t\\tsetBookInfo();\\r\\n\\t\\t\\t\\tcheckAVA(queryBk.parseVolume());\\r\\n\\t\\t\\t\\treturn true;\\r\\n\\t\\t\\t} else {\\r\\n\\t\\t\\t\\tmatch = false;\\r\\n\\t\\t\\t} // end if\\r\\n\\r\\n\\t\\t\\tif (!match && queryBk.parseEdition() != -1) {\\r\\n\\t\\t\\t\\tqueryStr = new String(\\r\\n\\t\\t\\t\\t\\t\\tprocessQueryTitle(queryBk.getTitle()) + processQueryEdition2(queryBk.parseEdition()));\\r\\n\\t\\t\\t\\tif (remoteQuery(queryStr)) {\\r\\n\\t\\t\\t\\t\\tmatch = true;\\r\\n\\t\\t\\t\\t\\tsetBookInfo();\\r\\n\\t\\t\\t\\t\\tcheckAVA(queryBk.parseVolume());\\r\\n\\t\\t\\t\\t\\treturn true;\\r\\n\\t\\t\\t\\t} else {\\r\\n\\t\\t\\t\\t\\tmatch = false;\\r\\n\\t\\t\\t\\t} // end if\\r\\n\\r\\n\\t\\t\\t\\tif (!match && queryBk.parseEdition() != -1) {\\r\\n\\t\\t\\t\\t\\tqueryStr = new String(\\r\\n\\t\\t\\t\\t\\t\\t\\tprocessQueryTitle(queryBk.getTitle()) + processQueryEdition3(queryBk.parseEdition()));\\r\\n\\t\\t\\t\\t\\tif (remoteQuery(queryStr)) {\\r\\n\\t\\t\\t\\t\\t\\tmatch = true;\\r\\n\\t\\t\\t\\t\\t\\tsetBookInfo();\\r\\n\\t\\t\\t\\t\\t\\tcheckAVA(queryBk.parseVolume());\\r\\n\\t\\t\\t\\t\\t\\treturn true;\\r\\n\\t\\t\\t\\t\\t} else {\\r\\n\\t\\t\\t\\t\\t\\tmatch = false;\\r\\n\\t\\t\\t\\t\\t} // end if\\r\\n\\t\\t\\t\\t} // end if\\r\\n\\t\\t\\t} // end if\\r\\n\\t\\t} // end if\\r\\n\\r\\n\\t\\t// Additional check for ISO Document number in <search> <genernal> PNX\\r\\n\\t\\t// tag\\r\\n\\t\\tif (!match && !CJKStringHandling.isCJKString(queryBk.getTitle())) {\\r\\n\\t\\t\\tqueryStr = new String(processQueryTitleISODoc(queryBk.getTitle()));\\r\\n\\t\\t\\tif (remoteQuery(queryStr)) {\\r\\n\\t\\t\\t\\tmatch = true;\\r\\n\\t\\t\\t\\tsetBookInfo();\\r\\n\\t\\t\\t\\tcheckAVA(queryBk.parseVolume());\\r\\n\\t\\t\\t\\treturn true;\\r\\n\\t\\t\\t} else {\\r\\n\\t\\t\\t\\tmatch = false;\\r\\n\\t\\t\\t\\terrMsg += \\\"Query: No record found on Primo.\\\" + Config.QUERY_SETTING;\\r\\n\\t\\t\\t} // end if\\r\\n\\t\\t} // end if\\r\\n\\t\\treturn false;\\r\\n\\t}\",\n \"private void queryList (String query) {\\n\\t\\tmemoListAdapter.query(query);\\n\\t}\",\n \"Term getQ();\",\n \"private static void prMode(DiskIndexWriter diskWriter, DiskPositionalIndex disk_posIndex) throws ClassNotFoundException, InstantiationException, IllegalAccessException, FileNotFoundException {\\n long time = 0;\\n GUI.JListModel.clear();\\n\\n if (query.equals(\\\"q\\\")) {\\n\\n System.exit(0);\\n }\\n MAP mean_ap = new MAP(path);\\n //returns qRel.keyset() i.e. queries \\n Set<String> queries = mean_ap.getQueries();\\n List<Long> time_per_query = new ArrayList<>();\\n //run ranked retrival for each query\\n for (String q : queries) {\\n time = 0;\\n List<String> word = new ArrayList();\\n\\n query = q;\\n long start = System.currentTimeMillis();\\n\\n String[] query_array = query.split(\\\"\\\\\\\\s+\\\");\\n TokenProcessor processor = new NewTokenProcessor();\\n\\n for (int i = 0; i < query_array.length; i++) {\\n word.add(processor.processToken(query_array[i]).get(0));\\n }\\n long t1 = System.currentTimeMillis();\\n time = t1 - start; //time to parse\\n StrategyFactory sf = new StrategyFactory();\\n StrategyInterface strategy = sf.execute(rankedOption);\\n\\n //maps postings to accumulator value\\n HashMap<Integer, Doc_accum> postingMap = new HashMap<Integer, Doc_accum>();\\n\\n PriorityQueue<Doc_accum> queue = new PriorityQueue<>(Collections.reverseOrder());\\n\\n List<Posting> postings = new ArrayList<>();\\n List<Doc_accum> results = new ArrayList<>();\\n\\n for (String term : word) {\\n long t2 = System.currentTimeMillis();\\n\\n if (term.equals(\\\"\\\")) {\\n continue;\\n } else {\\n\\n postings = disk_posIndex.getPosting_noPos(term);\\n long t3 = System.currentTimeMillis();\\n time = time + (t3 - t2);\\n\\n for (Posting p : postings) { //for each document in the postings list\\n double t_fd = p.getT_fd();\\n double d_ft = p.getD_ft();\\n double w_qt = strategy.calculate_wqt(N, d_ft);\\n double accum = 0;\\n double w_dt = strategy.get_wdt(t_fd, disk_posIndex, p.getDocumentId());\\n\\n //pairs (Ranked_posting, accumulator factor)\\n if (postingMap.containsKey(p.getDocumentId())) {\\n accum = postingMap.get(p.getDocumentId()).getAccumulator();\\n accum += (w_qt * w_dt);\\n postingMap.replace(p.getDocumentId(), new Doc_accum(p, accum)); //replaces old accum value\\n\\n } else {\\n accum += (w_qt * w_dt);\\n postingMap.put(p.getDocumentId(), new Doc_accum(p, accum));\\n }\\n }\\n\\n }\\n }\\n for (Integer p : postingMap.keySet()) {\\n Doc_accum doc_temp = postingMap.get(p);\\n double accum = doc_temp.getAccumulator(); //gets accum associated with doc\\n\\n if (accum > 0) {\\n //search for each p's Ld factor in docWeights.bin\\n double l_d = strategy.calculate_Ld(disk_posIndex, doc_temp.getPosting().getDocumentId());\\n\\n accum /= l_d;\\n doc_temp.setAccumulator(accum);\\n }\\n\\n queue.add(postingMap.get(p));\\n\\n }\\n\\n //returns top K=10 results \\n int topK = 50;\\n\\n while ((results.size() < topK) && queue.size() > 0) {\\n\\n results.add(queue.poll()); //gets the posting acc pair and returns only posting\\n\\n }\\n time_per_query.add(time);\\n List<String> filenames = get_RankedResults(results);\\n\\n mean_ap.add_poseRel(q, filenames);\\n\\n }\\n\\n double map_result = mean_ap.mean_ap();\\n String mapDisplay = \\\"Mean average precision: \\\" + map_result;\\n GUI.JListModel.addElement(mapDisplay);\\n System.out.println(\\\"\\\\n\\\" + mapDisplay);\\n\\n double throughput_result = mean_ap.calculate_throughput(time_per_query);\\n String throughput_Display = \\\"Throughput of the system is: \\\" + throughput_result;\\n GUI.JListModel.addElement(throughput_Display);\\n System.out.println(throughput_Display);\\n\\n double mrt_result = mean_ap.calculae_mean_response_time(time_per_query);\\n String mrt_Display = \\\"Mean Response Time of the system is: \\\" + mrt_result;\\n GUI.JListModel.addElement(mrt_Display);\\n System.out.println(mrt_Display);\\n\\n }\",\n \"public void run(){\\n\\t\\tif(searchHow==0){\\n\\t\\t\\tint isbnCount = 0;\\n\\t\\t\\tfor(int i=0; i<db.size(); i++){\\n\\t\\t\\t\\t\\tSearchRequest requestIsbn = new SearchRequest(db, searchForThis, isbnCount, db.size());\\n\\t\\t\\t\\t\\tdb.searchByISBN(requestIsbn);\\n\\t\\t\\t\\t\\tisbnCount = requestIsbn.foundPos;\\n\\t\\t\\t\\t\\tif (requestIsbn.foundPos >= 0) {\\n\\t\\t\\t\\t\\t\\tisbnCount++;\\n\\t\\t\\t\\t\\t\\tString formatThis = \\\"Matched ISBN at position: \\\" + requestIsbn.foundPos;\\n\\t\\t\\t\\t\\t\\tSystem.out.printf(\\\"%-35s || Title: \\\"+db.getBook(requestIsbn.foundPos)+\\\"\\\\n\\\",formatThis);\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\telse\\n\\t\\t\\t\\t\\t\\ti=db.size();\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\tif(searchHow==1){\\n\\t\\t\\tint titleCount = 0;\\n\\t\\t\\tfor(int i=0; i<db.size(); i++){\\n\\t\\t\\t\\t\\tSearchRequest requestTitle = new SearchRequest(db, searchForThis, titleCount, db.size());\\n\\t\\t\\t\\t\\tdb.searchByTitle(requestTitle);\\n\\t\\t\\t\\t\\ttitleCount = requestTitle.foundPos;\\n\\t\\t\\t\\t\\tif (requestTitle.foundPos >= 0) {\\n\\t\\t\\t\\t\\t\\ttitleCount++;\\n\\t\\t\\t\\t\\t\\tString formatThis = \\\"Matched title at position: \\\" + requestTitle.foundPos;\\n\\t\\t\\t\\t\\t\\tSystem.out.printf(\\\"%-35s || Title: \\\"+db.getBook(requestTitle.foundPos)+\\\"\\\\n\\\",formatThis);\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\telse\\n\\t\\t\\t\\t\\t\\ti=db.size();\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\tif(searchHow==2){\\n\\t\\t\\tint authorCount = 0;\\n\\t\\t\\tfor(int i=0; i<db.size(); i++){\\n\\t\\t\\t\\t\\tSearchRequest requestAuthor = new SearchRequest(db, searchForThis, authorCount, db.size());\\n\\t\\t\\t\\t\\tdb.searchByAuthor(requestAuthor);\\n\\t\\t\\t\\t\\tauthorCount = requestAuthor.foundPos;\\n\\t\\t\\t\\t\\tif (requestAuthor.foundPos >= 0) {\\n\\t\\t\\t\\t\\t\\tauthorCount++;\\n\\t\\t\\t\\t\\t\\tString formatThis = \\\"Matched author at position: \\\" + requestAuthor.foundPos;\\n\\t\\t\\t\\t\\t\\tSystem.out.printf(\\\"%-35s || Title: \\\"+db.getBook(requestAuthor.foundPos)+\\\"\\\\n\\\",formatThis);\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\telse\\n\\t\\t\\t\\t\\t\\ti=db.size();\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\tif(searchHow==3){\\n\\t\\t\\tint pageCount = 0;\\n\\t\\t\\tfor(int i=0; i<db.size(); i++){\\n\\t\\t\\t\\t\\tSearchRequest requestPage = new SearchRequest(db, searchForThis, pageCount, db.size());\\n\\t\\t\\t\\t\\tdb.searchByNumPages(requestPage);\\n\\t\\t\\t\\t\\tpageCount = requestPage.foundPos;\\n\\t\\t\\t\\t\\tif (requestPage.foundPos >= 0) {\\n\\t\\t\\t\\t\\t\\tpageCount++;\\n\\t\\t\\t\\t\\t\\tString formatThis = \\\"Matched pages at position: \\\" + requestPage.foundPos;\\n\\t\\t\\t\\t\\t\\tSystem.out.printf(\\\"%-35s || Title: \\\"+db.getBook(requestPage.foundPos)+\\\"\\\\n\\\",formatThis);\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\telse\\n\\t\\t\\t\\t\\t\\ti=db.size();\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\tif(searchHow==4){\\n\\t\\t\\tint yearCount = 0;\\n\\t\\t\\tfor(int i=0; i<db.size(); i++){\\n\\t\\t\\t\\t\\tSearchRequest requestYear = new SearchRequest(db, searchForThis, yearCount, db.size());\\n\\t\\t\\t\\t\\tdb.searchByYear(requestYear);\\n\\t\\t\\t\\t\\tyearCount = requestYear.foundPos;\\n\\t\\t\\t\\t\\tif (requestYear.foundPos >= 0) {\\n\\t\\t\\t\\t\\t\\tyearCount++;\\n\\t\\t\\t\\t\\t\\tString formatThis = \\\"Matched year at position: \\\" + requestYear.foundPos;\\n\\t\\t\\t\\t\\t\\tSystem.out.printf(\\\"%-35s || Title: \\\"+db.getBook(requestYear.foundPos)+\\\"\\\\n\\\",formatThis);\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\telse\\n\\t\\t\\t\\t\\t\\ti=db.size();\\n\\t\\t\\t}\\n\\t\\t}\\n\\t}\",\n \"@Override\\n public boolean onQueryTextSubmit(String query) {\\n topStories = false;\\n filter.setQuery(query);\\n gvResults.clearOnScrollListeners();\\n setUpRecycler();\\n findViewById(R.id.relativeLayout).setVisibility(View.GONE);\\n findViewById(R.id.tvHeading).setVisibility(View.GONE);\\n fetchArticles(0,true);\\n searchView.clearFocus();\\n return true;\\n }\",\n \"public void query()\\n\\t{\\n\\t\\tJSONObject queryInfo = new JSONObject();\\n\\t\\t\\n\\t\\ttry\\n\\t\\t{\\n\\t\\t\\tqueryInfo.put(\\\"type\\\", \\\"query\\\");\\n\\t\\t\\t\\n\\t\\t\\tos.println(queryInfo.toString());\\n\\t\\t\\tos.flush();\\n\\t\\t\\t\\n\\t\\t\\tSystem.out.println(\\\"send query request : \\\" + queryInfo.toString());\\n\\t\\t}\\n\\t\\tcatch (JSONException e)\\n\\t\\t{\\n\\t\\t\\te.printStackTrace();\\n\\t\\t}\\n\\t}\",\n \"protected void queryPosts()\\n {\\n ParseQuery<Post> query = ParseQuery.getQuery(Post.class);\\n query.include(Post.KEY_USER);\\n query.whereEqualTo(Post.KEY_USER, ParseUser.getCurrentUser());\\n query.setLimit(20);\\n query.addDescendingOrder(Post.KEY_CREATED_AT);\\n query.findInBackground(new FindCallback<Post>() {\\n @Override\\n public void done(List<Post> posts, ParseException e)\\n {\\n if(e != null)\\n {\\n Log.e(TAG, \\\"Issue with getting posts\\\", e);\\n }\\n for(Post post : posts)\\n {\\n Log.i(TAG, \\\"Post: \\\" + post.getDescription() + \\\", username\\\" + post.getUser().getUsername());\\n }\\n adapter.clear();\\n allPosts.addAll(posts);\\n swipeContainer.setRefreshing(false);\\n adapter.notifyDataSetChanged();\\n\\n }\\n });\\n }\",\n \"public void search(IndexShort < O > index, short range, short k)\\n throws Exception {\\n // assertEquals(index.aDB.count(), index.bDB.count());\\n // assertEquals(index.aDB.count(), index.bDB.count());\\n // index.stats();\\n index.resetStats();\\n // it is time to Search\\n int querySize = 1000; // amount of elements to read from the query\\n String re = null;\\n logger.info(\\\"Matching begins...\\\");\\n File query = new File(testProperties.getProperty(\\\"test.query.input\\\"));\\n File dbFolder = new File(testProperties.getProperty(\\\"test.db.path\\\"));\\n BufferedReader r = new BufferedReader(new FileReader(query));\\n List < OBPriorityQueueShort < O >> result = new LinkedList < OBPriorityQueueShort < O >>();\\n re = r.readLine();\\n int i = 0;\\n long realIndex = index.databaseSize();\\n\\n while (re != null) {\\n String line = parseLine(re);\\n if (line != null) {\\n OBPriorityQueueShort < O > x = new OBPriorityQueueShort < O >(\\n k);\\n if (i % 100 == 0) {\\n logger.info(\\\"Matching \\\" + i);\\n }\\n\\n O s = factory.create(line);\\n if (factory.shouldProcess(s)) {\\n if(i == 279){\\n System.out.println(\\\"hey\\\");\\n }\\n index.searchOB(s, range, x);\\n result.add(x);\\n i++;\\n }\\n }\\n if (i == querySize) {\\n logger.warn(\\\"Finishing test at i : \\\" + i);\\n break;\\n }\\n re = r.readLine();\\n }\\n \\n logger.info(index.getStats().toString());\\n \\n int maxQuery = i;\\n // logger.info(\\\"Matching ends... Stats follow:\\\");\\n // index.stats();\\n\\n // now we compare the results we got with the sequential search\\n Iterator < OBPriorityQueueShort < O >> it = result.iterator();\\n r.close();\\n r = new BufferedReader(new FileReader(query));\\n re = r.readLine();\\n i = 0;\\n while (re != null) {\\n String line = parseLine(re);\\n if (line != null) {\\n if (i % 300 == 0) {\\n logger.info(\\\"Matching \\\" + i + \\\" of \\\" + maxQuery);\\n }\\n O s = factory.create(line);\\n if (factory.shouldProcess(s)) {\\n OBPriorityQueueShort < O > x2 = new OBPriorityQueueShort < O >(\\n k);\\n searchSequential(realIndex, s, x2, index, range);\\n OBPriorityQueueShort < O > x1 = it.next();\\n //assertEquals(\\\"Error in query line: \\\" + i + \\\" slice: \\\"\\n // + line, x2, x1); \\n \\n assertEquals(\\\"Error in query line: \\\" + i + \\\" \\\" + index.debug(s) + \\\"\\\\n slice: \\\"\\n + line + \\\" \\\" + debug(x2,index ) + \\\"\\\\n\\\" + debug(x1,index), x2, x1);\\n\\n i++;\\n }\\n \\n }\\n if (i == querySize) {\\n logger.warn(\\\"Finishing test at i : \\\" + i);\\n break;\\n }\\n re = r.readLine();\\n }\\n r.close();\\n logger.info(\\\"Finished matching validation.\\\");\\n assertFalse(it.hasNext());\\n }\",\n \"@Override\\n protected void queryPosts() {\\n ParseQuery<Post> query = ParseQuery.getQuery(Post.class);\\n query.include(Post.KEY_USER);\\n query.whereEqualTo(Post.KEY_USER, ParseUser.getCurrentUser());\\n Log.d(TAG, \\\"ParseUser\\\" + ParseUser.getCurrentUser().toString());\\n query.setLimit(20);\\n query.addDescendingOrder(Post.KEY_CREATED_AT);\\n query.findInBackground(new FindCallback<Post>() {\\n @Override\\n public void done(List<Post> posts, ParseException e) {\\n if (e != null){\\n Log.e(TAG, \\\"Issue with getting posts\\\", e);\\n return;\\n }\\n for (Post post: posts){\\n Log.i(TAG, \\\"Post: \\\" + post.getDescription() + \\\", username: \\\" + post.getUser().getUsername());\\n }\\n allPosts.addAll(posts);\\n adapter.notifyDataSetChanged();\\n }\\n });\\n }\",\n \"private void queryPost() {\\n tv_search.setText(\\\"Recently Added Posts:\\\");\\n ParseQuery<Post> query = ParseQuery.getQuery(Post.class);\\n query.include(Post.KEY_USER);\\n query.setLimit(15);\\n query.addDescendingOrder(Post.KEY_CREATED);\\n query.findInBackground(new FindCallback<Post>() {\\n @Override\\n public void done(List<Post> posts, ParseException e) {\\n if(e!= null){\\n Log.e(tag, \\\"Issue with getting post\\\", e);\\n return;\\n }\\n adaptor.clear();\\n adaptor.addAll(posts);\\n //allPost.addAll(posts);\\n //adaptor.notifyDataSetChanged();\\n //swipeRefreshLayout.setRefreshing(false);\\n\\n //user just created a post\\n if (isJustCreatedNewPost == true)\\n {\\n //reset bool\\n isJustCreatedNewPost = false;\\n// //subscribe user to their new post channel\\n// String postChannel = \\\"POST_\\\"+posts.get(0).getObjectId();\\n// ParsePush.subscribeInBackground(postChannel);\\n\\n }\\n }\\n });\\n }\",\n \"public Qs() {\\n this(\\\"qs\\\", null);\\n }\",\n \"public void search() {\\n try {\\n for(int i = 0; i < this.queries.size(); i++){\\n search(i);\\n // in case of error stop\\n if(!this.searchOK(i)){\\n System.out.println(\\\"\\\\t\\\" + new Date().toString() + \\\" \\\" + db + \\\" Search for rest queries cancelled, because failed for query \\\" + i + \\\" : \\\" + this.queries.get(i));\\n break;\\n }\\n }\\n } catch (UnsupportedEncodingException ex) {\\n Logger.getLogger(EntrezSearcher.class.getName()).log(Level.SEVERE, null, ex);\\n }\\n }\",\n \"public static void searchJobs(String searchTerm) {\\n\\n for (int i = 0; i > PostJob.allJobs.size(); i++) {\\n\\n\\n if (PostJob.allJobs.contains(searchTerm)) {\\n int itemIndx = PostJob.allJobs.indexOf(searchTerm);\\n String output = PostJob.allJobs.get(itemIndx);\\n System.out.print(\\\"Available jobs within your search terms\\\" + output);\\n\\n }\\n }\\n }\",\n \"public void performQuack(){\\n qb.quack();\\n }\",\n \"SearchResponse query(SearchRequest request, Map<SearchParam, String> params);\",\n \"List<Revenue> search(String query);\",\n \"public static void query(String q) throws TwitterException, SQLException, ClassNotFoundException {\\n\\n\\t\\t//the search object returns a list of all the tweets from the query string q\\n\\t\\tSearch newQuery = new Search(q);\\n\\t\\t\\n\\t\\tClass.forName(\\\"org.h2.Driver\\\");\\n\\t\\tConnection conn = DriverManager.getConnection(DB, user, pass);\\n\\t\\t\\n\\t\\t//authentication allows a user to have up to 350 requests per hour over the normal 150\\n\\t\\tTwitter a = OAuth.authenticate();\\n\\n\\t\\ttry {\\n\\t\\t\\tArrayList<Long> sid = new ArrayList<Long>();\\n\\t\\t\\tfor (Tweet tweets : newQuery.statusList) {\\n\\t\\t\\t\\tlong statusID = tweets.getId();\\n\\t\\t\\t\\t//this checks for redudant statuses then inserts new ones into the DB\\n\\t\\t\\t\\tif (!(DB_Interface.exist_Status(statusID, conn))) {\\n\\t\\t\\t\\t\\tSystem.out.println(\\\"Preparin new insert of status \\\"\\n\\t\\t\\t\\t\\t\\t\\t+ statusID);\\n\\t\\t\\t\\t\\tsid.add(statusID);\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t/* a.showStatus transforms a query tweet into a normal status this takes up a rate limit\\n\\t\\t\\t\\t\\t * this is a difficult problem to address because scraped tweets and streamed tweets are\\n\\t\\t\\t\\t\\t * formatted as a normal status, but only queried tweets are structured this way\\n\\t\\t\\t\\t\\t */\\n\\t\\t\\t\\t\\tDB_Interface.insertTweet(conn, a.showStatus(statusID));\\n\\t\\t\\t\\t} else {\\n\\t\\t\\t\\t\\tSystem.out.println(\\\"Status Already exists!!!!\\\");\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t} catch (JdbcSQLException e) {\\n\\t\\t\\te.printStackTrace();\\n\\t\\t}\\n\\t\\t\\n\\t\\tconn.close();\\n\\n\\t}\",\n \"public void performSearch() {\\n final String url = String.format(BING_SEARCH_URL, Words.getRandomWord(), Words.getRandomWord());\\n\\n //open page with custom data\\n openWebPage(url, \\\"Search url: \\\" + url);\\n }\",\n \"@Override\\r\\n public boolean onQueryTextSubmit(String query) {\\n searchAdapter.setSearchResults(DataCache.getInstance().getSearchResults(query));\\r\\n return false;\\r\\n }\",\n \"@Override\\n public boolean onQueryTextSubmit(String query) {\\n if(!TextUtils.isEmpty(query)){\\n //seach\\n seachHispost(query);\\n }else {\\n loadHisPosts();\\n }\\n return false;\\n }\",\n \"List<Cemetery> search(String query);\",\n \"SearchResponse search(Pageable pageable, QueryBuilder query, Collection<AggregationBuilder> aggregations);\",\n \"void runQueries();\",\n \"private static void executeQuery4(PersistenceManager pm) {\\n Query query = pm.newQuery(Category.class);\\n query.declareParameters(\\\"int length\\\");\\n query.declareVariables(\\\"Item item\\\");\\n query.setFilter(\\n \\\"elements.contains(item) && item.name.length() <= length\\\");\\n Collection results = (Collection)query.execute(new Integer(10));\\n printCollection(\\\"Categories containing an item with a short name: \\\",\\n results.iterator());\\n query.closeAll();\\n }\",\n \"List<Job> findAllByLocation(String query);\",\n \"public IndexSearcher longQueryExpansion(String indexDir, String queriesFile, PrintWriter outputWriter, Debug debug, String similarity, Analyzer analyzer) throws IOException, ParseException {\\t\\t\\n\\t\\t\\n\\t\\t//Welcome to shortQueries\\n\\t\\tSystem.out.println(\\\"Set requests to LONG QUERIES EXPANSION\\\");\\n\\t\\t\\n\\t\\t//Create IndexReader and Searcher\\n\\t\\tIndexReader reader = DirectoryReader.open(FSDirectory.open( new File(indexDir).toPath()));\\t\\t//Creating an index reader\\n\\t\\tIndexSearcher searcher = new IndexSearcher(reader);\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t//Create an index searcher\\n\\t\\t\\n\\t\\t//Set similarity measure\\n\\t\\tsearcher = new SetSimilarity().SetSimilaritySearcher(searcher, similarity);\\n\\t\\t\\n\\t\\t//Read queries from file\\n\\t\\t\\tString[] queries = Search.readQueriesFile(queriesFile);\\n\\t\\t\\t\\n\\t\\t\\tfor (int i=0; i < queries.length; i++ ){ //for all queries\\n\\t\\t\\t\\t\\n\\t\\t\\t\\ttry {\\n\\t\\t\\t\\t\\t//Parse Multiple fields Query\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\n\\t\\t\\t\\t\\tString str = queries[i];\\t\\t\\t\\t//take all queries\\n\\t\\t\\t\\t\\tString[] parts = str.split(\\\"#\\\", 3);\\t\\t//split them in three\\n\\t\\t\\t\\t\\t//String num = parts[0];\\t\\t\\t\\t\\t//part 1 is number\\n\\t\\t\\t\\t\\tString title = parts[1];\\t\\t\\t\\t//part 2 is title\\n\\t\\t\\t\\t\\tString desc = parts[2];\\t\\t\\t\\t\\t//part 3 is description\\n\\t\\t\\t\\t\\tString num = Integer.toString(i + 1);\\t//(part 1 is number ) other option for queyrid\\n\\t\\t\\t\\t\\tSystem.out.println(\\\"Query number: \\\" + num);\\n\\t\\t\\t\\t\\tSystem.out.println(\\\"Title of query: \\\" + title); \\n\\t\\t\\t\\t\\tSystem.out.println(\\\"Description of query: \\\" + desc);\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t//Title query\\n\\t\\t\\t\\t\\tQueryParser titleQP = new QueryParser(\\\"contents\\\", analyzer);\\t\\t\\t\\t//Built QueryParser\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\tString newTitle = title.substring(3, title.length());\\t//Strip numbers from title\\n\\t\\t\\t\\t\\tQuery titleQuery = titleQP.parse(newTitle); \\t\\t\\t\\t\\t\\t\\t\\t\\t//Parse titles\\n\\t\\t\\t\\t\\t//Desc query\\n\\t\\t\\t\\t\\tQueryParser descQP = new QueryParser (\\\"contents\\\", analyzer);\\t\\t\\t\\t//Build QueryParser\\n\\t\\t\\t\\t\\tQuery descQuery = descQP.parse(desc);\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t//Parse descriptions\\t\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t//Final Query\\n\\t\\t\\t\\t\\tBuilder booleanQuery = new BooleanQuery.Builder();\\n\\t\\t\\t\\t\\tbooleanQuery.add(titleQuery, BooleanClause.Occur.SHOULD);\\n\\t\\t\\t\\t\\tbooleanQuery.add(descQuery, BooleanClause.Occur.SHOULD);\\n\\t\\t\\t\\t\\tQuery q = booleanQuery.build();\\n\\t\\t\\t\\t\\tSearch.displayQuery(q);\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t//Search\\n\\t\\t\\t\\t\\tTopScoreDocCollector collector = TopScoreDocCollector.create(1000);\\t\\t\\t\\t\\t\\t\\t\\t//Create a TopScore Collector\\n\\t\\t\\t\\t\\tsearcher.search(q, collector);\\t\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t//Print results\\n\\t\\t\\t\\t\\t//displayResults(searcher, collector);\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t//Output results to file\\n\\t\\t\\t\\t\\tSearch.outputResults(searcher, collector, outputWriter, num);\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t}//end try\\n\\t\\t\\t\\tcatch (Exception e) {\\n\\t\\t\\t\\t\\tSystem.out.println(\\\"Parse exception in query #\\\" + i);\\n\\t\\t\\t\\t\\te.printStackTrace();\\n\\t\\t\\t\\t}//end catch\\n\\t\\t\\t\\n\\t\\t}//end for\\n\\t\\t\\t//Close index reader\\n\\t\\t\\toutputWriter.close();\\n\\t\\t\\treader.close();\\n\\t\\t\\treturn searcher;\\n\\t\\t\\t\\n\\t}\",\n \"public void onSearchSubmit(String queryTerm);\",\n \"public static void QueryVector() {\\n for(Entry<String, List<Double>> entry: wtgMap.entrySet()){\\n List<Double> queryValue = new ArrayList();\\n queryValue = entry.getValue();\\n double temp = queryValue.get(totaldocument);\\n\\n query.add(temp);\\n }\\n }\",\n \"private void createAdapters() {\\n // Available quests for a Neutral hero\\n adapterAvailableNeutral = new QuestAdapter(this, new ParseQueryAdapter.QueryFactory<ParseObject>(){\\n @Override\\n public ParseQuery create() {\\n ParseQuery query = new ParseQuery(QuestApp.QUEST_DATABASE);\\n query.whereEqualTo(QuestApp.COMPLETED_KEY, false);\\n query.whereDoesNotMatchKeyInQuery(QuestApp.ACCEPTEDBY_KEY, QuestApp.OBJECTID_KEY, ParseUser.getQuery());\\n return query;\\n }\\n });\\n\\n // Available quests for a Good hero\\n adapterAvailableGood = new QuestAdapter(this, new ParseQueryAdapter.QueryFactory<ParseObject>(){\\n @Override\\n public ParseQuery create() {\\n ParseQuery query = new ParseQuery(QuestApp.QUEST_DATABASE);\\n query.whereEqualTo(QuestApp.COMPLETED_KEY, false);\\n query.whereEqualTo(QuestApp.ALIGNMENT_KEY, 0);\\n query.whereDoesNotMatchKeyInQuery(QuestApp.ACCEPTEDBY_KEY, QuestApp.OBJECTID_KEY, ParseUser.getQuery());\\n return query;\\n }\\n });\\n\\n // Available quests for an Evil hero\\n adapterAvailableEvil = new QuestAdapter(this, new ParseQueryAdapter.QueryFactory<ParseObject>(){\\n @Override\\n public ParseQuery create() {\\n ParseQuery query = new ParseQuery(QuestApp.QUEST_DATABASE);\\n query.whereEqualTo(QuestApp.COMPLETED_KEY, false);\\n query.whereEqualTo(QuestApp.ALIGNMENT_KEY, 2);\\n query.whereDoesNotMatchKeyInQuery(QuestApp.ACCEPTEDBY_KEY, QuestApp.OBJECTID_KEY, ParseUser.getQuery());\\n return query;\\n }\\n });\\n\\n // Quests accepted by user\\n adapterAccepted = new QuestAdapter(this, new ParseQueryAdapter.QueryFactory<ParseObject>(){\\n @Override\\n public ParseQuery create() {\\n ParseQuery query = new ParseQuery(QuestApp.QUEST_DATABASE);\\n query.whereEqualTo(QuestApp.COMPLETED_KEY, false);\\n query.whereEqualTo(QuestApp.ACCEPTEDBY_KEY, user);\\n return query;\\n }\\n });\\n\\n // Quests completed by user\\n adapterCompleted = new QuestAdapter(this, new ParseQueryAdapter.QueryFactory<ParseObject>(){\\n @Override\\n public ParseQuery create() {\\n ParseQuery query = new ParseQuery(QuestApp.QUEST_DATABASE);\\n query.whereEqualTo(QuestApp.COMPLETED_KEY, true);\\n query.whereEqualTo(QuestApp.ACCEPTEDBY_KEY, user);\\n return query;\\n }\\n });\\n }\",\n \"private void addQueries(String query){\\n ArrayList <String> idsFullSet = new ArrayList <String>(searchIDs);\\n while(idsFullSet.size() > 0){\\n ArrayList <String> idsSmallSet = new ArrayList <String>(); \\n if(debugMode) {\\n System.out.println(\\\"\\\\t Pmids not used in query available : \\\" + idsFullSet.size());\\n }\\n idsSmallSet.addAll(idsFullSet.subList(0,Math.min(getSearchIdsLimit(), idsFullSet.size())));\\n idsFullSet.removeAll(idsSmallSet);\\n String idsConstrain =\\\"\\\";\\n idsConstrain = idsConstrain(idsSmallSet);\\n addQuery(query,idsConstrain);\\n }\\n }\",\n \"public static void search(){\\n\\t\\tfor (Page p:heap){\\n\\t\\t\\tfor(Building b:p.buildings){\\n\\t\\t\\t\\t\\n\\t\\t\\t\\t//System.out.println(b.buildingName);\\n\\t\\t\\t\\tif(b.getBuildingName()!=null) {\\n\\t\\t\\t\\t\\tif(b.getBuildingName().contains(searchQuery)){\\n\\t\\t\\t\\t\\t\\tSystem.out.println(\\\"======================================================\\\");\\n\\t\\t\\t\\t\\t\\tSystem.out.println(\\\"Building Name: \\\" + b.getBuildingName());\\n\\t\\t\\t\\t\\t\\tSystem.out.println(\\\"Property ID: \\\" + b.getPropID());\\n\\t\\t\\t\\t\\t\\tSystem.out.println(\\\"Census year: \\\" + b.getCensusYear());\\n\\t\\t\\t\\t\\t\\tSystem.out.println(\\\"======================================================\\\");\\n\\t\\t\\t\\t\\t\\tSystem.out.println();\\n\\t\\t\\t\\t\\t\\tbuildingsFound++;\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\tpagesSearched++;\\n\\t\\t}\\n\\t}\",\n \"public void index(List<ParsedDocument> pdocs,int qid) {\\n\\t\\ttry {\\n\\t\\t\\tint count = iw.maxDoc()+1;\\n\\t\\t\\tDocument doc = null;\\n\\t\\t\\tIndexDocument iDoc=null;\\n\\t\\t\\tfor (ParsedDocument pdoc : pdocs) {\\n\\t\\t\\t\\t\\n\\t\\t\\t\\tiDoc=parseDocument(pdoc);\\n\\t\\t\\t\\tif(iDoc==null){\\n\\t\\t\\t\\t\\tcontinue;\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\tField queryField = new Field(\\\"qid\\\", qid+\\\"\\\", Store.YES,\\n\\t\\t\\t\\t\\t\\tIndex.NOT_ANALYZED);\\n\\t\\t\\t\\tField uniqueField = new Field(\\\"id\\\", count + \\\"\\\", Store.YES,\\n\\t\\t\\t\\t\\t\\tIndex.NOT_ANALYZED);\\n\\t\\t\\t\\tField titleField = new Field(\\\"title\\\", iDoc.getTitle(),\\n\\t\\t\\t\\t\\t\\tStore.YES, Index.ANALYZED, TermVector.YES);\\n\\t\\t\\t\\tField bodyField = new Field(\\\"body\\\", iDoc.getBody(), Store.YES,\\n\\t\\t\\t\\t\\t\\tIndex.ANALYZED, TermVector.YES);\\n\\t\\t\\t\\tField urlField = new Field(\\\"url\\\", iDoc.getUrl(), Store.YES,\\n\\t\\t\\t\\t\\t\\tIndex.NOT_ANALYZED);\\n\\t\\t\\t\\tField anchorField = new Field(\\\"anchor\\\", iDoc.getAnchor(), Store.YES,\\n\\t\\t\\t\\t\\t\\tIndex.ANALYZED, TermVector.YES);\\n\\n\\t\\t\\t\\tdoc = new Document();\\n\\t\\t\\t\\tdoc.add(uniqueField);//标示不同的document\\n\\t\\t\\t\\tdoc.add(queryField);//标示不同的query\\n\\t\\t\\t\\tdoc.add(titleField);\\n\\t\\t\\t\\tdoc.add(bodyField);\\n\\t\\t\\t\\tdoc.add(urlField);\\n\\t\\t\\t\\tdoc.add(anchorField);\\n\\t\\t\\t\\t\\n\\t\\t\\t\\tiw.addDocument(doc);\\n\\t\\t\\t\\tcount++;\\n\\t\\t\\t}\\n\\t\\t\\tiw.commit();\\n\\t\\t\\t\\n\\t\\t} catch (IOException e) {\\n\\t\\t\\te.printStackTrace();\\n\\t\\t} \\n\\t}\",\n \"public static void main(String[] args) {\\n\\t\\tSession s2=util.getSession();\\r\\n\\t\\tQuery qry=s2.getNamedQuery(\\\"q2\\\");\\r\\n\\t\\t//Query qry=s2.getNamedQuery(\\\"q3\\\");\\r\\n\\t\\t//qry.setInteger(0, 50);\\r\\n\\t\\tList<Object[]> lust=qry.list();\\r\\n\\t\\tfor(Object[] row:lust) {\\r\\n\\t\\t\\tSystem.out.println(Arrays.toString(row));\\r\\n\\t\\t}\\r\\n\\t\\tSystem.out.println(\\\"Completed\\\");\\r\\n\\t}\",\n \"public List<T> query(QueryObject qo) {\\n\\t\\treturn null;\\n\\t}\",\n \"private static String addQueryEntry(String query) throws IOException {\\n\\t\\t\\t\\t\\n\\t\\tString submittedQuery=null;\\n\\t\\tString queryParts[]=query.split(\\\"&\\\"); // get parameters from query\\t\\t\\n\\t\\tboolean isNextPage=false;\\n\\t\\tString key=null;\\n\\t\\tInteger value=null;\\n\\t\\tboolean docsProcessed=false; // identifies if 'docs' occurs more than once in the query\\t\\t\\n\\t\\tboolean termsProcessed=false; // identifies if 'terms' occurs more than once in the query\\n\\t\\t\\n\\t\\t// identify if it is a next page\\n\\t\\tfor (int i=0;i<queryParts.length;i++) { // verifies if it is a next page\\n\\t\\t\\tString queryPartsFields[]=queryParts[i].split(\\\"=\\\",2);\\t\\t\\t\\n\\t\\t\\tqueryPartsFields[0]=queryPartsFields[0].trim();\\n\\t\\t\\tif (queryPartsFields.length>1) {\\n\\t\\t\\t\\tqueryPartsFields[1]=queryPartsFields[1].trim();\\n\\t\\t\\t}\\n\\t\\t\\t\\n\\t\\t\\tif (queryPartsFields[0].equals(DOCS_KEY) && queryPartsFields.length>1 && !queryPartsFields[1].equals(\\\"\\\")) {\\t\\t\\t\\n\\t\\t\\t\\tint ipage;\\n\\t\\t\\t\\ttry {\\n\\t\\t\\t\\t\\tipage=Integer.parseInt(queryPartsFields[1]);\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\tcatch (NumberFormatException e) {\\n\\t\\t\\t\\t\\tipage=0;\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\n\\t\\t\\t\\tif (ipage!=0) { // regist only pages>0 \\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\tisNextPage=true;\\t\\t\\t\\n\\t\\t\\t\\t\\tif (ipage%RESULTS_PER_PAGE!=0) {\\n\\t\\t\\t\\t\\t\\tSystem.err.println(\\\"Page results not multiple of \\\"+RESULTS_PER_PAGE+\\\": \\\"+ipage);\\n\\t\\t\\t\\t\\t\\tipage+=ipage%RESULTS_PER_PAGE;\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\tif (!docsProcessed) {\\n\\t\\t\\t\\t\\t\\tint index=ipage/RESULTS_PER_PAGE>pagesViewedDistAux.length-1 ? pagesViewedDistAux.length-1 : ipage/RESULTS_PER_PAGE;\\t\\t\\t\\n\\t\\t\\t\\t\\t\\tif (index==0) { // sanity check\\n\\t\\t\\t\\t\\t\\t throw new IOException(\\\"Error of index=0 on a next page. ipage:\\\"+ipage);\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\tpagesViewedDistAux[index]++;\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\tdocsProcessed=true;\\t\\t\\t\\t\\n\\t\\t\\t\\t}\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t}\\n\\t\\t\\telse if (queryPartsFields[0].equals(QUERY_KEY)) {\\n\\t\\t\\t\\ttermsProcessed=true;\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\t// check wrong entries\\n\\t\\tif (docsProcessed && !termsProcessed) {\\n\\t\\t\\tSystem.err.println(\\\"Error of query with docs without terms: \\\"+query);\\n\\t\\t\\treturn null;\\n\\t\\t}\\t\\t\\t\\t\\n\\t\\tif (isNextPage) {\\n\\t\\t\\treturn null;\\n\\t\\t}\\n\\t\\t\\n\\t\\t// count only first page\\n\\t\\tdocsProcessed=false;\\n\\t\\tfor (int i=0;i<queryParts.length;i++) {\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\tString queryPartsFields[]=queryParts[i].split(\\\"=\\\",2);\\t\\t\\t\\n\\t\\t\\tqueryPartsFields[0]=queryPartsFields[0].trim();\\n\\t\\t\\t\\n\\t\\t\\tif (!queryPartsFields[0].equals(QUERY_KEY) || queryPartsFields.length!=2) {\\n\\t\\t\\t\\tcontinue;\\n\\t\\t\\t}\\n\\t\\t\\t\\n\\t\\t\\t// normalize query\\t\\t\\t\\n\\t\\t\\ttry {\\n\\t\\t\\t\\tqueryPartsFields[1]=decodeStrings(decodeNCR(java.net.URLDecoder.decode(queryPartsFields[1],\\\"ISO8859-1\\\").toLowerCase()));\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t}\\n\\t\\t\\tcatch(IllegalArgumentException e) {\\n\\t\\t\\t\\tqueryPartsFields[1]=decodeStrings(decodeNCR(queryPartsFields[1].toLowerCase()));\\n\\t\\t\\t}\\n\\t\\t\\t// remove spaces\\n\\t\\t\\tString terms[]=queryPartsFields[1].split(\\\"\\\\\\\\s\\\");\\n\\t\\t\\tqueryPartsFields[1]=\\\"\\\";\\n\\t\\t\\tfor (int j=0,k=0;j<terms.length;j++) {\\t\\t\\t\\t\\t\\n\\t\\t\\t\\tif (terms[j].equals(\\\"\\\")) {\\n\\t\\t\\t\\t\\tcontinue;\\n\\t\\t\\t\\t}\\t\\t\\t\\t\\t\\n\\t\\t\\t\\tif (k>0) {\\n\\t\\t\\t\\t\\tqueryPartsFields[1]+=\\\" \\\";\\t\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\tqueryPartsFields[1]+=terms[j];\\t\\t\\t\\t\\t\\n\\t\\t\\t\\tk++;\\n\\t\\t\\t}\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t// filter queries\\t\\t\\t\\t\\t\\n\\t\\t\\tif (queryFiltersMap.containsKey(queryPartsFields[1]) || queryPartsFields[1].startsWith(\\\"cache%3\\\") || queryPartsFields[1].equals(\\\"\\\")) {\\t\\t\\t\\t\\n\\t\\t\\t\\tcontinue;\\n\\t\\t\\t}\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t// set first page viewed\\n\\t\\t\\tif (!docsProcessed) {\\n\\t\\t\\t\\tpagesViewedDistAux[0]++;\\n\\t\\t\\t\\tdocsProcessed=true;\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t}\\n\\t\\t\\t\\n\\t\\t\\t//key=queryPartsFields[0]+\\\" \\\"+queryPartsFields[1];\\n\\t\\t\\tkey=NEW_QUERY_KEY+\\\" \\\"+queryPartsFields[1];\\t\\t\\t\\n\\t\\t\\tif ((value=queryPartsMap.get(key))==null) {\\n\\t\\t\\t\\tqueryPartsMap.put(key,1);\\n\\t\\t\\t}\\n\\t\\t\\telse {\\n\\t\\t\\t\\tqueryPartsMap.put(key,value+1);\\n\\t\\t\\t}\\n\\t\\t\\t\\n\\t\\t\\t// set submitted query\\n\\t\\t\\tif (submittedQuery!=null) { // sanity check\\n\\t\\t\\t\\tthrow new IOException(\\\"Submitted query already set.\\\");\\n\\t\\t\\t}\\n\\t\\t\\tsubmittedQuery=queryPartsFields[1];\\n\\t\\t\\t\\t\\n\\t\\t\\t// count queries per session\\t\\n\\t\\t\\tnQueriesSession++;\\n\\t\\t}\\n\\t\\treturn submittedQuery;\\n\\t}\",\n \"public void parseQueryStringAndSearch(String searchString) {\\n char[] chars = searchString.toCharArray();\\n for (int i = 0; i < chars.length; i++) {\\n Queue<Character> queue;\\n int k;\\n if (Character.isDigit(chars[i])) {\\n k = Integer.parseInt(String.valueOf(chars[i]));\\n i++;\\n queue = new LinkedList<>();\\n while (i < chars.length && chars[i] != ')') {\\n queue.add(chars[i]);\\n i++;\\n }\\n i++;\\n String query = queryToString(queue);\\n String[] terms = query.split(\\\" \\\");\\n //System.out.println(query + \\\" and k: \\\" + k);\\n positionIntersects(indexMap.get(analyzeTerm(terms[0])), indexMap.get(analyzeTerm(terms[1])), k);\\n } else {\\n queue = new LinkedList<>();\\n while (i < chars.length && !Character.isDigit(chars[i])) {\\n queue.add(chars[i]);\\n i++;\\n }\\n i--;\\n String query = queryToString(queue);\\n String[] terms = query.trim().split(\\\" \\\");\\n termQuerySearch(terms);\\n }\\n\\n }\\n\\n }\",\n \"@ActionTrigger(action=\\\"KEY-ENTQRY\\\", function=KeyFunction.SEARCH)\\n\\t\\tpublic void spriden_Search()\\n\\t\\t{\\n\\t\\t\\t\\n\\t\\t\\t\\texecuteAction(\\\"QUERY\\\");\\n\\t\\t\\t\\tgetTask().getGoqrpls().gCheckFailure();\\n\\t\\t\\t}\",\n \"List<E> queryAll(String namedQuery);\",\n \"private SeqIter query(final int db, final int qu) throws Exception {\\r\\n final int size = qressizes[db * nqueries + qu];\\r\\n final double qtime = qt[db * nqueries + qu];\\r\\n \\r\\n if(size == 0) return new SeqIter();\\r\\n \\r\\n // query and cache result\\r\\n final String que = XQM + \\\"for $i score $s in \\\" +\\r\\n queries.get(qu) + \\\" order by $s descending \\\" +\\r\\n \\\"return (basex:sum-path($i), $s, base-uri($i))\\\";\\r\\n \\r\\n final Process proc = new XQuery(que);\\r\\n final CachedOutput res = new CachedOutput();\\r\\n if(session.execute(proc)) session.output(res);\\r\\n \\r\\n final SeqIter sq = new SeqIter();\\r\\n final StringTokenizer st = new StringTokenizer(res.toString(), \\\" \\\");\\r\\n String lp = \\\"\\\";\\r\\n int z = 0;\\r\\n while(st.hasMoreTokens() && z < size) {\\r\\n qtimes[qu] += qtime;\\r\\n final String p = st.nextToken();\\r\\n if(!st.hasMoreTokens()) break;\\r\\n final String s = st.nextToken();\\r\\n if(!st.hasMoreTokens()) break;\\r\\n String uri = st.nextToken();\\r\\n //while(uri.indexOf(\\\".xml\\\") == -1) uri = st.nextToken();\\r\\n uri = uri.substring(uri.lastIndexOf('/') + 1);\\r\\n final String tmp = uri + \\\";\\\" + p;\\r\\n if(!lp.equals(tmp)) {\\r\\n final Str str = Str.get(token(uri + \\\";\\\" + p));\\r\\n str.score(Double.parseDouble(s));\\r\\n sq.add(str);\\r\\n lp = tmp;\\r\\n }\\r\\n z++;\\r\\n }\\r\\n \\r\\n Main.outln(\\\"Query % on %: %\\\", qu + 1, databases.get(db), qtime);\\r\\n return sq;\\r\\n }\",\n \"public QueryController(String[] args){\\n // Parse Args\\n QueryArgs queryArgs = new QueryArgs();\\n try {\\n queryArgs.parseArgs(args);\\n } catch (FileNotFoundException e) {\\n //e.printStackTrace();\\n System.err.println(\\\"Invalid Arguments received. Please check your arguments passed to ./search\\\");\\n return;\\n }\\n\\n // Run the Term Normaliser\\n TermNormalizer normalizer = new TermNormalizer();\\n String[] queryTerms = normalizer.transformedStringToTerms(queryArgs.queryString);\\n\\n //create the model\\n Model model = new Model();\\n model.loadCollectionFromMap(queryArgs.mapPath);\\n model.loadLexicon(queryArgs.lexiconPath);\\n model.loadInvertedList(queryArgs.invlistPath);\\n if(queryArgs.stopListEnabled)\\n {\\n model.loadStopList(queryArgs.stopListPath);\\n }\\n if(queryArgs.printSummary && queryArgs.collectionPath != \\\"\\\")\\n {\\n model.setPathToCollection(queryArgs.collectionPath);\\n }\\n\\n\\n //fetch the top results from the query module\\n QueryModule queryModule = new QueryModule();\\n queryModule.doQuery(queryTerms, model, queryArgs.bm25Enabled);\\n List<QueryResult> topResults = queryModule.getTopResult(queryArgs.maxResults);\\n\\n\\n\\n ResultsView resultsView = new ResultsView();\\n if(queryArgs.printSummary)\\n {\\n\\n DocSummary docSummary = new DocSummary();\\n for(QueryResult result:topResults)\\n {\\n // retrieve the actualy text from the document collection\\n result.setDoc(model.getDocumentCollection().getDocumentByIndex(result.getDoc().getIndex(), true));\\n\\n //set the summary on the result object by fetching it from the docSummary object\\n result.setSummaryNQB(docSummary.getNonQueryBiasedSummary(result.getDoc(), model.getStopListModule()));\\n result.setSummaryQB(docSummary.getQueryBiasedSummary(result.getDoc(), model.getStopListModule(), Arrays.asList(queryTerms)));\\n }\\n resultsView.printResultsWithSummary(topResults,queryArgs.queryLabel);\\n }else\\n {\\n resultsView.printResults(topResults,queryArgs.queryLabel);\\n }\\n\\n }\",\n \"@Test\\n\\tpublic void testKeywordQuery(){\\n\\t\\t//manager.getResponse(\\\"american football \\\"); //match multiple keywords\\n//\\t\\tmanager.getResponse(\\\"list of Bond 007 movies\\\");\\n//\\tmanager.getResponse(\\\"Disney movies\\\");\\n\\t\\t//manager.keywordQuery(\\\"Paul Brown Stadium location\\\");\\n\\t\\t//manager.keywordQuery(\\\"0Francesco\\\");\\n System.out.println(\\\"******* keyword query *******\\\");\\n\\t\\t//manager.keywordQuery(\\\"sportspeople in tennis\\\");\\n\\t\\t//manager.keywordSearch(\\\"list of movies starring Sean Connery\\\",ElasticIndex.analyzed,100 );\\n//\\t\\tmanager.keywordSearch(\\\"movies starring Sean Connery\\\",ElasticIndex.notStemmed,100 );\\n// manager.keywordSearch(\\\"musical movies tony award\\\",ElasticIndex.analyzed,100 );\\n// manager.keywordSearch(\\\"movies directed by Woody Allen\\\",ElasticIndex.analyzed,100 );\\n// manager.keywordSearch(\\\"United states professional sports teams\\\",ElasticIndex.analyzed,100 );\\n// manager.keywordSearch(\\\"computer games developed by Ubisoft\\\",ElasticIndex.analyzed,100 );\\n// manager.keywordSearch(\\\"computer games developed by Ubisoft\\\",ElasticIndex.notStemmed,100 );\\n// manager.keywordSearch(\\\"movies academy award nominations\\\",ElasticIndex.notStemmed,100 );\\n System.out.println(SearchResultUtil.toSummary(manager.keywordSearch(\\\"movies directed by Woody Allen\\\",ElasticIndex.notLowercased,20 )));\\n //manager.keywordSearch(\\\"grammy best album in 2012\\\",ElasticIndex.notAnalyzed,100 );\\n //(better than analyzed) manager.keywordSearch(\\\"grammy best album in 2012\\\",ElasticIndex.notStemmed,100 );\\n System.out.println(\\\"*****************************\\\");\\n\\n\\t\\t//manager.keywordQuery(\\\"Disney movies\\\");\\n\\t}\",\n \"public Query advancedQuery() \\n {\\n return null;\\n }\",\n \"@Override\\n public List<SearchResult> search(String queryString, int k) {\\n // TODO: YOUR CODE HERE\\n\\n // Tokenize the query and put it into a Set\\n HashSet<String> tokenSet = new HashSet<>(Searcher.tokenize(queryString));\\n\\n /*\\n * Section 1: FETCHING termId, termFreq and relevant docId from the Query\\n */\\n\\n // Init a set to store Relevant Document Id\\n HashSet<Integer> relevantDocIdSet = new HashSet<>();\\n for (String token : tokenSet) { // Iterates thru all query tokens\\n int termId;\\n try {\\n termId = indexer.getTermDict().get(token);\\n } catch (NullPointerException e) { // In case current token is not in the termDict\\n continue; // Skip this one\\n }\\n // Get the Posting associate to the termId\\n HashSet<Integer> posting = indexer.getPostingLists().get(termId);\\n relevantDocIdSet.addAll(posting); // Add them all to the Relevant Document Id set\\n }\\n\\n /*\\n * Section 2: Calculate Jaccard Coefficient between the Query and all POTENTIAL DOCUMENTS\\n */\\n\\n // ArrayList for the Final Result\\n ArrayList<SearchResult> searchResults = new ArrayList<>();\\n for (Document doc : documents) { // Iterates thru all documents\\n if (!relevantDocIdSet.contains(doc.getId())) { // If the document is relevant\\n searchResults.add(new SearchResult(doc, 0)); // Add the document as a SearchResult with zero score\\n } else {\\n HashSet<String> termIdSet = new HashSet<>(doc.getTokens()); // Get the token set from the document\\n\\n // Calculate Jaccard Coefficient of the document\\n double jaccardScore = JaccardMathHelper.calculateJaccardSimilarity(tokenSet, termIdSet);\\n\\n // Add the SearchResult with the computed Jaccard Score\\n searchResults.add(new SearchResult(doc, jaccardScore));\\n }\\n }\\n\\n return TFIDFSearcher.finalizeSearchResult(searchResults, k);\\n }\",\n \"public Query getQuery ()\\n {\\n\\n\\treturn this.q;\\n\\n }\",\n \"QueryResponse query(SolrParams solrParams) throws SolrServerException;\",\n \"@Override\\n public Data3DPlastic search() {\\n return super.search();\\n }\",\n \"public SearchResponse prepareSearchScrollRequest() {\\n GetSettingsResponse getSettingsResponse = client.admin().indices().getSettings(new GetSettingsRequest().indices(dataPointer.getIndexName())).actionGet();\\n int numShards = 0, numIndices = 0;\\n for(ObjectCursor<Settings> settings : getSettingsResponse.getIndexToSettings().values()) {\\n numShards += settings.value.getAsInt(\\\"index.number_of_shards\\\", 0);\\n numIndices++;\\n }\\n\\n int sizePerShard = (int)Math.ceil((double)SCROLL_SHARD_LIMIT/numShards);\\n logger.info(\\\"Found \\\" + numIndices + \\\" indices and \\\" + numShards + \\\" shards matching the index-pattern, thus setting the sizePerShard to \\\" + sizePerShard);\\n\\n SearchRequestBuilder searchRequestBuilder = client.prepareSearch(dataPointer.getIndexName())\\n .setTypes(dataPointer.getTypeName())\\n .setSearchType(SearchType.SCAN)\\n .addFields(\\\"_ttl\\\", \\\"_source\\\")\\n .setScroll(new TimeValue(SCROLL_TIME_LIMIT))\\n .setSize(sizePerShard);\\n\\n if (!Strings.isNullOrEmpty(query.getQuery())) {\\n searchRequestBuilder.setQuery(query.getQuery());\\n }\\n if (!Strings.isNullOrEmpty(query.getSortField())) {\\n searchRequestBuilder.addSort(new FieldSortBuilder(query.getSortField()).order(query.getSortOrder()));\\n }\\n\\n bound.map(resolvedBound -> boundedFilterFactory.createBoundedFilter(segmentationField.get(), resolvedBound))\\n .ifPresent(searchRequestBuilder::setQuery);\\n\\n return searchRequestBuilder.execute().actionGet();\\n }\",\n \"private void compute(IndexSearcher searcher, int size) throws IOException {\\n Bucket<Term> bucket = new Bucket<Term>(size);\\n DocumentCounter counter = new DocumentCounter();\\n for (TermQuery q : this._queries) {\\n searcher.search(q, counter);\\n bucket.add(q.getTerm(), counter.getCount());\\n counter.reset();\\n }\\n this._bucket = bucket;\\n }\",\n \"@Override\\n\\tprotected void executeSearch(String term) {\\n\\t\\t\\n\\t}\",\n \"@Override\\r\\n\\t\\t\\tpublic List<ScoredDocument> search(Query query) {\\n\\t\\t\\t\\treturn null;\\r\\n\\t\\t\\t}\",\n \"public void setQ(int q) {\\n this.q = q;\\n }\",\n \"private void search()\\n {\\n JTextField searchField = (currentSearchView.equals(SEARCH_PANE_VIEW))? searchBar : resultsSearchBar;\\n String searchTerm = searchField.getText();\\n \\n showTransition(2000);\\n \\n currentPage = 1;\\n showResultsView(true);\\n paginate(1, getResultsPerPage());\\n\\n if(searchWeb) showResultsTableView(WEB_RESULTS_PANE);\\n else showResultsTableView(IMAGE_RESULTS_PANE);\\n\\n \\n showSearchView(RESULTS_PANE_VIEW);\\n resultsSearchBar.setText(searchTerm);\\n }\",\n \"public interface Query {\\n\\n\\t/**\\n\\t * @return ID of the given query\\n\\t */\\n\\tint queryID();\\n\\t\\n\\t/**\\n\\t * @return given query\\n\\t */\\n\\tString query();\\n\\t\\n\\t/**\\n\\t * @return list of relevant documents to the corresponding query\\n\\t */\\n\\tList<RelevanceInfo> listOfRelevantDocuments();\\n\\t\\n\\t/**\\n\\t * @return list of results to the corresponding query after running one of the retrieval models\\n\\t */\\n\\tList<Result> resultList();\\n\\t\\n\\t/**\\n\\t * @param resultList\\n\\t * @Effects adds results to the result list of the corresponding query\\n\\t */\\n\\tvoid putResultList(List<Result> resultList);\\n}\",\n \"public void performSearch() {\\n OASelect<QueryInfo> sel = getQueryInfoSearch().getSelect();\\n sel.setSearchHub(getSearchFromHub());\\n sel.setFinder(getFinder());\\n getHub().select(sel);\\n }\",\n \"public void testSearchRules() throws Exception {\\n Project project = new Project();\\r\\n \\r\\n DateFormatSymbols symbols = new DateFormatSymbols(Locale.US);\\r\\n \\r\\n for (int i = 0; i < 12; i++) {\\r\\n \\r\\n String month = symbols.getMonths()[i];\\r\\n String shortMonth = symbols.getShortMonths()[i];\\r\\n \\r\\n // Basic project info\\r\\n project.setId(i);\\r\\n project.setCategoryId(1);\\r\\n project.setAllowGuests(true);\\r\\n project.setMembershipRequired(false);\\r\\n project.setApproved(true);\\r\\n project.setClosed(false);\\r\\n project.setPortal(false);\\r\\n \\r\\n // Unique Title\\r\\n project.setTitle(month + \\\" test project\\\");\\r\\n project.setShortDescription(month + \\\" description word\\\");\\r\\n project.setKeywords(shortMonth);\\r\\n \\r\\n // Unique Location\\r\\n project.setCity(\\\"Virginia Beach\\\");\\r\\n project.setState(\\\"VA\\\");\\r\\n project.setPostalCode(\\\"234\\\" + String.valueOf(50 + i));\\r\\n \\r\\n // Random Rating for now\\r\\n project.setRatingCount(i + 1);\\r\\n project.setRatingValue(project.getRatingCount() * StringUtils.rand(1, 5));\\r\\n project.setRatingAverage(project.getRatingValue() / project.getRatingCount());\\r\\n \\r\\n // Index it\\r\\n ProjectIndexer indexer = new ProjectIndexer();\\r\\n indexer.add(snowballWriter, project, true);\\r\\n }\\r\\n \\r\\n QueryParser parser = new QueryParser(\\\"contents\\\", snowballAnalyzer);\\r\\n \\r\\n {\\r\\n // Make sure a single matching term yields a single hit\\r\\n SearchBean search = new SearchBean();\\r\\n search.setQuery(symbols.getMonths()[0]);\\r\\n search.setLocation(\\\"Virginia Beach\\\");\\r\\n assertNotNull(search.getQuery());\\r\\n assertNotNull(search.getLocation());\\r\\n search.parseQuery();\\r\\n assertTrue(search.isValid());\\r\\n \\r\\n String queryString = SearchUtils.generateProjectQueryString(search, UserUtils.createGuestUser().getId(), -1, null);\\r\\n assertNotNull(queryString);\\r\\n \\r\\n // (approved:1)\\r\\n // AND (guests:1)\\r\\n // AND (closed:0)\\r\\n // AND (website:0)\\r\\n // AND (\\\"january\\\"^20 OR january^15 OR january*^4) AND (location:(\\\"virginia beach\\\"^30))\\r\\n \\r\\n Query query = parser.parse(queryString);\\r\\n Hits hits = getSnowballSearcher().search(query);\\r\\n assertTrue(hits.length() == 1);\\r\\n }\\r\\n \\r\\n {\\r\\n // Make sure a single matching term stem yields a single hit\\r\\n SearchBean search = new SearchBean();\\r\\n search.setQuery(symbols.getMonths()[0] + \\\"'s\\\");\\r\\n search.setLocation(\\\"Virginia Beach\\\");\\r\\n assertNotNull(search.getQuery());\\r\\n assertNotNull(search.getLocation());\\r\\n search.parseQuery();\\r\\n assertTrue(search.isValid());\\r\\n \\r\\n String queryString = SearchUtils.generateProjectQueryString(search, UserUtils.createGuestUser().getId(), -1, null);\\r\\n assertNotNull(queryString);\\r\\n \\r\\n // (approved:1)\\r\\n // AND (guests:1)\\r\\n // AND (closed:0)\\r\\n // AND (website:0)\\r\\n // AND (\\\"january's\\\"^20 OR january's^15 OR january's*^4) AND (location:(\\\"virginia beach\\\"^30))\\r\\n \\r\\n Query query = parser.parse(queryString);\\r\\n Hits hits = getSnowballSearcher().search(query);\\r\\n assertTrue(hits.length() == 1);\\r\\n }\\r\\n \\r\\n {\\r\\n // Make sure multiple matching words yield two hits\\r\\n SearchBean search = new SearchBean();\\r\\n search.setQuery(symbols.getMonths()[0] + \\\" \\\" + symbols.getMonths()[1]);\\r\\n search.setLocation(\\\"Virginia Beach\\\");\\r\\n search.parseQuery();\\r\\n assertTrue(search.isValid());\\r\\n \\r\\n String queryString = SearchUtils.generateProjectQueryString(search, UserUtils.createGuestUser().getId(), -1, null);\\r\\n assertNotNull(queryString);\\r\\n \\r\\n // (approved:1)\\r\\n // AND (guests:1)\\r\\n // AND (closed:0)\\r\\n // AND (website:0)\\r\\n // AND (\\\"january february\\\"^20 OR january^15 OR february^14 OR january*^4 OR february*^3) AND (location:(\\\"virginia beach\\\"^30))\\r\\n \\r\\n Query query = parser.parse(queryString);\\r\\n Hits hits = getSnowballSearcher().search(query);\\r\\n assertTrue(hits.length() == 2);\\r\\n }\\r\\n \\r\\n {\\r\\n // Make sure wilcards yield multiple hits\\r\\n SearchBean search = new SearchBean();\\r\\n search.setQuery(\\\"j\\\");\\r\\n search.setLocation(\\\"Virginia Beach\\\");\\r\\n search.parseQuery();\\r\\n assertTrue(search.isValid());\\r\\n \\r\\n // Look for data with a \\\"j\\\" for comparison\\r\\n int jCount = 0;\\r\\n for (int i = 0; i < symbols.getMonths().length; i++) {\\r\\n if (symbols.getMonths()[i].toLowerCase().indexOf(\\\"j\\\") > -1 ||\\r\\n symbols.getShortMonths()[i].toLowerCase().indexOf(\\\"j\\\") > -1) {\\r\\n ++jCount;\\r\\n }\\r\\n }\\r\\n assertTrue(jCount > 0);\\r\\n \\r\\n String queryString = SearchUtils.generateProjectQueryString(search, UserUtils.createGuestUser().getId(), -1, null);\\r\\n assertNotNull(queryString);\\r\\n \\r\\n // (approved:1)\\r\\n // AND (guests:1)\\r\\n // AND (closed:0)\\r\\n // AND (website:0)\\r\\n // AND (\\\"j\\\"^20 OR j^15 OR j*^4) AND (location:(\\\"virginia beach\\\"^30))\\r\\n \\r\\n Query query = parser.parse(queryString);\\r\\n Hits hits = getSnowballSearcher().search(query);\\r\\n assertTrue(hits.length() == jCount);\\r\\n }\\r\\n \\r\\n {\\r\\n // Make sure alternate locations do not yield any hits\\r\\n SearchBean search = new SearchBean();\\r\\n search.setQuery(symbols.getMonths()[0]);\\r\\n search.setLocation(\\\"Norfolk\\\");\\r\\n search.parseQuery();\\r\\n \\r\\n String queryString = SearchUtils.generateProjectQueryString(search, UserUtils.createGuestUser().getId(), -1, null);\\r\\n \\r\\n Query query = parser.parse(queryString);\\r\\n Hits hits = getSnowballSearcher().search(query);\\r\\n assertTrue(hits.length() == 0);\\r\\n }\\r\\n \\r\\n {\\r\\n // Make sure locations as query terms do not yield any hits\\r\\n SearchBean search = new SearchBean();\\r\\n search.setQuery(\\\"Virginia Beach\\\");\\r\\n search.setLocation(\\\"Virginia Beach\\\");\\r\\n search.parseQuery();\\r\\n \\r\\n String queryString = SearchUtils.generateProjectQueryString(search, UserUtils.createGuestUser().getId(), -1, null);\\r\\n \\r\\n Query query = parser.parse(queryString);\\r\\n Hits hits = getSnowballSearcher().search(query);\\r\\n assertTrue(hits.length() == 0);\\r\\n }\\r\\n }\",\n \"public WorldUps.UQuery getQueries(int index) {\\n return queries_.get(index);\\n }\",\n \"private void performNewQuery(){\\n\\n // update the label of the Activity\\n setLabelForActivity();\\n // reset the page number that is being used in queries\\n pageNumberBeingQueried = 1;\\n // clear the ArrayList of Movie objects\\n cachedMovieData.clear();\\n // notify our MovieAdapter about this\\n movieAdapter.notifyDataSetChanged();\\n // reset endless scroll listener when performing a new search\\n recyclerViewScrollListener.resetState();\\n\\n /*\\n * Loader call - case 3 of 3\\n * We call loader methods as we have just performed reset of the data set\\n * */\\n // initiate a new query\\n manageLoaders();\\n\\n }\",\n \"private void searchforResults() {\\n\\n List<String> queryList = new SavePreferences(this).getStringSetPref();\\n if(queryList != null && queryList.size() > 0){\\n Log.i(TAG, \\\"Searching for results \\\" + queryList.get(0));\\n Intent searchIntent = new Intent(Intent.ACTION_WEB_SEARCH);\\n searchIntent.addFlags(Intent.FLAG_ACTIVITY_NEW_TASK);\\n searchIntent.putExtra(SearchManager.QUERY, queryList.get(0));\\n this.startActivity(searchIntent);\\n }\\n }\",\n \"public void actionPerformed(ActionEvent e) {\\n displayInfoText(\\\" \\\");\\n // Turn the search string into a Query\\n String queryString = queryWindow.getText().toLowerCase().trim();\\n query = new Query(queryString);\\n // Take relevance feedback from the user into account (assignment 3)\\n // Check which documents the user has marked as relevant.\\n if (box != null) {\\n boolean[] relevant = new boolean[box.length];\\n for (int i = 0; i < box.length; i++) {\\n if (box[i] != null)\\n relevant[i] = box[i].isSelected();\\n }\\n query.relevanceFeedback(results, relevant, engine);\\n }\\n // Search and print results. Access to the index is synchronized since\\n // we don't want to search at the same time we're indexing new files\\n // (this might corrupt the index).\\n long startTime = System.currentTimeMillis();\\n synchronized (engine.indexLock) {\\n results = engine.searcher.search(query, queryType, rankingType);\\n }\\n long elapsedTime = System.currentTimeMillis() - startTime;\\n // Display the first few results + a button to see all results.\\n //\\n // We don't want to show all results directly since the displaying itself\\n // might take a long time, if there are many results.\\n if (results != null) {\\n displayResults(MAX_RESULTS, elapsedTime / 1000.0);\\n } else {\\n displayInfoText(\\\"Found 0 matching document(s)\\\");\\n\\n if (engine.speller != null) {\\n startTime = System.currentTimeMillis();\\n SpellingOptionsDialog dialog = new SpellingOptionsDialog(50);\\n String[] corrections = engine.speller.check(query, 10);\\n elapsedTime = System.currentTimeMillis() - startTime;\\n System.err.println(\\\"It took \\\" + elapsedTime / 1000.0 + \\\"s to check spelling\\\");\\n if (corrections != null && corrections.length > 0) {\\n String choice = dialog.show(corrections, corrections[0]);\\n if (choice != null) {\\n queryWindow.setText(choice);\\n queryWindow.grabFocus();\\n\\n this.actionPerformed(e);\\n }\\n }\\n }\\n }\\n }\",\n \"public List<Recipe> search(String queryText, Category category, CookingMethod cookingMethod);\",\n \"private void search(SearchRequest request) {\\r\\n\\t\\tif(request == null)return;\\r\\n\\t\\tList<Record> results = handler.search(request);\\r\\n\\t\\tlist.show(results);\\r\\n\\t\\tpanInfo.setNumRec(results.size());\\r\\n\\t\\tpanInfo.setTotalAmt(Record.sumBalance(results));\\r\\n\\t}\",\n \"public void testUsingQueriesFromQueryManger(){\\n\\t\\tSet<String> names = testDataMap.keySet();\\n\\t\\tUtils.prtObMess(this.getClass(), \\\"atm query\\\");\\n\\t\\tDseInputQuery<BigDecimal> atmq = \\n\\t\\t\\t\\tqm.getQuery(new AtmDiot());\\n\\t\\tMap<String, ComplexQueryResult<BigDecimal>> bdResult = \\n\\t\\t\\t\\tatmq.get(names, 1, TimeUnit.SECONDS);\\n\\t\\tCollectionsStaticMethods.prtMapItems(bdResult);\\n\\n\\t\\tUtils.prtObMess(this.getClass(), \\\"vol query\\\");\\n\\t\\tDseInputQuery<BigDecimal> volq = \\n\\t\\t\\t\\tqm.getQuery(new VolDiotForTest());\\n\\t\\tMap<String, ComplexQueryResult<BigDecimal>> dbResult = \\n\\t\\t\\t\\tvolq.get(names, 1, TimeUnit.SECONDS);\\n\\t\\tCollectionsStaticMethods.prtMapItems(dbResult);\\n\\t\\n\\t\\tUtils.prtObMess(this.getClass(), \\\"integer query\\\");\\n\\t\\tDseInputQuery<BigDecimal> strikeq = \\n\\t\\t\\t\\tqm.getQuery(new StrikeDiotForTest());\\n\\t\\tMap<String, ComplexQueryResult<BigDecimal>> strikeResult = \\n\\t\\t\\t\\tstrikeq.get(names, 1, TimeUnit.SECONDS);\\n\\t\\tCollectionsStaticMethods.prtMapItems(strikeResult);\\n\\t\\n\\t}\",\n \"PaginatedSearchResponseModel findAllPostsForUser(Party partyBean, Pageable page);\",\n \"@Override\\r\\n\\t\\t\\tpublic double matchingItems(Query query) {\\n\\t\\t\\t\\treturn 0;\\r\\n\\t\\t\\t}\",\n \"List<ShipmentInfoPODDTO> search(String query);\",\n \"@Override\\n\\t\\t\\tpublic void run() {\\n\\n\\t\\t\\t\\tpostParameters[0] = new PostParameter(\\\"keyword\\\", searchKeyword);\\n\\t\\t\\t\\tpostParameters[1] = new PostParameter(\\\"university\\\", university);\\n\\t\\t\\t\\tpostParameters[2] = new PostParameter(\\\"page\\\", Integer.toString(requestTime));\\n\\t\\t\\t\\t\\n\\t\\t\\t\\tjsonString = HttpUtil.httpRequest(HttpUtil.USER_SEARCHBOOKS, postParameters, HttpUtil.POST);\\n\\t\\t\\t\\tif (jsonString != null) {\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\tMessage msg = handler.obtainMessage();\\n\\t\\t\\t\\t\\tmsg.what = what;\\n\\t\\t\\t\\t\\thandler.sendMessage(msg);\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\telse{\\n\\t\\t\\t\\t\\thandler.sendEmptyMessage(-1);\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\",\n \"default List<SearchResult> search(String tvShowName, int season, int episode, Quality quality) {\\n return search(new SearchQuery(tvShowName, season, episode, quality));\\n }\",\n \"public void searchAndWriteQueryResultsToOutput() {\\n\\n List<String> queryList = fu.textFileToList(QUERY_FILE_PATH);\\n\\n for (int queryID = 0; queryID < queryList.size(); queryID++) {\\n String query = queryList.get(queryID);\\n // ===================================================\\n // 4. Sort the documents by the BM25 scores.\\n // ===================================================\\n HashMap<String, Double> docScore = search(query);\\n List<Map.Entry<String, Double>> rankedDocList =\\n new LinkedList<Map.Entry<String, Double>>(docScore.entrySet());\\n Collections.sort(rankedDocList, new MapComparatorByValues());\\n\\n // ===================================================\\n // 5. Write Query Results to output\\n // =================================================== \\n String outputFilePath =\\n RANKING_RESULTS_PATH + \\\"queryID_\\\" + (queryID + 1) + \\\".txt\\\";\\n StringBuilder toOutput = new StringBuilder();\\n // display results in console\\n System.out.println(\\\"Found \\\" + docScore.size() + \\\" hits.\\\");\\n int i = 0;\\n for (Entry<String, Double> scoreEntry : rankedDocList) {\\n if (i >= NUM_OF_RESULTS_TO_RETURN)\\n break;\\n String docId = scoreEntry.getKey();\\n Double score = scoreEntry.getValue();\\n String resultLine =\\n (queryID + 1) + \\\" Q0 \\\" + docId + \\\" \\\" + (i + 1) + \\\" \\\" + score + \\\" BM25\\\";\\n toOutput.append(resultLine);\\n toOutput.append(System.getProperty(\\\"line.separator\\\"));\\n System.out.println(resultLine);\\n i++;\\n }\\n fu.writeStringToFile(toOutput.toString(), outputFilePath);\\n }\\n }\",\n \"private Collection<Record> handleRequest(SearchRequest request) {\\n\\t\\tCollection<Record> resultSet = getResults(request.getQuery());\\n\\t\\treturn resultSet;\\n\\t}\",\n \"TSearchQuery prepareSearchQuery(SearchQueryDefinitionAPI searchQueryDefinition);\",\n \"public Map<String, String> directQuoteSearch (String q, String contentOrTitle) throws IOException, ParseException{\\n\\n\\t\\t\\n\\t\\tif (contentOrTitle.equals(\\\"content\\\")){\\n\\t\\t\\tcontentOrTitle=field;\\n\\t\\t} else if (contentOrTitle.equals(\\\"title\\\")){\\n\\t\\t\\tcontentOrTitle=title;\\n\\t\\t}\\n\\t\\t\\n\\t\\tIndexReader reader = DirectoryReader.open(FSDirectory.open(Paths.get(index)));\\n\\t\\tIndexSearcher searcher = new IndexSearcher(reader);\\n\\t\\tboolean raw = false;\\n\\t\\tint repeat = 0;\\n\\n\\t\\tfinal List<String> stopWords = Arrays.asList();\\n\\t\\tfinal CharArraySet stopSet = new CharArraySet(stopWords, true);\\n\\n\\t\\tAnalyzer analyzer = new StandardAnalyzer(stopSet);\\n\\t\\tAnalyzingQueryParser parser = new AnalyzingQueryParser(contentOrTitle, analyzer);\\n\\t\\t\\n\\n\\t\\t\\n\\t\\tString[] items = q.split(\\\" \\\");\\n\\t\\tList<String> itemList = Arrays.asList(items);\\n\\t\\tQuery query=null;\\n\\t\\t\\n\\t\\t\\n\\t\\tif (q.equals(\\\"\\\")){\\n\\t\\t\\tSystem.out.println(\\\"no input\\\");\\n\\t\\t\\t\\n\\t\\t} else {\\n\\t\\t\\tquery = parser.parse(q);\\n\\n\\t\\t}\\n\\n\\t\\t\\n\\t\\t\\n\\t\\tBufferedReader in = null;\\n\\t\\tin = new BufferedReader(new InputStreamReader(System.in, StandardCharsets.UTF_8));\\n\\n\\t\\tif (repeat > 0) { // repeat & time as benchmark\\n\\t\\t\\tDate start = new Date();\\n\\t\\t\\tfor (int i = 0; i < repeat; i++) {\\n\\t\\t\\t\\tsearcher.search(query, 100);\\n\\t\\t\\t}\\n\\t\\t\\tDate end = new Date();\\n\\t\\t\\tSystem.out.println(\\\"Time: \\\"+(end.getTime()-start.getTime())+\\\"ms\\\");\\n\\t\\t}\\n\\n\\t\\treturn doPagingSearch(in, searcher, query, hitsPerPage, raw, true);\\n\\t}\",\n \"public Map<String, DataModel> getQuery() {\\n if (queries == null) {\\n queries = FxSharedUtils.getMappedFunction(new FxSharedUtils.ParameterMapper<String, DataModel>() {\\n @Override\\n public DataModel get(Object key) {\\n try {\\n final FxResultSet result = EJBLookup.getSearchEngine().search((String) key, 0, -1, null);\\n return new FxResultSetDataModel(result);\\n } catch (FxApplicationException e) {\\n throw e.asRuntimeException();\\n }\\n }\\n }, true);\\n }\\n return queries;\\n }\",\n \"public PostingsList getPostings( String token ) {\\n PostingsList post = new PostingsList();\\n if(this.index.containsKey(token))\\n post = (this.index.get(token)).clone();\\n /*System.err.println(\\\"start search...\\\");\\n // Read JSON file associated to token and return it as a postingslist\\n String filename = \\\"postings/t\\\"+hash(token)+\\\".json\\\";\\n PostingsList post = new PostingsList();\\n try(Reader reader = new FileReader(filename)){\\n post = (new Gson()).fromJson(reader, PostingsList.class);\\n } catch (IOException e) {\\n e.printStackTrace();\\n }*/\\n return post;\\n }\",\n \"public static void main(String[] args) throws Exception {\\n\\n IndexManager indexManager = new IndexManager();\\n Query query = new TermQuery(new Term(\\\"name\\\", \\\"求职\\\"));\\n indexManager.excQuery(query);\\n\\n }\",\n \"public void doSearch(String query)\\n \\t{\\n \\t\\tlistener.onQueryTextSubmit(query);\\n \\t}\",\n \"@Override\\n public Set<Restaurant> getMatches(String queryString) {\\n\\n /* Setup grammar listener */\\n CharStream stream = new ANTLRInputStream(queryString);\\n QueryLexer lexer = new QueryLexer(stream);\\n TokenStream tokens = new CommonTokenStream(lexer);\\n QueryParser parser = new QueryParser(tokens);\\n ParseTree tree = parser.root();\\n ParseTreeWalker walker = new ParseTreeWalker();\\n\\n // Setup custom walker\\n QueryCreator creator = new QueryCreator();\\n walker.walk(creator, tree);\\n\\n Set<Restaurant> matches = new HashSet<Restaurant>();\\n RestaurantHandle rH = creator.getHandle();\\n Expression expTree = creator.getExpression();\\n\\n // Look through every restaurant, if one matches query add it to the set\\n for (Restaurant r : this.restaurantMap.values()) {\\n rH.setRestaurant(r);\\n if (expTree.eval()) {\\n matches.add(r);\\n }\\n }\\n\\n return matches;\\n }\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.5320133","0.52384716","0.51909447","0.51793134","0.51689667","0.5166202","0.51531994","0.511496","0.51019454","0.50839907","0.5083817","0.5078615","0.5059571","0.5005355","0.5002798","0.49850202","0.49844736","0.49838942","0.49333358","0.4925261","0.4891706","0.48816422","0.48766887","0.48577175","0.48196107","0.4803351","0.4796386","0.47883135","0.47861728","0.4770656","0.47681835","0.47563535","0.47405282","0.47252274","0.4714537","0.4702731","0.4695658","0.4680343","0.46686047","0.46577442","0.4656255","0.46429175","0.4633484","0.46318266","0.4631485","0.46303356","0.4628821","0.4622601","0.4619522","0.46154833","0.46138468","0.46138206","0.46008316","0.45999223","0.45943874","0.45833945","0.45812356","0.45800745","0.45745844","0.45735294","0.45727086","0.45721406","0.45714852","0.4571419","0.45688608","0.45562577","0.45474562","0.4543923","0.45233175","0.45175025","0.450942","0.4502668","0.44969207","0.44843516","0.44829416","0.44739553","0.44693533","0.44693476","0.44648525","0.4462255","0.44556433","0.4451209","0.44503224","0.4444923","0.44449106","0.44444564","0.44408336","0.4437653","0.44374847","0.4434583","0.4432412","0.44267124","0.44266358","0.44258076","0.44251183","0.44224918","0.44202486","0.4414116","0.4411601","0.4409517"],"string":"[\n \"0.5320133\",\n \"0.52384716\",\n \"0.51909447\",\n \"0.51793134\",\n \"0.51689667\",\n \"0.5166202\",\n \"0.51531994\",\n \"0.511496\",\n \"0.51019454\",\n \"0.50839907\",\n \"0.5083817\",\n \"0.5078615\",\n \"0.5059571\",\n \"0.5005355\",\n \"0.5002798\",\n \"0.49850202\",\n \"0.49844736\",\n \"0.49838942\",\n \"0.49333358\",\n \"0.4925261\",\n \"0.4891706\",\n \"0.48816422\",\n \"0.48766887\",\n \"0.48577175\",\n \"0.48196107\",\n \"0.4803351\",\n \"0.4796386\",\n \"0.47883135\",\n \"0.47861728\",\n \"0.4770656\",\n \"0.47681835\",\n \"0.47563535\",\n \"0.47405282\",\n \"0.47252274\",\n \"0.4714537\",\n \"0.4702731\",\n \"0.4695658\",\n \"0.4680343\",\n \"0.46686047\",\n \"0.46577442\",\n \"0.4656255\",\n \"0.46429175\",\n \"0.4633484\",\n \"0.46318266\",\n \"0.4631485\",\n \"0.46303356\",\n \"0.4628821\",\n \"0.4622601\",\n \"0.4619522\",\n \"0.46154833\",\n \"0.46138468\",\n \"0.46138206\",\n \"0.46008316\",\n \"0.45999223\",\n \"0.45943874\",\n \"0.45833945\",\n \"0.45812356\",\n \"0.45800745\",\n \"0.45745844\",\n \"0.45735294\",\n \"0.45727086\",\n \"0.45721406\",\n \"0.45714852\",\n \"0.4571419\",\n \"0.45688608\",\n \"0.45562577\",\n \"0.45474562\",\n \"0.4543923\",\n \"0.45233175\",\n \"0.45175025\",\n \"0.450942\",\n \"0.4502668\",\n \"0.44969207\",\n \"0.44843516\",\n \"0.44829416\",\n \"0.44739553\",\n \"0.44693533\",\n \"0.44693476\",\n \"0.44648525\",\n \"0.4462255\",\n \"0.44556433\",\n \"0.4451209\",\n \"0.44503224\",\n \"0.4444923\",\n \"0.44449106\",\n \"0.44444564\",\n \"0.44408336\",\n \"0.4437653\",\n \"0.44374847\",\n \"0.4434583\",\n \"0.4432412\",\n \"0.44267124\",\n \"0.44266358\",\n \"0.44258076\",\n \"0.44251183\",\n \"0.44224918\",\n \"0.44202486\",\n \"0.4414116\",\n \"0.4411601\",\n \"0.4409517\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.4517407"},"document_rank":{"kind":"string","value":"70"}}},{"rowIdx":13888,"cells":{"query":{"kind":"string","value":"query: Query inserted by the user w: Weight the tfidf score, usually very small to account for scale difference with pagerank idf_threshold: Threshold to perform index elimination / 1) Obtain union of results containing the considered query terms"},"document":{"kind":"string","value":"public PostingsList ranked_query(Query query, double w, double idf_threshold){\n long startTime = System.nanoTime();\n PostingsList result = new PostingsList();\n\n // Obtain union of terms above idf threshold if indexElimination is true\n // (Set idf_threshold to zero to disable this feature)\n Set<String> termsToConsider = this.queryTermsConsidered(query, idf_threshold);\n result = this.union_query(query, termsToConsider);\n //System.err.println(\"Size of result is \" + result.size());\n\n long estimatedTime = (System.nanoTime() - startTime)/1000000;\n System.err.println(\"* Union took: \" + estimatedTime);\n\n\n /*\n * 2) Iterate over PostingsEntries and build the solution\n */\n startTime = System.nanoTime();\n // Required when iterating over a PostingsList\n PostingsEntry postEnt = new PostingsEntry();\n // Number of documents in the collection\n double nDocs = this.docIDs.size();\n // Weight of a query vector coefficient\n double w_query_term;\n // Document tf-idf variables\n double termFrequency_doc, documentFrequency_doc, w_doc_term;\n\n for(String term : termsToConsider){\n // Obtain idf of the term\n documentFrequency_doc = Math.log(nDocs/new Double(this.idfMap.get(term)));\n\n // Obtain weight of the term\n w_query_term = query.weights.get(term);\n // Iterate over all documents containing the term and update the score(q,d)\n Iterator<PostingsEntry> it_d = result.iterator();\n while(it_d.hasNext()){\n postEnt = it_d.next();\n if (this.tfMap.get(postEnt.docID).containsKey(term)){\n termFrequency_doc = this.tfMap.get(postEnt.docID).get(term);\n w_doc_term = documentFrequency_doc*termFrequency_doc;\n postEnt.score += w_query_term*w_doc_term;\n }\n }\n }\n estimatedTime = (System.nanoTime() - startTime)/1000000;\n System.err.println(\"* Building solution took: \" + estimatedTime);\n\n /*\n * 3) Normalize the scores\n */\n startTime = System.nanoTime();\n Iterator<PostingsEntry> it = result.iterator();\n while(it.hasNext()){\n postEnt = it.next();\n postEnt.score /= (new Double(this.docLengths.get(\"\"+postEnt.docID)));//(Math.sqrt(postEnt.norm2));\n postEnt.score = w * postEnt.score + (1-w) * quality(postEnt.docID);\n }\n estimatedTime = (System.nanoTime() - startTime)/1000000;\n System.err.println(\"* Normalizing took: \" + estimatedTime);\n\n /*\n * 4) Sort the resulting solution\n */\n startTime = System.nanoTime();\n result.sort();\n estimatedTime = (System.nanoTime() - startTime)/1000000;\n System.err.println(\"* Sorting took: \" + estimatedTime);\n\n return result;\n }"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["public Set<String> queryTermsConsidered(Query query, double idf_threshold){\n double idf, nDocs = this.docIDs.size();\n String term;\n\n Set<String> termsToConsider = new HashSet<String>();\n\n Iterator<String> it = query.terms.iterator();\n while(it.hasNext()){\n term = it.next();\n idf = -1;\n if(this.idfMap.containsKey(term))\n idf = Math.log(nDocs/new Double(this.idfMap.get(term)));\n if (idf >= idf_threshold){\n termsToConsider.add(term);\n }\n /*else{\n System.err.println(term + \" not considered since idf = \" + idf);\n }*/\n }\n\n return termsToConsider;\n\n }","private HashMap<String,HashMap<String,Integer>> computeTFForQueryWords(ArrayList<String> queryPostingLines) {\n HashMap<String,HashMap<String,Integer>> queryWordsTF = new HashMap<>();\n HashMap<String,HashMap<String,Integer>> queryWordsTFPerDoc = new HashMap<>();\n String docID,term;\n Integer tf;\n HashSet<String> docIDs = new HashSet<>();\n for(String postingLine : queryPostingLines){\n HashMap<String,Integer> frequenciesInDocuments = new HashMap<>();\n term = postingLine.substring(0,postingLine.indexOf(\"|\"));\n postingLine = postingLine.substring(postingLine.indexOf(\"|\")+1);\n while(!postingLine.equals(\"\")) {\n docID = postingLine.substring(0, postingLine.indexOf(\":\"));\n docIDs.add(docID);\n postingLine = postingLine.substring(postingLine.indexOf(\"_\") + 1);\n tf = Integer.valueOf(postingLine.substring(0, postingLine.indexOf(\"_\")));\n postingLine = postingLine.substring(postingLine.indexOf(\"_\") + 1);\n frequenciesInDocuments.put(docID,tf);\n }\n queryWordsTF.put(term,frequenciesInDocuments);\n }\n\n ArrayList<String> allTermsInQuery = new ArrayList<>(queryWordsTF.keySet());\n for(String doc : docIDs){\n HashMap<String,Integer> tfsInDoc = new HashMap<>();\n for(String termInQuery : allTermsInQuery){\n HashMap<String,Integer> termsTFInDoc = queryWordsTF.get(termInQuery);\n if(termsTFInDoc.containsKey(doc)){\n tfsInDoc.put(termInQuery,termsTFInDoc.get(doc));\n }\n }\n queryWordsTFPerDoc.put(doc,tfsInDoc);\n }\n return queryWordsTFPerDoc;\n }","public List<IResult> getResults(List<Integer> relatedDocs, String query) {\r\n\r\n // results\r\n List<IResult> rs = new ArrayList<>();\r\n List<Double> documentVector, queryVector = new ArrayList<>();\r\n\r\n Map<String, Integer> termFreqs = this.preprocessor.processQuery(query);\r\n\r\n for(String op : new String[]{\"and\", \"or\", \"not\"}) {\r\n termFreqs.remove(op);\r\n }\r\n\r\n\r\n double highestVal = 0;\r\n\r\n // query TF-IDF vector\r\n for(String term : termFreqs.keySet()) {\r\n\r\n // unknown term == contained in no doc\r\n if(!this.index.getDict().containsKey(term)) {\r\n continue;\r\n }\r\n\r\n // # docs where term occurs in\r\n int termTotalFreq = this.index.getTermInDocCount(term);\r\n\r\n // query tf-idf vector\r\n double qTfIdf = this.tfidf.tfidfQuery(termFreqs.get(term), termTotalFreq);\r\n queryVector.add(qTfIdf);\r\n\r\n if(qTfIdf > highestVal) highestVal = qTfIdf;\r\n }\r\n\r\n // query vector normalization\r\n for(int i = 0; i < queryVector.size(); i++) {\r\n queryVector.set(i, queryVector.get(i)/highestVal);\r\n }\r\n\r\n\r\n for(int docId : relatedDocs) {\r\n documentVector = new ArrayList<>();\r\n highestVal = 0;\r\n\r\n for(String term : termFreqs.keySet()) {\r\n\r\n // unknown term == contained in no doc\r\n if(!this.index.getDict().containsKey(term)) {\r\n continue;\r\n }\r\n\r\n // document tf-idf vector\r\n double dTfIdf = this.tfidf.getTfIdf(term, docId);\r\n documentVector.add(dTfIdf);\r\n\r\n if(dTfIdf > highestVal) highestVal = dTfIdf;\r\n }\r\n\r\n // document vector normalization\r\n for(int i = 0; i < documentVector.size(); i++) {\r\n documentVector.set(i, documentVector.get(i)/highestVal);\r\n }\r\n\r\n Result result = new Result();\r\n result.setDocumentId(this.docs.get(docId).getUrl());\r\n result.setDocument(this.docs.get(docId));\r\n result.setScore((float) CosineSimilarity.process(documentVector, queryVector));\r\n rs.add(result);\r\n }\r\n\r\n Collections.sort(rs, new ResultComparator());\r\n\r\n // limit number of results\r\n if(rs.size() > IndexerConfig.MAX_RESULT_COUNT)\r\n rs = rs.subList(0, IndexerConfig.MAX_RESULT_COUNT);\r\n\r\n // rank it\r\n for(int i = 0; i < rs.size(); i++) {\r\n ((Result) rs.get(i)).setRank (i + 1);\r\n }\r\n\r\n return rs;\r\n }","public HashMap<String, Double> search(String query) {\n // ===================================================\n // 1. Fetch all inverted lists corresponding to terms\n // in the query.\n // ===================================================\n String[] terms = query.split(\" \");\n HashMap<String, Integer> qf = new HashMap<String, Integer>();\n // Calculate term frequencies in the query\n for (String term : terms) {\n if (qf.containsKey(term))\n qf.put(term, qf.get(term) + 1);\n else\n qf.put(term, 1);\n }\n HashMap<String, Double> docScore = new HashMap<String, Double>();\n for (Entry<String, Integer> termEntry : qf.entrySet()) {\n String term = termEntry.getKey();\n int qfi = termEntry.getValue();\n\n // ===================================================\n // 2. Compute BM25 scores for documents in the lists.\n // Make a score list for documents in the inverted\n // lists. Assume that no relevance information is \n // available. For parameters, use k1=1.2, b=0.75, \n // k2=100.\n // ===================================================\n double k1 = 1.2;\n double b = 0.75;\n double k2 = 100;\n int ni = invIndex.get(term).size();\n\n\n for (Entry<String, IndexEntry> invListEntry : invIndex.get(term).entrySet()) {\n String docID = invListEntry.getKey();\n double bm25Score;\n if (docScore.containsKey(docID))\n bm25Score = docScore.get(docID);\n else\n bm25Score = 0;\n\n // length of the document\n int dl = docStat.get(docID);\n // frequency of the term in the document\n int fi = invListEntry.getValue().getTf();\n double K = k1 * ((1 - b) + b * ((double) dl / avdl));\n\n // ===================================================\n // 3. Accumulate scores for each term in a query\n // on the score list.\n // ===================================================\n bm25Score += Math.log((N - ni + 0.5) / (ni + 0.5))\n * (((k1 + 1) * fi * (k2 + 1) * qfi) / ((K + fi) * (k2 + qfi)));\n docScore.put(docID, bm25Score);\n }\n }\n\n return docScore;\n }","public /*TreeMap<String, Float>*/void getTopnTermsOverlapWithQuery() throws IOException, ParseException{\n\t\tString outputfile = \"./output/score/test3.txt\";\n\n\t\tFileOutputStream out = new FileOutputStream(outputfile);\n\t\tPrintStream ps = new PrintStream(out);\n\t\t/*-------------------------------------------------------------------------------*/\n\n\t\tTreeMap<String,Float> termsscoressorted = null;\n\t\tCollectionReader reader = new CollectionReader(indexDir); \n\t\tIndexReader ir = reader.getIndexReader();\t\t\n\n\t\tTopicsInMemory topics = new TopicsInMemory(\"data/CLEF-IP-2010/PAC_test/topics/PAC_topics-test2.xml\"/*omit-PAC-1094.xml\"*/);\n\t\tfor(Map.Entry<String, PatentDocument> topic : topics.getTopics().entrySet()){\n\t\t\tString qUcid = topic.getValue().getUcid();\n\t\t\tString queryid = topic.getKey();\n\t\t\tString queryName = topic.getKey() + \"_\" + topic.getValue().getUcid();\n\t\t\tString queryfile = topic.getKey() + \"_\" + topic.getValue().getUcid() + \".xml\";\n\n\t\t\t/*System.out.println(\"=========================================\");\n\t\t\tSystem.out.println(queryName);\n\t\t\tSystem.out.println(\"=========================================\");*/\n\t\t\t/*int docid = reader.getDocId(\"UN-EP-0663270\", PatentDocument.FileName);\n\t\t\tir.getTermVector(docid, field) getTermVectors(b);*/\n\n\t\t\tEvaluateResults er = new EvaluateResults();\n\t\t\tArrayList<String> tps = er.evaluatePatents(queryid, \"TP\");\n\t\t\tArrayList<String> fps = er.evaluatePatents(queryid, \"FP\");\n\t\t\tHashMap<String, Float> /*TFreqs*/ termsscores = new HashMap<>();\n\n\n\t\t\t/*--------------------------------- Query Words -------------------------------*/\n\t\t\t//\t\t\tHashMap<String, Integer> query_termsfreqspair = reader.gettermfreqpair(qUcid, PatentDocument.Description);\n\t\t\tHashSet<String> query_terms = reader.getDocTerms(qUcid, PatentDocument.Description);\n\t\t\t//\t\t\tSystem.out.println(query_termsfreqspair.size() +\"\\t\"+ query_termsfreqspair);\n//\t\t\tSystem.out.println(query_terms.size() + \"\\t\" + query_terms);\n\t\t\t/*-----------------------------------------------------------------------------*/\t\t\t\n\n\n\t\t\t//\t\t\tSystem.out.println(\"-----TPs----\");\n\t\t\tfor (String tp : tps) {\n\t\t\t\t/*System.out.println(\"---------\");\n\t\t\t\tSystem.out.println(tp);*/\n\t\t\t\tHashMap<String, Integer> termsfreqsTP = reader.gettermfreqpairAllsecs(\"UN-\" + tp);\n\n\t\t\t\tfor(Entry<String, Integer> tfTP:termsfreqsTP.entrySet()){\n\t\t\t\t\tif(termsscores.containsKey(tfTP.getKey())){\n\t\t\t\t\t\ttermsscores.put(tfTP.getKey(), termsscores.get(tfTP.getKey()) + (float)tfTP.getValue()/tps.size());\n\t\t\t\t\t}else{\n\t\t\t\t\t\t//\t\t\t\t\t\tfloat test = (float)t.getValue()/tps.size();\n\t\t\t\t\t\t//\t\t\t\t\t\tSystem.out.println(test);\n\t\t\t\t\t\ttermsscores.put(tfTP.getKey(), (float)tfTP.getValue()/tps.size());\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t\t//\t\t\t\tSystem.out.println(termsscores.size() + \" \" + termsscores);\t\t\t\t\t\n\t\t\t}\n\n\t\t\t/*System.out.println();\n\t\t\tSystem.out.println(\"-----FNs----\");*/\n\t\t\tfor (String fp : fps) {\n\t\t\t\t/*System.out.println(\"---------\");\n\t\t\t\tSystem.out.println(fp);*/\n\t\t\t\tHashMap<String, Integer> termsfreqsFP = reader.gettermfreqpairAllsecs(\"UN-\" + fp);\n\n\t\t\t\tfor(Entry<String, Integer> t:termsfreqsFP.entrySet()){\n\t\t\t\t\tif(termsscores.containsKey(t.getKey())){\n\t\t\t\t\t\ttermsscores.put(t.getKey(), termsscores.get(t.getKey()) - (float)t.getValue()/fps.size());\n\t\t\t\t\t}else{\t\t\t\t\t\t\n\t\t\t\t\t\ttermsscores.put(t.getKey(), -(float)t.getValue()/fps.size());\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t\t//\t\t\t\tSystem.out.println(TFreqs.size() + \" \" + TFreqs);\n\t\t\t}\n\t\t\t//\t\t\tSystem.out.println(termsscores.size() + \" \" + termsscores);\n\t\t\tValueComparator bvc = new ValueComparator(termsscores);\n\t\t\ttermsscoressorted = new TreeMap<String,Float>(bvc);\t\t\t\n\t\t\ttermsscoressorted.putAll(termsscores);\n\t\t\tSystem.out.println(queryid + \"\\t\"+ termsscoressorted.size() + \"\\t\" + termsscoressorted/*.keySet()*/);\n\t\t\tint overlap = 0;\n\t\t\tint i = 0;\n\t\t\tfor(Entry<String, Float> scoresorted:termsscoressorted.entrySet()){\n\t\t\t\ti++;\n\t\t\t\tif(i<=100){\n\t\t\t\t\tif(query_terms.contains(scoresorted.getKey())){\n\t\t\t\t\t\toverlap++;\n\t\t\t\t\t}\t\t\t\t\t\n\t\t\t\t}\n\t\t\t}\t\n\t\t\tSystem.out.println(queryName + \"\\t\"+overlap);\n//\t\t\tps.println(queryName + \"\\t\"+overlap);\n\t\t}\n\t}","private static void statsForQuery(String query) {\n\t\tHashMap<String,Integer> oldTerms=newTerms; // record the terms to analyze modified queries\n\t\tnewTerms=new HashMap<String,Integer>();\n\t\t\t\t\n\t\tString terms[]=query.split(\"\\\\s\");\t\t\t\t\n\t\tint matchingTerms=0;\n\t\tint matchingTermsStopwords=0;\n\t\tint matchingTermsOrder=0;\n\t\tfor (int j=0;j<terms.length;j++) {\n\t\t\tif (!terms[j].equals(\"\")) {\n\t\t\t \tif (oldTerms.containsKey(terms[j])) {\n\t\t\t \t\tmatchingTerms++;\t\t\t\t\t \n\t\t\t \t\tif (stopwordsMap.containsKey(terms[j])) { // match if it is stopword\n\t\t\t \t\t\tmatchingTermsStopwords++;\n\t\t\t \t\t}\n\t\t\t \t\tif (oldTerms.get(terms[j])==j) { // match if it has the same order\n\t\t\t \t\t\tmatchingTermsOrder++;\n\t\t\t \t\t}\n\t\t\t \t}\n\t\t\t \tnewTerms.put(terms[j],j);\n\t\t\t}\n\t\t}\t\n\n\t\tif (newTerms.size()==oldTerms.size() && matchingTerms==oldTerms.size() && matchingTerms>0) { // the queries have the same terms\n\t\t totalEqualTermsQueries++;\n\t\t\t\t \t\t\t\t \t\t\t\t\t\t \t\t\t\t \t\t\t\t \n\t\t if (matchingTermsStopwords==oldTerms.size()) {\n\t\t \ttotalEqualTermsStopwordsQueries++;\n\t\t }\n\t\t if (matchingTermsOrder==oldTerms.size()) {\n\t\t \ttotalEqualTermsOrderQueries++;\n\t\t }\n\t\t if (query.equals(oldQuery)) {\n\t\t \ttotalIdenticalQueries++;\n\t\t }\n\t\t if (sessionQueries.contains(query)) {\n\t\t \ttotalIdenticalSessionQueries++;\n\t\t }\n\t\t}\n\t\telse if (matchingTerms-matchingTermsStopwords>0) { // the queries have at least one term equal and diferent from a stopword\n\t\t totalModifiedQueries++;\n\t\t int index=newTerms.size()-oldTerms.size()+N_MODIFIED_TERMS_RANGE/2;\n\t\t if (index<0) {\n\t\t \tindex=0;\n\t\t }\n\t\t else if (index>N_MODIFIED_TERMS_RANGE-1) {\n\t\t \tindex=N_MODIFIED_TERMS_RANGE-1;\n\t\t }\n\t\t nModifiedTerms[index]++;\n\t\t}\n\t\toldQuery=query; \n\t\t\t\t\t\t\n\t\t// store session query\n\t\tsessionQueries.add(query);\n\t}","static void returnTfIdfResults() {\n\t\tSet<String> specificWords = findKeywords();\n\n\t\t// for every phrase\n\t\tfor (String word : specificWords) {\n\t\t\t// get the total number of documents\n\t\t\tdouble totalSize = size;\n\n\t\t\t// get the collection of documents containing that word\n\t\t\tCollection<File> containingWordSet = invertedMap.getValues(word);\n\n\t\t\t// makes a new one if null (for ease of code)\n\t\t\tif (containingWordSet == null) {\n\t\t\t\tcontainingWordSet = new HashSet<File>();\n\t\t\t}\n\n\t\t\t// the number containing the word\n\t\t\tdouble numContainingWord = containingWordSet.size();\n\n\t\t\t// get the idf (log(total/(1 + |# contain word|)\n\t\t\t// it is normalize with 1 to prevent division by 0\n\t\t\tdouble idf = Math.log(totalSize / (1 + numContainingWord));\n\n\t\t\t// System.out.println(\"------------------\");\n\t\t\t// System.out.println(word + \" totalSize \" + totalSize);\n\t\t\t// System.out.println(word + \" numContainingWord \" +\n\t\t\t// numContainingWord);\n\t\t\t// System.out.println(word + \" idf \" + idf);\n\t\t\t// System.out.println(\"------------------\");\n\n\t\t\t// set the wordscore to 0\n\t\t\tdouble wordScore = 0;\n\n\t\t\t// for all of the files with the word\n\t\t\tfor (File file : containingWordSet) {\n\t\t\t\tString fileName = file.getName();\n\n\t\t\t\t// get the phrase count for this document\n\t\t\t\tInteger phraseCount = phraseCountMap.get(fileName);\n\t\t\t\tdouble numPhrases = phraseCount.doubleValue();\n\n\t\t\t\t// get the word frequency map for this page\n\t\t\t\tHashMap<String, Integer> docFreqMap = wordFreqMap.get(fileName);\n\t\t\t\tInteger freq = docFreqMap.get(word);\n\n\t\t\t\t// otherwise, get the tf\n\t\t\t\tdouble tf;\n\t\t\t\tif (freq == null) {\n\t\t\t\t\t// if it's not present, it's 0\n\t\t\t\t\ttf = 0;\n\t\t\t\t} else {\n\t\t\t\t\t// otherwise, it's the value\n\t\t\t\t\ttf = freq / numPhrases;\n\t\t\t\t\t// System.out.println(tf);\n\t\t\t\t}\n\n\t\t\t\t// multiply for this score\n\t\t\t\tdouble score = tf * idf;\n\n\t\t\t\t// add it to the page score\n\t\t\t\twordScore += score;\n\t\t\t}\n\n\t\t\t// make a node with the sum of tf-idf for all relevant phrases and\n\t\t\t// add to pq\n\t\t\tWordNode w = new WordNode(word, wordScore);\n\t\t\tpq.add(w);\n\t\t}\n\t}","@Override\n protected QueryProcessor computeResult(ResultComputingContext<? extends TermsIndexingEquipment> context) {\n final TermWeight idf = context.preliminaryResult(CalculatingInvertedTermFrequency.getInstance());\n final TermDocumentWeight tf = context.preliminaryResult(context.equipment().termFrequencyCalculation());\n //for obtaining set of terms in each document.\n final EachDocumentTermsExtraction documentsTerms = context.preliminaryResult(ExtractingEachDocumentTerms.getInstance());\n //for obtaining document length\n final Map<Document, TermsOccurences> termsOccurences = context.preliminaryResult(CountingTermsOccurencesInEachDocument.getInstance());\n final double averageDocLength = context.preliminaryResult(ComputingAverageDocumentLength.getInstance());\n\n QueryProcessor res = new QueryProcessor() {\n @Override\n public DocumentRanker rankForQuery(final Collection<String> query) {\n return new DocumentRanker() {\n @Override\n public double score(Document document) {\n /*\n * BM25 score is calculated here\n */\n\n //obtaining the set of terms in the document\n Set<String> allDocTerms = documentsTerms.termsExtractedFromDocument(document).allTerms();\n\n //keeping only the query terms that are in the document\n Collection<String> relevantTerms = new LinkedHashSet<>(query);\n relevantTerms.retainAll(allDocTerms);\n\n //compute score using a sum formula on each query term\n int docLength = termsOccurences.get(document).totalNumberOfOccurences();\n double score = 0.0;\n for (String term : relevantTerms) {\n double termIDF = idf.weight(term);\n double termTF = tf.weight(term, document);\n\n score += termIDF * (termTF * (k1 + 1)) / (termTF + k1 * (1 - b + b * (docLength / averageDocLength)));\n }\n\n return score;\n }\n };\n\n }\n };\n\n logger.log(Level.INFO, \"Just created a BM25 query processor with parameters : \" + \"k1={0}, b={1}\", new Object[]{k1, b});\n\n return res;\n }","public TreeSet<TermFrequencyPerFile> search(Query query)\n\t\t\tthrows SearcherException, InterruptedException, ExecutionException {\n\t\tClause tempClause;\n\t\t// Clauses with (start operator|default operator)\n\t\tList<Clause> andAndClauses = new LinkedList<Clause>();\n\t\tList<Clause> andOrClauses = new LinkedList<Clause>();\n\t\tList<Clause> orAndClauses = new LinkedList<Clause>();\n\t\tList<Clause> orOrClauses = new LinkedList<Clause>();\n\t\tList<Clause> tempClauses;\n\t\t// Sets with the clauses of (start operator|default operator)\n\t\tList<Future<TreeSet<TermFrequencyPerFile>>> andSets =\n\t\t\t\tnew LinkedList<Future<TreeSet<TermFrequencyPerFile>>>();\n\t\tList<Future<TreeSet<TermFrequencyPerFile>>> orSets =\n\t\t\t\tnew LinkedList<Future<TreeSet<TermFrequencyPerFile>>>();\n\t\t// Result set from sub-query\n\t\tList<TreeSet<TermFrequencyPerFile>> subAndSet =\n\t\t\t\tnew LinkedList<TreeSet<TermFrequencyPerFile>>();\n\t\tList<TreeSet<TermFrequencyPerFile>> subOrSet =\n\t\t\t\tnew LinkedList<TreeSet<TermFrequencyPerFile>>();\n\t\tList<TreeSet<TermFrequencyPerFile>> subNotSet =\n\t\t\t\tnew LinkedList<TreeSet<TermFrequencyPerFile>>();\n\t\t// Result set\n\t\tTreeSet<TermFrequencyPerFile> result;\n\t\t\n\t\tfor (int i = 0; i < query.size(); ++i) {\n\t\t\ttempClause = query.getClause(i);\n\t\t\t\n\t\t\tif (tempClause.isQuery()) {\n\t\t\t\tassignAllWorks(andAndClauses, andOrClauses\n\t\t\t\t\t\t, orAndClauses, orOrClauses, andSets, orSets);\n\t\t\t\tif ((tempClause.getStartOP() == null)\n\t\t\t\t\t\t|| tempClause.getStartOP().equals(Operator.AND)) {\n\t\t\t\t\tsubAndSet.add(search((Query) tempClause.getComponent()));\n\t\t\t\t} else if (tempClause.getStartOP().equals(Operator.OR)) {\n\t\t\t\t\tsubOrSet.add(search((Query) tempClause.getComponent()));\n\t\t\t\t} else {\n\t\t\t\t\tsubNotSet.add(search((Query) tempClause.getComponent()));\n\t\t\t\t}\n\t\t\t}\n\t\t\t\n\t\t\t// Group similar clauses\n\t\t\ttempClauses = termSearch(tempClause, andAndClauses\n\t\t\t\t\t, andOrClauses, orAndClauses, orOrClauses);\n\t\t\t\n\t\t\t// Assign work\n\t\t\tif (tempClauses != null) {\n\t\t\t\t// A clause is ready to get queried\n\t\t\t\tassignWork(tempClauses, andSets, orSets);\n\t\t\t} else {\n\t\t\t\tif ((tempClause.getStartOP() != null) \n\t\t\t\t\t\t&& tempClause.getStartOP().equals(Operator.NOT)) {\n\t\t\t\t\tTerm t = (Term)tempClause.getComponent();\n\t\t\t\t\tassert(t.size() == 1);\n\t\t\t\t\ttry {\n\t\t\t\t\t\tsubNotSet.add(notSearch(tempClause));\n\t\t\t\t\t} catch (ClassNotFoundException e) {\n\t\t\t\t\t\te.printStackTrace();\n\t\t\t\t\t} catch (IOException e) {\n\t\t\t\t\t\te.printStackTrace();\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t\tassignAllWorks(andAndClauses, andOrClauses\n\t\t\t\t, orAndClauses, orOrClauses, andSets, orSets);\n\t\t\n\t\t// Wait for AND set result\n\t\tfor (Future<TreeSet<TermFrequencyPerFile>> future: andSets) {\n\t\t\tsubAndSet.add(future.get());\n\t\t}\n\t\t// Integrate All relations at current clause level\n\t\tresult = intersect(subAndSet);\n\t\t\n\t\t// Wait for OR set result\n\t\tfor (Future<TreeSet<TermFrequencyPerFile>> future: orSets) {\n\t\t\tsubOrSet.add(future.get());\n\t\t}\n\t\tfor (TreeSet<TermFrequencyPerFile> set: subOrSet) {\n\t\t\tresult.addAll(set);\n\t\t}\n\n\t\t// Exclude NOT queries\n\t\tresult.removeAll(subNotSet);\n\t\t\n\t\treturn result;\n\t}","private void termQuerySearch(String[] terms) {\n for (String term : terms) {\n LinkedList<TermPositions> postingLists = indexMap.get(analyzeTerm(term));\n if (postingLists != null) {\n for (TermPositions matches : postingLists) {\n double score = (double) 1 + Math.log((double) matches.getPositionList().size()) *\n Math.log((double) N / (double) postingLists.size());\n resultsCollector.add(new DocCollector(matches.getDocId(), score));\n }\n }\n }\n }","protected void calculaterVSMforAllQuery(String type)\n {\n ArrayList<String> resultAll=new ArrayList<>();\n for(String qid: this.queryTFscore.keySet())\n {\n //System.out.println(qid+\"----------------------------------------------------------------------------------------------\"+this.maxLength+\" \"+this.minLength);\n HashMap<String, Double> queryInfo=this.queryTFscore.get(qid);\n System.out.println(qid+\" \"+queryInfo);\n HashMap <String, Double> finalResult=new HashMap<>();\n for(String docID:this.corpusTFscore.keySet())\n {\n HashMap<String, Double> docInfo=this.corpusTFscore.get(docID);\n double upperscore=this.calculateUpperPart(queryInfo, docInfo, docID);\n double lowerscore=this.calculateLowerPart(queryInfo, docInfo, docID);\n double score=0.0;\n \n //Calculate gTerms\n //Calculate Nx\n double Nx=0.0;\n if(this.LengthInfoMap.containsKey(docID)){\n Nx=(this.LengthInfoMap.get(docID)-this.minLength)/(this.maxLength-this.minLength);\n }\n \n //Calculate gTerms\n double gTerms=1/(1+Math.exp(-Nx));\n if(upperscore!=0&&lowerscore!=0) score=gTerms*(upperscore)/lowerscore;\n //if(upperscore!=0&&lowerscore!=0) score=(upperscore)/lowerscore;\n if(score>0) {\n //System.out.println(docID+\" = \"+score);\n finalResult.put(docID, score);\n }\n \n }\n HashMap<String, Double> normalizedAndSortedResult=doNormalization(finalResult);\n //HashMap<String, Double> sortedResult=MiscUtility.sortByValues(finalResult);\n //System.out.println(normalizedAndSortedResult);\n int count=0;\n for(String docID:normalizedAndSortedResult.keySet())\n {\n if(count>9) break;\n String fullPath=this.corpusMap.get(docID);\n resultAll.add(qid+\",\"+fullPath+\",\"+normalizedAndSortedResult.get(docID));\n count++;\n }\n }\n ContentWriter.writeContent(this.base+\"\\\\Result\\\\\"+this.corpus+\"_result\"+type+\".txt\", resultAll);\n }","public static void QueryVector() {\n for(Entry<String, List<Double>> entry: wtgMap.entrySet()){\n List<Double> queryValue = new ArrayList();\n queryValue = entry.getValue();\n double temp = queryValue.get(totaldocument);\n\n query.add(temp);\n }\n }","public Query( String queryString ) {\r\n\tStringTokenizer tok = new StringTokenizer( queryString );\r\n\twhile ( tok.hasMoreTokens() ) {\r\n\t terms.add( tok.nextToken() );\r\n\t weights.add( new Double(1) );\r\n\t} \r\n }","@Override\n public double score(Document document) {\n Set<String> allDocTerms = documentsTerms.termsExtractedFromDocument(document).allTerms();\n\n //keeping only the query terms that are in the document\n Collection<String> relevantTerms = new LinkedHashSet<>(query);\n relevantTerms.retainAll(allDocTerms);\n\n //compute score using a sum formula on each query term\n int docLength = termsOccurences.get(document).totalNumberOfOccurences();\n double score = 0.0;\n for (String term : relevantTerms) {\n double termIDF = idf.weight(term);\n double termTF = tf.weight(term, document);\n\n score += termIDF * (termTF * (k1 + 1)) / (termTF + k1 * (1 - b + b * (docLength / averageDocLength)));\n }\n\n return score;\n }","public PostingsList phrase_query(Query query){\n\n LinkedList<PostingsList> listQueriedPostings = new LinkedList<PostingsList>();\n // List with postings corresponding to the queries\n for (int i = 0; i<query.size(); i++){\n // If any query has zero matches, return 0 results\n //if(!(new File(\"postings/t\"+hash(query.terms.get(i))+\".json\")).exists()){\n if (!this.index.containsKey(query.terms.get(i))){\n return null;\n }\n // Otherwise store postings in the list\n listQueriedPostings.add(this.getPostings(query.terms.get(i)));\n }\n\n PostingsList result = new PostingsList();\n result = listQueriedPostings.get(0);\n\n // In case only one word is queried\n if (listQueriedPostings.size() == 1){\n return result;\n }\n\n // Apply algorithm as many times as words in the query\n for(int i = 1; i < listQueriedPostings.size(); i++){\n result = phrase_query(result, listQueriedPostings.get(i));\n if (result.isEmpty()){\n return null;\n }\n }\n return result;\n }","@Override\n public List<SearchResult> search(String queryString, int k) {\n // TODO: YOUR CODE HERE\n\n // Tokenize the query and put it into a Set\n HashSet<String> tokenSet = new HashSet<>(Searcher.tokenize(queryString));\n\n /*\n * Section 1: FETCHING termId, termFreq and relevant docId from the Query\n */\n\n // Init a set to store Relevant Document Id\n HashSet<Integer> relevantDocIdSet = new HashSet<>();\n for (String token : tokenSet) { // Iterates thru all query tokens\n int termId;\n try {\n termId = indexer.getTermDict().get(token);\n } catch (NullPointerException e) { // In case current token is not in the termDict\n continue; // Skip this one\n }\n // Get the Posting associate to the termId\n HashSet<Integer> posting = indexer.getPostingLists().get(termId);\n relevantDocIdSet.addAll(posting); // Add them all to the Relevant Document Id set\n }\n\n /*\n * Section 2: Calculate Jaccard Coefficient between the Query and all POTENTIAL DOCUMENTS\n */\n\n // ArrayList for the Final Result\n ArrayList<SearchResult> searchResults = new ArrayList<>();\n for (Document doc : documents) { // Iterates thru all documents\n if (!relevantDocIdSet.contains(doc.getId())) { // If the document is relevant\n searchResults.add(new SearchResult(doc, 0)); // Add the document as a SearchResult with zero score\n } else {\n HashSet<String> termIdSet = new HashSet<>(doc.getTokens()); // Get the token set from the document\n\n // Calculate Jaccard Coefficient of the document\n double jaccardScore = JaccardMathHelper.calculateJaccardSimilarity(tokenSet, termIdSet);\n\n // Add the SearchResult with the computed Jaccard Score\n searchResults.add(new SearchResult(doc, jaccardScore));\n }\n }\n\n return TFIDFSearcher.finalizeSearchResult(searchResults, k);\n }","private static List<SearchData> booleanSearchFrequency(Query query, Indexer si) {\n Tokenizer tkn = new SimpleTokenizer();\n tkn.tokenize(query.getStr(), \"[a-zA-Z]{3,}\", true, true);\n List<SearchData> searchList = new ArrayList<>();\n LinkedList<Token> wordsList = tkn.getTokens();\n Iterator<Token> wordsIt = wordsList.iterator();\n HashMap<String, LinkedList<Posting>> indexer = si.getIndexer();\n int idx;\n SearchData searched_doc;\n\n while (wordsIt.hasNext()) {\n String word = wordsIt.next().getSequence();\n if (indexer.containsKey(word)) {\n\n LinkedList<Posting> posting = indexer.get(word);\n\n for (Posting pst : posting) {\n\n SearchData sd = new SearchData(query, pst.getDocId());\n\n if (!searchList.contains(sd)) {\n sd.setScore(pst.getTermFreq());\n searchList.add(sd);\n } else {\n idx = searchList.indexOf(sd);\n searched_doc = searchList.get(idx);\n searched_doc.setScore(searched_doc.getScore() + pst.getTermFreq());\n }\n }\n }\n }\n\n Collections.sort(searchList);\n\n return searchList;\n }","private double rankByBM25(List<String> query, String docId, HashMap<String,Integer> queryWordsTFPerDoc){\n int termFrequency, documentFrequency;\n double numOfDocs = documentDetails.size(), idf, rank = 0, k = 1.2, b = 0.75, numerator, denominator;\n int documentLength = Integer.valueOf(documentDetails.get(docId)[3]);\n\n for(String term : query){\n if(queryWordsTFPerDoc.containsKey(term.toUpperCase())) {\n term = term.toUpperCase();\n }\n else if(queryWordsTFPerDoc.containsKey(term.toLowerCase())){\n term = term.toLowerCase();\n }\n termFrequency = queryWordsTFPerDoc.getOrDefault(term,0);\n\n if(termFrequency != 0) {\n documentFrequency = Integer.valueOf(termsDF.get(term));\n idf = log2(numOfDocs / documentFrequency);\n\n numerator = termFrequency * (k + 1);\n denominator = termFrequency + k * (1 - b + b * (documentLength / averageDocumentLength));\n\n rank += idf * (numerator / denominator);\n }\n }\n return rank;\n }","private static List<SearchData> booleanSearchWord(Query query, Indexer si) {\n Tokenizer tkn = new SimpleTokenizer();\n tkn.tokenize(query.getStr(), \"[a-zA-Z]{3,}\", true, true);\n List<SearchData> searchList = new ArrayList<>();\n LinkedList<Token> wordsList = tkn.getTokens();\n Iterator<Token> wordsIt = wordsList.iterator();\n HashMap<String, LinkedList<Posting>> indexer = si.getIndexer();\n int idx;\n SearchData searched_doc;\n\n while (wordsIt.hasNext()) {\n String word = wordsIt.next().getSequence();\n if (indexer.containsKey(word)) {\n\n LinkedList<Posting> posting = indexer.get(word);\n\n for (Posting pst : posting) {\n\n SearchData sd = new SearchData(query, pst.getDocId());\n\n if (!searchList.contains(sd)) {\n sd.setScore(1);\n searchList.add(sd);\n } else {\n idx = searchList.indexOf(sd);\n searched_doc = searchList.get(idx);\n searched_doc.setScore(searched_doc.getScore() + 1);\n }\n }\n\n }\n\n\n }\n\n Collections.sort(searchList);\n\n return searchList;\n }","public PostingsList intersect(Query query){\n\n LinkedList<PostingsList> listQueriedPostings = new LinkedList<PostingsList>();\n // List with postings corresponding to the queries\n for (int i = 0; i<query.size(); i++){\n // If any query has zero matches, return 0 results\n //if(!(new File(\"postings/t\"+hash(query.terms.get(i))+\".json\")).exists()){\n if (!this.index.containsKey(query.terms.get(i))){\n return null;\n }\n // Otherwise store postings in the list\n listQueriedPostings.add(this.getPostings(query.terms.get(i)));\n }\n\n // Order the posting list by increasing document frequency\n listQueriedPostings = sortByIncreasingFrequency(listQueriedPostings);\n\n PostingsList result = (PostingsList)listQueriedPostings.get(0);\n\n // In case only one word is queried\n if (listQueriedPostings.size() == 1){\n return result;\n }\n\n // Apply algorithm as many times as words in the query\n for(int i = 1; i < listQueriedPostings.size(); i++){\n result = intersect(result, listQueriedPostings.get(i));\n if (result.isEmpty()){\n return null;\n }\n }\n return result;\n }","private List<Integer> processRelatedDocsQuery(String query) {\r\n List<Integer> result = new ArrayList<>();\r\n\r\n for(String term : this.preprocessor.processQuery(query).keySet()) {\r\n\r\n // skip unknown terms\r\n if (!this.index.getDict().containsKey(term)) continue;\r\n\r\n // for each occurrence\r\n for(TermFrequency tf : this.index.getDict().get(term)){\r\n int id = tf.getDocId();\r\n if(!result.contains(id))\r\n result.add(id);\r\n }\r\n }\r\n\r\n return result;\r\n }","@Override\r\n\t\t\tpublic List<ScoredDocument> search(Query query) {\n\t\t\t\treturn null;\r\n\t\t\t}","public Double computeRelevance(IList<String> query, URI pageUri) {\n\t if (query == null || pageUri == null) {\n\t\t throw new NullPointerException();\n\t }\n\t \n IDictionary<String, Double> documentVector = documentTfIdfVectors.get(pageUri);\n IDictionary<String, Double> queryTfScores = computeTfScores(query);\n IDictionary<String, Double> queryVector = new ChainedHashDictionary<String, Double>();\n Double numerator = 0.0;\n \n for (KVPair<String, Double> pair: queryTfScores) {\n\t \t\tDouble queryWordScore = 0.0;\n\t \t\tDouble docWordScore = 0.0;\n\t \t\tif (idfScores.containsKey(pair.getKey())) {\t\n\t \t\t queryWordScore = queryTfScores.get(pair.getKey()) * idfScores.get(pair.getKey());\n\t \t\t}\n \t\t\tqueryVector.put(pair.getKey(), queryWordScore);\n\t \t\tif (documentVector.containsKey(pair.getKey())) {\n\t \t\t\tdocWordScore = documentVector.get(pair.getKey());\n\t \t\t} \n\t \t\tnumerator += queryWordScore * docWordScore;\n } \n \n Double denominator = docDenomScore.get(pageUri) * norm(queryVector);\n \n // A check to avoid division by zero\n if (denominator != 0.0) {\n \t\t return numerator / denominator;\n } else {\n return 0.0;\n }\n }","static void ReadQuery(String input) throws FileNotFoundException {\n input = input.replaceAll(\"[^A-Za-z]\",\" \");\n String[] arr = input.split(\" \"); // splitting the whole string into words by split on the basis of white spaces\n\n\n for(int i=0; i<arr.length; i++) {\n String termWord = arr[i].toLowerCase();\t//same pre-processing is applied to all the query word\n //termWord = RemoveSpecialCharacter(termWord);\n termWord = removeStopWords(termWord);\n\n if(!termWord.equalsIgnoreCase(\"\")) { // all the white spaces are removed as if not removed then lemmatization wont be successfully done\n\n termWord = Lemmatize(termWord);\n System.out.println(termWord);\n if(dictionary.containsKey(termWord)) {\n List<Integer> wordList = new ArrayList<>();\n wordList = dictionary.get(termWord);\n int queryWordFrequency = wordList.get(totaldocument);\n queryWordFrequency++;\n wordList.set(totaldocument, queryWordFrequency); // all the frequencies of the query words are stored at the 56th index of the List stored in the\n //hashmap associated with its word-terms\n dictionary.put(termWord, wordList);\n }\n else {\n //if any of the enterd query word not present in all the docs so list will have 0.0 value from 0th index to 55th and 56th index is reserver\n // for query word frequency\n List<Integer> wordList = new ArrayList<>();\n for(int j=0; j<totaldocument+1; j++) {\n wordList.add(0);\n }\n wordList.add(1);\n dictionary.put(termWord, wordList); //updating the dictionary hashmap now containing all the query words frequencies\n }\n }\n }\n save();\n }","private static void RankedQueryMode(DiskIndexWriter diskWriter, DiskPositionalIndex disk_posIndex) throws IOException, ClassNotFoundException, InstantiationException, IllegalAccessException {\n\n if (query.equals(\"q\")) {\n\n System.exit(0);\n }\n\n List<String> word = new ArrayList();\n String[] query_array = query.split(\"\\\\s+\");\n TokenProcessor processor = new NewTokenProcessor();\n\n for (int i = 0; i < query_array.length; i++) {\n word.add(processor.processToken(query_array[i]).get(0));\n }\n\n StrategyFactory sf = new StrategyFactory();\n StrategyInterface strategy = sf.execute(rankedOption);\n\n //maps postings to accumulator value\n HashMap<Integer, Doc_accum> postingMap = new HashMap<Integer, Doc_accum>();\n\n PriorityQueue<Doc_accum> queue = new PriorityQueue<>(Collections.reverseOrder());\n\n List<Posting> postings = new ArrayList<>();\n List<Doc_accum> results = new ArrayList<>();\n\n for (String term : word) {\n\n postings = disk_posIndex.getPosting_noPos(term);\n for (Posting p : postings) { //for each document in the postings list\n double t_fd = p.getT_fd();\n double d_ft = p.getD_ft();\n double w_qt = strategy.calculate_wqt(N, d_ft);\n double accum = 0;\n double w_dt = strategy.get_wdt(t_fd, disk_posIndex, p.getDocumentId());\n\n //pairs (Ranked_posting, accumulator factor)\n if (postingMap.containsKey(p.getDocumentId())) {\n accum = postingMap.get(p.getDocumentId()).getAccumulator();\n accum += (w_qt * w_dt);\n postingMap.replace(p.getDocumentId(), new Doc_accum(p, accum)); //replaces old accum value\n\n } else {\n accum += (w_qt * w_dt);\n postingMap.put(p.getDocumentId(), new Doc_accum(p, accum));\n }\n }\n\n }\n\n for (Integer p : postingMap.keySet()) {\n Doc_accum doc_temp = postingMap.get(p);\n double accum = doc_temp.getAccumulator(); //gets accum associated with doc\n\n if (accum > 0) {\n //search for each p's Ld factor in docWeights.bin\n double l_d = strategy.calculate_Ld(disk_posIndex, doc_temp.getPosting().getDocumentId());\n\n accum /= l_d;\n doc_temp.setAccumulator(accum);\n }\n\n queue.add(postingMap.get(p));\n\n }\n\n //returns top K=10 results \n int topK = 50;\n\n while ((results.size() < topK) && queue.size() > 0) {\n\n results.add(queue.poll()); //gets the posting acc pair and returns only posting\n\n }\n\n display_RankedResults(results);\n\n }","public void searchAndWriteQueryResultsToOutput() {\n\n List<String> queryList = fu.textFileToList(QUERY_FILE_PATH);\n\n for (int queryID = 0; queryID < queryList.size(); queryID++) {\n String query = queryList.get(queryID);\n // ===================================================\n // 4. Sort the documents by the BM25 scores.\n // ===================================================\n HashMap<String, Double> docScore = search(query);\n List<Map.Entry<String, Double>> rankedDocList =\n new LinkedList<Map.Entry<String, Double>>(docScore.entrySet());\n Collections.sort(rankedDocList, new MapComparatorByValues());\n\n // ===================================================\n // 5. Write Query Results to output\n // =================================================== \n String outputFilePath =\n RANKING_RESULTS_PATH + \"queryID_\" + (queryID + 1) + \".txt\";\n StringBuilder toOutput = new StringBuilder();\n // display results in console\n System.out.println(\"Found \" + docScore.size() + \" hits.\");\n int i = 0;\n for (Entry<String, Double> scoreEntry : rankedDocList) {\n if (i >= NUM_OF_RESULTS_TO_RETURN)\n break;\n String docId = scoreEntry.getKey();\n Double score = scoreEntry.getValue();\n String resultLine =\n (queryID + 1) + \" Q0 \" + docId + \" \" + (i + 1) + \" \" + score + \" BM25\";\n toOutput.append(resultLine);\n toOutput.append(System.getProperty(\"line.separator\"));\n System.out.println(resultLine);\n i++;\n }\n fu.writeStringToFile(toOutput.toString(), outputFilePath);\n }\n }","private static Boolean specialQueries(String query) throws ClassNotFoundException, InstantiationException, IllegalAccessException {\n clickList = false;\n //newCorpus = true;\n\n if (query.equals(\"q\")) {\n\n System.exit(0);\n return true;\n }\n\n String[] subqueries = query.split(\"\\\\s+\"); //split around white space\n\n if (subqueries[0].equals(\"stem\")) //first term in subqueries tells computer what to do \n {\n GUI.JListModel.clear();\n GUI.ResultsLabel.setText(\"\");\n TokenProcessor processor = new NewTokenProcessor();\n if (subqueries.length > 1) //user meant to stem the token not to search stem\n {\n List<String> stems = processor.processToken(subqueries[1]);\n\n //clears list and repopulates it \n String stem = \"Stem of query '\" + subqueries[1] + \"' is '\" + stems.get(0) + \"'\";\n\n GUI.ResultsLabel.setText(stem);\n\n return true;\n }\n\n } else if (subqueries[0].equals(\"vocab\")) {\n List<String> vocabList = Disk_posIndex.getVocabulary();\n GUI.JListModel.clear();\n GUI.ResultsLabel.setText(\"\");\n\n int vocabCount = 0;\n for (String v : vocabList) {\n if (vocabCount < 1000) {\n vocabCount++;\n GUI.JListModel.addElement(v);\n }\n }\n GUI.ResultsLabel.setText(\"Total size of vocabulary: \" + vocabCount);\n return true;\n }\n\n return false;\n }","SwiftScoredSet getTfIdf(String text,ASTNode n,boolean kgram)\n{\n Map<String,Integer> words = null;\n Map<String,Integer> totals = null;\n double tot = 0;\n if (kgram){\n words = buildKgramCounts(text,n);\n totals = kgram_counts;\n tot = total_kdocuments;\n } \n else {\n words = handleDocumentText(text);\n totals = document_counts;\n tot = total_documents;\n }\n double termtot = 1;\n \n for (Integer iv : words.values()) {\n termtot += iv;\n }\n \n SwiftScoredSet rslt = new SwiftScoredSet();\n for (Map.Entry<String,Integer> ent : words.entrySet()) {\n String wd = ent.getKey();\n double ct = ent.getValue();\n Integer docs = totals.get(wd);\n double docct = 0;\n if (docs != null) docct = docs;\n double idf = Math.log(tot/(1+docct));\n double tf = ct/termtot;\n double tfidf = tf*idf;\n rslt.add(wd,tfidf);\n }\n rslt.normalize();\n \n return rslt;\n}","public void queryDataPreProcess(String queryText) throws Exception {\n StopwordRemover stopwordRemover = new StopwordRemover();\n WordNormalizer wordNormalizer = new WordNormalizer();\n\n // initiate the BufferedWriter to output result\n FilePathGenerator fpg = new FilePathGenerator(\"result.txt\");\n String path = fpg.getPath();\n\n // queryId\n String queryId = \"\";\n if (queryId == null || queryId.length() == 0){\n// queryId = UUID.randomUUID().toString().replace(\"-\", \"\");\n queryId = String.valueOf(FileConst.query_doc_id);\n }\n\n // append query_id:query_text to exiting doc_id:doc_content text file\n try (FileWriter fileWriter = new FileWriter(path, true); // Path.ResultAssignment1\n BufferedWriter bw = new BufferedWriter(fileWriter)){\n // write doc_id into the result file\n bw.write(queryId + '\\n');\n\n // load doc content\n char[] content = queryText.toCharArray();\n\n // initiate a word object to hold a word\n char[] word;\n\n // initiate the WordTokenizer\n WordTokenizer tokenizer = new WordTokenizer(content);\n\n // process the query word by word iteratively\n while ((word = tokenizer.nextWord()) != null){\n word = wordNormalizer.lowercase(word);\n // write only non-stopword into result file\n if (!stopwordRemover.isStopword(Arrays.toString(word))){\n bw.append(wordNormalizer.toStem(word)).append(\" \");\n query_tokens.add(wordNormalizer.toStem(word));\n }\n }\n bw.append(\"\\n\");\n } catch (Exception e) {\n e.printStackTrace();\n }\n }","public String [] getTerm (String [] query) {\r\n String [] unique = query;\r\n //find duplicate for get unique\r\n return unique;\r\n }","private static ArrayList<Result> distanceMatching(Query query, DataManager myVocab) {\n\t\tString queryterm = query.getQuery();\n\t\tint maxScore;\n\t\tif (queryterm.length()<9)\n\t\t\tmaxScore= queryterm.length()-THRESHOLD_LEV;\n\t\telse\n\t\t\tmaxScore = queryterm.length()-(queryterm.length()/THRESHOLD_LEV);\n\t\tArrayList<Result> fuzzyResults = new ArrayList<Result>();\n\t\tfor (int i = 0; i < myVocab.vocab.size(); i++){\n\t\t\tString vocabterm = myVocab.vocab.get(i).trim();\n\t\t\tint distance = levenshteinDistance(vocabterm, queryterm);\n\t\t\t// subtract the distance that's just the length difference\n\t\t\t// to only take into account the character substitution\n\t\t\tdistance = distance - (Math.abs(vocabterm.length() - queryterm.length()));\n\t\t\tif (distance < maxScore){\n\t\t\t\tdouble score;\n\t\t\t\tif (vocabterm.length() < queryterm.length())\n\t\t\t\t\tscore = ((double)(vocabterm.length())/(double)(queryterm.length()+distance))*99;\n\t\t\t\telse\n\t\t\t\t\tscore = (((double)queryterm.length()/(double)(vocabterm.length()+distance)))*99;\n\t\t\t\tfuzzyResults.add(new Result(query.getType()+\"/\"+myVocab.vocab.get(i), myVocab.vocab.get(i), query.getType(),score, false));\n\t\t\t}\n\t\t}\n\t\treturn fuzzyResults;\n\t}","public static Map<Integer, Double> accumulate(DiskPositionalIndex index, int corpusSize, String query) throws IOException {\n Map<Integer, Double> accumulator = new HashMap<>();\n\n getTokens(query).forEach((token) -> {\n List<Posting> postings = index.getPostings(token);\n\n System.out.println(\"Postings size: \" + postings.size());\n \n //Calculate w(q,t) \n double wQT = 0.0, accu = 0.0, wDT = 0.0;\n \n if (!postings.isEmpty()) {\n wQT = Math.log(1.0 + ((double) corpusSize / (double) postings.size()));\n }\n\n for (Posting p : postings) {\n // Never encountered, add and initialize\n // if (!accumulator.containsKey(p.getDocumentId())) {\n // accumulator.put(p.getDocumentId(), 0.0);\n // }\n \n // Calculate weight of doc = 1 + ln(tf(t,d)) \n // wDT = 1.0 + Math.log((double) p.getPositions().size());\n wDT = p.getTermFrequency();\n \n // Acquire A(d)\n accu = accumulator.getOrDefault(p.getDocumentId(), 0.0); \n \n accumulator.put(p.getDocumentId(), accu + (wQT * wDT));\n }\n });\n \n // Divide all A(d) by L(d)\n for (Integer key : accumulator.keySet()) {\n if (accumulator.get(key) != 0.0) {\n // Accumulator = Accumulator / L(d)\n accumulator.put(key, (double) accumulator.get(key) / index.getDocWeight(key));\n }\n }\n \n return accumulator; \n }","public void queryRecommended(Query query, float score, String original);","public void search(Indexer indexer, CityIndexer cityIndexer, Ranker ranker, String query, boolean withSemantic, ArrayList<String> chosenCities, ObservableList<String> citiesByTag, boolean withStemming, String saveInPath, String queryId, String queryDescription) {\n String[] originalQueryTerms = query.split(\" \");\n String originQuery = query;\n docsResults = new HashMap<>();\n parser = new Parse(withStemming, saveInPath, saveInPath);\n HashSet<String> docsOfChosenCities = new HashSet<>();\n query = \"\" + query + queryDescription;\n HashMap<String, Integer> queryTerms = parser.parseQuery(query);\n HashMap<String, ArrayList<Integer>> dictionary = indexer.getDictionary();\n if (!withStemming){\n setDocsInfo(saveInPath + \"\\\\docsInformation.txt\");\n }\n else{\n setDocsInfo(saveInPath + \"\\\\docsInformation_stemming.txt\");\n }\n\n\n //add semantic words of each term in query to 'queryTerms'\n if(withSemantic) {\n HashMap<String,ArrayList<String>> semanticWords = ws.connectToApi(originQuery);\n }\n\n //give an ID to query if it's a regular query (not queries file)\n if(queryId.equals(\"\")){\n queryId = \"\" + Searcher.queryID;\n Searcher.queryID++;\n }\n\n String postingDir;\n if (!withStemming) {\n postingDir = \"\\\\indexResults\\\\postingFiles\";\n } else {\n postingDir = \"\\\\indexResults\\\\postingFiles_Stemming\";\n }\n int pointer = 0;\n\n //find docs that contain the terms in the query in their text\n HashMap<String, Integer> queryTermsIgnoreCase = new HashMap<>();\n for (String term : queryTerms.keySet()) {\n String originTerm = term;\n if (!dictionary.containsKey(term.toUpperCase()) && !dictionary.containsKey(term.toLowerCase())) {\n continue;\n }\n if(dictionary.containsKey(term.toLowerCase())){\n term = term.toLowerCase();\n }\n else {\n term = term.toUpperCase();\n }\n queryTermsIgnoreCase.put(term,queryTerms.get(originTerm));\n pointer = dictionary.get(term).get(2);\n String chunk = (\"\" + term.charAt(0)).toUpperCase();\n\n //get the relevant line from posting file\n BufferedReader br = null;\n try {\n br = new BufferedReader(new FileReader(new File(saveInPath + postingDir + \"\\\\posting_\" + chunk + \".txt\")));\n String line = \"\";\n int i = 1;\n while ((line = (br.readLine())) != null) {\n if (i == pointer) {\n break;\n }\n i++;\n }\n br.close();\n\n //get docs from posting line and add them to the data structure 'docsResults'\n if(line != null) {\n findDocsFromLine(line, term);\n }\n\n } catch (IOException e) {\n e.printStackTrace();\n }\n }\n\n //find docs that contain the chosen cities in their text\n for (String cityTerm : chosenCities) {\n if (!dictionary.containsKey(cityTerm) && !dictionary.containsKey(cityTerm.toLowerCase())) {\n continue;\n }\n if(dictionary.containsKey(cityTerm.toLowerCase())){\n cityTerm = cityTerm.toLowerCase();\n }\n pointer = dictionary.get(cityTerm).get(2);\n // char chunk = indexer.classifyToPosting(term).charAt(0);\n String chunk = (\"\" + cityTerm.charAt(0)).toUpperCase();\n\n //get the relevant line from posting file\n BufferedReader br = null;\n try {\n br = new BufferedReader(new FileReader(new File(saveInPath + postingDir + \"\\\\posting_\" + chunk + \".txt\")));\n String line = \"\";\n int i = 1;\n while ((line = (br.readLine())) != null) {\n if (i == pointer) {\n break;\n }\n i++;\n }\n br.close();\n\n //get docs from posting line and add them to the data structure 'docsOfChosenCities'\n String docs = line.substring(0, line.indexOf(\"[\") - 1); //get 'docsListStr'\n String[] docsArr = docs.split(\";\");\n for (String docInfo : docsArr) {\n String doc = docInfo.substring(0, docInfo.indexOf(\": \"));\n while(doc.charAt(0) == ' '){\n doc = doc.substring(1);\n }\n docsOfChosenCities.add(doc);\n }\n } catch (IOException e) {\n e.printStackTrace();\n }\n }\n\n //find docs that contain the chosen cities in their city tag\n if(!chosenCities.isEmpty()){\n for (String cityDicRec: chosenCities) {\n //get pointer to posting from cityDictionary\n try {\n pointer = cityIndexer.getCitiesDictionary().get(cityDicRec);\n } catch (NumberFormatException e) {\n e.printStackTrace();\n }\n //get the relevant line from posting file\n BufferedReader br = null;\n try {\n br = new BufferedReader(new FileReader(new File(saveInPath + \"\\\\cityIndexResults\" + \"\\\\posting_city\" + \".txt\")));\n String line = \"\";\n int i = 1;\n while ((line = (br.readLine())) != null) {\n if (i == pointer) {\n break;\n }\n i++;\n }\n br.close();\n\n //get docs from posting line and add them to the data structure 'docsOfChosenCities'\n String docs = line.substring(line.indexOf(\"[\") + 1, line.indexOf(\"]\")); //get 'docsListStr'\n String[] docsArr = docs.split(\"; \");\n for (String doc : docsArr) {\n docsOfChosenCities.add(doc);\n }\n } catch (IOException e) {\n e.printStackTrace();\n }\n }\n }\n\n\n ranker.rank(docsResults, docsOfChosenCities, queryTermsIgnoreCase, dictionary, docsInfo,entities, queryId);\n }","public HashMap<String, Double> GetTokenRFScore(Query aQuery, int TopK) throws Exception {\r\n\t\t// Store <token, score> for being returned\r\n\t\tHashMap<String, Double> TokenRFScore = new HashMap<>();\r\n\t\t\r\n\t\t// Get tokens in the given query\r\n\t String[] tokens = aQuery.getQueryContent().split(\" \");\r\n\t \r\n\t // Get feedback docs by the given query using feedback retrieval model\r\n\t List<Classes.Document> feedbackDocs = new QueryRetrievalModel().retrieveQuery(aQuery, TopK);\r\n\r\n\t // Initiate qeuryResult map <docid, <term, tf>> and termFreq map <term, cf>\r\n\t queryResult = new HashMap<>();\r\n\t termFreq = new HashMap<>();\r\n\r\n\t // Search each token appearing in the given query \r\n\t for(String token : tokens) {\r\n\t \t// Determine whether the current token exists in collection \r\n\t \tlong cf = myireader.CollectionFreq(token);\r\n\t \ttermFreq.put(token, cf);\r\n\t \tif(cf == 0) {\r\n\t \t\tcontinue; \r\n\t \t}\r\n\t \r\n\t \tint[][] postingList = myireader.getPostingList(token);\r\n\t \tfor(int[] posting : postingList) {\r\n\t \t\tif(!queryResult.containsKey(posting[0])) { // posting[0]: docid\r\n\t \t\t\tHashMap<String, Integer> tfMap = new HashMap<>();\r\n\t \t\t\ttfMap.put(token, posting[1]); // posting[1]: tf\r\n\t \t\t\tqueryResult.put(posting[0], tfMap);\r\n\t \t\t} else {\r\n\t \t\t\tqueryResult.get(posting[0]).put(token, posting[1]);\r\n\t \t\t}\r\n\t \t}\r\n\t }\r\n\t /*\r\n\t\t * After the for loop, we have the map <docid, <term, term_freq>> for each doc to all terms in the query\r\n\t\t * tokens = [Hong, Kong, economics, Singapore]\r\n\t\t * \r\n\t\t * queryResult : <docid, <term, term_freq>>\r\n\t\t * 1, hong, 15\r\n\t\t * Singapore, 3\r\n\t\t * 3, Singapore, 1\r\n\t\t * kong, 10\r\n\t\t * economics, 30\r\n\t\t * ..., ...\r\n\t\t */\t\r\n\r\n\t // Here all feedback docs are treated as one big pseudo document!!!!!!\r\n\t int len = 0;\r\n\t // Store <term, tf>\r\n\t Map<String, Integer> pseudoDoc = new HashMap<>();\r\n\t for(Classes.Document doc : feedbackDocs) {\r\n\t \tqueryResult.get(Integer.parseInt(doc.getLuceneID())).forEach((term, tf) -> { // Iterate each tfMap\r\n\t \t\tif(!pseudoDoc.containsKey(term)) {\r\n\t \t\t\tpseudoDoc.put(term, tf);\r\n\t \t\t} else {\r\n\t \t\t\tpseudoDoc.put(term, tf + pseudoDoc.get(term));\r\n\t \t\t}\r\n\t \t});\r\n\t \t\r\n\t \t// Accumulate by the current doc's length\r\n\t \tlen += myireader.docLength(Integer.parseInt(doc.getLuceneID()));\r\n\t }\r\n\t \r\n\t /**\r\n\t\t * Dirichlet Prior Smoothing:\r\n\t\t * p(w|D) = (|D|/(|D|+MU))*(c(w,D)/|D|) + (MU/(|D|+MU))*p(w|REF)\r\n\t * score = λ*p_doc + (1-λ)*p_ref\r\n\t * = c1*p_doc + c2*p_ref\r\n\t\t */\r\n\t int pseudoLen = len;\r\n\t double c1 = pseudoLen / (pseudoLen + MU);\r\n\t double c2 = MU / (pseudoLen + MU);\r\n\t // Calculate the probability of pseudoDoc generating each term\r\n\t pseudoDoc.forEach((token, tf) -> {\r\n\t \tlong cf = termFreq.get(token);\r\n\t \tdouble pDoc = (double) tf / pseudoLen; // p(w|D)\r\n\t \tdouble pRef = (double) cf / CORPUS_SIZE; // p(w|REF)\r\n\t \tdouble score = c1 * pDoc + c2 * pRef;\r\n\t \t\r\n\t \t// Get the RF probability of each token \r\n\t \tTokenRFScore.put(token, score); \r\n\t });\r\n\r\n\t\treturn TokenRFScore;\r\n\t}","@Test\n\tpublic void testKeywordQuery(){\n\t\t//manager.getResponse(\"american football \"); //match multiple keywords\n//\t\tmanager.getResponse(\"list of Bond 007 movies\");\n//\tmanager.getResponse(\"Disney movies\");\n\t\t//manager.keywordQuery(\"Paul Brown Stadium location\");\n\t\t//manager.keywordQuery(\"0Francesco\");\n System.out.println(\"******* keyword query *******\");\n\t\t//manager.keywordQuery(\"sportspeople in tennis\");\n\t\t//manager.keywordSearch(\"list of movies starring Sean Connery\",ElasticIndex.analyzed,100 );\n//\t\tmanager.keywordSearch(\"movies starring Sean Connery\",ElasticIndex.notStemmed,100 );\n// manager.keywordSearch(\"musical movies tony award\",ElasticIndex.analyzed,100 );\n// manager.keywordSearch(\"movies directed by Woody Allen\",ElasticIndex.analyzed,100 );\n// manager.keywordSearch(\"United states professional sports teams\",ElasticIndex.analyzed,100 );\n// manager.keywordSearch(\"computer games developed by Ubisoft\",ElasticIndex.analyzed,100 );\n// manager.keywordSearch(\"computer games developed by Ubisoft\",ElasticIndex.notStemmed,100 );\n// manager.keywordSearch(\"movies academy award nominations\",ElasticIndex.notStemmed,100 );\n System.out.println(SearchResultUtil.toSummary(manager.keywordSearch(\"movies directed by Woody Allen\",ElasticIndex.notLowercased,20 )));\n //manager.keywordSearch(\"grammy best album in 2012\",ElasticIndex.notAnalyzed,100 );\n //(better than analyzed) manager.keywordSearch(\"grammy best album in 2012\",ElasticIndex.notStemmed,100 );\n System.out.println(\"*****************************\");\n\n\t\t//manager.keywordQuery(\"Disney movies\");\n\t}","public static ArrayList<Result> findMatches(Query query, DataManager myVocab){\n\n\t\t//Uncomment this for logging in this class\t\n//\t\tmyLogger.setLevel(Level.INFO); \n\n\t\t// get the term we're going to search for and\n\t\t// take out any leading or trailing whitespaces\n\t\tString querystr = query.getQuery();\n\t\tquerystr = querystr.trim();\n\t\tString uncleaned = querystr;\n\t\t\n\t\t// This is in case of numeric entries. Google Refine doesn't seem\n\t\t// to have int cell types, instead it adds an invisible .0 to all\n\t\t// numbers. This fixes that issue, as it sometimes causes false negatives.\n\t\tif (querystr.endsWith(\".0\")){\n\t\t Pattern p = Pattern.compile(\"[^0-9\\\\.]+\");\n\t\t Matcher m = p.matcher(querystr);\n\t\t boolean result = m.find();\n\t\t if (!result){\n\t\t \t querystr = querystr.substring(0, querystr.length()-2);\n\t\t }\n\t\t}\n\t\t// see if it's in the synonyms map, if it is\n\t\t// replace it with the appropriate term, if it's\n\t\t// not, don't do anything. \n\n\t\tif (myVocab.subMap.get(querystr)!=null){\n\t\t\tquerystr = myVocab.subMap.get(querystr);\n\t\t\tquery.setQuery(querystr);\n\t\t}\n\t\t\n\t\t// Clean up the query string if it isn't case/punctuation sensitive\n\t\tif (!myVocab.capsSensitive()){\t\t\n\t\t\tquerystr = querystr.toLowerCase();\n\t\t}\n\t\tif (! myVocab.punctSensitive()){\t\t\n\t\t\tquerystr = querystr.replaceAll(\"[\\\\W_]\", \"\");\n\t\t}\n\t\t\n\t\t// see if it's in the synonyms map, if it is\n\t\t// replace it with the appropriate term, if it's\n\t\t// not, don't do anything. \n\t\tif(myVocab.subMap.get(querystr)!=null){\n\t\t\tquerystr = myVocab.subMap.get(querystr);\n\t\t\tquery.setQuery(querystr);\n\t\t}\n\n\t\tString type = query.getType();\n\n\t\t// This ArrayList is the results that are going to be returned. \n\t\tArrayList<Result> results = getDirectMatches(myVocab, querystr, uncleaned, type);\n\t\t\n\t\t// If there's a perfect match return it.\n\t\tif (results.size() == 1 && results.get(0).match){\n\t\t\treturn results;\n\t\t}else{\n\t\t\t// Otherwise, add the initial ones and try matching\n\t\t\t// based on distance to vocabulary terms.\n\t\t\tresults.addAll(distanceMatching(query, myVocab));\n\t\t\t\n\t\t\t// Split the original query term by space and non-alphanumeric characters \n\t\t\t// to find how many words there are.\n\t\t\t//querystr = query.getQuery().replaceAll(\"[\\\\W_]\", \" \");\n\t\t\tString [] termList = querystr.split(\" \");\n\t\t\t\n\t\t\t// if there's more than one, run bagOfWords\n\t\t\t// which tries to find a match for each of the words.\n\t\t\tif (termList.length > 1){\n\t\t\t\tresults.addAll(bagOfWords(query, myVocab));\n\t\t\t}\n\t\t}\n\t\t\n\t\t// Clean the results: no duplicates\n\t\t// no extra results to return, and sorted\n\t\t// them by score before returning them\n\t\tresults = removeDuplicates(results);\n\t\t\n\t\t// They do not need to be reduced in \n\t\t// number if there are fewer than \n\t\t// the max results.\n\t\t// The pruneResults sorts them\n\t\t// by score already.\n\t\tif(query.getLimit()!=null){\n\t\t\tresults = pruneResults(results,Integer.parseInt(query.getLimit()));\n\t\t}else{\n\t\t\tresults = pruneResults(results,MAX_RESULTS);\n\t\t}\n\t\t\t\n\t\tresults = sortByScore(results);\n\t\tfor (int i = 0; i< results.size(); i++){\n//\t\t\tmyLogger.log(Level.SEVERE,results.get(i).getScore()+ \" is bigger than 100?\");\n\t\t\tif(results.get(i).getScore() > (double)100){\n\t\t\t\tresults.get(i).setScore((double)100 - (results.get(i).getScore()-(double)100));\n//\t\t\t\tmyLogger.log(Level.SEVERE,results.get(i).getScore()+\" is bigger than 100! and was set to \"+\n//\t\t\t\t\t\t((double)100 - (results.get(i).getScore()-(double)100)));\n\t\t\t}\n\t\t}\n\t\treturn results;\n\t}","protected HashMap<String,Double> rank(ArrayList<String> queryPostingLines, ArrayList<String> query){\n HashMap<String,HashMap<String,Integer>> queryWordsTFPerDoc = computeTFForQueryWords(queryPostingLines);\n ArrayList<String> retrievedDocuments = new ArrayList<>(queryWordsTFPerDoc.keySet());\n HashMap<String,Double> rankedDocs = new HashMap<>();\n\n for(String doc : retrievedDocuments){\n HashMap<String,Integer> docTFs = queryWordsTFPerDoc.get(doc);\n double rank = 0.3*rankByBM25(query,doc,docTFs) + 0.7*rankByPosition(query,doc,queryPostingLines);// - rankByCosSim(query,doc,docTFs);\n rankedDocs.put(doc,rank);\n }\n rankedDocs = sortByValue(rankedDocs);\n ArrayList<String> docsAfterSort = new ArrayList<>(rankedDocs.keySet());\n HashMap<String,Double> docsToRetrieve = new HashMap<>();\n int i=0;\n for(String doc: docsAfterSort){\n docsToRetrieve.put(documentDetails.get(doc)[0],rankedDocs.get(doc));\n i++;\n if(i == 50)\n break;\n }\n return docsToRetrieve;\n }","public void relevanceFeedback(PostingsList results, boolean[] docIsRelevant, Indexer indexer ) {\r\n// results contain the ranked list from the current search\r\n// docIsRelevant contains the users feedback on which of the 10 first hits are relevant\r\n\tdouble gamma = 0.0; // används ej, de orelevanta dokumenterna. städa upp queryn. Vad innehller de orelevanta dokumenterna för termer\r\n// dess termer tar vi bort från den relebanta.)\r\n\r\n\tdouble alfa = 0.8; // hur mycket litar på det gamla sökning innan feedback\r\n\tdouble beta = 0.6; // hur mycket hänsyn du ska ta till nya sökningen efter feedback \r\n\r\n\r\n\t/* \r\n\r\n\tAlgorithm: \r\n\tThe Rocchio algorithm is based on a method of relevance \r\n\tfeedback found in information retrieval systems\r\n\tThe algorithm is based on the assumption that most users \r\n\thave a general conception of which documents should be denoted \r\n\tas relevant or non-relevant.[1] Therefore, the user's search \r\n\tquery is revised to include an arbitrary percentage of relevant \r\n\tand non-relevant documents as a means of increasing the search \r\n\tengine's recall, and possibly the precision as well. The number \r\n\tof relevant and non-relevant documents allowed to enter a query \r\n\tis dictated by the weights of the a, b.\r\n\tthe associated weights (a, b) are responsible for shaping the \r\n\tmodified vector in a direction closer, or farther away, from the \r\n\toriginal query, related documents, and non-related documents.\r\n\r\n\r\n\r\n\tLimitations of rocchio:\r\n\t\tTherefore the two queries of \"Burma\" and \"Myanmar\" will \r\n\t\tappear much farther apart in the vector space model, \r\n\t\tthough they both contain similar origins\r\n\tWhy not use non-relevant documents:\r\n\t\tThough there are benefits to ranking documents as not-relevant, \r\n\t\ta relevant document ranking will result in more precise documents \r\n\t\tbeing made available to the user. \r\n\t\r\n\r\n\r\n\tRoccio algoritmen: \r\n\t\talfa = Original query weight \r\n\t\tbeta = related document weight\r\n\t\t\r\n\t\thigher alpha means that we give more focus to the original query terms\r\n\t\thigher beta means that we give more focus to the new search feedback. i.e new terms.\r\n\r\n\t\tTar en org query\r\n\t\tTar den gamla gånnger en viss vikt \r\n\t\tvikt är alfa + beta (entill vektor) plus att den kollar på original vektor, q0 \r\n\t\t\thögre alfa mer fokus på original queryn \r\n\t\t\thögra beta skiftar till mer fokus på de nya termerna. \r\n\t\tdvs utökas med ord/termer från dokument vektorerna som var relevanta. \r\n\r\n\tVanligtvis har man väldigt häg alfa och beta lite under för att det är standard. man tycker att den \r\n\tförsta queryn är väldigt bra.\r\n\r\n\t\r\n\t*/\r\n\r\n\tPostingsList related_doc_vector = new PostingsList();\r\n\tHashMap<String, Double> qm = new HashMap<String, Double>(); // spara termer och weights.\r\n\t// normalize weights\r\n\tfor(Double w : weights){\r\n\t\tw = w/weights.size();\r\n\t}\r\n\r\n\tIterator<PostingsEntry> it = results.iterator();\r\n\tfor(int i = 0; i < docIsRelevant.length; i++){\r\n\t\tif(docIsRelevant[i] == true){\r\n\t\t\trelated_doc_vector.list.add(results.get(i));\r\n\t\t} \r\n\t}\r\n\r\n\t// apply Rocchio algorithm.\r\n\tfor(int i = 0; i < terms.size(); i++){\r\n\t\tdouble new_weigt = weights.get(i) * alfa;\r\n\t\tqm.put(terms.get(i), new_weigt);\r\n\t}\r\n\r\n\tfor(int i = 0; i < related_doc_vector.size(); i++){\r\n\t\tIterator<PostingsEntry> ite = related_doc_vector.iterator();\r\n\t\twhile(ite.hasNext()){\r\n\t\t\tPostingsEntry postingsentry = ite.next();\r\n\t\t\tint docID = postingsentry.docID;\r\n\t\t\tString filename = indexer.index.docIDs.get(Integer.toString(docID)); // hämtar filnamnet\r\n\t\t\tString path = \"/Users/monadadoun/Desktop/ir/lab/davisWiki/\" + filename; \r\n\t\t\tFile file = new File(path);\r\n\t\t\tHashSet<String> hs = new HashSet<>();\r\n\t\t\t// lägger till alla ord som finns till mitt hashet\r\n\t\t\ttry (Reader reader = new InputStreamReader( new FileInputStream(file), StandardCharsets.UTF_8 )){\r\n\t\t\t\tTokenizer tok = new Tokenizer( reader, true, false, true, indexer.patterns_file );\r\n\t\t\t\twhile (tok.hasMoreTokens()) {\r\n\t\t\t\t\ths.add(tok.nextToken());\r\n\t\t\t\t}\r\n\t\t\t} catch (IOException e) {\r\n\t\t\t\te.printStackTrace();\r\n\t\t\t}\r\n\t\t\t\r\n\t\t\tIterator<String> iter = hs.iterator();\r\n\t\t\twhile(iter.hasNext()){\r\n\t\t\t\tString s = iter.next();\r\n\t\t\t\tif(qm.containsKey(s)){\r\n\t\t\t\t\tDouble tmp = qm.get(s);\r\n\t\t\t\t\tqm.put(s, tmp + beta * postingsentry.score);\r\n\t\t\t\t} else {\r\n\t\t\t\t\tqm.put(s, beta * postingsentry.score);\r\n\t\t\t\t}\r\n\t\t\t}\r\n\t\t}\r\n\t}\r\n\tLinkedList<String> term = new LinkedList<>();\r\n\tLinkedList<Double> weight = new LinkedList<>();\r\n\tList<Map.Entry<String,Double>> answer = new ArrayList<Map.Entry<String,Double>>(qm.entrySet());\r\n\tanswer.sort((e1,e2) -> e2.getValue().compareTo(e1.getValue())); // sorterar efter värde så att orden med högst score ligger först\r\n\tfor (int i = 0; i < answer.size(); i++) {\r\n\t\tterm.add(answer.get(i).getKey());\r\n\t\tweight.add(answer.get(i).getValue()/answer.size());\r\n\t}\r\n\r\n\tterms = term;\r\n\tweights = weight;\r\n\t}","public List<Document> retrieveQuery( Query aQuery, int TopN ) throws IOException {\n\t\t// NT: you will find our IndexingLucene.Myindexreader provides method: docLength()\n\t\t// implement your retrieval model here, and for each input query, return the topN retrieved documents\n\t\t// sort the documents based on their relevance score, from high to low\n\n\t\tHashMap<Integer, HashMap<String,Integer>> idTokenDocFrequencyMap = new HashMap<>();\t//docid - (token - document frequency) map\n\t\tHashMap<String, Long> tokenColFrequencyMap = new HashMap<>();\t// token - collection frequency map\n\t\tString content = aQuery.GetQueryContent();\n\t\tString[] tokens = content.split(\" \");\n\n\t\tfor(String token : tokens){\n\t\t\ttokenColFrequencyMap.put(token, indexReader.CollectionFreq(token)); \t// update the second map\n\t\t\tint [][]postingList = indexReader.getPostingList(token);\n\t\t\tif(postingList == null) continue;\n\t\t\tfor(int i = 0; i < postingList.length; i++){\n\t\t\t\tint docid = postingList[i][0];\n\t\t\t\tint freq = postingList[i][1];\n\t\t\t\tif(idTokenDocFrequencyMap.containsKey(docid)){\t\t// update the first map\n\t\t\t\t\tidTokenDocFrequencyMap.get(docid).put(token,freq);\n\t\t\t\t}else {\n\t\t\t\t\tHashMap<String,Integer> tokenFrequencyMap = new HashMap<>();\n\t\t\t\t\ttokenFrequencyMap.put(token,freq);\n\t\t\t\t\tidTokenDocFrequencyMap.put(docid,tokenFrequencyMap);\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t\tdouble U = 2000.0;\n\t\tList<Document> documentList = new ArrayList<>();\n\t\t// if use a docidList, it will have some duplicates.\n\t\tfor(Map.Entry<Integer, HashMap<String,Integer>> entry : idTokenDocFrequencyMap.entrySet()){\n\t\t\tdouble score = 1.0;\t\t\t// each document have one score\n\t\t\tint docid = entry.getKey();\n\t\t\tint docLen = indexReader.docLength(docid);\t// get document length\n\t\t\tHashMap<String,Integer> tokenDocFrequencyMap = idTokenDocFrequencyMap.get(docid);\n\t\t\tfor(String token : tokens){\t\t// for each token, not the token just exist in the document\n\t\t\t\tlong colFreq = tokenColFrequencyMap.getOrDefault(token,0l);\t// get collection frequency\n\t\t\t\tif(colFreq != 0){\n\t\t\t\t\tint docFreq = 0;\t// if this document don't have token, just set document frequency as 0\n\t\t\t\t\tif(tokenDocFrequencyMap.containsKey(token)){\n\t\t\t\t\t\tdocFreq = tokenDocFrequencyMap.get(token);\n\t\t\t\t\t}\n\t\t\t\t\tscore = score * (docFreq + U * ((double)colFreq / colLen)) / (docLen + U);\t//equation\n\t\t\t\t}\n\t\t\t}\n\t\t\tDocument document = new Document(docid+\"\", indexReader.getDocno(docid),score);\n\t\t\tdocumentList.add(document);\n\t\t}\n\n\t\tCollections.sort(documentList, new Comparator<Document>() {\n\t\t\t@Override\n\t\t\tpublic int compare(Document o1, Document o2) {\n\t\t\t\treturn Double.compare(o2.score(),o1.score());\n\t\t\t}\n\t\t});\n\t\tList<Document> res = new ArrayList<>();\n\t\tfor(int i = 0 ; i < TopN; i++){\n\t\t\tres.add(documentList.get(i));\n\t\t}\n\t\treturn res;\n\t}","private static Query computeBooleanQueryNP(String textQuery){\n\t\tBooleanQuery query = new BooleanQuery();\n\n\t\tHmmDecoder mPosTagger = null;\n\t\tTokenizerFactory mTokenizerFactory = null;\n\t\tPhraseChunker pChunker = new PhraseChunker(mPosTagger,mTokenizerFactory);\n\t\tArrayList<String> pchuncker = new ArrayList<String>();\n\n\t\tpchuncker = pChunker.getCHunkNounPhrases(textQuery.toLowerCase());\n\n\t\tfor (int k = 0; k<= pchuncker.size()-1;k++ ){\n\t\t\tString wordInList = ((String) pchuncker.get(k));\n\t\t\twordInList = wordInList.toLowerCase().replaceAll(\"-\",\" \");\n\t\t\tString [] wordInListSplit = wordInList.split(\" \");\n\t\t\tfor (String word: wordInListSplit){\n\n\t\t\t\tquery.add(new TermQuery(new Term(\"content\", word)), Occur.SHOULD );\n\t\t\t}\n\n\t\t}\n\n\t\t/* String[] tQuery = textQuery.split(\" \");\n\t\t for(String s: tQuery )\n\t\t\t query.add(new TermQuery(new Term(\"text\", s)), Occur.SHOULD);*/\n\n\t\treturn query;\n\t}","private static ArrayList<Result> bagOfWords(Query query, DataManager myVocab) {\n\t\tString queryname = query.getQuery();\n\t\t// split on space and punctuation\n\t\tString[] termList = queryname.split(\" \");\n\t\tArrayList<Result> bagResults = new ArrayList<Result>();\n\t\tfor (int i=0; i<termList.length; i++){\n\t\t\tQuery newQuery = new Query(termList[i], query.getLimit(), query.getType(), query.getTypeStrict(), query.properties()) ;\n\t\t\tArrayList<Result> tempResults = new ArrayList<Result>(findMatches(newQuery, myVocab));\n\t\t\tfor(int j=0; j<tempResults.size(); j++){\n\n\t\t\t\ttempResults.get(j).setMatch(false);\n\t\t\t\ttempResults.get(j).decreaseScore(termList.length);\n\t\t\t\tif(tempResults.get(j).getScore()>100){\n\t\t\t\t\ttempResults.get(j).setScore(99.0);\n\t\t\t\t}else if (tempResults.get(j).getScore()<1){\n\t\t\t\t\ttempResults.get(j).setScore(tempResults.get(j).getScore()*10);\n\t\t\t\t}\n\t\t\t}\n\t\t\tbagResults.addAll(tempResults);\n\t\t}\n\t\treturn bagResults;\n\t}","public double getTfIdf(){ return tf_idf; }","public void updateUnseenTermInThisQuery(int relevanceFeedbackMethod) {\n System.out.println(\"Nomor Query Lama : \" + listDocumentRetrievedForThisQuery.getQuery().getIndex());\n System.out.println(\"Isi Query Lama : \" + listDocumentRetrievedForThisQuery.getQuery().getQueryContent());\n int thisQueryIndex = listDocumentRetrievedForThisQuery.getQuery().getIndex();\n for (Map.Entry m : invertedFile.getListTermWeights().entrySet()) {\n String keyTerm = (String) m.getKey();\n if (!isTermAppearInQuery(keyTerm)) {\n double newWeight = computeNewWeightTerm(relevanceFeedbackMethod,keyTerm,0.0);\n if (newWeight > 0) {\n String filteredWord = \"\";\n if (invertedFile.isStemmingApplied()) {\n filteredWord = invertedFile.getMappingStemmedTermToNormalTerm().get(keyTerm);\n } else {\n filteredWord = keyTerm;\n }\n newQueryComposition.put(filteredWord,newWeight);\n invertedFileQuery.insertRowTable(keyTerm,thisQueryIndex,newWeight);\n normalFileQuery.insertElement(thisQueryIndex,keyTerm);\n }\n }\n }\n System.out.println(\"Nomor Query Baru : \" + convertNewQueryComposition().getIndex());\n System.out.println(\"Isi Query Baru : \" + convertNewQueryComposition().getQueryContent());\n }","@Test\n public void testCombineRankZeroPageRankWeight() {\n Iterator<Pair<Document, Double>> resultIterator = icsSearchEngine.searchQuery(Arrays.asList(\"anteater\"),\n 100, 0.0);\n ImmutableList<Pair<Document, Double>> resultListCombined = ImmutableList.copyOf(resultIterator);\n\n Iterator<Pair<Document, Double>> resultIteratorTfIdf = invertedIndexManager.searchTfIdf(Arrays.asList(\"anteater\"), 100);\n ImmutableList<Pair<Document, Double>> resultListTfIdf = ImmutableList.copyOf(resultIteratorTfIdf);\n\n Assert.assertEquals(resultListTfIdf, resultListCombined);\n }","private Node estimateRelevance(Node original) throws Exception {\n Node combineNode = new Node(\"combine\", new NodeParameters(), original.getInternalNodes(), original.getPosition());\n\n // Only get as many as we need\n Parameters localParameters = retrieval.getGlobalParameters().clone();\n int fbDocs = (int) retrieval.getGlobalParameters().get(\"fbDocs\", 10);\n localParameters.set(\"requested\", fbDocs);\n\n // transform and run\n Node transformedCombineNode = retrieval.transformQuery(combineNode, localParameters);\n List<ScoredDocument> initialResults = retrieval.executeQuery(transformedCombineNode, localParameters).scoredDocuments;\n \n // Gather content\n ArrayList<String> names = new ArrayList<String>();\n for (ScoredDocument sd : initialResults) {\n names.add(sd.documentName);\n }\n List<Document> docs = getDocuments(names);\n\n // Now the maps from the different information sources\n // Each of these is a term -> field -> score double-mapping\n HashMap<String, TObjectDoubleHashMap<String>> uCFSs = null;\n double ucfw = p.get(\"ucfw\", 1.0);\n if (ucfw != 0.0) {\n uCFSs = getUnigramCollFieldScores();\n }\n\n HashMap<String, TObjectDoubleHashMap<String>> bCFSs = null;\n double bcfw = p.get(\"bcfw\", 1.0);\n if (bcfw != 0.0) {\n bCFSs = getBigramCollFieldScores();\n }\n\n HashMap<String, TObjectDoubleHashMap<String>> uPRFSs = null;\n double uprfw = p.get(\"uprfw\", 1.0);\n if (uprfw != 0.0) {\n uPRFSs = getUnigramPRFScores(docs);\n }\n\n HashMap<String, TObjectDoubleHashMap<String>> bPRFSs = null;\n double bprfw = p.get(\"bprfw\", 1.0);\n if (bprfw != 0.0) {\n bPRFSs = getBigramPRFScores(docs);\n }\n\n // We can now construct term-field weights using our supplied lambdas\n // and scores\n Node termNodes = new Node(\"combine\", new NodeParameters(), new ArrayList<Node>(), 0);\n termNodes.getNodeParameters().set(\"norm\", false);\n TObjectDoubleHashMap<String> weights = new TObjectDoubleHashMap<String>();\n for (String term : queryTerms) {\n weights.clear();\n for (String field : fields) {\n double sum = 0.0;\n if (uCFSs != null) {\n sum += (ucfw * uCFSs.get(term).get(field));\n }\n\n if (bCFSs != null) {\n TObjectDoubleHashMap<String> termMap = bCFSs.get(term);\n if (termMap != null) {\n sum += (bcfw * termMap.get(field));\n }\n }\n\n if (uPRFSs != null) {\n sum += (uprfw * uPRFSs.get(term).get(field));\n }\n\n if (bPRFSs != null) {\n TObjectDoubleHashMap<String> termMap = bPRFSs.get(term);\n if (termMap != null) {\n sum += (bprfw * termMap.get(field));\n }\n }\n weights.put(field, sum);\n }\n termNodes.addChild(createTermFieldNodes(term, weights));\n }\n return termNodes;\n }","public static String tfidf(String str) throws Exception{\n\t\tIndexReader r = IndexReader.open(FSDirectory.open(new File(\"index\")));\r\n\r\n\t\t// this code takes care of calculating idf for each term\r\n\r\n\t\tHashMap<String, Double> idf_map = new HashMap<String, Double>();\r\n\t\tTermEnum t = r.terms();\r\n\t\tdouble docs_count = r.maxDoc();\r\n\t\twhile (t.next()) {\r\n\t\t\tTerm te = new Term(\"contents\", t.term().text());\r\n\t\t\tdouble idf = Math.log(docs_count / r.docFreq(te));\r\n\t\t\tidf_map.put(t.term().text(), idf);\r\n\t\t}\r\n\r\n\t\t// This code is a test stub to get the term with lowest IDF value\r\n\r\n\t\t/*\r\n\t\t * double minVal = Collections.min(idf_map.values()); for(Entry<String,\r\n\t\t * Double> entry:idf_map.entrySet()){ if(entry.getValue() == minVal){\r\n\t\t * System.out.println(\"Term with lowest idf is: \"+entry.getKey()); } }\r\n\t\t */\r\n\r\n\t\tlong t1, t2;\r\n\t\tlong start = System.currentTimeMillis();\r\n\r\n\t\t// code to get |d| for every document\r\n\r\n\t\tHashMap<Integer, HashMap<String, Integer>> hmap = new HashMap<Integer, HashMap<String, Integer>>();\r\n\t\tTermEnum trm = r.terms();\r\n\t\twhile (trm.next()) {\r\n\t\t\tTerm te1 = new Term(\"contents\", trm.term().text());\r\n\t\t\tTermDocs td1 = r.termDocs(te1);\r\n\r\n\t\t\twhile (td1.next()) {\r\n\t\t\t\tHashMap<String, Integer> a1 = hmap.get(td1.doc());\r\n\t\t\t\tif (a1 == null) {\r\n\t\t\t\t\ta1 = new HashMap<String, Integer>();\r\n\t\t\t\t\ta1.put(trm.term().text(), td1.freq());\r\n\t\t\t\t\thmap.put(td1.doc(), a1);\r\n\t\t\t\t} else {\r\n\t\t\t\t\ta1.put(trm.term().text(), td1.freq());\r\n\t\t\t\t}\r\n\t\t\t}\r\n\t\t}\r\n\r\n\t\t// compute magnitude of each document vector and store it in array\r\n\r\n\t\tArrayList<Double> doc_magnitude = new ArrayList<Double>();\r\n\t\tHashMap<String, Integer> val = new HashMap<String, Integer>();\r\n\t\tSet<Entry<Integer, HashMap<String, Integer>>> entrySet = hmap.entrySet();\r\n\r\n\t\tjava.util.Iterator<Entry<Integer, HashMap<String, Integer>>> it = entrySet.iterator();\r\n\t\twhile (it.hasNext()) { // foreach document id\r\n\t\t\tdouble square_sum = 0.0;\r\n\t\t\tMap.Entry<Integer, HashMap<String, Integer>> me = (Entry<Integer, HashMap<String, Integer>>) it.next();\r\n\t\t\tval = me.getValue();\r\n\t\t\tSet<Map.Entry<String, Integer>> entry = val.entrySet();\r\n\t\t\tjava.util.Iterator<Map.Entry<String, Integer>> iterator = entry.iterator();\r\n\t\t\twhile (iterator.hasNext()) { // foreach term\r\n\t\t\t\tMap.Entry<String, Integer> mp = iterator.next();\r\n\t\t\t\tsquare_sum += mp.getValue() * mp.getValue();\r\n\t\t\t}\r\n\t\t\tdouble root = Math.sqrt(square_sum);\r\n\t\t\tdoc_magnitude.add(me.getKey(), root);\r\n\t\t}\r\n\r\n\t\t// long end = System.currentTimeMillis();\r\n\t\t// double diff = end - start;\r\n\t\t// System.out.println(\"Time taken to compute norms(in seconds): \" + diff\r\n\t\t// / 1000 + \"\\n\");\r\n\r\n\t\t// get the query and find similarity with the documents\r\n\t\tHashMap<Integer, Double> similarity_map = new HashMap<Integer, Double>();\r\n\t\tSet<Entry<Integer, HashMap<String, Integer>>> entrySet1 = hmap.entrySet();\r\n\t\tjava.util.Iterator<Entry<Integer, HashMap<String, Integer>>> it1 = entrySet1.iterator();\r\n\t\t\r\n\t\t\r\n\t\t\r\n\t\tHashMap<Integer, Double> dot_product_map = new HashMap<Integer, Double>();\r\n\r\n\t\t\r\n\t\t\tdot_product_map.clear();\r\n\t\t\tsimilarity_map.clear();\r\n\r\n\t\t\tString[] terms = str.split(\"\\\\s+\");\r\n\t\t\tint cnt = 0;\r\n\r\n\t\t\tlong result_st = System.currentTimeMillis();\r\n\t\t\tt1 = System.nanoTime();\r\n\r\n\t\t\t// for each term get the documents containing the corresponding term\r\n\t\t\tfor (String word : terms) // foreach term in query\r\n\t\t\t{\r\n\t\t\t\tTerm te = new Term(\"contents\", word);\r\n\t\t\t\tTermDocs tdocs = r.termDocs(te);\r\n\t\t\t\twhile (tdocs.next() /* && tdocs.doc() < number */) {\r\n\t\t\t\t\t// Map.Entry<Integer, HashMap<String, Integer>> me =\r\n\t\t\t\t\t// (Entry<Integer, HashMap<String, Integer>>) it1.next();\r\n\t\t\t\t\tdouble freq = hmap.get(tdocs.doc()).get(word);\r\n\t\t\t\t\tDouble temp = dot_product_map.get(tdocs.doc());\r\n\t\t\t\t\tif (temp == null) {\r\n\t\t\t\t\t\tdot_product_map.put(tdocs.doc(), freq * idf_map.get(word));\r\n\t\t\t\t\t} else {\r\n\t\t\t\t\t\tdot_product_map.put(tdocs.doc(), dot_product_map.get(tdocs.doc()) + freq * idf_map.get(word));\r\n\t\t\t\t\t}\r\n\t\t\t\t}\r\n\t\t\t\tcnt++;\r\n\t\t\t}\r\n\t\t\tSet<Entry<Integer, Double>> se = dot_product_map.entrySet();\r\n\t\t\tjava.util.Iterator<Entry<Integer, Double>> iter = se.iterator();\r\n\t\t\twhile (iter.hasNext()) {\r\n\t\t\t\tMap.Entry<Integer, Double> me = (Entry<Integer, Double>) iter.next();\r\n\t\t\t\tsimilarity_map.put(me.getKey(), me.getValue() / (Math.sqrt(cnt) * doc_magnitude.get(me.getKey())));\r\n\t\t\t}\r\n\r\n\t\t\t// Normalize the map\r\n\t\t\tdouble sum = 0;\r\n\t\t\tfor (int i : similarity_map.keySet()) {\r\n\t\t\t\tsum += similarity_map.get(i);\r\n\t\t\t}\r\n\r\n\t\t\tfor (int i : similarity_map.keySet()) {\r\n\t\t\t\tdouble temp = similarity_map.get(i) / sum;\r\n\t\t\t\tsimilarity_map.put(i, temp);\r\n\t\t\t}\r\n\r\n\t\t\tString result=\"\";\r\n\r\n\t\t\tList<Integer> l1 = new ArrayList<Integer>();\r\n\t\t\tHashMap<Integer, Double> sim_map = sortMap(similarity_map, r);\r\n\t\t\tfor(Integer i:sim_map.keySet()){\r\n\t\t\t\tl1.add(i);\r\n\t\t\t\tDocument d1 = r.document(i);\r\n\t\t\t\tString url = d1.getFieldable(\"path\").stringValue();\r\n\t\t\t\t//String snippet = getSnippet(hmap.get(i));\r\n\t\t\t\turl = url.replace(\"%%\", \"/\");\r\n\t\t\t\tString snippet = Snippet.getContent(url,terms[0]); //read the content of url\r\n\t\t\t\tresult +=/*i+\" \"+*/url+\"\\n\";\r\n\t\t\t\tresult +=snippet+\"\\n\\n\\n\";\r\n\t\t\t\t//result += snippet+\"\\n\\n\";\r\n\t\t\t}\r\n\t\t\treturn result;\r\n\t\t\t\r\n}","public void analyzequery(JSONObject json) {\n\t\ttry {\n\t\t\t\n\t\t\tJSONArray jarray = json.getJSONArray(\"Reviews\");\n\t\t\t\n\t\t\tfor (int i = 0; i < jarray.length(); i++) {\n\t\t\t\t\n\t\t\t\tPost review = new Post(jarray.getJSONObject(i));\n\t\t\t\tSystem.out.println(\"55\");\n\t\t\t\tString content = review.getContent();\n\t\t\t\t\n\t\t\t\t\n\t\t\t\t\n\n\t\t\t\tHashMap<String, Integer> querytf = new HashMap<String, Integer>();\n\n\t\t\t\tHashSet<String> biminiset = new HashSet<String>();\n\n\t\t\t\tArrayList uniquery = new ArrayList();\n\n\t\t\t\tfor (String token : tokenizer.tokenize(content)) {\n\t\t\t\t\tif (m_stopwords.contains(token))\n\t\t\t\t\t\tcontinue;\n\t\t\t\t\tif (token.isEmpty())\n\t\t\t\t\t\tcontinue;\n\n\t\t\t\t\tuniquery.add(PorterStemmingDemo(SnowballStemmingDemo(NormalizationDemo(token))));\n\n\t\t\t\t}\n\n\t\t\t\tfor (int k = 0; k < uniquery.size(); k++) {\n\n\t\t\t\t\tif (querytf.containsKey(uniquery.get(i).toString())) {\n\t\t\t\t\t\tquerytf.put(uniquery.get(i).toString(),\n\t\t\t\t\t\t\t\tquerytf.get(uniquery.get(i).toString()) + 1);\n\t\t\t\t\t} else {\n\t\t\t\t\t\tquerytf.put(uniquery.get(i).toString(), 1);\n\t\t\t\t\t}\n\n\t\t\t\t}\n\n\t\t\t\tArrayList<String> N_gram = new ArrayList<String>();\n\n\t\t\t\tfor (String token : tokenizer.tokenize(content)) {\n\n\t\t\t\t\ttoken = PorterStemmingDemo(SnowballStemmingDemo(NormalizationDemo(token)));\n\t\t\t\t\tif (token.isEmpty()) {\n\n\t\t\t\t\t\tcontinue;\n\t\t\t\t\t} else {\n\n\t\t\t\t\t\tN_gram.add(token);\n\t\t\t\t\t}\n\n\t\t\t\t}\n\n\t\t\t\tString[] fine = new String[N_gram.size()];\n\n\t\t\t\tfor (int p = 0; p < N_gram.size() - 1; p++) {\n\t\t\t\t\tif (m_stopwords.contains(N_gram.get(p)))\n\t\t\t\t\t\tcontinue;\n\t\t\t\t\tif (m_stopwords.contains(N_gram.get(p + 1)))\n\t\t\t\t\t\tcontinue;\n\n\t\t\t\t\tfine[p] = N_gram.get(p) + \"-\" + N_gram.get(p + 1);\n\n\t\t\t\t}\n\n\t\t\t\t\n\t\t\t\tfor (String str2 : fine) {\n\n\t\t\t\t\tif (querytf.containsKey(str2)) {\n\t\t\t\t\t\tquerytf.put(str2, querytf.get(str2) + 1);\n\t\t\t\t\t} else {\n\t\t\t\t\t\tquerytf.put(str2, 1);\n\t\t\t\t\t}\n\t\t\t\t}\n\n\t\t\t\tfor (String key : querytf.keySet()) {\n\t\t\t\t\tif (m_stats.containsKey(key)) {\n\t\t\t\t\t\tdouble df = (double) m_stats.get(key);\n\n\t\t\t\t\t\tdouble idf = (1 + Math.log(102201 / df));\n\n\t\t\t\t\t\tdouble tf = querytf.get(key);\n\n\t\t\t\t\t\tdouble result = tf * idf;\n\n\t\t\t\t\t\tquery_idf.put(key, result);\n\t\t\t\t\t} else {\n\t\t\t\t\t\tquery_idf.put(key, 0.0);\n\t\t\t\t\t}\n\n\t\t\t\t}\n\t\t\t\t\n\t\t\t\t\n\t\t\t}\n\t\t\t\n\t\t\t\n\t\t}\n\t\tcatch (JSONException e) {\n\t\t\te.printStackTrace();\n\t\t}\n\t\t\n\t\t}","public void ComputeSimilarity() {\n\t\t\n\t\t//first construct the vector space representations for these five reviews\n\t\t// the our smaples vector, finally get the similarity metric \n\t\tanalyzequery(LoadJson(\"./data/samples/query.json\"));\n\t\n\t\t\n\t\tHashMap<String, Double> Similarity = new HashMap<String, Double>();\n\n\t\tfor (int i = 0; i < m_reviews.size(); i++) {\n\t\t\tString content = m_reviews.get(i).getContent();\n\n\t\t\tHashMap<String, Integer> conunttf = new HashMap<String, Integer>();\n\n\t\t\tHashSet<String> biminiset = new HashSet<String>();\n \n\t\t\t//danci means word unit: one or two words\n\t\t\tArrayList danci = new ArrayList();\n\n\t\t\tfor (String token : tokenizer.tokenize(content)) {\n\t\t\t\tif (m_stopwords.contains(token))\n\t\t\t\t\tcontinue;\n\t\t\t\tif (token.isEmpty())\n\t\t\t\t\tcontinue;\n\n\t\t\t\tdanci.add(PorterStemmingDemo(SnowballStemmingDemo(NormalizationDemo(token))));\n\n\t\t\t}\n \n\t\t\t//get word count in a document\n\t\t\tfor (int k = 0; k < danci.size(); k++) {\n\n\t\t\t\tif (conunttf.containsKey(danci.get(k).toString())) {\n\t\t\t\t\tconunttf.put(danci.get(k).toString(),\n\t\t\t\t\t\t\tconunttf.get(danci.get(k).toString()) + 1);\n\t\t\t\t} else {\n\t\t\t\t\tconunttf.put(danci.get(k).toString(), 1);\n\t\t\t\t}\n\n\t\t\t}\n\n\t\t\tArrayList<String> N_gram = new ArrayList<String>();\n\n\t\t\tfor (String token : tokenizer.tokenize(content)) {\n\n\t\t\t\ttoken = PorterStemmingDemo(SnowballStemmingDemo(NormalizationDemo(token)));\n\t\t\t\tif (token.isEmpty()) {\n\n\t\t\t\t\tcontinue;\n\t\t\t\t} else {\n\n\t\t\t\t\tN_gram.add(token);\n\t\t\t\t}\n\n\t\t\t}\n\n\t\t\tString[] fine = new String[N_gram.size()];\n \n\t\t\t//get rid of stopwords\n\t\t\tfor (int p = 0; p < N_gram.size() - 1; p++) {\n\t\t\t\tif (m_stopwords.contains(N_gram.get(p)))\n\t\t\t\t\tcontinue;\n\t\t\t\tif (m_stopwords.contains(N_gram.get(p + 1)))\n\t\t\t\t\tcontinue;\n\n\t\t\t\tfine[p] = N_gram.get(p) + \"-\" + N_gram.get(p + 1);\n\n\t\t\t}\n\n\t\t\t\n\t\t\tfor (String str2 : fine) {\n\n\t\t\t\tif (conunttf.containsKey(str2)) {\n\t\t\t\t\tconunttf.put(str2, conunttf.get(str2) + 1);\n\t\t\t\t} else {\n\t\t\t\t\tconunttf.put(str2, 1);\n\t\t\t\t}\n\t\t\t}\n \n\t\t\t//compute tf * idf for each document\n\t\t\tfor (String key : conunttf.keySet()) {\n\t\t\t\tif (m_stats.containsKey(key)) {\n\t\t\t\t\tdouble df = (double) m_stats.get(key);\n\n\t\t\t\t\tdouble idf = (1 + Math.log(102201 / df));\n\n\t\t\t\t\tdouble tf = conunttf.get(key);\n\n\t\t\t\t\tdouble result = tf * idf;\n\n\t\t\t\t\tm_idf.put(key, result);\n\t\t\t\t} else {\n\t\t\t\t\tm_idf.put(key, 0.0);\n\t\t\t\t}\n\n\t\t\t}\n\n\t\t\t\n\n\t\t\tHashMap<String, Double> query = new HashMap<String, Double>();\n\t\t\tHashMap<String, Double> test = new HashMap<String, Double>();\n \n\t\t\t//If query contains this word, store it for future computation \n\t\t\tfor (Map.Entry<String, Double> entry : m_idf.entrySet()) {\n\t\t\t\tString key = entry.getKey();\n\t\t\t\tif (query_idf.containsKey(key)) {\n\t\t\t\t\tquery.put(key, query_idf.get(key));\n\t\t\t\t\ttest.put(key, m_idf.get(key));\n\t\t\t\t}\n\t\t\t}\n\n\t\t\tdouble dotProduct = 0.00;\n\t\t\tdouble magnitude1 = 0.0;\n\t\t\tdouble magnitude2 = 0.0;\n\t\t\tdouble magnitude3 = 0.0;\n\t\t\tdouble magnitude4 = 0.0;\n\t\t\tdouble cosineSimilarity = 0;\n \n\t\t\t\n\t\t\t//compute Compute similarity between query document and each document in file\n\t\t\tfor (String cal : test.keySet()) {\n\t\t\t\tdotProduct += query.get(cal) * test.get(cal); // a.b\n\t\t\t\tmagnitude1 += Math.pow(query.get(cal), 2); // (a^2)\n\t\t\t\tmagnitude2 += Math.pow(test.get(cal), 2); // (b^2)\n\n\t\t\t\tmagnitude3 = Math.sqrt(magnitude1);// sqrt(a^2)\n\t\t\t\tmagnitude4 = Math.sqrt(magnitude2);// sqrt(b^2)\n\t\t\t}\n\n\t\t\tif (magnitude3 != 0.0 | magnitude4 != 0.0)\n\t\t\t\tcosineSimilarity = dotProduct / (magnitude3 * magnitude4);\n\n\t\t\telse\n\t\t\t\tcosineSimilarity = 0;\n\n\t\t\tSimilarity.put(content, cosineSimilarity);\n\n\t\t\t\t\t\n\n\t\t}\n\n\t\t// sort output to get 3 reviews with the highest similarity with query review\n\t\tList<Map.Entry<String, Double>> infoIds = new ArrayList<Map.Entry<String, Double>>(\n\t\t\t\tSimilarity.entrySet());\n\n\t\tCollections.sort(infoIds, new Comparator<Map.Entry<String, Double>>() {\n\t\t\tpublic int compare(Map.Entry<String, Double> o1,\n\t\t\t\t\tMap.Entry<String, Double> o2) {\n\t\t\t\treturn (int) (o1.getValue() - o2.getValue());\n\t\t\t}\n\t\t});\n\n\t\tfor (int i = infoIds.size() - 1; i > infoIds.size() - 4; i--) {\n\t\t\tEntry<String, Double> ent = infoIds.get(i);\n\t\t\tSystem.out.println(ent.getValue()+\"++\"+ent.getKey()+\"\\n\");\n\n\t\t}\n\n\t}","private ScoreDoc[] searchExec (Query query) {\n\n ScoreDoc[] hits = null;\n\n try {\n IndexReader reader = DirectoryReader.open(indexDir);\n IndexSearcher searcher = new IndexSearcher(reader);\n TopDocs docs = searcher.search(query, hitsPerPage, new Sort(SortField.FIELD_SCORE)); //search(query, docs);\n hits = docs.scoreDocs;\n } catch (IOException e) {\n e.printStackTrace();\n }\n\n return hits;\n }","private static String addQueryEntry(String query) throws IOException {\n\t\t\t\t\n\t\tString submittedQuery=null;\n\t\tString queryParts[]=query.split(\"&\"); // get parameters from query\t\t\n\t\tboolean isNextPage=false;\n\t\tString key=null;\n\t\tInteger value=null;\n\t\tboolean docsProcessed=false; // identifies if 'docs' occurs more than once in the query\t\t\n\t\tboolean termsProcessed=false; // identifies if 'terms' occurs more than once in the query\n\t\t\n\t\t// identify if it is a next page\n\t\tfor (int i=0;i<queryParts.length;i++) { // verifies if it is a next page\n\t\t\tString queryPartsFields[]=queryParts[i].split(\"=\",2);\t\t\t\n\t\t\tqueryPartsFields[0]=queryPartsFields[0].trim();\n\t\t\tif (queryPartsFields.length>1) {\n\t\t\t\tqueryPartsFields[1]=queryPartsFields[1].trim();\n\t\t\t}\n\t\t\t\n\t\t\tif (queryPartsFields[0].equals(DOCS_KEY) && queryPartsFields.length>1 && !queryPartsFields[1].equals(\"\")) {\t\t\t\n\t\t\t\tint ipage;\n\t\t\t\ttry {\n\t\t\t\t\tipage=Integer.parseInt(queryPartsFields[1]);\n\t\t\t\t}\n\t\t\t\tcatch (NumberFormatException e) {\n\t\t\t\t\tipage=0;\n\t\t\t\t}\n\t\t\t\t\n\t\t\t\tif (ipage!=0) { // regist only pages>0 \t\t\t\t\t\t\t\n\t\t\t\t\tisNextPage=true;\t\t\t\n\t\t\t\t\tif (ipage%RESULTS_PER_PAGE!=0) {\n\t\t\t\t\t\tSystem.err.println(\"Page results not multiple of \"+RESULTS_PER_PAGE+\": \"+ipage);\n\t\t\t\t\t\tipage+=ipage%RESULTS_PER_PAGE;\n\t\t\t\t\t}\n\t\t\t\t\tif (!docsProcessed) {\n\t\t\t\t\t\tint index=ipage/RESULTS_PER_PAGE>pagesViewedDistAux.length-1 ? pagesViewedDistAux.length-1 : ipage/RESULTS_PER_PAGE;\t\t\t\n\t\t\t\t\t\tif (index==0) { // sanity check\n\t\t\t\t\t\t throw new IOException(\"Error of index=0 on a next page. ipage:\"+ipage);\n\t\t\t\t\t\t}\n\t\t\t\t\t\tpagesViewedDistAux[index]++;\n\t\t\t\t\t}\n\t\t\t\t\tdocsProcessed=true;\t\t\t\t\n\t\t\t\t}\t\t\t\t\t\t\n\t\t\t}\n\t\t\telse if (queryPartsFields[0].equals(QUERY_KEY)) {\n\t\t\t\ttermsProcessed=true;\n\t\t\t}\n\t\t}\n\t\t// check wrong entries\n\t\tif (docsProcessed && !termsProcessed) {\n\t\t\tSystem.err.println(\"Error of query with docs without terms: \"+query);\n\t\t\treturn null;\n\t\t}\t\t\t\t\n\t\tif (isNextPage) {\n\t\t\treturn null;\n\t\t}\n\t\t\n\t\t// count only first page\n\t\tdocsProcessed=false;\n\t\tfor (int i=0;i<queryParts.length;i++) {\t\t\t\t\t\t\t\t\t\n\t\t\tString queryPartsFields[]=queryParts[i].split(\"=\",2);\t\t\t\n\t\t\tqueryPartsFields[0]=queryPartsFields[0].trim();\n\t\t\t\n\t\t\tif (!queryPartsFields[0].equals(QUERY_KEY) || queryPartsFields.length!=2) {\n\t\t\t\tcontinue;\n\t\t\t}\n\t\t\t\n\t\t\t// normalize query\t\t\t\n\t\t\ttry {\n\t\t\t\tqueryPartsFields[1]=decodeStrings(decodeNCR(java.net.URLDecoder.decode(queryPartsFields[1],\"ISO8859-1\").toLowerCase()));\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t}\n\t\t\tcatch(IllegalArgumentException e) {\n\t\t\t\tqueryPartsFields[1]=decodeStrings(decodeNCR(queryPartsFields[1].toLowerCase()));\n\t\t\t}\n\t\t\t// remove spaces\n\t\t\tString terms[]=queryPartsFields[1].split(\"\\\\s\");\n\t\t\tqueryPartsFields[1]=\"\";\n\t\t\tfor (int j=0,k=0;j<terms.length;j++) {\t\t\t\t\t\n\t\t\t\tif (terms[j].equals(\"\")) {\n\t\t\t\t\tcontinue;\n\t\t\t\t}\t\t\t\t\t\n\t\t\t\tif (k>0) {\n\t\t\t\t\tqueryPartsFields[1]+=\" \";\t\n\t\t\t\t}\n\t\t\t\tqueryPartsFields[1]+=terms[j];\t\t\t\t\t\n\t\t\t\tk++;\n\t\t\t}\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t// filter queries\t\t\t\t\t\n\t\t\tif (queryFiltersMap.containsKey(queryPartsFields[1]) || queryPartsFields[1].startsWith(\"cache%3\") || queryPartsFields[1].equals(\"\")) {\t\t\t\t\n\t\t\t\tcontinue;\n\t\t\t}\t\t\t\t\t\t\t\t\n\t\t\t// set first page viewed\n\t\t\tif (!docsProcessed) {\n\t\t\t\tpagesViewedDistAux[0]++;\n\t\t\t\tdocsProcessed=true;\t\t\t\t\t\t\n\t\t\t}\n\t\t\t\n\t\t\t//key=queryPartsFields[0]+\" \"+queryPartsFields[1];\n\t\t\tkey=NEW_QUERY_KEY+\" \"+queryPartsFields[1];\t\t\t\n\t\t\tif ((value=queryPartsMap.get(key))==null) {\n\t\t\t\tqueryPartsMap.put(key,1);\n\t\t\t}\n\t\t\telse {\n\t\t\t\tqueryPartsMap.put(key,value+1);\n\t\t\t}\n\t\t\t\n\t\t\t// set submitted query\n\t\t\tif (submittedQuery!=null) { // sanity check\n\t\t\t\tthrow new IOException(\"Submitted query already set.\");\n\t\t\t}\n\t\t\tsubmittedQuery=queryPartsFields[1];\n\t\t\t\t\n\t\t\t// count queries per session\t\n\t\t\tnQueriesSession++;\n\t\t}\n\t\treturn submittedQuery;\n\t}","public Set<String> calculateDistance() throws IOException {\n booleanSearch();\n\n Set<String> words = invertedIndexForQuerryWords.keySet();\n Map<String, Double> tfidfQuerry = new TreeMap<>();\n\n //load idf\n char c='a';\n char prC = 'v';\n for (String word : words){\n c = word.charAt(0);\n if(c != prC) {\n String path = Constants.PATH_TO_IDF + c + \"IDF.idf\";\n prC = c;\n idfMap.putAll(objectMapper.readValue(new File(path), new TypeReference<TreeMap<String, Double>>(){}));\n }\n }\n\n Map<String, Double> distanceMap = new HashMap<>();\n double sum = 0.0;\n //calculez norma interogarii\n for(String word:words){\n double idf, tf;\n if(idfMap.containsKey(word)) {\n idf = idfMap.get(word);\n tf = 1.0 / words.size();\n tfidfQuerry.put(word, tf * idf);\n\n sum += (tf * idf) * (tf * idf);\n } else {\n sum += 0.0;\n }\n }\n\n double normQuerry = Math.sqrt(sum);\n\n //iau toate documentele rezultate din boolean search\n Set<String> docs = new TreeSet<>();\n for(List<MyPair> list : invertedIndexForQuerryWords.values()) {\n if (list != null) {\n docs.addAll(list.stream().map(p -> p.getKey()).collect(Collectors.toSet()));\n }\n }\n\n List<File> documents = FileLoader.getFilesForInternalPath(\"Norms\", \".norm\");\n\n Map<String, Double> norms = new HashMap<>();\n for(File file : documents) {\n norms.putAll(objectMapper.readValue(file, new TypeReference<TreeMap<String, Double>>(){}));\n }\n\n //pentru fiecare document din boolean search calculez distanta cosinus\n for(String doc : docs) {\n\n String fileName = Paths.get(doc).getFileName().toString();\n\n String filePath = Constants.PATH_TO_TF + fileName.replaceFirst(\"[.][^.]+$\", \".tf\");\n\n Map<String, Double> tf = objectMapper.readValue(new File(filePath), new TypeReference<TreeMap<String, Double>>(){});\n double wordTF, wordIDF;\n double vectorialProduct = 0.0;\n double tfidfForQueryWord;\n\n for(String word : words) {\n if (tf.containsKey(word)) {\n wordTF = tf.get(word);\n wordIDF = idfMap.get(word);\n tfidfForQueryWord = tfidfQuerry.get(word);\n\n vectorialProduct += tfidfForQueryWord * wordIDF * wordTF;\n }\n }\n\n double normProduct = normQuerry * norms.get(Paths.get(doc).getFileName().toString());\n\n distanceMap.put(doc, vectorialProduct / normProduct);\n }\n\n //sortare distance map\n distanceMap = distanceMap.entrySet().stream()\n .sorted(Map.Entry.comparingByValue(Collections.reverseOrder()))\n .collect(Collectors.toMap(\n Map.Entry::getKey,\n Map.Entry::getValue,\n (e1, e2) -> e1,\n LinkedHashMap::new));\n\n// System.out.println(\"Cos distance:\");\n// for(Map.Entry entry : distanceMap.entrySet()){\n// System.out.println(entry);\n// }\n\n return distanceMap.keySet();\n }","public static void calcuTFIDF() throws IOException {\n\n\t\tHashtable<String, Double> idf = new Hashtable<String, Double>();\n\t\tArrayList<String> terms = new ArrayList<String>();\n\t\tdouble fileCount = 0.0;\n\t\tString featurePath = \"./corpus/features\";\n\t\tString featureWeight = \"./corpus/featureWeight\";\n\t\tString trainPath = \"./corpus/trainData\";\n\t\tString testPath = \"./corpus/testData\";\n\t\tString stopPath = \"./corpus/english.stop\";\n\t\tString trainOutPath = \"./corpus/trainVectors\";\n\t\tString testOutPath = \"./corpus/testVectors\";\n\t\tBufferedReader br = new BufferedReader(new FileReader(featurePath));\n\t\tBufferedWriter featureWriter = new BufferedWriter(new FileWriter(\n\t\t\t\tfeatureWeight));\n\t\tBufferedReader trainReader = new BufferedReader(new FileReader(\n\t\t\t\ttrainPath));\n\t\tBufferedReader testReader = new BufferedReader(new FileReader(testPath));\n\t\tBufferedReader br2 = new BufferedReader(new FileReader(stopPath));\n\t\tBufferedWriter writer = new BufferedWriter(new FileWriter(trainOutPath));\n\t\tBufferedWriter testWriter = new BufferedWriter(new FileWriter(\n\t\t\t\ttestOutPath));\n\t\tString oneline;\n\t\tArrayList<String> as = new ArrayList<String>();\n\t\twhile ((oneline = br2.readLine()) != null) {\n\t\t\tas.add(oneline);\n\t\t}\n\t\tString[] stopWords = new String[as.size()];\n\t\tas.toArray(stopWords);\n\t\tAnalyzer analyzer = new SnowballAnalyzer(\"English\", stopWords);\n\n\t\twhile ((oneline = br.readLine()) != null) {\n\t\t\tidf.put(oneline, 0.0);\n\t\t\tterms.add(oneline);\n\t\t}\n\n\t\twhile ((oneline = trainReader.readLine()) != null) {\n\n\t\t\tint pos = oneline.indexOf(\"\\t\");\n\t\t\tString topic = oneline.substring(0, pos);\n\t\t\tString content = oneline.substring(pos + 1);\n\t\t\tfileCount++;\n\t\t\tHashtable<String, Integer> termList = new Hashtable<String, Integer>();\n\t\t\tTokenStream stream = analyzer.tokenStream(\"\", new StringReader(\n\t\t\t\t\tcontent));\n\t\t\twhile (true) {\n\t\t\t\tToken token = stream.next();\n\t\t\t\tif (token == null)\n\t\t\t\t\tbreak;\n\t\t\t\tString tmp = token.termText();\n\t\t\t\tif (!termList.containsKey(tmp))\n\t\t\t\t\ttermList.put(tmp, new Integer(1));\n\t\t\t}\n\t\t\tSet<String> keys = termList.keySet();\n\t\t\tfor (String tmp : keys) {\n\t\t\t\tif (idf.containsKey(tmp)) {\n\t\t\t\t\tDouble num = idf.get(tmp);\n\t\t\t\t\tidf.put(tmp, num + 1);\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\n\t\tfor (String term : terms) {\n\n\t\t\tdouble weightOfTerm = Math.log((double) fileCount / idf.get(term)\n\t\t\t\t\t+ 0.01);\n\t\t\tfeatureWriter.write(term + \" \" + weightOfTerm);\n\t\t\tfeatureWriter.newLine();\n\t\t\tidf.put(term, weightOfTerm);\n\n\t\t}\n\t\tfeatureWriter.flush();\n\t\tfeatureWriter.close();\n\n\t\ttrainReader = new BufferedReader(new FileReader(trainPath));\n\t\twhile ((oneline = trainReader.readLine()) != null) {\n\n\t\t\tint pos = oneline.indexOf(\"\\t\");\n\t\t\tString topic = oneline.substring(0, pos);\n\t\t\tString content = oneline.substring(pos + 1);\n\t\t\tHashtable<String, Integer> termFrequent = new Hashtable<String, Integer>();\n\t\t\tTokenStream stream = analyzer.tokenStream(\"\", new StringReader(\n\t\t\t\t\tcontent));\n\t\t\twhile (true) {\n\t\t\t\tToken token = stream.next();\n\t\t\t\tif (token == null)\n\t\t\t\t\tbreak;\n\t\t\t\tString tmp = token.termText();\n\t\t\t\tif (!termFrequent.containsKey(tmp))\n\t\t\t\t\ttermFrequent.put(tmp, new Integer(1));\n\t\t\t\telse {\n\t\t\t\t\tInteger num = termFrequent.get(tmp);\n\t\t\t\t\ttermFrequent.put(tmp, num + 1);\n\t\t\t\t}\n\t\t\t}\n\t\t\tdouble weights[] = new double[terms.size()];\n\t\t\tdouble denominator = 0.0;\n\t\t\tint i = 0;\n\t\t\tfor (String term : terms) {\n\t\t\t\tdouble count;\n\t\t\t\tif (termFrequent.containsKey(term)) {\n\t\t\t\t\tcount = termFrequent.get(term);\n\t\t\t\t} else {\n\t\t\t\t\tcount = 0;\n\t\t\t\t}\n\n\t\t\t\tdouble tmp = count * idf.get(term);\n\t\t\t\tdenominator += tmp;\n\t\t\t\tweights[i++] = tmp;\n\t\t\t}\n\t\t\tdenominator = Math.sqrt(denominator);\n\t\t\twriter.write(topic);\n\t\t\tfor (int j = 1; j <= weights.length; j++) {\n\t\t\t\tdouble tmp = weights[j - 1];\n\t\t\t\tif (tmp > 0.0) {\n\t\t\t\t\ttmp = Math.sqrt(tmp) / denominator;\n\t\t\t\t\twriter.write(\" \" + j + \":\" + tmp);\n\t\t\t\t}\n\t\t\t}\n\t\t\twriter.newLine();\n\t\t}\n\n\t\twhile ((oneline = testReader.readLine()) != null) {\n\n\t\t\tint pos = oneline.indexOf(\"\\t\");\n\t\t\tString topic = oneline.substring(0, pos);\n\t\t\tString content = oneline.substring(pos + 1);\n\t\t\tHashtable<String, Integer> termFrequent = new Hashtable<String, Integer>();\n\t\t\tTokenStream stream = analyzer.tokenStream(\"\", new StringReader(\n\t\t\t\t\tcontent));\n\t\t\twhile (true) {\n\t\t\t\tToken token = stream.next();\n\t\t\t\tif (token == null)\n\t\t\t\t\tbreak;\n\t\t\t\tString tmp = token.termText();\n\t\t\t\tif (!termFrequent.containsKey(tmp))\n\t\t\t\t\ttermFrequent.put(tmp, new Integer(1));\n\t\t\t\telse {\n\t\t\t\t\tInteger num = termFrequent.get(tmp);\n\t\t\t\t\ttermFrequent.put(tmp, num + 1);\n\t\t\t\t}\n\t\t\t}\n\t\t\tdouble weights[] = new double[terms.size()];\n\t\t\tdouble denominator = 0.0;\n\t\t\tint i = 0;\n\t\t\tfor (String term : terms) {\n\t\t\t\tdouble count;\n\t\t\t\tif (termFrequent.containsKey(term)) {\n\t\t\t\t\tcount = termFrequent.get(term);\n\t\t\t\t} else {\n\t\t\t\t\tcount = 0;\n\t\t\t\t}\n\t\t\t\tdouble tmp = count * idf.get(term);\n\t\t\t\tdenominator += tmp;\n\t\t\t\tweights[i++] = tmp;\n\t\t\t}\n\t\t\tdenominator = Math.sqrt(denominator);\n\t\t\ttestWriter.write(topic);\n\t\t\tfor (int j = 1; j <= weights.length; j++) {\n\t\t\t\tdouble tmp = weights[j - 1];\n\t\t\t\tif (tmp > 0.0) {\n\t\t\t\t\ttmp = Math.sqrt(tmp) / denominator;\n\t\t\t\t\ttestWriter.write(\" \" + j + \":\" + tmp);\n\t\t\t\t}\n\t\t\t}\n\t\t\ttestWriter.newLine();\n\t\t}\n\t\twriter.close();\n\t\ttestWriter.close();\n\t}","public void makeQueryTermList() {\n for (int i = 0; i < this.stemmed_query.size(); i++) {\n boolean added = false;\n String curTerm = this.stemmed_query.get(i);\n for (int j = 0; j < this.query_terms_list.size(); j++) {\n if (this.query_terms_list.get(j).strTerm.compareTo(curTerm) == 0) {\n this.query_terms_list.get(j).timeOccur++;\n added = true;\n break;\n }\n }\n if (added == false) {\n this.query_terms_list.add(new QueryTerm(curTerm));\n }\n }\n }","public interface Query {\n\n\t/**\n\t * @return ID of the given query\n\t */\n\tint queryID();\n\t\n\t/**\n\t * @return given query\n\t */\n\tString query();\n\t\n\t/**\n\t * @return list of relevant documents to the corresponding query\n\t */\n\tList<RelevanceInfo> listOfRelevantDocuments();\n\t\n\t/**\n\t * @return list of results to the corresponding query after running one of the retrieval models\n\t */\n\tList<Result> resultList();\n\t\n\t/**\n\t * @param resultList\n\t * @Effects adds results to the result list of the corresponding query\n\t */\n\tvoid putResultList(List<Result> resultList);\n}","private ArrayList<WordDocument> executeAdvancedQuery(){\n ArrayList<WordDocument> documents = customDijkstrasTwoStack(this.query.split(\" \"));\n ArrayList<WordDocument> result = new ArrayList<WordDocument>();\n\n try{\n String[] orderByPart = query.substring(query.indexOf(\"ORDERBY\")).trim().toLowerCase().split(\" \");\n if(isOrderByCommand(orderByPart[0]))\n result = orderBy(documents, orderByPart[1], orderByPart[2]);\n }catch (StringIndexOutOfBoundsException ex){\n result = documents;\n }\n\n return result;\n }","public List<Integer> processRelatedDocs(Query query) {\r\n List<Integer> result = new ArrayList<>();\r\n\r\n if (query.isTerm()) {\r\n\r\n result = this.processRelatedDocsQuery(query.getText());\r\n\r\n } else {\r\n\r\n //query.getNodes().keySet()\r\n for (BooleanClause.Occur key : new BooleanClause.Occur[] {\r\n BooleanClause.Occur.MUST,\r\n BooleanClause.Occur.SHOULD,\r\n BooleanClause.Occur.MUST_NOT }) {\r\n\r\n List<Query> nodes = query.getNodes().get(key);\r\n\r\n // no-op\r\n if(nodes.isEmpty()) continue;\r\n\r\n switch (key) {\r\n /* AND */ case MUST:\r\n for (Query node : nodes) {\r\n List<Integer> rel = this.processRelatedDocs(node);\r\n result = this.operator.and(result, rel);\r\n }\r\n break;\r\n /* OR */ case SHOULD:\r\n for (Query node : nodes) {\r\n List<Integer> rel = this.processRelatedDocs(node);\r\n result = this.operator.or(result, rel);\r\n }\r\n break;\r\n /* NOT */ case MUST_NOT:\r\n for (Query node : nodes) {\r\n List<Integer> rel = this.processRelatedDocs(node);\r\n result = this.operator.not(result, rel);\r\n }\r\n break;\r\n }\r\n }\r\n }\r\n\r\n return result;\r\n }","@Override\n public synchronized Long count(String query) {\n long count = 0L;\n String nQuery = normalizeQuery(query);\n Set<String> keys = suggestIndex.getKeys();\n Map index = suggestIndex.getIndex();\n LinkedHashSet<Long> result = new LinkedHashSet<Long>();\n\n logger.debug(\"IN SEARCH: query={}, keys={}\", query, keys);\n\n StringBuilder patternBuilder;\n List<Pattern> patterns = new ArrayList<Pattern>();\n for (String keyPart : nQuery.split(\" \")) {\n patternBuilder = new StringBuilder(\"^(?iu)\");\n patternBuilder.append(ALLOWED_CHARS_REGEXP);\n keyPart = Normalizer.normalize(keyPart, Normalizer.Form.NFD);\n patternBuilder.append(keyPart)\n .append(ALLOWED_CHARS_REGEXP)\n .append('$');\n patterns.add(Pattern.compile(patternBuilder.toString()));\n }\n\n for (String key : keys) {\n for (Pattern pattern : patterns) {\n\n if (pattern.matcher(key).matches()) {\n result.addAll((LinkedHashSet<Long>) index.get(key));\n count += ((LinkedHashSet<Long>) index.get(key)).size();\n }\n }\n }\n return Long.valueOf(result.size());\n }","CampusSearchQuery generateQuery();","public void set_graph() throws ParseException, IOException {\n \tg = new WeightedUndirectedGraph(words.length);\n //g = new WeightedUndirectedGraph(most_important_terms.size());\n \n Directory dir = new SimpleFSDirectory(new File(\".\\\\data\\\\lucene_index_r_r\"));\n Analyzer analyzer = new StandardAnalyzer(LUCENE_41);\n \n // creat a map that stores, for each word (in the cluster), a set of all the documents that contain that word\n HashMap<String,HashSet<Integer>> word_to_docs_map = new HashMap<String,HashSet<Integer>>();\n int n_strings = words.length; \n \n // for each word...\n for (int idx = 0; idx < n_strings; idx++) {\n // query the index with that given word and retrieve all the documents that contains that word\n String query = words[idx]; \n QueryParser parser = new QueryParser(Version.LUCENE_41, \"text\", analyzer); \n Query q = parser.parse(query); \n\n IndexReader reader = DirectoryReader.open(dir);\n IndexSearcher searcher = new IndexSearcher(reader);\n TopDocs docs = searcher.search(q, reader.numDocs());\n ScoreDoc[] hits = docs.scoreDocs;\n \n // update map from word to docs it appears in \n //HashSet<Integer> tmp = null;\n // tmp is the set of all the document ids in which the current word is contained\n HashSet<Integer> tmp = new HashSet<>();\n //word_to_docs_map.put(query, tmp);\n \n // for each document, retrieved from the query\n for(Integer i=0;i<hits.length;i++) {\n Integer docId = hits[i].doc;\n // tmp = word_to_docs_map.get(query); \n // if the document is a document written by an user of interest \n if(indices.contains(docId)) {\n tmp.add(docId);\n }\n //word_to_docs_map.put(query, tmp); \n }\n word_to_docs_map.put(query, tmp);\n\t }\n\t \n\t // add edges: iterate over possible term pairs ...\n\t for(int idx_1 = 0; idx_1 < n_strings - 1; idx_1++) {\n\t \n\t for(int idx_2 = idx_1 + 1 ; idx_2 < n_strings ; idx_2 ++ ) {\n\t \n\t // extract document sets associated with the considered terms \n\t HashSet<Integer> set_a = word_to_docs_map.get(words[idx_1]); \n\t HashSet<Integer> set_b = word_to_docs_map.get(words[idx_2]); \n\t \n\t // compute set intersection \n\t int n = intersectionSize(set_a, set_b);\n\t \n\t // if the terms appear in at least one common document\n\t if(n>0) {\n\t // add edge \n\t g.testAndAdd(idx_1, idx_2 , n); \n\t }\n\t } \n\t }\n\t}","@Override\n public boolean onQueryTextSubmit(String query) {\n prepareBooks(engine.search(query.toLowerCase(),filter));\n return false;\n }","public static List<String> query_intersect(List<String> queryWords) throws IOException {\n\t\tif (!initialized) initialize();\n\t\tList<PostingList> pls = new ArrayList<PostingList> ();\n\t\tfor (String queryWord : queryWords) {\n\t\t\tqueryWord = queryWord.toLowerCase();\n\t\t\tif (!termDict.containsKey(queryWord)) {\n\t\t\t\tpls.clear();\n\t\t\t\tbreak;\n\t\t\t}\n\t\t\tPostingList pl = readPosting(fc, termDict.get(queryWord));\n\t\t\tif (pl == null) {\n\t\t\t\tpls.clear();\n\t\t\t\tbreak;\n\t\t\t}\n\t\t\tpls.add(readPosting(fc, termDict.get(queryWord)));\n\t\t}\n\t\tCollections.sort(pls, new Comparator<PostingList>(){\n\t\t public int compare(PostingList p1, PostingList p2) {\n\t\t return p1.size() - p2.size(); // assumes you want biggest to smallest\n\t\t }\n\t\t});\n\t\tif (pls.size() == 0) {\n\t\t\treturn null;\n\t\t} else {\n\t\t\tList<Integer> current = pls.get(0).getList();\n\t\t\tfor (int i = 1; i < pls.size(); i++) {\n\t\t\t\tList<Integer> toBeAdd = pls.get(i).getList();\n\t\t\t\tcurrent = intersect(current, toBeAdd);\n\t\t\t}\n\t\t\tif (current.size() == 0) {\n\t\t\t\treturn null;\n\t\t\t} else {\n\t\t\t\tList<String> result = new ArrayList<String>();\n\t\t\t\tfor (int docId : current) {\n\t\t\t\t\tresult.add(docDict.get(docId));\n\t\t\t\t}\n\t\t\t\treturn result;\n\t\t\t}\n\t\t}\n\t}","public void calculateTermWeights() {\n\t\tfor (String termString : terms.keySet()) {\n\t\t\tTerm t = terms.get(termString);\n\t\t\tMap<Integer, TermDoc> posting = t.getPostings();\n\n\t\t\t// Iterate through the docs in which the selected term is found.\n\t\t\tfor (Integer docId : posting.keySet()) {\n\n\t\t\t\tTermDoc td = posting.get(docId);\n\t\t\t\tDocument doc = this.getDocument(docId);\n\n\t\t\t\tfinal double a = 0.4;\n\t\t\t\tdouble ntf = a + (1 - a) * (double) td.getFreq() / (double) doc.getMaxTermFreq();\n\t\t\t\tdouble idf = Math.log((double) documents.size() / (1 + (double) t.getDocFreq()));\n\t\t\t\tdoc.addWeight(termString, ntf * idf);\n\t\t\t}\n\t\t}\n\n\t\tfor (Document doc : documents.values())\n\t\t\tdoc.setEuclideanDistance();\n\t}","public void parseAndRankQuery(String stringNumber) throws Exception {\n\n if (this.semantics) { //if the user choose semantic\n semantic=new ArrayList<>();\n Word2VecModel model = Word2VecModel.fromTextFile(new File(\"word2vec.c.output.model.txt\"));\n com.medallia.word2vec.Searcher semanticSearchrt = model.forSearch();\n int num = 10;\n String[] semanQuery = query.split(\" \");\n for (String s : semanQuery)\n {\n try {\n List<com.medallia.word2vec.Searcher.Match> matches = semanticSearchrt.getMatches(s.toLowerCase(), num);\n for (com.medallia.word2vec.Searcher.Match match : matches) {\n match.match();\n }\n if(matches.get(0).equals(s)) {\n query = query + \" \" + matches.get(1);\n String dd=\"\"+matches.get(1);\n semantic.add(dd);\n }\n else {\n query = query + \" \" + matches.get(0); //add to query the high semantics 3 top words score\n String dd=\"\"+matches.get(0);\n semantic.add(dd);\n }\n } catch(com.medallia.word2vec.Searcher.UnknownWordException e){\n }\n }\n }\n\n ranker = new Ranker(this.indexer,stringNumber,path,originalString); // new ranker\n ArrayList<String> cleanQuery;\n ArrayList<String> parsedQueryList;\n ReadFile rd=new ReadFile();\n cleanQuery=rd.cleanLine(stemming,query); //clean the query from dots and other signs\n HashMap<String, Pair<Integer,String>> parsedQuery=new HashMap<>();\n parsedQuery=parser.Tokenizer(cleanQuery,\"\",stemming); //parse the query\n Iterator it = parsedQuery.entrySet().iterator();\n parsedQueryList=new ArrayList<>();\n while (it.hasNext()) {\n Map.Entry pair = (Map.Entry)it.next();\n parsedQueryList.add((String)pair.getKey());\n it.remove(); // avoids a ConcurrentModificationException\n }\n ranker.setParseredQuery(parsedQueryList);\n try {\n ranker.orgByPostFile();\n } catch (FileNotFoundException e) {\n e.printStackTrace();\n }\n }","public void testAdvancedQuery() {\n\t\t//manager.advancedQuery(ElasticIndex.analyzed, \"metropolitan areas\", \"sports clubs\");\n\t\t//manager.advancedQuery(ElasticIndex.analyzed, \"\", \"Award\");\n\n\t//manager.advancedQuery(ElasticIndex.analyzed,\"american actor\", \"list of movies starring Sean Connery\");\n//\tmanager.categorySearch(\"Sportspeople\", \"tennis\",ElasticIndex.analyzed,30);\n\t//manager.advancedQuery(ElasticIndex.analyzed,\"Broadway musicals\", \"Grammy Award\");\n\t//manager.advancedQuery(ElasticIndex.analyzed,\"musical movies\", \"Tony Award\");\n\t//manager.advancedQuery(ElasticIndex.analyzed,\"Top level football leagues\", \"teams\");\n\t//manager.advancedQuery(ElasticIndex.analyzed,\"american movies\", \"directed by Woody Allen\");\n\t//manager.advancedQuery(ElasticIndex.analyzed,\"United states\", \"professional sports teams\");\n\t\t//manager.advancedQuery(\"musical movies\", \"tony award\");\n\t\t//manager.advancedQuery(\"grammy\", \"best album in 2012\"); \n\t\t//manager.advancedQuery(\"american movies\", \"directed by Woody Allen\"); \n\t\t//Canceled manager.advancedQuery(\"tennis\", \"international players\"); \n\t\t// canceled manager.advancedQuery(\"tennis\", \"french open\"); \n\t\t// canceled manager.advancedQuery(\"film movie\", \"1933\"); \n//\t\tmanager.advancedQuery(\"United states\", \"professional sports teams \");\n//\t\t manager.advancedQuery(\"computer games\", \"developed by Ubisoft\");\n//\t\tmanager.advancedQuery(\"movies\", \"academy award nominations\");\n //manager.advancedQuery(\"movies\", \"starring Dustin Hoffman\");\n // manager.advancedQuery(\"movies\", \"best costume design\");\n // manager.advancedQuery(\"concert tours\", \"england\");\n // manager.advancedQuery(\"sport\", \"Francesco\");\n\t\t//System.out.println(\"******* advanced query *******\");\n\t\t//manager.advancedQuery(\"sportspeople\", \"tennis\");\n//\t\tmanager.advancedQuery(ElasticIndex.analyzed, \"Broadway musicals\", \"Grammy Award\");\n //System.out.println(\"*****************************\");\n\n\n\t\t\n\t\t//manager.advancedQuery(\"football\", \"italian championship\");\n\t\t//manager.advancedQuery(\"american basketball\", \"team\");\n\t\t //manager.advancedQuery(\"Goya Award\", \"Winner and nominees from FRA\");\n\t\t//manager.advancedQuery(\"films\", \"american comedy \");\n\t\t//manager.advancedQuery(\"films\", \"american Adventure directed by James P. Hogan\");\n\t\t//manager.advancedQuery(\"NCAA Division\", \"american universities in Arkansas\");\n\t\t//manager.advancedQuery(\"Academy award\", \"winners and nominees in acting in 2011\");\n\t\t//manager.advancedQuery(\"canadian soccer\", \"Alain Rochat position \");\n\n\t}","public Vector mapDocument(BOW bow) {\n //logger.info(\"lsm.mapDocument\");\n SparseVector vector = new SparseVector();\n\n Iterator<String> it = bow.termSet().iterator();\n String term = null;\n int index = 0;\n //int tf = 0;\n float tfIdf;\n for (int i = 0; it.hasNext(); i++) {\n //logger.info(i + \" \" + t[i]);\n term = it.next();\n index = termIndex.get(term);\n\n if (index != -1) {\n //tf = bow.getFrequency(term);\n //tfIdf = (float) (log2(tf)) * Iidf[index];\n //tfIdf = (float) bow.augmentedFrequency(term) * Iidf[index];\n tfIdf = (float) bow.tf(term) * Iidf[index];\n //logger.info(term + \" ==> \" + index + \", tf.idf = \" + tf + \"(\" + (log2(tf)) + \") * \" + Iidf[index] + \" = \" + tfIdf);\n vector.add(index, tfIdf);\n\n }\n } // end for\n\n return vector;\n }","public void updateTermInThisQuery(int relevanceFeedbackMethod) {\n query thisQuery = listDocumentRetrievedForThisQuery.getQuery();\n StringTokenizer token = new StringTokenizer(thisQuery.getQueryContent(), \" %&\\\"*#@$^_<>|`+=-1234567890'(){}[]/.:;?!,\\n\");\n while (token.hasMoreTokens()) {\n String keyTerm = token.nextToken();\n String filteredWord;\n if (invertedFileQuery.isStemmingApplied()) {\n filteredWord = StemmingPorter.stripAffixes(keyTerm);\n } else {\n filteredWord = keyTerm;\n }\n try {\n termWeightingDocument relation = invertedFileQuery.getListTermWeights().get(filteredWord);\n if (relation.getDocumentWeightCounterInOneTerm().get(thisQuery.getIndex()) != null) {\n double oldWeight = relation.getDocumentWeightCounterInOneTerm().get(thisQuery.getIndex()).getWeight();\n double newWeight = computeNewWeightTerm(relevanceFeedbackMethod,filteredWord,oldWeight);\n if (newWeight > 0) {\n newQueryComposition.put(keyTerm, newWeight);\n relation.getDocumentWeightCounterInOneTerm().get(thisQuery.getIndex()).setWeight(newWeight);\n } else {\n relation.getDocumentWeightCounterInOneTerm().get(thisQuery.getIndex()).setWeight(0.0);\n }\n }\n } catch (Exception e) {\n\n }\n }\n }","public List<Classes.Document> RetrieveQuery(Classes.Query cQuery, int TopN, int TopK, double alpha) throws Exception { \r\n\t\t// Get P(token|feedback model)\r\n\t\tHashMap<String, Double> TokenRFScore = GetTokenRFScore(cQuery, TopK);\r\n\r\n\t\t// Store sorted top N results (from most relevant to least)\r\n\t\tList<Classes.Document> rankedList = new ArrayList<>();\r\n\t\t\r\n\t\t// Get query's content as input into retrieval model\r\n\t\tString[] tokens = cQuery.getQueryContent().split(\" \");\r\n\t\tList<DocScore> docScoreList = new ArrayList<>();\r\n\t\tqueryResult.forEach((luceneID, tfMap) -> {\r\n\t\t int doclen = 0;\r\n\t\t double score = 1.0;\r\n\t\t try {\r\n\t\t doclen = myireader.docLength(luceneID);\r\n\t\t } catch (Exception e) {\r\n\t\t \t e.printStackTrace();\r\n\t\t };\r\n\t\t \r\n\t\t /**\r\n\t\t\t * Dirichlet Prior Smoothing:\r\n\t\t\t * p(w|D) = (|D|/(|D|+MU))*(c(w,D)/|D|) + (MU/(|D|+MU))*p(w|REF)\r\n\t\t * score = λ*p_doc + (1-λ)*p_ref\r\n\t\t * = c1*p_doc + c2*p_ref\r\n\t\t\t */\r\n\t\t double c1 = doclen / (doclen + MU);\r\n\t\t double c2 = MU / (doclen + MU);\r\n\t\t for(String token : tokens) {\r\n\t\t \t long cf = termFreq.get(token);\r\n\t\t \t if(cf == 0) {\t\r\n\t\t \t\t continue;\r\n\t\t \t }\r\n\t\t \r\n\t\t \t int tf = tfMap.getOrDefault(token, 0);\r\n\t\t \t double p_doc = (double) tf / doclen; // c(w, D)\r\n\t\t \t double p_ref = (double) cf / CORPUS_SIZE; // p(w|REF)\r\n\t\t \t \r\n\t\t \t // Get the final probability of each token with pseudo RF score\r\n\t\t \t score *= alpha * (c1 * p_doc + c2 * p_ref) + (1 - alpha) * TokenRFScore.get(token);\r\n\t\t }\r\n\t\t \r\n\t\t DocScore docScore = new DocScore(luceneID, score);\r\n\t\t docScoreList.add(docScore);\r\n\t\t}); // The end of forEach loop block\r\n\r\n\t\t// Sort the result List \r\n\t\tCollections.sort(docScoreList, new Comparator<DocScore>() {\r\n\t\t\t@Override\r\n\t\t\tpublic int compare(DocScore ds1, DocScore ds2) {\r\n\t\t\t\tif(ds1.score != ds2.score) {\r\n\t\t\t\t\treturn ds1.score < ds2.score ? 1 : -1;\r\n\t\t\t\t} else {\r\n\t\t\t\t\treturn 1;\r\n\t\t\t\t}\r\n\t\t\t}\r\n\t\t});\r\n\r\n\t\t// Put all documents into result list\r\n\t\tfor(int n = 0; n < TopN; n++) {\r\n\t\t DocScore docScore = docScoreList.get(n);\r\n\t\t Classes.Document doc = null;\r\n\t\t try {\r\n\t\t \t int luceneID = docScore.getId(); // Get Lucene id\r\n\t\t \t doc = new Document(Integer.toString(luceneID), \r\n\t\t \t\t\t \t\t\tmyireader.getDocno(luceneID), \r\n\t\t \t\t\t docScore.getScore(),\r\n\t\t \t\t\t dreader.document(luceneID).get(\"restName\"),\r\n\t\t \t\t\t dreader.document(luceneID).get(\"restUrl\"),\r\n\t\t \t\t\t dreader.document(luceneID).get(\"originalContent\"));\r\n\t\t } catch(Exception e) {\r\n\t\t \t e.printStackTrace();\r\n\t\t };\r\n\t\t \r\n\t\t rankedList.add(doc);\r\n\t\t}\r\n\r\n\t\treturn rankedList;\r\n\t}","public static void docWtgArray() {\n int docCount = 0;\n\n while(docCount<totaldocument) {\n List<Double> pass = new ArrayList();\n for(Entry<String,List<Double>> entry : wtgMap.entrySet()) {\n List<Double> docList = new ArrayList();\n docList = entry.getValue();\n double temp = docList.get(docCount);\n pass.add(temp);\n }\n\n double answer = CosineSimilarity(pass,query);\n if(answer >= alpha) {\n DocID.put(docCount,answer);\n }\n docCount++;\n }\n }","protected Query newTermQuery(Term term, float boost) {\n Query q = new TermQuery(term);\n if (boost == DEFAULT_BOOST) {\n return q;\n }\n return new BoostQuery(q, boost);\n }","@Override\r\n\t\t\tpublic List<ScoredDocument> search(Query query, long maxNumberOfDocuments) {\n\t\t\t\treturn null;\r\n\t\t\t}","public ArrayList<String> getResults(String query) {\r\n\t\t// TODO: Add code here\r\n\t\tHashMap<String,Double> map=new HashMap<>();\r\n\t\tArrayList<String> urls=wordIndex.get(query);\r\n\t\tif(urls==null){\r\n\t\t\treturn new ArrayList<>();\r\n\t\t}\r\n\t\tfor(String url:urls){\r\n\t\t\tmap.put(url,internet.getPageRank(url));\r\n\t\t}\r\n\t\treturn Sorting.fastSort(map);\r\n\t}","public void actionPerformed(ActionEvent e) {\n displayInfoText(\" \");\n // Turn the search string into a Query\n String queryString = queryWindow.getText().toLowerCase().trim();\n query = new Query(queryString);\n // Take relevance feedback from the user into account (assignment 3)\n // Check which documents the user has marked as relevant.\n if (box != null) {\n boolean[] relevant = new boolean[box.length];\n for (int i = 0; i < box.length; i++) {\n if (box[i] != null)\n relevant[i] = box[i].isSelected();\n }\n query.relevanceFeedback(results, relevant, engine);\n }\n // Search and print results. Access to the index is synchronized since\n // we don't want to search at the same time we're indexing new files\n // (this might corrupt the index).\n long startTime = System.currentTimeMillis();\n synchronized (engine.indexLock) {\n results = engine.searcher.search(query, queryType, rankingType);\n }\n long elapsedTime = System.currentTimeMillis() - startTime;\n // Display the first few results + a button to see all results.\n //\n // We don't want to show all results directly since the displaying itself\n // might take a long time, if there are many results.\n if (results != null) {\n displayResults(MAX_RESULTS, elapsedTime / 1000.0);\n } else {\n displayInfoText(\"Found 0 matching document(s)\");\n\n if (engine.speller != null) {\n startTime = System.currentTimeMillis();\n SpellingOptionsDialog dialog = new SpellingOptionsDialog(50);\n String[] corrections = engine.speller.check(query, 10);\n elapsedTime = System.currentTimeMillis() - startTime;\n System.err.println(\"It took \" + elapsedTime / 1000.0 + \"s to check spelling\");\n if (corrections != null && corrections.length > 0) {\n String choice = dialog.show(corrections, corrections[0]);\n if (choice != null) {\n queryWindow.setText(choice);\n queryWindow.grabFocus();\n\n this.actionPerformed(e);\n }\n }\n }\n }\n }","public QueryController(String[] args){\n // Parse Args\n QueryArgs queryArgs = new QueryArgs();\n try {\n queryArgs.parseArgs(args);\n } catch (FileNotFoundException e) {\n //e.printStackTrace();\n System.err.println(\"Invalid Arguments received. Please check your arguments passed to ./search\");\n return;\n }\n\n // Run the Term Normaliser\n TermNormalizer normalizer = new TermNormalizer();\n String[] queryTerms = normalizer.transformedStringToTerms(queryArgs.queryString);\n\n //create the model\n Model model = new Model();\n model.loadCollectionFromMap(queryArgs.mapPath);\n model.loadLexicon(queryArgs.lexiconPath);\n model.loadInvertedList(queryArgs.invlistPath);\n if(queryArgs.stopListEnabled)\n {\n model.loadStopList(queryArgs.stopListPath);\n }\n if(queryArgs.printSummary && queryArgs.collectionPath != \"\")\n {\n model.setPathToCollection(queryArgs.collectionPath);\n }\n\n\n //fetch the top results from the query module\n QueryModule queryModule = new QueryModule();\n queryModule.doQuery(queryTerms, model, queryArgs.bm25Enabled);\n List<QueryResult> topResults = queryModule.getTopResult(queryArgs.maxResults);\n\n\n\n ResultsView resultsView = new ResultsView();\n if(queryArgs.printSummary)\n {\n\n DocSummary docSummary = new DocSummary();\n for(QueryResult result:topResults)\n {\n // retrieve the actualy text from the document collection\n result.setDoc(model.getDocumentCollection().getDocumentByIndex(result.getDoc().getIndex(), true));\n\n //set the summary on the result object by fetching it from the docSummary object\n result.setSummaryNQB(docSummary.getNonQueryBiasedSummary(result.getDoc(), model.getStopListModule()));\n result.setSummaryQB(docSummary.getQueryBiasedSummary(result.getDoc(), model.getStopListModule(), Arrays.asList(queryTerms)));\n }\n resultsView.printResultsWithSummary(topResults,queryArgs.queryLabel);\n }else\n {\n resultsView.printResults(topResults,queryArgs.queryLabel);\n }\n\n }","@Test\n public void testPhrase() {\n assertQ(req(\"q\",\"text:now-cow\", \"indent\",\"true\")\n ,\"//*[@numFound='1']\"\n );\n // should generate a query of (now OR cow) and match both docs\n assertQ(req(\"q\",\"text_np:now-cow\", \"indent\",\"true\")\n ,\"//*[@numFound='2']\"\n );\n }","public Vector mapDocument(MultiSet<String> bow) {\n //logger.info(\"lsm.mapDocument\");\n SparseVector vector = new SparseVector();\n\n Iterator<String> it = bow.iterator();\n String term = null;\n int index = 0;\n int tf = 0;\n float tfIdf;\n for (int i = 0; it.hasNext(); i++) {\n //logger.info(i + \" \" + t[i]);\n term = it.next();\n index = termIndex.get(term);\n\n if (index != -1) {\n tf = bow.getFrequency(term);\n tfIdf = (float) (log2(tf)) * Iidf[index];\n\n //logger.info(term + \" ==> \" + index + \", tf.idf = \" + tf + \"(\" + (log2(tf)) + \") * \" + Iidf[index] + \" = \" + tfIdf);\n vector.add(index, tfIdf);\n\n }\n } // end for\n\n return vector;\n }","public SortedSet<LabeledVector> query(double[] queryVector) {\n SortedSet<LabeledVector> sortedSet = new TreeSet<LabeledVector>(new LabeledVectorCompare(queryVector));\n for (int i = 0; i < vectors.length; i++) {\n boolean addedDoc = sortedSet.add(new LabeledVector(i, vectors[i]));\n assert(addedDoc);\n }\n return sortedSet;\n }","public Utwor search2(String query) {\n for (Utwor utwor : utwory) {\n if (utwor.getTitle().equals(query)) {\n return utwor;\n }\n }\n return null;\n }","@Override\n public void postInserts() \n {\n for(IndexObject i: myIndex.values())\n {\n i.tfidf(documentData);\n }\n }","public abstract double score(double tf, double docLength);","public ArrayList<String> top5search(String kw1, String kw2) {\n\t\t/** COMPLETE THIS METHOD **/\n\t\tArrayList<String> results = new ArrayList<String>();\n\t\tArrayList<Occurrence> ocArr1 = new ArrayList<Occurrence>();\n\t\tArrayList<Occurrence> ocArr2 = new ArrayList<Occurrence>();\n\t\tArrayList<Occurrence> combined = new ArrayList<Occurrence>();\n\t\t\n\t\tif (keywordsIndex.containsKey(kw1))\n\t\t\tocArr1 = keywordsIndex.get(kw1);\n\t\t\n\t\tif (keywordsIndex.containsKey(kw2))\n\t\t\tocArr2 = keywordsIndex.get(kw2);\n\t\t\n\t\tcombined.addAll(ocArr1);\n\t\tcombined.addAll(ocArr2);\n\t\t\n\t\tif (!(ocArr1.isEmpty()) && !(ocArr2.isEmpty()))\n\t\t{\n\t\t\t// Sort with preference for ocArr1\n\t\t\tfor (int x = 0; x < combined.size()-1; x++)\n\t\t\t{\n\t\t\t\tfor (int y = 1; y < combined.size()-x; y++)\n\t\t\t\t{\n\t\t\t\t\tif (combined.get(y-1).frequency < combined.get(y).frequency)\n\t\t\t\t\t{\n\t\t\t\t\t\tOccurrence temp = combined.get(y-1);\n\t\t\t\t\t\tcombined.set(y-1, combined.get(y));\n\t\t\t\t\t\tcombined.set(y, temp);\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\n\t\t\t// Remove duplicates\n\t\t\tfor (int x = 0; x < combined.size()-1; x++)\n\t\t\t{\n\t\t\t\tfor (int y = x + 1; y < combined.size(); y++)\n\t\t\t\t{\n\t\t\t\t\tif (combined.get(x).document == combined.get(y).document)\n\t\t\t\t\t\tcombined.remove(y);\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\n\t\t// Top 5\n\t\twhile (combined.size() > 5)\n\t\t\tcombined.remove(combined.size()-1);\n\t\t\n\t\t//System.out.println(combined);\n\t\t\n\t\tfor (Occurrence oc : combined)\n\t\t\tresults.add(oc.document);\n\n\t\treturn results;\n\t\n\t\t\n\t\t// following line is a placeholder to make the program compile\n\t\t// you should modify it as needed when you write your code\n\t\n\t}","private static void printTable(int numberOfDocs) {\n \n Gson gs = new Gson();\n String json = gs.toJson(wor);\n // System.out.println(json);\n \n List<String> queryWords = new ArrayList();\n //to test it for other query word you can change the following two words\n //queryWords.add(\"carpet\");\n //queryWords.add(\"hous\");\n queryWords.add(\"the\");\n queryWords.add(\"crystallin\");\n queryWords.add(\"len\");\n queryWords.add(\"vertebr\");\n queryWords.add(\"includ\");\n \n \n FrequencySummary frequencySummary = new FrequencySummary();\n frequencySummary.getSummary(json,docName, queryWords);\n \n System.exit(0);\n \n Hashtable<Integer,Integer> g = new Hashtable<>();\n \n /* wor.entrySet().forEach((wordToDocument) -> {\n String currentWord = wordToDocument.getKey();\n Map<String, Integer> documentToWordCount = wordToDocument.getValue();\n freq.set(0);\n df.set(0);\n documentToWordCount.entrySet().forEach((documentToFrequency) -> {\n String document = documentToFrequency.getKey();\n Integer wordCount = documentToFrequency.getValue();\n freq.addAndGet(wordCount);\n System.out.println(\"Word \" + currentWord + \" found \" + wordCount +\n \" times in document \" + document);\n \n if(g.getOrDefault(currentWord.hashCode(), null)==null){\n g.put(currentWord.hashCode(),1);\n \n }else {\n System.out.println(\"Hello\");\n \n int i = g.get(currentWord.hashCode());\n System.out.println(\"i \"+i);\n g.put(currentWord.hashCode(), i++);\n }\n // System.out.println(currentWord+\" \"+ g.get(currentWord.hashCode()));\n // g.put(currentWord.hashCode(), g.getOrDefault(currentWord.hashCode(), 0)+wordCount);\n \n });\n // System.out.println(freq.doubleValue());\n \n // System.out.println(\"IDF for this word: \"+Math.log10( (double)(counter/freq.doubleValue())));\n });\n // System.out.println(g.get(\"plai\".hashCode()));\n //System.out.println(\"IDF for this word: \"+Math.log10( (double)(counter/(double)g.get(\"plai\".hashCode()))));\n */\n }","public ArrayList<String> top5search(String kw1, String kw2) {\n // COMPLETE THIS METHOD\n ArrayList<Occurrence> Res1 = keywordsIndex.get(getKeyWord(kw1));\n ArrayList<Occurrence> res2 = keywordsIndex.get(getKeyWord(kw1));\n ArrayList<String> arrayList = new ArrayList<String>();\n\n while (arrayList.size() < 6) {\n Occurrence aa = null;\n Occurrence b = null;\n {\n if (Res1 != null) {\n for (Occurrence occr : Res1) {\n if (!arrayList.contains(occr.document)) {\n aa = occr;\n }\n }\n } if(Res1 == null){\n aa = new Occurrence(null, 0);\n }\n else aa = new Occurrence(null,0);\n }\n {\n if(res2 != null){\n for(Occurrence occr : res2){\n if(!arrayList.contains(occr.document)){\n b = occr;\n }\n }\n }\n if(res2 == null){\n b = new Occurrence(null,0);\n }\n else b = new Occurrence(null,0);\n }\n Occurrence[] a = {aa,b};//{search(arrayList, Res1), search(arrayList, res2)};\n Occurrence m = null;\n if (a[0].frequency < a[1].frequency) {\n m = a[1];\n } else m = a[0];\n if (m.document != null) {\n arrayList.add(m.document);\n } else break;\n }\n return arrayList;\n }","private static String handleNonPhraseToken(String stringPart) {\r\n // Set of final terms to be used (no empty elements, right syntax of index fields)\r\n ArrayList <String> terms = new ArrayList <String> ();\r\n \r\n /** Case Index field **/\r\n if(stringPart.contains(\"[\") | stringPart.contains(\"[\")){ // at least an Index field contained here\r\n //separate brackets for term with one space (extra spaces dont matter, trim() is used later)\r\n stringPart = stringPart.replace(\"[\", \" [\");\r\n stringPart = stringPart.replace(\"]\", \"] \");\r\n }\r\n\r\n /** Case Bag of terms **/\r\n //replace space with AND (change default operator to match pubMed's)\r\n // No need for this if setDefaultOperator(QueryParser.Operator.AND) is used\r\n \r\n String[] tokens = stringPart.split(\"\\\\s\");\r\n if(tokens.length > 0){ \r\n for(int i = 1 ; i < tokens.length ; i++){\r\n tokens[i] = tokens[i].trim();\r\n /* Case index field [fieldName] */\r\n if(tokens[i].startsWith(\"[\") & tokens[i].endsWith(\"]\")){\r\n tokens[i] = tokens[i].replace(\"[\",\"\");// clean field name from brackets\r\n tokens[i] = tokens[i].replace(\"]\",\"\");// clean field name from brackets\r\n //Add index field as prefix to previus (not empty) term (as opening index fields handled separately, this index field should not be the first term of string part)\r\n int tmp = i-1;\r\n boolean perviusTermFound = false;\r\n while(!perviusTermFound & tmp >= 0){\r\n if(!tokens[tmp].equals(\"\")){\r\n perviusTermFound = true;\r\n //TO DO : handle wrong syntax (e.g. ... AND [ArticleTitle])\r\n String luceneField = supportedIndexFields.get(tokens[i]);\r\n if(luceneField != null){\r\n tokens[tmp] = luceneField + \":\" + tokens[tmp];\r\n } // else : Lucene counterpart not found, unsupported field - do nothing\r\n } else {\r\n tmp--;\r\n }\r\n }\r\n //Empty field to not be added as a search term in query\r\n tokens[i] = \"\";\r\n } \r\n \r\n /*\r\n \r\n else if(!tokens[i].equals(\"AND\") & !tokens[i].equals(\"\")) {\r\n terms.add(tokens[i]);\r\n }\r\n */\r\n }\r\n }\r\n \r\n String luceneQueryPart = \"\";\r\n boolean notWaiting = false;\r\n boolean orWaiting = false;\r\n for(int i = 0 ; i < tokens.length ; i++){\r\n\r\n if(!tokens[i].equals(\"AND\") & !tokens[i].equals(\"\")){\r\n //in case of AND nothing should happen, it is the default operator\r\n //empty elements are also ignored as useless\r\n \r\n if(!tokens[i].equals(\"NOT\") & !tokens[i].equals(\"OR\") ){ // it's not an operator, it's a term\r\n \r\n if(!luceneQueryPart.endsWith(\" OR \") & !luceneQueryPart.endsWith(\" -\") ) { \r\n luceneQueryPart += \" +\"; \r\n } \r\n luceneQueryPart += tokens[i];\r\n } else {\r\n if(tokens[i].equals(\"NOT\")) {\r\n luceneQueryPart += \" -\";\r\n }\r\n if(tokens[i].equals(\"OR\")){\r\n luceneQueryPart += \" OR \";\r\n }\r\n \r\n } \r\n } \r\n }\r\n \r\n return luceneQueryPart;\r\n }","public Query getQuery(String[] values, Collection<String> termCollector) {\n Query result = null;\n\n String[] termValues = values;\n if (values != null){\n if(isOffByOne()){\n for(int i = 0; i < values.length; i++){\n termValues[i] = String.valueOf(Integer.parseInt(values[i]) - 1);\n }\n }\n }\n\n if (index == Field.Index.ANALYZED || normalizer == null) {\n result = LuceneUtils.toQuery(getAnalyzer(), label, termValues, termCollector);\n }\n else {\n if (termValues != null && termValues.length > 0) {\n if (termValues.length == 1) {\n result = LuceneUtils.tokensToQuery(label, tokenize(termValues[0]), termCollector);\n }\n else {\n final PhraseQuery phraseQuery = new PhraseQuery();\n for (String value : termValues) {\n final String[] tokens = tokenize(value);\n if (tokens != null && tokens.length > 0) {\n for (String token : tokens) {\n phraseQuery.add(new Term(label, token));\n if (termCollector != null) termCollector.add(token);\n }\n }\n }\n result = phraseQuery;\n }\n }\n }\n\n return result;\n }","public ArrayList<String> tokeniseQuery(String query) {\n ArrayList<String> tokens;\n\n tokens = this.tokeniseString(query);\n\n // Normalise the tokens\n tokens = this.normaliseTokens(tokens);\n\n // Remove commas\n tokens = this.removeCommas(tokens);\n\n // Remove the stopwords\n this.removeStopwords(tokens);\n\n // Remove empty tokens that resulted from normalisation\n this.removeEmptyTokens(tokens);\n\n // Stem the tokens\n tokens = this.stemTokens(tokens);\n\n return tokens;\n }","SearchResult getBestResult(List<SearchResult> results, SearchQuery query);","public DocFile[] searchResponse(ScoreDoc[] results, Query query) {\n\n DocFile[] result = new DocFile[results.length];\n FastVectorHighlighter highlighter = new FastVectorHighlighter(true,true);\n FieldQuery highlightQuery = highlighter.getFieldQuery(query); \n\n try {\n IndexReader reader = DirectoryReader.open(indexDir);\n IndexSearcher searcher = new IndexSearcher(reader);\n\n for (int i = 0; i < results.length; i++) {\n int docId = results[i].doc;\n Document document = searcher.doc(docId);\n \n //Highlight the best Content context from each Doc\n String contextString = highlighter.getBestFragment(highlightQuery, \n searcher.getIndexReader(), results[i].doc,Constants.INDEX_KEY_CONTENT,140);\n \n DocFile toAdd = new DocFile(\n document.get(Constants.INDEX_KEY_FILENAME),\n document.get(Constants.INDEX_KEY_TITLE),\n document.get(Constants.INDEX_KEY_OWNER),\n document.get(Constants.INDEX_KEY_PATH),\n document.get(Constants.INDEX_KEY_STATUS).equalsIgnoreCase(\"true\"));\n \n if (contextString != null) {\n toAdd.setContextString(contextString);\n }\n \n toAdd.setId(document.get(Constants.INDEX_KEY_ID));\n toAdd.setPermissions(Integer.parseInt(document.get(Constants.INDEX_KEY_PERMISSION)));\n toAdd.setCourseCode(document.get(Constants.INDEX_KEY_COURSE));\n result[i] = toAdd;\n\n }\n } catch (Exception e) {\n e.printStackTrace();\n }\n\n return result;\n }","public VSM(String[] docs) {\n\t\tmyDocs = docs;\n\t\ttermList = new ArrayList<String>();\n\t\tdocLists = new ArrayList<ArrayList<Doc>>();\n\t\tArrayList<Doc> docList;\n\t\t// parse the documents to construct the index and collect the raw\n\t\t// frequencies.\n\t\tfor (int i = 0; i < myDocs.length; i++) {\n\t\t\tString[] tokens = myDocs[i].split(\" \");\n\t\t\tString token;\n\t\t\tfor (int j = 0; j < tokens.length; j++) {\n\t\t\t\ttoken = tokens[j];\n\t\t\t\tif (!termList.contains(token)) {\n\t\t\t\t\ttermList.add(token);\n\t\t\t\t\tdocList = new ArrayList<Doc>();\n\t\t\t\t\tDoc doc = new Doc(i, 1); // initial raw frequency is 1\n\t\t\t\t\tdocList.add(doc);\n\t\t\t\t\tdocLists.add(docList);\n\t\t\t\t} else {\n\t\t\t\t\tint index = termList.indexOf(token);\n\t\t\t\t\tdocList = docLists.get(index);\n\t\t\t\t\tint k = 0;\n\t\t\t\t\tboolean match = false;\n\n\t\t\t\t\t// search the postings list for a document id, if match,\n\t\t\t\t\t// insert a new position number to the document id\n\t\t\t\t\tfor (Doc doc : docList) {\n\t\t\t\t\t\tif (doc.docId == i) {\n\t\t\t\t\t\t\tdoc.tw++; // increase word count\n\t\t\t\t\t\t\tmatch = true;\n\t\t\t\t\t\t\tbreak;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tk++;\n\t\t\t\t\t}\n\t\t\t\t\t// if no match, add a new document id along with the\n\t\t\t\t\t// position number\n\t\t\t\t\tif (!match) {\n\t\t\t\t\t\tDoc doc = new Doc(i, 1);\n\t\t\t\t\t\tdocList.add(doc);\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}//\n\t\t}// end with parsing\n\n\t\t// compute the tf-idf term weights and the doc lengths\n\t\tint N = myDocs.length;\n\t\tdocLength = new double[N];\n\t\tfor (int i = 0; i < termList.size(); i++) {\n\t\t\tdocList = docLists.get(i);\n\t\t\tint df = docList.size();\n\t\t\tDoc doc;\n\t\t\tfor (int j = 0; j < docList.size(); j++) {\n\t\t\t\tdoc = docList.get(j);\n\t\t\t\tdouble tfidf = (1 + Math.log(doc.tw))\n\t\t\t\t\t\t* Math.log(N / (df * 1.0));\n\t\t\t\tdocLength[doc.docId] += Math.pow(tfidf, 2);\n\t\t\t\tdoc.tw = tfidf;\n\t\t\t\tdocList.set(j, doc);\n\t\t\t}\n\t\t}\n\t\t// update the length\n\t\tfor (int i = 0; i < N; i++) {\n\t\t\tdocLength[i] = Math.sqrt(docLength[i]);\n\t\t}\n\n\t}","public void onSearchSubmit(String queryTerm);","static AnalysisResult analyseQuery(String query) {\n for (String attack : commonAttacks) {\n attack = attack.toLowerCase();\n if (trim(query.toLowerCase()).contains(trim(attack))) {\n return new AnalysisResult(true, null, attack, true);\n }\n }\n return new AnalysisResult(false, null, null, true);\n }","private IDictionary<URI, IDictionary<String, Double>> computeAllDocumentTfIdfVectors(ISet<Webpage> pages) {\n // Hint: this method should use the idfScores field and\n // call the computeTfScores(...) method.\n\t\tdocumentTfIdfVectors = new ChainedHashDictionary<URI, IDictionary<String, Double>>();\n\t\t\n\t\t// Iterates through the given set of webpages\n\t\tfor (Webpage page: pages) {\n\t\t\tIDictionary<String, Double> tfIdfScores = new ChainedHashDictionary<String, Double>();\n\t\t\tIDictionary<String, Double> tfScores = computeTfScores(page.getWords());\n\t\t\t\n\t\t\t// Computes TfIdf scores\n\t\t\tfor (KVPair<String, Double> pair: tfScores) {\n\t\t\t\tDouble tfIdfScore = pair.getValue() * idfScores.get(pair.getKey());\n\t\t\t\ttfIdfScores.put(pair.getKey(), tfIdfScore);\n\t\t\t}\n\t\t\tdocumentTfIdfVectors.put(page.getUri(), tfIdfScores);\n\t\t}\n\t\treturn documentTfIdfVectors;\n }","@Test\n void testAndFilterWithoutExplicitIndex() {\n Query q = newQueryFromEncoded(\"?query=trump\" +\n \"&model.type=all\" +\n \"&model.defaultIndex=text\" +\n \"&filter=%2B%28filterTerm%29\");\n assertEquals(\"AND text:trump |text:filterTerm\",\n q.getModel().getQueryTree().toString());\n }","public static String getAllEvaluationAsString(String query, Vector<String> retrievalResults, Map<String, DocumentRelevances> judgments) throws IOException{\n double precisionAt1 = precisionAtK(retrievalResults, 1, judgments);\n double precisionAt5 = precisionAtK(retrievalResults, 5, judgments);\n double precisionAt10 = precisionAtK(retrievalResults, 10, judgments);\n double recallAt1 = recallAtK(retrievalResults, 1, judgments);\n double recallAt5 = recallAtK(retrievalResults, 5, judgments);\n double recallAt10 = recallAtK(retrievalResults, 10, judgments);\n double F05At1 = F05AtK(retrievalResults, 1, judgments);\n double F05At5 = F05AtK(retrievalResults, 5, judgments);\n double F05At10 = F05AtK(retrievalResults, 10, judgments);\n double[] precisionsAtRecalls = precisionAtRecall(retrievalResults, judgments);\n double averagePrecision = averagePrecision(retrievalResults, judgments);\n double NDCGAt1 = NDCGAtK(retrievalResults, 1, judgments);\n double NDCGAt5 = NDCGAtK(retrievalResults, 5, judgments);\n double NDCGAt10 = NDCGAtK(retrievalResults, 10, judgments);\n double reciprocalRank = reciprocalRank(retrievalResults, judgments);\n \n String output = query+\"\\n\"+\n \t\t \"Precision at 1: \"+Double.toString(precisionAt1)+\"\\n\"+\n \t\t \"Precision at 5: \"+Double.toString(precisionAt5)+\"\\n\"+\n \t\t \"Precision at 10: \"+Double.toString(precisionAt10)+\"\\n\"+\n \t\t \"Recall at 1: \"+Double.toString(recallAt1)+\"\\n\"+\n \t\t \"Recall at 5: \"+Double.toString(recallAt5)+\"\\n\"+\n \t\t \"Recall at 10: \"+Double.toString(recallAt10)+\"\\n\"+\n \t\t \"F05 at 1: \"+Double.toString(F05At1)+\"\\n\"+\n \t\t \"F05 at 5: \"+Double.toString(F05At5)+\"\\n\"+\n \t\t \"F05 at 10: \"+Double.toString(F05At10)+\"\\n\"+\n \t\t \"Precision at Recall 0.0: \"+Double.toString(precisionsAtRecalls[0])+\"\\n\"+\n \t\t \"Precision at Recall 0.1: \"+Double.toString(precisionsAtRecalls[1])+\"\\n\"+\n \t\t \"Precision at Recall 0.2: \"+Double.toString(precisionsAtRecalls[2])+\"\\n\"+\n \t\t \"Precision at Recall 0.3: \"+Double.toString(precisionsAtRecalls[3])+\"\\n\"+\n \t\t \"Precision at Recall 0.4: \"+Double.toString(precisionsAtRecalls[4])+\"\\n\"+\n \t\t \"Precision at Recall 0.5: \"+Double.toString(precisionsAtRecalls[5])+\"\\n\"+\n \t\t \"Precision at Recall 0.6: \"+Double.toString(precisionsAtRecalls[6])+\"\\n\"+\n \t\t \"Precision at Recall 0.7: \"+Double.toString(precisionsAtRecalls[7])+\"\\n\"+\n \t\t \"Precision at Recall 0.8: \"+Double.toString(precisionsAtRecalls[8])+\"\\n\"+\n \t\t \"Precision at Recall 0.9: \"+Double.toString(precisionsAtRecalls[9])+\"\\n\"+\n \t\t \"Precision at Recall 1.0: \"+Double.toString(precisionsAtRecalls[10])+\"\\n\"+\n \t\t \"Average precision: \"+Double.toString(averagePrecision)+\"\\n\"+\n \t\t \"NDCG at 1: \"+Double.toString(NDCGAt1)+\"\\n\"+\n \t\t \"NDCG at 5: \"+Double.toString(NDCGAt5)+\"\\n\"+\n \t\t \"NDCG at 10: \"+Double.toString(NDCGAt10)+\"\\n\"+\n \t\t \"Reciprocal rank: \"+Double.toString(reciprocalRank);\n\t\t\t\t\t\t\t\t\n return output;\n }","@Override\n\tpublic String toString() {\n\t\treturn weight + \"\\t\" + query;\n\t}","public void doSearch(String query)\n \t{\n \t\tlistener.onQueryTextSubmit(query);\n \t}","public void splitQuery(){\n for (int i=0;i<stemmed_query.size();i++){\n String stemmed_term = stemmed_query.get(i);\n for (int j=0;j<num_slave_client_threads;j++){\n if (stemmed_term.compareTo(ServerThread.start_terms[j]) >= 0 && stemmed_term.compareTo(ServerThread.end_terms[j]) <= 0){\n slave_queries.set(j, slave_queries.get(j)+\" \"+stemmed_term);\n break;\n }\n }\n }\n }","@Override\n public void init(SearchHits hits) { \n\n \tint numFbDocs = 50;\n \tint numFbTerms = 20;\n \tdouble lambda = 1.0;\n \tdouble alpha = 5.0;\n \t\n if (paramTable.get(FB_DOCS) != null ) \n \tnumFbDocs = paramTable.get(FB_DOCS).intValue();\n if (paramTable.get(FB_TERMS) != null ) \n \tnumFbTerms = paramTable.get(FB_TERMS).intValue();\n if (paramTable.get(LAMBDA) != null ) \n \tlambda = paramTable.get(LAMBDA).doubleValue();\n if (paramTable.get(ALPHA) != null ) \n \talpha = paramTable.get(ALPHA).doubleValue(); \n \n if (hits.size() < numFbDocs) \n \tnumFbDocs = hits.size();\n \n SearchHits fbDocs = new SearchHits(hits.hits().subList(0, numFbDocs));\n FeedbackRelevanceModel rm = new FeedbackRelevanceModel();\n rm.setDocCount(numFbDocs);\n rm.setTermCount(numFbTerms);\n rm.setIndex(index);\n rm.setStopper(null);\n rm.setRes(fbDocs);\n rm.build(); \n \n FeatureVector rmVector = rm.asFeatureVector();\n rmVector.clip(numFbTerms);\n rmVector.normalize();\n \n TermTimeSeries ts = new TermTimeSeries(startTime, endTime, interval, \n \t\trm.asFeatureVector().getFeatures());\n \n for (SearchHit hit: hits.hits()) {\n \t\tlong docTime = TemporalScorer.getTime(hit);\n \t\tdouble score = hit.getScore();\n \t\tts.addDocument(docTime, score, hit.getFeatureVector());\n }\n \n RUtil rutil = new RUtil();\n \n double sdps =0;\n for (String term: rmVector.getFeatures()) {\n \tdouble[] tsw = ts.getTermFrequencies(term);\n \tif (sum(tsw) > 0) {\n \t\ttry {\n \t\t\tsdps += rutil.dps(tsw);\n \t\t} catch (Exception e) {\n \t\t\te.printStackTrace();\n \t\t}\n \t}\n } \n \n FeatureVector tsfv = new FeatureVector(null);\n for (String term: rmVector.getFeatures()) {\n \tdouble[] termts = ts.getTermFrequencies(term);\n \ttry {\n \t\tdouble dps = rutil.dps(termts)/sdps;\n \t\t\n \tdouble weight = Math.pow(dps, alpha) * Math.pow(rmVector.getFeatureWeight(term), (1-alpha));\n tsfv.addTerm(term, weight);\n \n \t} catch (Exception e) {\n \t\te.printStackTrace();\n \t}\n }\n tsfv.normalize();\n\n gQuery.getFeatureVector().normalize();\n FeatureVector fv =\n \t\tFeatureVector.interpolate(gQuery.getFeatureVector(), tsfv, lambda);\n gQuery.setFeatureVector(fv);\n \n System.out.println(rmVector.toString(10));\n System.out.println(tsfv.toString(10));\n System.out.println(fv.toString(10));\n rutil.close();\n \n }","private void addQueries(String query){\n ArrayList <String> idsFullSet = new ArrayList <String>(searchIDs);\n while(idsFullSet.size() > 0){\n ArrayList <String> idsSmallSet = new ArrayList <String>(); \n if(debugMode) {\n System.out.println(\"\\t Pmids not used in query available : \" + idsFullSet.size());\n }\n idsSmallSet.addAll(idsFullSet.subList(0,Math.min(getSearchIdsLimit(), idsFullSet.size())));\n idsFullSet.removeAll(idsSmallSet);\n String idsConstrain =\"\";\n idsConstrain = idsConstrain(idsSmallSet);\n addQuery(query,idsConstrain);\n }\n }","public byte filter(Manager m, SearchRequest q, ResultSet rs, int DocAtNumber, int DocNo)\n\t{\t\t\n\t\tString originalQuery = q.getOriginalQuery();\n\t\t//highlight query terms only for the queries, \n\t\t//which are not about finding related documents\n\t\t//this check may be removed, because the preparation of the \n\t\t//query terms for highlighting takes into account\n\t\t//the related: operator\n\t\tboolean highlightQueryTerms = true;\n\t\tif (originalQuery.matches(\"\\\\brelated:\\\\d+\\\\b\") || //check if the query uses the related: operator \n\t\t\t!enableQueryTermsHighlight || //check if the highlighting of terms is enabled\n\t\t\thighlight.pattern().equals(\"(\\\\b)()(\\\\b)\")) //check if there are no query terms to highlight\n\t\t\thighlightQueryTerms = false;\n\t\t\n\t\tString[] qTerms = q.getOriginalQuery().replaceAll(\" \\\\w+\\\\p{Punct}\\\\w+ \",\" \").toLowerCase().split(\" \");\n\t\t\n\t\tString[] metadata = null;\n\t\tint tmpSentence;\n\t\tdouble tmpScore;\n\t\tsynchronized(metaCache) {\n\t\t\ttry {\n\t\t\t\tInteger DocNoObject = new Integer(DocNo);\n\t\t\t\tif (metaCache.containsKey(DocNoObject))\n\t\t\t\t\t\tmetadata = (String[]) metaCache.get(DocNoObject);\n\t\t\t\telse {\n\t\t\t\t\tmetadata = metaIndex.getItems(keys, DocNo);\n\t\t\t\t\tmetaCache.put(DocNoObject,metadata);\n\t\t\t\t}\n\t\t\t} catch(IOException ioe) {} \n\t\t}\n\t\n\t\tif (show_snippet)\n\t\t{\n\t\t\tString extract = metadata[1];\n\t\t\tString[] sentences = sentencePattern.split(extract, 50); //use 50 sentences at most\n\t\t\tdouble[] sentenceScores = new double[sentences.length]; \n\t\t\tint frsSentence = -1;\n\t\t\tint sndSentence = -1;\n\t\t\tint top1Sentence = 0;\n\t\t\tint top2Sentence = 0;\n\t\t\tdouble max1Score = -1;\n\t\t\tdouble max2Score = 0;\n\t\t\tfinal int qTermsLength = qTerms.length;\n\t\t\tfor (int i=0; i<qTermsLength; i++) {\n\t\t\t\tqTerms[i] = removeEndings.matcher(qTerms[i]).replaceAll(\"\");\n\t\t\t}\n\t\t\tString lowerCaseSentence;\n\t\t\tint sentenceLength;\n\t\t\tfinal int sentencesLength = sentences.length;\n\n\t\t\tfor (int i=0; i<sentencesLength; i++) {\n\t\t\t\t\n\t\t\t\tlowerCaseSentence = sentences[i].toLowerCase();\n\t\t\t\tsentenceLength=sentences[i].length();\n\t\t\t\tif (sentenceLength < 20 || sentenceLength > 250) {\n\t\t\t\t\tfor (int j=0; j<qTermsLength; j++) {\n\t\t\t\t\t\tif (lowerCaseSentence.indexOf(qTerms[j])>=0) {\n\t\t\t\t\t\t\tsentenceScores[i]+=1.0d + sentenceLength / (20.0d + sentenceLength);\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\n\t\t\t\t\t\n\t\t\t\t} else {\n\t\t\t\t\tfor (int j=0; j<qTermsLength; j++) {\n\t\t\t\t\t\tif (lowerCaseSentence.indexOf(qTerms[j])>=0) {\n\t\t\t\t\t\t\tsentenceScores[i]+=qTerms[j].length() + sentenceLength / (1.0d + sentenceLength);\n\t\t\t\t\t\t}\n\t\t\t\t\t}\t\t\t\t\t\n\t\t\t\t}\n\t\t\t\t\t\t\t\t\n\t\t\t\t//do your best to get at least a second sentence for the snippet, \n\t\t\t\t//after having found the first one\n\t\t\t\tif (frsSentence > -1 && sndSentence == -1 && sentenceLength > 5) {\n\t\t\t\t\tsndSentence = i;\n\t\t\t\t}\n\n\t\t\t\t//do your best to get at least one sentence for the snippet\n\t\t\t\tif (frsSentence == -1 && sentenceLength > 5) { \n\t\t\t\t\tfrsSentence = i;\n\t\t\t\t}\n\n\t\t\t\tif (max2Score < sentenceScores[i]) {\n\t\t\t\t\tmax2Score = sentenceScores[i];\n\t\t\t\t\ttop2Sentence = i;\n\t\t\t\t\t//logger.debug(\"top 2 sentence is \" + i);\n\t\t\t\t\tif (max2Score > max1Score) {\n\t\t\t\t\t\ttmpScore = max1Score; max1Score = max2Score; max2Score = tmpScore;\n\t\t\t\t\t\ttmpSentence = top1Sentence; top1Sentence = top2Sentence; top2Sentence = tmpSentence;\n\t\t\t\t\t}\n\t\t\t\t}\n\n\t\t\t}\n\t\t\tint lastIndexOfSpace = -1;\n\t\t\tString sentence=\"\";\n\t\t\tString secondSentence=\"\";\n\t\t\tString snippet = \"\";\n\t\t\tif (max1Score == -1) {\n\t\t\t\tif (frsSentence>=0) {\n\t\t\t\t\tsentence = sentences[frsSentence];\n\t\t\t\t\tif (sentence.length() > 100) {\n\t\t\t\t\t\tlastIndexOfSpace = sentence.substring(0, 100).lastIndexOf(\" \");\n\t\t\t\t\t\tsentence = sentence.substring(0, lastIndexOfSpace > 0 ? lastIndexOfSpace : 100);\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t\t\n\t\t\t\tif (sndSentence>=0) {\n\t\t\t\t\tsecondSentence = sentences[sndSentence];\n\t\t\t\t\tif (secondSentence.length() > 100) {\n\t\t\t\t\t\tlastIndexOfSpace = secondSentence.substring(0, 100).lastIndexOf(\" \");\n\t\t\t\t\t\tsecondSentence = secondSentence.substring(0, lastIndexOfSpace>0 ? lastIndexOfSpace : 100);\n\t\t\t\t\t}\t\t\t\t\t\n\t\t\t\t}\n\t\t\t\t\n\t\t\t\tif (frsSentence >=0 && sndSentence >= 0) \n\t\t\t\t\tsnippet = sentence.trim() + \"...\" + secondSentence.trim();\n\t\t\t\telse if (frsSentence >= 0 && sndSentence<0) \n\t\t\t\t\tsnippet = sentence.trim();\n\t\t\t\t\n\t\t\t} else if (sentences[top1Sentence].length()<100 && top1Sentence!=top2Sentence) {\n\t\t\t\tsentence = sentences[top1Sentence];\n\t\t\t\tif (sentence.length() > 100) {\n\t\t\t\t\tlastIndexOfSpace = sentence.substring(0, 100).lastIndexOf(\" \");\n\t\t\t\t\tsentence = sentence.substring(0, lastIndexOfSpace > 0 ? lastIndexOfSpace : 100);\n\t\t\t\t}\n\t\t\t\t\t\t\t\t\n\t\t\t\tsecondSentence = sentences[top2Sentence];\n\t\t\t\tif (secondSentence.length() > 100) {\n\t\t\t\t\tlastIndexOfSpace = secondSentence.substring(0, 100).lastIndexOf(\" \");\n\t\t\t\t\tsecondSentence = secondSentence.substring(0, lastIndexOfSpace>0 ? lastIndexOfSpace : 100);\n\t\t\t\t}\n\t\t\t\tsnippet = sentence.trim() + \"...\" + secondSentence.trim();\n\t\t\t} else {\n\t\t\t\tsentence = sentences[top1Sentence];\n\t\t\t\tif (sentence.length()>200) {\n\t\t\t\t\tlastIndexOfSpace = sentence.substring(0, 200).lastIndexOf(\" \");\n\t\t\t\t\tsentence = sentence.substring(0, lastIndexOfSpace > 0 ? lastIndexOfSpace : 200);\n\t\t\t\t}\n\t\t\t\tsnippet = sentence.trim();\n\t\t\t}\n\t\t\t\n\t\t\t//checking and removing any control characters\n\t\t\tcontrolNonVisibleCharactersMatcher.reset(snippet);\n\t\t\tsnippet = controlNonVisibleCharactersMatcher.replaceAll(\"\");\n\t\t\t\n\t\t\t//String escapedSnippet = StringEscapeUtils.escapeHtml(snippet);\n\t\t\t//if (highlightQueryTerms)\n\t\t\t//\tescapedSnippet = highlight.matcher(escapedSnippet).replaceAll(\"$1<b>$2</b>$3\");\n\t\t\tif (highlightQueryTerms)\n\t\t\t\tsnippet = highlight.matcher(snippet).replaceAll(\"$1<b>$2</b>$3\");\n\t\t\t//else \n\t\t\t//\tsnippet = StringEscapeUtils.escapeHtml(snippet);\n\t\t\t\n\t\t\t//change by Vassilis, 20/09/2006\n\t\t\t//disabling the xml escaping in order to move the data into ![CDATA[ ]]\n\t\t\t//the code was:\n\t\t\t//rs.addMetaItem(\"snippet\", DocAtNumber, StringEscapeUtils.escapeXml(snippet));\n\t\t\t//and now it is:\n\t\t\t//snippet.replaceAll(\"[^\\\\u0009\\\\u000A\\\\u000D\\\\u0020-\\\\uD7FF\\\\uE000-\\\\uFFFD\\\\u10000-\\\\u10FFFF]\",\"\");\n\t\t\trs.addMetaItem(\"snippet\", DocAtNumber, snippet);\n\t\t\t\n\t\t}\n\t\tif (show_title)\n\t\t{\n\t\t\tString title = metadata[2];\n\t\t\t\n\t\t\t//checking and removing any control characters\n\t\t\tcontrolNonVisibleCharactersMatcher.reset(title);\n\t\t\ttitle = controlNonVisibleCharactersMatcher.replaceAll(\"\");\n\t\t\ttitle = (highlightQueryTerms)\n\t\t\t\t ? highlight.matcher(metadata[2]).replaceAll(\"$1<b>$2</b>$3\") \n\t\t\t\t : metadata[2];\n\t\t\t\n\t\t\t\n\t\t\t//String escapedTitle = StringEscapeUtils.escapeHtml(metadata[2]);\n\t\t\t//String title = (highlightQueryTerms)\n\t\t\t//\t\t\t ? highlight.matcher(escapedTitle).replaceAll(\"$1<b>$2</b>$3\") \n\t\t\t//\t\t\t : escapedTitle;\n\t\t\t//String title = (highlightQueryTerms) \n\t\t\t//\t\t? highlight.matcher(metadata[2]).replaceAll(\"$1<b>$2</b>$3\") \n\t\t\t//\t\t: metadata[2];\n\n\t\t\t//change by Vassilis, 20/09/2006\n\t\t\t//disabling the xml escaping in order to move the data into ![CDATA[ ]]\n\t\t\t//the code was:\n\t\t\t//rs.addMetaItem(\"title\", DocAtNumber, StringEscapeUtils.escapeXml(title));\n\t\t\t//and now is:\n\t\t\t//title.replaceAll(\"[^\\\\u0009\\\\u000A\\\\u000D\\\\u0020-\\\\uD7FF\\\\uE000-\\\\uFFFD\\\\u10000-\\\\u10FFFF]\",\"\");\n\t\t\trs.addMetaItem(\"title\", DocAtNumber, title);\n\t\t\t\n\t\t}\n\t\tif (!show_docid_early && show_docid)\n\t\t{\n\t\t\trs.addMetaItem(\"docid\", DocAtNumber, docIndex.getDocumentNumber(DocNo));\n\t\t}\n\t\tif (!show_url_early && show_url)\n\t\t{\n\n\t\t\trs.addMetaItem(\"url\", DocAtNumber, StringEscapeUtils.escapeXml(metadata[0]));\n\t\t}\n\t\t\n\t\treturn FILTER_OK;\n\t}"],"string":"[\n \"public Set<String> queryTermsConsidered(Query query, double idf_threshold){\\n double idf, nDocs = this.docIDs.size();\\n String term;\\n\\n Set<String> termsToConsider = new HashSet<String>();\\n\\n Iterator<String> it = query.terms.iterator();\\n while(it.hasNext()){\\n term = it.next();\\n idf = -1;\\n if(this.idfMap.containsKey(term))\\n idf = Math.log(nDocs/new Double(this.idfMap.get(term)));\\n if (idf >= idf_threshold){\\n termsToConsider.add(term);\\n }\\n /*else{\\n System.err.println(term + \\\" not considered since idf = \\\" + idf);\\n }*/\\n }\\n\\n return termsToConsider;\\n\\n }\",\n \"private HashMap<String,HashMap<String,Integer>> computeTFForQueryWords(ArrayList<String> queryPostingLines) {\\n HashMap<String,HashMap<String,Integer>> queryWordsTF = new HashMap<>();\\n HashMap<String,HashMap<String,Integer>> queryWordsTFPerDoc = new HashMap<>();\\n String docID,term;\\n Integer tf;\\n HashSet<String> docIDs = new HashSet<>();\\n for(String postingLine : queryPostingLines){\\n HashMap<String,Integer> frequenciesInDocuments = new HashMap<>();\\n term = postingLine.substring(0,postingLine.indexOf(\\\"|\\\"));\\n postingLine = postingLine.substring(postingLine.indexOf(\\\"|\\\")+1);\\n while(!postingLine.equals(\\\"\\\")) {\\n docID = postingLine.substring(0, postingLine.indexOf(\\\":\\\"));\\n docIDs.add(docID);\\n postingLine = postingLine.substring(postingLine.indexOf(\\\"_\\\") + 1);\\n tf = Integer.valueOf(postingLine.substring(0, postingLine.indexOf(\\\"_\\\")));\\n postingLine = postingLine.substring(postingLine.indexOf(\\\"_\\\") + 1);\\n frequenciesInDocuments.put(docID,tf);\\n }\\n queryWordsTF.put(term,frequenciesInDocuments);\\n }\\n\\n ArrayList<String> allTermsInQuery = new ArrayList<>(queryWordsTF.keySet());\\n for(String doc : docIDs){\\n HashMap<String,Integer> tfsInDoc = new HashMap<>();\\n for(String termInQuery : allTermsInQuery){\\n HashMap<String,Integer> termsTFInDoc = queryWordsTF.get(termInQuery);\\n if(termsTFInDoc.containsKey(doc)){\\n tfsInDoc.put(termInQuery,termsTFInDoc.get(doc));\\n }\\n }\\n queryWordsTFPerDoc.put(doc,tfsInDoc);\\n }\\n return queryWordsTFPerDoc;\\n }\",\n \"public List<IResult> getResults(List<Integer> relatedDocs, String query) {\\r\\n\\r\\n // results\\r\\n List<IResult> rs = new ArrayList<>();\\r\\n List<Double> documentVector, queryVector = new ArrayList<>();\\r\\n\\r\\n Map<String, Integer> termFreqs = this.preprocessor.processQuery(query);\\r\\n\\r\\n for(String op : new String[]{\\\"and\\\", \\\"or\\\", \\\"not\\\"}) {\\r\\n termFreqs.remove(op);\\r\\n }\\r\\n\\r\\n\\r\\n double highestVal = 0;\\r\\n\\r\\n // query TF-IDF vector\\r\\n for(String term : termFreqs.keySet()) {\\r\\n\\r\\n // unknown term == contained in no doc\\r\\n if(!this.index.getDict().containsKey(term)) {\\r\\n continue;\\r\\n }\\r\\n\\r\\n // # docs where term occurs in\\r\\n int termTotalFreq = this.index.getTermInDocCount(term);\\r\\n\\r\\n // query tf-idf vector\\r\\n double qTfIdf = this.tfidf.tfidfQuery(termFreqs.get(term), termTotalFreq);\\r\\n queryVector.add(qTfIdf);\\r\\n\\r\\n if(qTfIdf > highestVal) highestVal = qTfIdf;\\r\\n }\\r\\n\\r\\n // query vector normalization\\r\\n for(int i = 0; i < queryVector.size(); i++) {\\r\\n queryVector.set(i, queryVector.get(i)/highestVal);\\r\\n }\\r\\n\\r\\n\\r\\n for(int docId : relatedDocs) {\\r\\n documentVector = new ArrayList<>();\\r\\n highestVal = 0;\\r\\n\\r\\n for(String term : termFreqs.keySet()) {\\r\\n\\r\\n // unknown term == contained in no doc\\r\\n if(!this.index.getDict().containsKey(term)) {\\r\\n continue;\\r\\n }\\r\\n\\r\\n // document tf-idf vector\\r\\n double dTfIdf = this.tfidf.getTfIdf(term, docId);\\r\\n documentVector.add(dTfIdf);\\r\\n\\r\\n if(dTfIdf > highestVal) highestVal = dTfIdf;\\r\\n }\\r\\n\\r\\n // document vector normalization\\r\\n for(int i = 0; i < documentVector.size(); i++) {\\r\\n documentVector.set(i, documentVector.get(i)/highestVal);\\r\\n }\\r\\n\\r\\n Result result = new Result();\\r\\n result.setDocumentId(this.docs.get(docId).getUrl());\\r\\n result.setDocument(this.docs.get(docId));\\r\\n result.setScore((float) CosineSimilarity.process(documentVector, queryVector));\\r\\n rs.add(result);\\r\\n }\\r\\n\\r\\n Collections.sort(rs, new ResultComparator());\\r\\n\\r\\n // limit number of results\\r\\n if(rs.size() > IndexerConfig.MAX_RESULT_COUNT)\\r\\n rs = rs.subList(0, IndexerConfig.MAX_RESULT_COUNT);\\r\\n\\r\\n // rank it\\r\\n for(int i = 0; i < rs.size(); i++) {\\r\\n ((Result) rs.get(i)).setRank (i + 1);\\r\\n }\\r\\n\\r\\n return rs;\\r\\n }\",\n \"public HashMap<String, Double> search(String query) {\\n // ===================================================\\n // 1. Fetch all inverted lists corresponding to terms\\n // in the query.\\n // ===================================================\\n String[] terms = query.split(\\\" \\\");\\n HashMap<String, Integer> qf = new HashMap<String, Integer>();\\n // Calculate term frequencies in the query\\n for (String term : terms) {\\n if (qf.containsKey(term))\\n qf.put(term, qf.get(term) + 1);\\n else\\n qf.put(term, 1);\\n }\\n HashMap<String, Double> docScore = new HashMap<String, Double>();\\n for (Entry<String, Integer> termEntry : qf.entrySet()) {\\n String term = termEntry.getKey();\\n int qfi = termEntry.getValue();\\n\\n // ===================================================\\n // 2. Compute BM25 scores for documents in the lists.\\n // Make a score list for documents in the inverted\\n // lists. Assume that no relevance information is \\n // available. For parameters, use k1=1.2, b=0.75, \\n // k2=100.\\n // ===================================================\\n double k1 = 1.2;\\n double b = 0.75;\\n double k2 = 100;\\n int ni = invIndex.get(term).size();\\n\\n\\n for (Entry<String, IndexEntry> invListEntry : invIndex.get(term).entrySet()) {\\n String docID = invListEntry.getKey();\\n double bm25Score;\\n if (docScore.containsKey(docID))\\n bm25Score = docScore.get(docID);\\n else\\n bm25Score = 0;\\n\\n // length of the document\\n int dl = docStat.get(docID);\\n // frequency of the term in the document\\n int fi = invListEntry.getValue().getTf();\\n double K = k1 * ((1 - b) + b * ((double) dl / avdl));\\n\\n // ===================================================\\n // 3. Accumulate scores for each term in a query\\n // on the score list.\\n // ===================================================\\n bm25Score += Math.log((N - ni + 0.5) / (ni + 0.5))\\n * (((k1 + 1) * fi * (k2 + 1) * qfi) / ((K + fi) * (k2 + qfi)));\\n docScore.put(docID, bm25Score);\\n }\\n }\\n\\n return docScore;\\n }\",\n \"public /*TreeMap<String, Float>*/void getTopnTermsOverlapWithQuery() throws IOException, ParseException{\\n\\t\\tString outputfile = \\\"./output/score/test3.txt\\\";\\n\\n\\t\\tFileOutputStream out = new FileOutputStream(outputfile);\\n\\t\\tPrintStream ps = new PrintStream(out);\\n\\t\\t/*-------------------------------------------------------------------------------*/\\n\\n\\t\\tTreeMap<String,Float> termsscoressorted = null;\\n\\t\\tCollectionReader reader = new CollectionReader(indexDir); \\n\\t\\tIndexReader ir = reader.getIndexReader();\\t\\t\\n\\n\\t\\tTopicsInMemory topics = new TopicsInMemory(\\\"data/CLEF-IP-2010/PAC_test/topics/PAC_topics-test2.xml\\\"/*omit-PAC-1094.xml\\\"*/);\\n\\t\\tfor(Map.Entry<String, PatentDocument> topic : topics.getTopics().entrySet()){\\n\\t\\t\\tString qUcid = topic.getValue().getUcid();\\n\\t\\t\\tString queryid = topic.getKey();\\n\\t\\t\\tString queryName = topic.getKey() + \\\"_\\\" + topic.getValue().getUcid();\\n\\t\\t\\tString queryfile = topic.getKey() + \\\"_\\\" + topic.getValue().getUcid() + \\\".xml\\\";\\n\\n\\t\\t\\t/*System.out.println(\\\"=========================================\\\");\\n\\t\\t\\tSystem.out.println(queryName);\\n\\t\\t\\tSystem.out.println(\\\"=========================================\\\");*/\\n\\t\\t\\t/*int docid = reader.getDocId(\\\"UN-EP-0663270\\\", PatentDocument.FileName);\\n\\t\\t\\tir.getTermVector(docid, field) getTermVectors(b);*/\\n\\n\\t\\t\\tEvaluateResults er = new EvaluateResults();\\n\\t\\t\\tArrayList<String> tps = er.evaluatePatents(queryid, \\\"TP\\\");\\n\\t\\t\\tArrayList<String> fps = er.evaluatePatents(queryid, \\\"FP\\\");\\n\\t\\t\\tHashMap<String, Float> /*TFreqs*/ termsscores = new HashMap<>();\\n\\n\\n\\t\\t\\t/*--------------------------------- Query Words -------------------------------*/\\n\\t\\t\\t//\\t\\t\\tHashMap<String, Integer> query_termsfreqspair = reader.gettermfreqpair(qUcid, PatentDocument.Description);\\n\\t\\t\\tHashSet<String> query_terms = reader.getDocTerms(qUcid, PatentDocument.Description);\\n\\t\\t\\t//\\t\\t\\tSystem.out.println(query_termsfreqspair.size() +\\\"\\\\t\\\"+ query_termsfreqspair);\\n//\\t\\t\\tSystem.out.println(query_terms.size() + \\\"\\\\t\\\" + query_terms);\\n\\t\\t\\t/*-----------------------------------------------------------------------------*/\\t\\t\\t\\n\\n\\n\\t\\t\\t//\\t\\t\\tSystem.out.println(\\\"-----TPs----\\\");\\n\\t\\t\\tfor (String tp : tps) {\\n\\t\\t\\t\\t/*System.out.println(\\\"---------\\\");\\n\\t\\t\\t\\tSystem.out.println(tp);*/\\n\\t\\t\\t\\tHashMap<String, Integer> termsfreqsTP = reader.gettermfreqpairAllsecs(\\\"UN-\\\" + tp);\\n\\n\\t\\t\\t\\tfor(Entry<String, Integer> tfTP:termsfreqsTP.entrySet()){\\n\\t\\t\\t\\t\\tif(termsscores.containsKey(tfTP.getKey())){\\n\\t\\t\\t\\t\\t\\ttermsscores.put(tfTP.getKey(), termsscores.get(tfTP.getKey()) + (float)tfTP.getValue()/tps.size());\\n\\t\\t\\t\\t\\t}else{\\n\\t\\t\\t\\t\\t\\t//\\t\\t\\t\\t\\t\\tfloat test = (float)t.getValue()/tps.size();\\n\\t\\t\\t\\t\\t\\t//\\t\\t\\t\\t\\t\\tSystem.out.println(test);\\n\\t\\t\\t\\t\\t\\ttermsscores.put(tfTP.getKey(), (float)tfTP.getValue()/tps.size());\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\t//\\t\\t\\t\\tSystem.out.println(termsscores.size() + \\\" \\\" + termsscores);\\t\\t\\t\\t\\t\\n\\t\\t\\t}\\n\\n\\t\\t\\t/*System.out.println();\\n\\t\\t\\tSystem.out.println(\\\"-----FNs----\\\");*/\\n\\t\\t\\tfor (String fp : fps) {\\n\\t\\t\\t\\t/*System.out.println(\\\"---------\\\");\\n\\t\\t\\t\\tSystem.out.println(fp);*/\\n\\t\\t\\t\\tHashMap<String, Integer> termsfreqsFP = reader.gettermfreqpairAllsecs(\\\"UN-\\\" + fp);\\n\\n\\t\\t\\t\\tfor(Entry<String, Integer> t:termsfreqsFP.entrySet()){\\n\\t\\t\\t\\t\\tif(termsscores.containsKey(t.getKey())){\\n\\t\\t\\t\\t\\t\\ttermsscores.put(t.getKey(), termsscores.get(t.getKey()) - (float)t.getValue()/fps.size());\\n\\t\\t\\t\\t\\t}else{\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\ttermsscores.put(t.getKey(), -(float)t.getValue()/fps.size());\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\t//\\t\\t\\t\\tSystem.out.println(TFreqs.size() + \\\" \\\" + TFreqs);\\n\\t\\t\\t}\\n\\t\\t\\t//\\t\\t\\tSystem.out.println(termsscores.size() + \\\" \\\" + termsscores);\\n\\t\\t\\tValueComparator bvc = new ValueComparator(termsscores);\\n\\t\\t\\ttermsscoressorted = new TreeMap<String,Float>(bvc);\\t\\t\\t\\n\\t\\t\\ttermsscoressorted.putAll(termsscores);\\n\\t\\t\\tSystem.out.println(queryid + \\\"\\\\t\\\"+ termsscoressorted.size() + \\\"\\\\t\\\" + termsscoressorted/*.keySet()*/);\\n\\t\\t\\tint overlap = 0;\\n\\t\\t\\tint i = 0;\\n\\t\\t\\tfor(Entry<String, Float> scoresorted:termsscoressorted.entrySet()){\\n\\t\\t\\t\\ti++;\\n\\t\\t\\t\\tif(i<=100){\\n\\t\\t\\t\\t\\tif(query_terms.contains(scoresorted.getKey())){\\n\\t\\t\\t\\t\\t\\toverlap++;\\n\\t\\t\\t\\t\\t}\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\t\\n\\t\\t\\tSystem.out.println(queryName + \\\"\\\\t\\\"+overlap);\\n//\\t\\t\\tps.println(queryName + \\\"\\\\t\\\"+overlap);\\n\\t\\t}\\n\\t}\",\n \"private static void statsForQuery(String query) {\\n\\t\\tHashMap<String,Integer> oldTerms=newTerms; // record the terms to analyze modified queries\\n\\t\\tnewTerms=new HashMap<String,Integer>();\\n\\t\\t\\t\\t\\n\\t\\tString terms[]=query.split(\\\"\\\\\\\\s\\\");\\t\\t\\t\\t\\n\\t\\tint matchingTerms=0;\\n\\t\\tint matchingTermsStopwords=0;\\n\\t\\tint matchingTermsOrder=0;\\n\\t\\tfor (int j=0;j<terms.length;j++) {\\n\\t\\t\\tif (!terms[j].equals(\\\"\\\")) {\\n\\t\\t\\t \\tif (oldTerms.containsKey(terms[j])) {\\n\\t\\t\\t \\t\\tmatchingTerms++;\\t\\t\\t\\t\\t \\n\\t\\t\\t \\t\\tif (stopwordsMap.containsKey(terms[j])) { // match if it is stopword\\n\\t\\t\\t \\t\\t\\tmatchingTermsStopwords++;\\n\\t\\t\\t \\t\\t}\\n\\t\\t\\t \\t\\tif (oldTerms.get(terms[j])==j) { // match if it has the same order\\n\\t\\t\\t \\t\\t\\tmatchingTermsOrder++;\\n\\t\\t\\t \\t\\t}\\n\\t\\t\\t \\t}\\n\\t\\t\\t \\tnewTerms.put(terms[j],j);\\n\\t\\t\\t}\\n\\t\\t}\\t\\n\\n\\t\\tif (newTerms.size()==oldTerms.size() && matchingTerms==oldTerms.size() && matchingTerms>0) { // the queries have the same terms\\n\\t\\t totalEqualTermsQueries++;\\n\\t\\t\\t\\t \\t\\t\\t\\t \\t\\t\\t\\t\\t\\t \\t\\t\\t\\t \\t\\t\\t\\t \\n\\t\\t if (matchingTermsStopwords==oldTerms.size()) {\\n\\t\\t \\ttotalEqualTermsStopwordsQueries++;\\n\\t\\t }\\n\\t\\t if (matchingTermsOrder==oldTerms.size()) {\\n\\t\\t \\ttotalEqualTermsOrderQueries++;\\n\\t\\t }\\n\\t\\t if (query.equals(oldQuery)) {\\n\\t\\t \\ttotalIdenticalQueries++;\\n\\t\\t }\\n\\t\\t if (sessionQueries.contains(query)) {\\n\\t\\t \\ttotalIdenticalSessionQueries++;\\n\\t\\t }\\n\\t\\t}\\n\\t\\telse if (matchingTerms-matchingTermsStopwords>0) { // the queries have at least one term equal and diferent from a stopword\\n\\t\\t totalModifiedQueries++;\\n\\t\\t int index=newTerms.size()-oldTerms.size()+N_MODIFIED_TERMS_RANGE/2;\\n\\t\\t if (index<0) {\\n\\t\\t \\tindex=0;\\n\\t\\t }\\n\\t\\t else if (index>N_MODIFIED_TERMS_RANGE-1) {\\n\\t\\t \\tindex=N_MODIFIED_TERMS_RANGE-1;\\n\\t\\t }\\n\\t\\t nModifiedTerms[index]++;\\n\\t\\t}\\n\\t\\toldQuery=query; \\n\\t\\t\\t\\t\\t\\t\\n\\t\\t// store session query\\n\\t\\tsessionQueries.add(query);\\n\\t}\",\n \"static void returnTfIdfResults() {\\n\\t\\tSet<String> specificWords = findKeywords();\\n\\n\\t\\t// for every phrase\\n\\t\\tfor (String word : specificWords) {\\n\\t\\t\\t// get the total number of documents\\n\\t\\t\\tdouble totalSize = size;\\n\\n\\t\\t\\t// get the collection of documents containing that word\\n\\t\\t\\tCollection<File> containingWordSet = invertedMap.getValues(word);\\n\\n\\t\\t\\t// makes a new one if null (for ease of code)\\n\\t\\t\\tif (containingWordSet == null) {\\n\\t\\t\\t\\tcontainingWordSet = new HashSet<File>();\\n\\t\\t\\t}\\n\\n\\t\\t\\t// the number containing the word\\n\\t\\t\\tdouble numContainingWord = containingWordSet.size();\\n\\n\\t\\t\\t// get the idf (log(total/(1 + |# contain word|)\\n\\t\\t\\t// it is normalize with 1 to prevent division by 0\\n\\t\\t\\tdouble idf = Math.log(totalSize / (1 + numContainingWord));\\n\\n\\t\\t\\t// System.out.println(\\\"------------------\\\");\\n\\t\\t\\t// System.out.println(word + \\\" totalSize \\\" + totalSize);\\n\\t\\t\\t// System.out.println(word + \\\" numContainingWord \\\" +\\n\\t\\t\\t// numContainingWord);\\n\\t\\t\\t// System.out.println(word + \\\" idf \\\" + idf);\\n\\t\\t\\t// System.out.println(\\\"------------------\\\");\\n\\n\\t\\t\\t// set the wordscore to 0\\n\\t\\t\\tdouble wordScore = 0;\\n\\n\\t\\t\\t// for all of the files with the word\\n\\t\\t\\tfor (File file : containingWordSet) {\\n\\t\\t\\t\\tString fileName = file.getName();\\n\\n\\t\\t\\t\\t// get the phrase count for this document\\n\\t\\t\\t\\tInteger phraseCount = phraseCountMap.get(fileName);\\n\\t\\t\\t\\tdouble numPhrases = phraseCount.doubleValue();\\n\\n\\t\\t\\t\\t// get the word frequency map for this page\\n\\t\\t\\t\\tHashMap<String, Integer> docFreqMap = wordFreqMap.get(fileName);\\n\\t\\t\\t\\tInteger freq = docFreqMap.get(word);\\n\\n\\t\\t\\t\\t// otherwise, get the tf\\n\\t\\t\\t\\tdouble tf;\\n\\t\\t\\t\\tif (freq == null) {\\n\\t\\t\\t\\t\\t// if it's not present, it's 0\\n\\t\\t\\t\\t\\ttf = 0;\\n\\t\\t\\t\\t} else {\\n\\t\\t\\t\\t\\t// otherwise, it's the value\\n\\t\\t\\t\\t\\ttf = freq / numPhrases;\\n\\t\\t\\t\\t\\t// System.out.println(tf);\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\t// multiply for this score\\n\\t\\t\\t\\tdouble score = tf * idf;\\n\\n\\t\\t\\t\\t// add it to the page score\\n\\t\\t\\t\\twordScore += score;\\n\\t\\t\\t}\\n\\n\\t\\t\\t// make a node with the sum of tf-idf for all relevant phrases and\\n\\t\\t\\t// add to pq\\n\\t\\t\\tWordNode w = new WordNode(word, wordScore);\\n\\t\\t\\tpq.add(w);\\n\\t\\t}\\n\\t}\",\n \"@Override\\n protected QueryProcessor computeResult(ResultComputingContext<? extends TermsIndexingEquipment> context) {\\n final TermWeight idf = context.preliminaryResult(CalculatingInvertedTermFrequency.getInstance());\\n final TermDocumentWeight tf = context.preliminaryResult(context.equipment().termFrequencyCalculation());\\n //for obtaining set of terms in each document.\\n final EachDocumentTermsExtraction documentsTerms = context.preliminaryResult(ExtractingEachDocumentTerms.getInstance());\\n //for obtaining document length\\n final Map<Document, TermsOccurences> termsOccurences = context.preliminaryResult(CountingTermsOccurencesInEachDocument.getInstance());\\n final double averageDocLength = context.preliminaryResult(ComputingAverageDocumentLength.getInstance());\\n\\n QueryProcessor res = new QueryProcessor() {\\n @Override\\n public DocumentRanker rankForQuery(final Collection<String> query) {\\n return new DocumentRanker() {\\n @Override\\n public double score(Document document) {\\n /*\\n * BM25 score is calculated here\\n */\\n\\n //obtaining the set of terms in the document\\n Set<String> allDocTerms = documentsTerms.termsExtractedFromDocument(document).allTerms();\\n\\n //keeping only the query terms that are in the document\\n Collection<String> relevantTerms = new LinkedHashSet<>(query);\\n relevantTerms.retainAll(allDocTerms);\\n\\n //compute score using a sum formula on each query term\\n int docLength = termsOccurences.get(document).totalNumberOfOccurences();\\n double score = 0.0;\\n for (String term : relevantTerms) {\\n double termIDF = idf.weight(term);\\n double termTF = tf.weight(term, document);\\n\\n score += termIDF * (termTF * (k1 + 1)) / (termTF + k1 * (1 - b + b * (docLength / averageDocLength)));\\n }\\n\\n return score;\\n }\\n };\\n\\n }\\n };\\n\\n logger.log(Level.INFO, \\\"Just created a BM25 query processor with parameters : \\\" + \\\"k1={0}, b={1}\\\", new Object[]{k1, b});\\n\\n return res;\\n }\",\n \"public TreeSet<TermFrequencyPerFile> search(Query query)\\n\\t\\t\\tthrows SearcherException, InterruptedException, ExecutionException {\\n\\t\\tClause tempClause;\\n\\t\\t// Clauses with (start operator|default operator)\\n\\t\\tList<Clause> andAndClauses = new LinkedList<Clause>();\\n\\t\\tList<Clause> andOrClauses = new LinkedList<Clause>();\\n\\t\\tList<Clause> orAndClauses = new LinkedList<Clause>();\\n\\t\\tList<Clause> orOrClauses = new LinkedList<Clause>();\\n\\t\\tList<Clause> tempClauses;\\n\\t\\t// Sets with the clauses of (start operator|default operator)\\n\\t\\tList<Future<TreeSet<TermFrequencyPerFile>>> andSets =\\n\\t\\t\\t\\tnew LinkedList<Future<TreeSet<TermFrequencyPerFile>>>();\\n\\t\\tList<Future<TreeSet<TermFrequencyPerFile>>> orSets =\\n\\t\\t\\t\\tnew LinkedList<Future<TreeSet<TermFrequencyPerFile>>>();\\n\\t\\t// Result set from sub-query\\n\\t\\tList<TreeSet<TermFrequencyPerFile>> subAndSet =\\n\\t\\t\\t\\tnew LinkedList<TreeSet<TermFrequencyPerFile>>();\\n\\t\\tList<TreeSet<TermFrequencyPerFile>> subOrSet =\\n\\t\\t\\t\\tnew LinkedList<TreeSet<TermFrequencyPerFile>>();\\n\\t\\tList<TreeSet<TermFrequencyPerFile>> subNotSet =\\n\\t\\t\\t\\tnew LinkedList<TreeSet<TermFrequencyPerFile>>();\\n\\t\\t// Result set\\n\\t\\tTreeSet<TermFrequencyPerFile> result;\\n\\t\\t\\n\\t\\tfor (int i = 0; i < query.size(); ++i) {\\n\\t\\t\\ttempClause = query.getClause(i);\\n\\t\\t\\t\\n\\t\\t\\tif (tempClause.isQuery()) {\\n\\t\\t\\t\\tassignAllWorks(andAndClauses, andOrClauses\\n\\t\\t\\t\\t\\t\\t, orAndClauses, orOrClauses, andSets, orSets);\\n\\t\\t\\t\\tif ((tempClause.getStartOP() == null)\\n\\t\\t\\t\\t\\t\\t|| tempClause.getStartOP().equals(Operator.AND)) {\\n\\t\\t\\t\\t\\tsubAndSet.add(search((Query) tempClause.getComponent()));\\n\\t\\t\\t\\t} else if (tempClause.getStartOP().equals(Operator.OR)) {\\n\\t\\t\\t\\t\\tsubOrSet.add(search((Query) tempClause.getComponent()));\\n\\t\\t\\t\\t} else {\\n\\t\\t\\t\\t\\tsubNotSet.add(search((Query) tempClause.getComponent()));\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t\\t\\n\\t\\t\\t// Group similar clauses\\n\\t\\t\\ttempClauses = termSearch(tempClause, andAndClauses\\n\\t\\t\\t\\t\\t, andOrClauses, orAndClauses, orOrClauses);\\n\\t\\t\\t\\n\\t\\t\\t// Assign work\\n\\t\\t\\tif (tempClauses != null) {\\n\\t\\t\\t\\t// A clause is ready to get queried\\n\\t\\t\\t\\tassignWork(tempClauses, andSets, orSets);\\n\\t\\t\\t} else {\\n\\t\\t\\t\\tif ((tempClause.getStartOP() != null) \\n\\t\\t\\t\\t\\t\\t&& tempClause.getStartOP().equals(Operator.NOT)) {\\n\\t\\t\\t\\t\\tTerm t = (Term)tempClause.getComponent();\\n\\t\\t\\t\\t\\tassert(t.size() == 1);\\n\\t\\t\\t\\t\\ttry {\\n\\t\\t\\t\\t\\t\\tsubNotSet.add(notSearch(tempClause));\\n\\t\\t\\t\\t\\t} catch (ClassNotFoundException e) {\\n\\t\\t\\t\\t\\t\\te.printStackTrace();\\n\\t\\t\\t\\t\\t} catch (IOException e) {\\n\\t\\t\\t\\t\\t\\te.printStackTrace();\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\tassignAllWorks(andAndClauses, andOrClauses\\n\\t\\t\\t\\t, orAndClauses, orOrClauses, andSets, orSets);\\n\\t\\t\\n\\t\\t// Wait for AND set result\\n\\t\\tfor (Future<TreeSet<TermFrequencyPerFile>> future: andSets) {\\n\\t\\t\\tsubAndSet.add(future.get());\\n\\t\\t}\\n\\t\\t// Integrate All relations at current clause level\\n\\t\\tresult = intersect(subAndSet);\\n\\t\\t\\n\\t\\t// Wait for OR set result\\n\\t\\tfor (Future<TreeSet<TermFrequencyPerFile>> future: orSets) {\\n\\t\\t\\tsubOrSet.add(future.get());\\n\\t\\t}\\n\\t\\tfor (TreeSet<TermFrequencyPerFile> set: subOrSet) {\\n\\t\\t\\tresult.addAll(set);\\n\\t\\t}\\n\\n\\t\\t// Exclude NOT queries\\n\\t\\tresult.removeAll(subNotSet);\\n\\t\\t\\n\\t\\treturn result;\\n\\t}\",\n \"private void termQuerySearch(String[] terms) {\\n for (String term : terms) {\\n LinkedList<TermPositions> postingLists = indexMap.get(analyzeTerm(term));\\n if (postingLists != null) {\\n for (TermPositions matches : postingLists) {\\n double score = (double) 1 + Math.log((double) matches.getPositionList().size()) *\\n Math.log((double) N / (double) postingLists.size());\\n resultsCollector.add(new DocCollector(matches.getDocId(), score));\\n }\\n }\\n }\\n }\",\n \"protected void calculaterVSMforAllQuery(String type)\\n {\\n ArrayList<String> resultAll=new ArrayList<>();\\n for(String qid: this.queryTFscore.keySet())\\n {\\n //System.out.println(qid+\\\"----------------------------------------------------------------------------------------------\\\"+this.maxLength+\\\" \\\"+this.minLength);\\n HashMap<String, Double> queryInfo=this.queryTFscore.get(qid);\\n System.out.println(qid+\\\" \\\"+queryInfo);\\n HashMap <String, Double> finalResult=new HashMap<>();\\n for(String docID:this.corpusTFscore.keySet())\\n {\\n HashMap<String, Double> docInfo=this.corpusTFscore.get(docID);\\n double upperscore=this.calculateUpperPart(queryInfo, docInfo, docID);\\n double lowerscore=this.calculateLowerPart(queryInfo, docInfo, docID);\\n double score=0.0;\\n \\n //Calculate gTerms\\n //Calculate Nx\\n double Nx=0.0;\\n if(this.LengthInfoMap.containsKey(docID)){\\n Nx=(this.LengthInfoMap.get(docID)-this.minLength)/(this.maxLength-this.minLength);\\n }\\n \\n //Calculate gTerms\\n double gTerms=1/(1+Math.exp(-Nx));\\n if(upperscore!=0&&lowerscore!=0) score=gTerms*(upperscore)/lowerscore;\\n //if(upperscore!=0&&lowerscore!=0) score=(upperscore)/lowerscore;\\n if(score>0) {\\n //System.out.println(docID+\\\" = \\\"+score);\\n finalResult.put(docID, score);\\n }\\n \\n }\\n HashMap<String, Double> normalizedAndSortedResult=doNormalization(finalResult);\\n //HashMap<String, Double> sortedResult=MiscUtility.sortByValues(finalResult);\\n //System.out.println(normalizedAndSortedResult);\\n int count=0;\\n for(String docID:normalizedAndSortedResult.keySet())\\n {\\n if(count>9) break;\\n String fullPath=this.corpusMap.get(docID);\\n resultAll.add(qid+\\\",\\\"+fullPath+\\\",\\\"+normalizedAndSortedResult.get(docID));\\n count++;\\n }\\n }\\n ContentWriter.writeContent(this.base+\\\"\\\\\\\\Result\\\\\\\\\\\"+this.corpus+\\\"_result\\\"+type+\\\".txt\\\", resultAll);\\n }\",\n \"public static void QueryVector() {\\n for(Entry<String, List<Double>> entry: wtgMap.entrySet()){\\n List<Double> queryValue = new ArrayList();\\n queryValue = entry.getValue();\\n double temp = queryValue.get(totaldocument);\\n\\n query.add(temp);\\n }\\n }\",\n \"public Query( String queryString ) {\\r\\n\\tStringTokenizer tok = new StringTokenizer( queryString );\\r\\n\\twhile ( tok.hasMoreTokens() ) {\\r\\n\\t terms.add( tok.nextToken() );\\r\\n\\t weights.add( new Double(1) );\\r\\n\\t} \\r\\n }\",\n \"@Override\\n public double score(Document document) {\\n Set<String> allDocTerms = documentsTerms.termsExtractedFromDocument(document).allTerms();\\n\\n //keeping only the query terms that are in the document\\n Collection<String> relevantTerms = new LinkedHashSet<>(query);\\n relevantTerms.retainAll(allDocTerms);\\n\\n //compute score using a sum formula on each query term\\n int docLength = termsOccurences.get(document).totalNumberOfOccurences();\\n double score = 0.0;\\n for (String term : relevantTerms) {\\n double termIDF = idf.weight(term);\\n double termTF = tf.weight(term, document);\\n\\n score += termIDF * (termTF * (k1 + 1)) / (termTF + k1 * (1 - b + b * (docLength / averageDocLength)));\\n }\\n\\n return score;\\n }\",\n \"public PostingsList phrase_query(Query query){\\n\\n LinkedList<PostingsList> listQueriedPostings = new LinkedList<PostingsList>();\\n // List with postings corresponding to the queries\\n for (int i = 0; i<query.size(); i++){\\n // If any query has zero matches, return 0 results\\n //if(!(new File(\\\"postings/t\\\"+hash(query.terms.get(i))+\\\".json\\\")).exists()){\\n if (!this.index.containsKey(query.terms.get(i))){\\n return null;\\n }\\n // Otherwise store postings in the list\\n listQueriedPostings.add(this.getPostings(query.terms.get(i)));\\n }\\n\\n PostingsList result = new PostingsList();\\n result = listQueriedPostings.get(0);\\n\\n // In case only one word is queried\\n if (listQueriedPostings.size() == 1){\\n return result;\\n }\\n\\n // Apply algorithm as many times as words in the query\\n for(int i = 1; i < listQueriedPostings.size(); i++){\\n result = phrase_query(result, listQueriedPostings.get(i));\\n if (result.isEmpty()){\\n return null;\\n }\\n }\\n return result;\\n }\",\n \"@Override\\n public List<SearchResult> search(String queryString, int k) {\\n // TODO: YOUR CODE HERE\\n\\n // Tokenize the query and put it into a Set\\n HashSet<String> tokenSet = new HashSet<>(Searcher.tokenize(queryString));\\n\\n /*\\n * Section 1: FETCHING termId, termFreq and relevant docId from the Query\\n */\\n\\n // Init a set to store Relevant Document Id\\n HashSet<Integer> relevantDocIdSet = new HashSet<>();\\n for (String token : tokenSet) { // Iterates thru all query tokens\\n int termId;\\n try {\\n termId = indexer.getTermDict().get(token);\\n } catch (NullPointerException e) { // In case current token is not in the termDict\\n continue; // Skip this one\\n }\\n // Get the Posting associate to the termId\\n HashSet<Integer> posting = indexer.getPostingLists().get(termId);\\n relevantDocIdSet.addAll(posting); // Add them all to the Relevant Document Id set\\n }\\n\\n /*\\n * Section 2: Calculate Jaccard Coefficient between the Query and all POTENTIAL DOCUMENTS\\n */\\n\\n // ArrayList for the Final Result\\n ArrayList<SearchResult> searchResults = new ArrayList<>();\\n for (Document doc : documents) { // Iterates thru all documents\\n if (!relevantDocIdSet.contains(doc.getId())) { // If the document is relevant\\n searchResults.add(new SearchResult(doc, 0)); // Add the document as a SearchResult with zero score\\n } else {\\n HashSet<String> termIdSet = new HashSet<>(doc.getTokens()); // Get the token set from the document\\n\\n // Calculate Jaccard Coefficient of the document\\n double jaccardScore = JaccardMathHelper.calculateJaccardSimilarity(tokenSet, termIdSet);\\n\\n // Add the SearchResult with the computed Jaccard Score\\n searchResults.add(new SearchResult(doc, jaccardScore));\\n }\\n }\\n\\n return TFIDFSearcher.finalizeSearchResult(searchResults, k);\\n }\",\n \"private static List<SearchData> booleanSearchFrequency(Query query, Indexer si) {\\n Tokenizer tkn = new SimpleTokenizer();\\n tkn.tokenize(query.getStr(), \\\"[a-zA-Z]{3,}\\\", true, true);\\n List<SearchData> searchList = new ArrayList<>();\\n LinkedList<Token> wordsList = tkn.getTokens();\\n Iterator<Token> wordsIt = wordsList.iterator();\\n HashMap<String, LinkedList<Posting>> indexer = si.getIndexer();\\n int idx;\\n SearchData searched_doc;\\n\\n while (wordsIt.hasNext()) {\\n String word = wordsIt.next().getSequence();\\n if (indexer.containsKey(word)) {\\n\\n LinkedList<Posting> posting = indexer.get(word);\\n\\n for (Posting pst : posting) {\\n\\n SearchData sd = new SearchData(query, pst.getDocId());\\n\\n if (!searchList.contains(sd)) {\\n sd.setScore(pst.getTermFreq());\\n searchList.add(sd);\\n } else {\\n idx = searchList.indexOf(sd);\\n searched_doc = searchList.get(idx);\\n searched_doc.setScore(searched_doc.getScore() + pst.getTermFreq());\\n }\\n }\\n }\\n }\\n\\n Collections.sort(searchList);\\n\\n return searchList;\\n }\",\n \"private double rankByBM25(List<String> query, String docId, HashMap<String,Integer> queryWordsTFPerDoc){\\n int termFrequency, documentFrequency;\\n double numOfDocs = documentDetails.size(), idf, rank = 0, k = 1.2, b = 0.75, numerator, denominator;\\n int documentLength = Integer.valueOf(documentDetails.get(docId)[3]);\\n\\n for(String term : query){\\n if(queryWordsTFPerDoc.containsKey(term.toUpperCase())) {\\n term = term.toUpperCase();\\n }\\n else if(queryWordsTFPerDoc.containsKey(term.toLowerCase())){\\n term = term.toLowerCase();\\n }\\n termFrequency = queryWordsTFPerDoc.getOrDefault(term,0);\\n\\n if(termFrequency != 0) {\\n documentFrequency = Integer.valueOf(termsDF.get(term));\\n idf = log2(numOfDocs / documentFrequency);\\n\\n numerator = termFrequency * (k + 1);\\n denominator = termFrequency + k * (1 - b + b * (documentLength / averageDocumentLength));\\n\\n rank += idf * (numerator / denominator);\\n }\\n }\\n return rank;\\n }\",\n \"private static List<SearchData> booleanSearchWord(Query query, Indexer si) {\\n Tokenizer tkn = new SimpleTokenizer();\\n tkn.tokenize(query.getStr(), \\\"[a-zA-Z]{3,}\\\", true, true);\\n List<SearchData> searchList = new ArrayList<>();\\n LinkedList<Token> wordsList = tkn.getTokens();\\n Iterator<Token> wordsIt = wordsList.iterator();\\n HashMap<String, LinkedList<Posting>> indexer = si.getIndexer();\\n int idx;\\n SearchData searched_doc;\\n\\n while (wordsIt.hasNext()) {\\n String word = wordsIt.next().getSequence();\\n if (indexer.containsKey(word)) {\\n\\n LinkedList<Posting> posting = indexer.get(word);\\n\\n for (Posting pst : posting) {\\n\\n SearchData sd = new SearchData(query, pst.getDocId());\\n\\n if (!searchList.contains(sd)) {\\n sd.setScore(1);\\n searchList.add(sd);\\n } else {\\n idx = searchList.indexOf(sd);\\n searched_doc = searchList.get(idx);\\n searched_doc.setScore(searched_doc.getScore() + 1);\\n }\\n }\\n\\n }\\n\\n\\n }\\n\\n Collections.sort(searchList);\\n\\n return searchList;\\n }\",\n \"public PostingsList intersect(Query query){\\n\\n LinkedList<PostingsList> listQueriedPostings = new LinkedList<PostingsList>();\\n // List with postings corresponding to the queries\\n for (int i = 0; i<query.size(); i++){\\n // If any query has zero matches, return 0 results\\n //if(!(new File(\\\"postings/t\\\"+hash(query.terms.get(i))+\\\".json\\\")).exists()){\\n if (!this.index.containsKey(query.terms.get(i))){\\n return null;\\n }\\n // Otherwise store postings in the list\\n listQueriedPostings.add(this.getPostings(query.terms.get(i)));\\n }\\n\\n // Order the posting list by increasing document frequency\\n listQueriedPostings = sortByIncreasingFrequency(listQueriedPostings);\\n\\n PostingsList result = (PostingsList)listQueriedPostings.get(0);\\n\\n // In case only one word is queried\\n if (listQueriedPostings.size() == 1){\\n return result;\\n }\\n\\n // Apply algorithm as many times as words in the query\\n for(int i = 1; i < listQueriedPostings.size(); i++){\\n result = intersect(result, listQueriedPostings.get(i));\\n if (result.isEmpty()){\\n return null;\\n }\\n }\\n return result;\\n }\",\n \"private List<Integer> processRelatedDocsQuery(String query) {\\r\\n List<Integer> result = new ArrayList<>();\\r\\n\\r\\n for(String term : this.preprocessor.processQuery(query).keySet()) {\\r\\n\\r\\n // skip unknown terms\\r\\n if (!this.index.getDict().containsKey(term)) continue;\\r\\n\\r\\n // for each occurrence\\r\\n for(TermFrequency tf : this.index.getDict().get(term)){\\r\\n int id = tf.getDocId();\\r\\n if(!result.contains(id))\\r\\n result.add(id);\\r\\n }\\r\\n }\\r\\n\\r\\n return result;\\r\\n }\",\n \"@Override\\r\\n\\t\\t\\tpublic List<ScoredDocument> search(Query query) {\\n\\t\\t\\t\\treturn null;\\r\\n\\t\\t\\t}\",\n \"public Double computeRelevance(IList<String> query, URI pageUri) {\\n\\t if (query == null || pageUri == null) {\\n\\t\\t throw new NullPointerException();\\n\\t }\\n\\t \\n IDictionary<String, Double> documentVector = documentTfIdfVectors.get(pageUri);\\n IDictionary<String, Double> queryTfScores = computeTfScores(query);\\n IDictionary<String, Double> queryVector = new ChainedHashDictionary<String, Double>();\\n Double numerator = 0.0;\\n \\n for (KVPair<String, Double> pair: queryTfScores) {\\n\\t \\t\\tDouble queryWordScore = 0.0;\\n\\t \\t\\tDouble docWordScore = 0.0;\\n\\t \\t\\tif (idfScores.containsKey(pair.getKey())) {\\t\\n\\t \\t\\t queryWordScore = queryTfScores.get(pair.getKey()) * idfScores.get(pair.getKey());\\n\\t \\t\\t}\\n \\t\\t\\tqueryVector.put(pair.getKey(), queryWordScore);\\n\\t \\t\\tif (documentVector.containsKey(pair.getKey())) {\\n\\t \\t\\t\\tdocWordScore = documentVector.get(pair.getKey());\\n\\t \\t\\t} \\n\\t \\t\\tnumerator += queryWordScore * docWordScore;\\n } \\n \\n Double denominator = docDenomScore.get(pageUri) * norm(queryVector);\\n \\n // A check to avoid division by zero\\n if (denominator != 0.0) {\\n \\t\\t return numerator / denominator;\\n } else {\\n return 0.0;\\n }\\n }\",\n \"static void ReadQuery(String input) throws FileNotFoundException {\\n input = input.replaceAll(\\\"[^A-Za-z]\\\",\\\" \\\");\\n String[] arr = input.split(\\\" \\\"); // splitting the whole string into words by split on the basis of white spaces\\n\\n\\n for(int i=0; i<arr.length; i++) {\\n String termWord = arr[i].toLowerCase();\\t//same pre-processing is applied to all the query word\\n //termWord = RemoveSpecialCharacter(termWord);\\n termWord = removeStopWords(termWord);\\n\\n if(!termWord.equalsIgnoreCase(\\\"\\\")) { // all the white spaces are removed as if not removed then lemmatization wont be successfully done\\n\\n termWord = Lemmatize(termWord);\\n System.out.println(termWord);\\n if(dictionary.containsKey(termWord)) {\\n List<Integer> wordList = new ArrayList<>();\\n wordList = dictionary.get(termWord);\\n int queryWordFrequency = wordList.get(totaldocument);\\n queryWordFrequency++;\\n wordList.set(totaldocument, queryWordFrequency); // all the frequencies of the query words are stored at the 56th index of the List stored in the\\n //hashmap associated with its word-terms\\n dictionary.put(termWord, wordList);\\n }\\n else {\\n //if any of the enterd query word not present in all the docs so list will have 0.0 value from 0th index to 55th and 56th index is reserver\\n // for query word frequency\\n List<Integer> wordList = new ArrayList<>();\\n for(int j=0; j<totaldocument+1; j++) {\\n wordList.add(0);\\n }\\n wordList.add(1);\\n dictionary.put(termWord, wordList); //updating the dictionary hashmap now containing all the query words frequencies\\n }\\n }\\n }\\n save();\\n }\",\n \"private static void RankedQueryMode(DiskIndexWriter diskWriter, DiskPositionalIndex disk_posIndex) throws IOException, ClassNotFoundException, InstantiationException, IllegalAccessException {\\n\\n if (query.equals(\\\"q\\\")) {\\n\\n System.exit(0);\\n }\\n\\n List<String> word = new ArrayList();\\n String[] query_array = query.split(\\\"\\\\\\\\s+\\\");\\n TokenProcessor processor = new NewTokenProcessor();\\n\\n for (int i = 0; i < query_array.length; i++) {\\n word.add(processor.processToken(query_array[i]).get(0));\\n }\\n\\n StrategyFactory sf = new StrategyFactory();\\n StrategyInterface strategy = sf.execute(rankedOption);\\n\\n //maps postings to accumulator value\\n HashMap<Integer, Doc_accum> postingMap = new HashMap<Integer, Doc_accum>();\\n\\n PriorityQueue<Doc_accum> queue = new PriorityQueue<>(Collections.reverseOrder());\\n\\n List<Posting> postings = new ArrayList<>();\\n List<Doc_accum> results = new ArrayList<>();\\n\\n for (String term : word) {\\n\\n postings = disk_posIndex.getPosting_noPos(term);\\n for (Posting p : postings) { //for each document in the postings list\\n double t_fd = p.getT_fd();\\n double d_ft = p.getD_ft();\\n double w_qt = strategy.calculate_wqt(N, d_ft);\\n double accum = 0;\\n double w_dt = strategy.get_wdt(t_fd, disk_posIndex, p.getDocumentId());\\n\\n //pairs (Ranked_posting, accumulator factor)\\n if (postingMap.containsKey(p.getDocumentId())) {\\n accum = postingMap.get(p.getDocumentId()).getAccumulator();\\n accum += (w_qt * w_dt);\\n postingMap.replace(p.getDocumentId(), new Doc_accum(p, accum)); //replaces old accum value\\n\\n } else {\\n accum += (w_qt * w_dt);\\n postingMap.put(p.getDocumentId(), new Doc_accum(p, accum));\\n }\\n }\\n\\n }\\n\\n for (Integer p : postingMap.keySet()) {\\n Doc_accum doc_temp = postingMap.get(p);\\n double accum = doc_temp.getAccumulator(); //gets accum associated with doc\\n\\n if (accum > 0) {\\n //search for each p's Ld factor in docWeights.bin\\n double l_d = strategy.calculate_Ld(disk_posIndex, doc_temp.getPosting().getDocumentId());\\n\\n accum /= l_d;\\n doc_temp.setAccumulator(accum);\\n }\\n\\n queue.add(postingMap.get(p));\\n\\n }\\n\\n //returns top K=10 results \\n int topK = 50;\\n\\n while ((results.size() < topK) && queue.size() > 0) {\\n\\n results.add(queue.poll()); //gets the posting acc pair and returns only posting\\n\\n }\\n\\n display_RankedResults(results);\\n\\n }\",\n \"public void searchAndWriteQueryResultsToOutput() {\\n\\n List<String> queryList = fu.textFileToList(QUERY_FILE_PATH);\\n\\n for (int queryID = 0; queryID < queryList.size(); queryID++) {\\n String query = queryList.get(queryID);\\n // ===================================================\\n // 4. Sort the documents by the BM25 scores.\\n // ===================================================\\n HashMap<String, Double> docScore = search(query);\\n List<Map.Entry<String, Double>> rankedDocList =\\n new LinkedList<Map.Entry<String, Double>>(docScore.entrySet());\\n Collections.sort(rankedDocList, new MapComparatorByValues());\\n\\n // ===================================================\\n // 5. Write Query Results to output\\n // =================================================== \\n String outputFilePath =\\n RANKING_RESULTS_PATH + \\\"queryID_\\\" + (queryID + 1) + \\\".txt\\\";\\n StringBuilder toOutput = new StringBuilder();\\n // display results in console\\n System.out.println(\\\"Found \\\" + docScore.size() + \\\" hits.\\\");\\n int i = 0;\\n for (Entry<String, Double> scoreEntry : rankedDocList) {\\n if (i >= NUM_OF_RESULTS_TO_RETURN)\\n break;\\n String docId = scoreEntry.getKey();\\n Double score = scoreEntry.getValue();\\n String resultLine =\\n (queryID + 1) + \\\" Q0 \\\" + docId + \\\" \\\" + (i + 1) + \\\" \\\" + score + \\\" BM25\\\";\\n toOutput.append(resultLine);\\n toOutput.append(System.getProperty(\\\"line.separator\\\"));\\n System.out.println(resultLine);\\n i++;\\n }\\n fu.writeStringToFile(toOutput.toString(), outputFilePath);\\n }\\n }\",\n \"private static Boolean specialQueries(String query) throws ClassNotFoundException, InstantiationException, IllegalAccessException {\\n clickList = false;\\n //newCorpus = true;\\n\\n if (query.equals(\\\"q\\\")) {\\n\\n System.exit(0);\\n return true;\\n }\\n\\n String[] subqueries = query.split(\\\"\\\\\\\\s+\\\"); //split around white space\\n\\n if (subqueries[0].equals(\\\"stem\\\")) //first term in subqueries tells computer what to do \\n {\\n GUI.JListModel.clear();\\n GUI.ResultsLabel.setText(\\\"\\\");\\n TokenProcessor processor = new NewTokenProcessor();\\n if (subqueries.length > 1) //user meant to stem the token not to search stem\\n {\\n List<String> stems = processor.processToken(subqueries[1]);\\n\\n //clears list and repopulates it \\n String stem = \\\"Stem of query '\\\" + subqueries[1] + \\\"' is '\\\" + stems.get(0) + \\\"'\\\";\\n\\n GUI.ResultsLabel.setText(stem);\\n\\n return true;\\n }\\n\\n } else if (subqueries[0].equals(\\\"vocab\\\")) {\\n List<String> vocabList = Disk_posIndex.getVocabulary();\\n GUI.JListModel.clear();\\n GUI.ResultsLabel.setText(\\\"\\\");\\n\\n int vocabCount = 0;\\n for (String v : vocabList) {\\n if (vocabCount < 1000) {\\n vocabCount++;\\n GUI.JListModel.addElement(v);\\n }\\n }\\n GUI.ResultsLabel.setText(\\\"Total size of vocabulary: \\\" + vocabCount);\\n return true;\\n }\\n\\n return false;\\n }\",\n \"SwiftScoredSet getTfIdf(String text,ASTNode n,boolean kgram)\\n{\\n Map<String,Integer> words = null;\\n Map<String,Integer> totals = null;\\n double tot = 0;\\n if (kgram){\\n words = buildKgramCounts(text,n);\\n totals = kgram_counts;\\n tot = total_kdocuments;\\n } \\n else {\\n words = handleDocumentText(text);\\n totals = document_counts;\\n tot = total_documents;\\n }\\n double termtot = 1;\\n \\n for (Integer iv : words.values()) {\\n termtot += iv;\\n }\\n \\n SwiftScoredSet rslt = new SwiftScoredSet();\\n for (Map.Entry<String,Integer> ent : words.entrySet()) {\\n String wd = ent.getKey();\\n double ct = ent.getValue();\\n Integer docs = totals.get(wd);\\n double docct = 0;\\n if (docs != null) docct = docs;\\n double idf = Math.log(tot/(1+docct));\\n double tf = ct/termtot;\\n double tfidf = tf*idf;\\n rslt.add(wd,tfidf);\\n }\\n rslt.normalize();\\n \\n return rslt;\\n}\",\n \"public void queryDataPreProcess(String queryText) throws Exception {\\n StopwordRemover stopwordRemover = new StopwordRemover();\\n WordNormalizer wordNormalizer = new WordNormalizer();\\n\\n // initiate the BufferedWriter to output result\\n FilePathGenerator fpg = new FilePathGenerator(\\\"result.txt\\\");\\n String path = fpg.getPath();\\n\\n // queryId\\n String queryId = \\\"\\\";\\n if (queryId == null || queryId.length() == 0){\\n// queryId = UUID.randomUUID().toString().replace(\\\"-\\\", \\\"\\\");\\n queryId = String.valueOf(FileConst.query_doc_id);\\n }\\n\\n // append query_id:query_text to exiting doc_id:doc_content text file\\n try (FileWriter fileWriter = new FileWriter(path, true); // Path.ResultAssignment1\\n BufferedWriter bw = new BufferedWriter(fileWriter)){\\n // write doc_id into the result file\\n bw.write(queryId + '\\\\n');\\n\\n // load doc content\\n char[] content = queryText.toCharArray();\\n\\n // initiate a word object to hold a word\\n char[] word;\\n\\n // initiate the WordTokenizer\\n WordTokenizer tokenizer = new WordTokenizer(content);\\n\\n // process the query word by word iteratively\\n while ((word = tokenizer.nextWord()) != null){\\n word = wordNormalizer.lowercase(word);\\n // write only non-stopword into result file\\n if (!stopwordRemover.isStopword(Arrays.toString(word))){\\n bw.append(wordNormalizer.toStem(word)).append(\\\" \\\");\\n query_tokens.add(wordNormalizer.toStem(word));\\n }\\n }\\n bw.append(\\\"\\\\n\\\");\\n } catch (Exception e) {\\n e.printStackTrace();\\n }\\n }\",\n \"public String [] getTerm (String [] query) {\\r\\n String [] unique = query;\\r\\n //find duplicate for get unique\\r\\n return unique;\\r\\n }\",\n \"private static ArrayList<Result> distanceMatching(Query query, DataManager myVocab) {\\n\\t\\tString queryterm = query.getQuery();\\n\\t\\tint maxScore;\\n\\t\\tif (queryterm.length()<9)\\n\\t\\t\\tmaxScore= queryterm.length()-THRESHOLD_LEV;\\n\\t\\telse\\n\\t\\t\\tmaxScore = queryterm.length()-(queryterm.length()/THRESHOLD_LEV);\\n\\t\\tArrayList<Result> fuzzyResults = new ArrayList<Result>();\\n\\t\\tfor (int i = 0; i < myVocab.vocab.size(); i++){\\n\\t\\t\\tString vocabterm = myVocab.vocab.get(i).trim();\\n\\t\\t\\tint distance = levenshteinDistance(vocabterm, queryterm);\\n\\t\\t\\t// subtract the distance that's just the length difference\\n\\t\\t\\t// to only take into account the character substitution\\n\\t\\t\\tdistance = distance - (Math.abs(vocabterm.length() - queryterm.length()));\\n\\t\\t\\tif (distance < maxScore){\\n\\t\\t\\t\\tdouble score;\\n\\t\\t\\t\\tif (vocabterm.length() < queryterm.length())\\n\\t\\t\\t\\t\\tscore = ((double)(vocabterm.length())/(double)(queryterm.length()+distance))*99;\\n\\t\\t\\t\\telse\\n\\t\\t\\t\\t\\tscore = (((double)queryterm.length()/(double)(vocabterm.length()+distance)))*99;\\n\\t\\t\\t\\tfuzzyResults.add(new Result(query.getType()+\\\"/\\\"+myVocab.vocab.get(i), myVocab.vocab.get(i), query.getType(),score, false));\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\treturn fuzzyResults;\\n\\t}\",\n \"public static Map<Integer, Double> accumulate(DiskPositionalIndex index, int corpusSize, String query) throws IOException {\\n Map<Integer, Double> accumulator = new HashMap<>();\\n\\n getTokens(query).forEach((token) -> {\\n List<Posting> postings = index.getPostings(token);\\n\\n System.out.println(\\\"Postings size: \\\" + postings.size());\\n \\n //Calculate w(q,t) \\n double wQT = 0.0, accu = 0.0, wDT = 0.0;\\n \\n if (!postings.isEmpty()) {\\n wQT = Math.log(1.0 + ((double) corpusSize / (double) postings.size()));\\n }\\n\\n for (Posting p : postings) {\\n // Never encountered, add and initialize\\n // if (!accumulator.containsKey(p.getDocumentId())) {\\n // accumulator.put(p.getDocumentId(), 0.0);\\n // }\\n \\n // Calculate weight of doc = 1 + ln(tf(t,d)) \\n // wDT = 1.0 + Math.log((double) p.getPositions().size());\\n wDT = p.getTermFrequency();\\n \\n // Acquire A(d)\\n accu = accumulator.getOrDefault(p.getDocumentId(), 0.0); \\n \\n accumulator.put(p.getDocumentId(), accu + (wQT * wDT));\\n }\\n });\\n \\n // Divide all A(d) by L(d)\\n for (Integer key : accumulator.keySet()) {\\n if (accumulator.get(key) != 0.0) {\\n // Accumulator = Accumulator / L(d)\\n accumulator.put(key, (double) accumulator.get(key) / index.getDocWeight(key));\\n }\\n }\\n \\n return accumulator; \\n }\",\n \"public void queryRecommended(Query query, float score, String original);\",\n \"public void search(Indexer indexer, CityIndexer cityIndexer, Ranker ranker, String query, boolean withSemantic, ArrayList<String> chosenCities, ObservableList<String> citiesByTag, boolean withStemming, String saveInPath, String queryId, String queryDescription) {\\n String[] originalQueryTerms = query.split(\\\" \\\");\\n String originQuery = query;\\n docsResults = new HashMap<>();\\n parser = new Parse(withStemming, saveInPath, saveInPath);\\n HashSet<String> docsOfChosenCities = new HashSet<>();\\n query = \\\"\\\" + query + queryDescription;\\n HashMap<String, Integer> queryTerms = parser.parseQuery(query);\\n HashMap<String, ArrayList<Integer>> dictionary = indexer.getDictionary();\\n if (!withStemming){\\n setDocsInfo(saveInPath + \\\"\\\\\\\\docsInformation.txt\\\");\\n }\\n else{\\n setDocsInfo(saveInPath + \\\"\\\\\\\\docsInformation_stemming.txt\\\");\\n }\\n\\n\\n //add semantic words of each term in query to 'queryTerms'\\n if(withSemantic) {\\n HashMap<String,ArrayList<String>> semanticWords = ws.connectToApi(originQuery);\\n }\\n\\n //give an ID to query if it's a regular query (not queries file)\\n if(queryId.equals(\\\"\\\")){\\n queryId = \\\"\\\" + Searcher.queryID;\\n Searcher.queryID++;\\n }\\n\\n String postingDir;\\n if (!withStemming) {\\n postingDir = \\\"\\\\\\\\indexResults\\\\\\\\postingFiles\\\";\\n } else {\\n postingDir = \\\"\\\\\\\\indexResults\\\\\\\\postingFiles_Stemming\\\";\\n }\\n int pointer = 0;\\n\\n //find docs that contain the terms in the query in their text\\n HashMap<String, Integer> queryTermsIgnoreCase = new HashMap<>();\\n for (String term : queryTerms.keySet()) {\\n String originTerm = term;\\n if (!dictionary.containsKey(term.toUpperCase()) && !dictionary.containsKey(term.toLowerCase())) {\\n continue;\\n }\\n if(dictionary.containsKey(term.toLowerCase())){\\n term = term.toLowerCase();\\n }\\n else {\\n term = term.toUpperCase();\\n }\\n queryTermsIgnoreCase.put(term,queryTerms.get(originTerm));\\n pointer = dictionary.get(term).get(2);\\n String chunk = (\\\"\\\" + term.charAt(0)).toUpperCase();\\n\\n //get the relevant line from posting file\\n BufferedReader br = null;\\n try {\\n br = new BufferedReader(new FileReader(new File(saveInPath + postingDir + \\\"\\\\\\\\posting_\\\" + chunk + \\\".txt\\\")));\\n String line = \\\"\\\";\\n int i = 1;\\n while ((line = (br.readLine())) != null) {\\n if (i == pointer) {\\n break;\\n }\\n i++;\\n }\\n br.close();\\n\\n //get docs from posting line and add them to the data structure 'docsResults'\\n if(line != null) {\\n findDocsFromLine(line, term);\\n }\\n\\n } catch (IOException e) {\\n e.printStackTrace();\\n }\\n }\\n\\n //find docs that contain the chosen cities in their text\\n for (String cityTerm : chosenCities) {\\n if (!dictionary.containsKey(cityTerm) && !dictionary.containsKey(cityTerm.toLowerCase())) {\\n continue;\\n }\\n if(dictionary.containsKey(cityTerm.toLowerCase())){\\n cityTerm = cityTerm.toLowerCase();\\n }\\n pointer = dictionary.get(cityTerm).get(2);\\n // char chunk = indexer.classifyToPosting(term).charAt(0);\\n String chunk = (\\\"\\\" + cityTerm.charAt(0)).toUpperCase();\\n\\n //get the relevant line from posting file\\n BufferedReader br = null;\\n try {\\n br = new BufferedReader(new FileReader(new File(saveInPath + postingDir + \\\"\\\\\\\\posting_\\\" + chunk + \\\".txt\\\")));\\n String line = \\\"\\\";\\n int i = 1;\\n while ((line = (br.readLine())) != null) {\\n if (i == pointer) {\\n break;\\n }\\n i++;\\n }\\n br.close();\\n\\n //get docs from posting line and add them to the data structure 'docsOfChosenCities'\\n String docs = line.substring(0, line.indexOf(\\\"[\\\") - 1); //get 'docsListStr'\\n String[] docsArr = docs.split(\\\";\\\");\\n for (String docInfo : docsArr) {\\n String doc = docInfo.substring(0, docInfo.indexOf(\\\": \\\"));\\n while(doc.charAt(0) == ' '){\\n doc = doc.substring(1);\\n }\\n docsOfChosenCities.add(doc);\\n }\\n } catch (IOException e) {\\n e.printStackTrace();\\n }\\n }\\n\\n //find docs that contain the chosen cities in their city tag\\n if(!chosenCities.isEmpty()){\\n for (String cityDicRec: chosenCities) {\\n //get pointer to posting from cityDictionary\\n try {\\n pointer = cityIndexer.getCitiesDictionary().get(cityDicRec);\\n } catch (NumberFormatException e) {\\n e.printStackTrace();\\n }\\n //get the relevant line from posting file\\n BufferedReader br = null;\\n try {\\n br = new BufferedReader(new FileReader(new File(saveInPath + \\\"\\\\\\\\cityIndexResults\\\" + \\\"\\\\\\\\posting_city\\\" + \\\".txt\\\")));\\n String line = \\\"\\\";\\n int i = 1;\\n while ((line = (br.readLine())) != null) {\\n if (i == pointer) {\\n break;\\n }\\n i++;\\n }\\n br.close();\\n\\n //get docs from posting line and add them to the data structure 'docsOfChosenCities'\\n String docs = line.substring(line.indexOf(\\\"[\\\") + 1, line.indexOf(\\\"]\\\")); //get 'docsListStr'\\n String[] docsArr = docs.split(\\\"; \\\");\\n for (String doc : docsArr) {\\n docsOfChosenCities.add(doc);\\n }\\n } catch (IOException e) {\\n e.printStackTrace();\\n }\\n }\\n }\\n\\n\\n ranker.rank(docsResults, docsOfChosenCities, queryTermsIgnoreCase, dictionary, docsInfo,entities, queryId);\\n }\",\n \"public HashMap<String, Double> GetTokenRFScore(Query aQuery, int TopK) throws Exception {\\r\\n\\t\\t// Store <token, score> for being returned\\r\\n\\t\\tHashMap<String, Double> TokenRFScore = new HashMap<>();\\r\\n\\t\\t\\r\\n\\t\\t// Get tokens in the given query\\r\\n\\t String[] tokens = aQuery.getQueryContent().split(\\\" \\\");\\r\\n\\t \\r\\n\\t // Get feedback docs by the given query using feedback retrieval model\\r\\n\\t List<Classes.Document> feedbackDocs = new QueryRetrievalModel().retrieveQuery(aQuery, TopK);\\r\\n\\r\\n\\t // Initiate qeuryResult map <docid, <term, tf>> and termFreq map <term, cf>\\r\\n\\t queryResult = new HashMap<>();\\r\\n\\t termFreq = new HashMap<>();\\r\\n\\r\\n\\t // Search each token appearing in the given query \\r\\n\\t for(String token : tokens) {\\r\\n\\t \\t// Determine whether the current token exists in collection \\r\\n\\t \\tlong cf = myireader.CollectionFreq(token);\\r\\n\\t \\ttermFreq.put(token, cf);\\r\\n\\t \\tif(cf == 0) {\\r\\n\\t \\t\\tcontinue; \\r\\n\\t \\t}\\r\\n\\t \\r\\n\\t \\tint[][] postingList = myireader.getPostingList(token);\\r\\n\\t \\tfor(int[] posting : postingList) {\\r\\n\\t \\t\\tif(!queryResult.containsKey(posting[0])) { // posting[0]: docid\\r\\n\\t \\t\\t\\tHashMap<String, Integer> tfMap = new HashMap<>();\\r\\n\\t \\t\\t\\ttfMap.put(token, posting[1]); // posting[1]: tf\\r\\n\\t \\t\\t\\tqueryResult.put(posting[0], tfMap);\\r\\n\\t \\t\\t} else {\\r\\n\\t \\t\\t\\tqueryResult.get(posting[0]).put(token, posting[1]);\\r\\n\\t \\t\\t}\\r\\n\\t \\t}\\r\\n\\t }\\r\\n\\t /*\\r\\n\\t\\t * After the for loop, we have the map <docid, <term, term_freq>> for each doc to all terms in the query\\r\\n\\t\\t * tokens = [Hong, Kong, economics, Singapore]\\r\\n\\t\\t * \\r\\n\\t\\t * queryResult : <docid, <term, term_freq>>\\r\\n\\t\\t * 1, hong, 15\\r\\n\\t\\t * Singapore, 3\\r\\n\\t\\t * 3, Singapore, 1\\r\\n\\t\\t * kong, 10\\r\\n\\t\\t * economics, 30\\r\\n\\t\\t * ..., ...\\r\\n\\t\\t */\\t\\r\\n\\r\\n\\t // Here all feedback docs are treated as one big pseudo document!!!!!!\\r\\n\\t int len = 0;\\r\\n\\t // Store <term, tf>\\r\\n\\t Map<String, Integer> pseudoDoc = new HashMap<>();\\r\\n\\t for(Classes.Document doc : feedbackDocs) {\\r\\n\\t \\tqueryResult.get(Integer.parseInt(doc.getLuceneID())).forEach((term, tf) -> { // Iterate each tfMap\\r\\n\\t \\t\\tif(!pseudoDoc.containsKey(term)) {\\r\\n\\t \\t\\t\\tpseudoDoc.put(term, tf);\\r\\n\\t \\t\\t} else {\\r\\n\\t \\t\\t\\tpseudoDoc.put(term, tf + pseudoDoc.get(term));\\r\\n\\t \\t\\t}\\r\\n\\t \\t});\\r\\n\\t \\t\\r\\n\\t \\t// Accumulate by the current doc's length\\r\\n\\t \\tlen += myireader.docLength(Integer.parseInt(doc.getLuceneID()));\\r\\n\\t }\\r\\n\\t \\r\\n\\t /**\\r\\n\\t\\t * Dirichlet Prior Smoothing:\\r\\n\\t\\t * p(w|D) = (|D|/(|D|+MU))*(c(w,D)/|D|) + (MU/(|D|+MU))*p(w|REF)\\r\\n\\t * score = λ*p_doc + (1-λ)*p_ref\\r\\n\\t * = c1*p_doc + c2*p_ref\\r\\n\\t\\t */\\r\\n\\t int pseudoLen = len;\\r\\n\\t double c1 = pseudoLen / (pseudoLen + MU);\\r\\n\\t double c2 = MU / (pseudoLen + MU);\\r\\n\\t // Calculate the probability of pseudoDoc generating each term\\r\\n\\t pseudoDoc.forEach((token, tf) -> {\\r\\n\\t \\tlong cf = termFreq.get(token);\\r\\n\\t \\tdouble pDoc = (double) tf / pseudoLen; // p(w|D)\\r\\n\\t \\tdouble pRef = (double) cf / CORPUS_SIZE; // p(w|REF)\\r\\n\\t \\tdouble score = c1 * pDoc + c2 * pRef;\\r\\n\\t \\t\\r\\n\\t \\t// Get the RF probability of each token \\r\\n\\t \\tTokenRFScore.put(token, score); \\r\\n\\t });\\r\\n\\r\\n\\t\\treturn TokenRFScore;\\r\\n\\t}\",\n \"@Test\\n\\tpublic void testKeywordQuery(){\\n\\t\\t//manager.getResponse(\\\"american football \\\"); //match multiple keywords\\n//\\t\\tmanager.getResponse(\\\"list of Bond 007 movies\\\");\\n//\\tmanager.getResponse(\\\"Disney movies\\\");\\n\\t\\t//manager.keywordQuery(\\\"Paul Brown Stadium location\\\");\\n\\t\\t//manager.keywordQuery(\\\"0Francesco\\\");\\n System.out.println(\\\"******* keyword query *******\\\");\\n\\t\\t//manager.keywordQuery(\\\"sportspeople in tennis\\\");\\n\\t\\t//manager.keywordSearch(\\\"list of movies starring Sean Connery\\\",ElasticIndex.analyzed,100 );\\n//\\t\\tmanager.keywordSearch(\\\"movies starring Sean Connery\\\",ElasticIndex.notStemmed,100 );\\n// manager.keywordSearch(\\\"musical movies tony award\\\",ElasticIndex.analyzed,100 );\\n// manager.keywordSearch(\\\"movies directed by Woody Allen\\\",ElasticIndex.analyzed,100 );\\n// manager.keywordSearch(\\\"United states professional sports teams\\\",ElasticIndex.analyzed,100 );\\n// manager.keywordSearch(\\\"computer games developed by Ubisoft\\\",ElasticIndex.analyzed,100 );\\n// manager.keywordSearch(\\\"computer games developed by Ubisoft\\\",ElasticIndex.notStemmed,100 );\\n// manager.keywordSearch(\\\"movies academy award nominations\\\",ElasticIndex.notStemmed,100 );\\n System.out.println(SearchResultUtil.toSummary(manager.keywordSearch(\\\"movies directed by Woody Allen\\\",ElasticIndex.notLowercased,20 )));\\n //manager.keywordSearch(\\\"grammy best album in 2012\\\",ElasticIndex.notAnalyzed,100 );\\n //(better than analyzed) manager.keywordSearch(\\\"grammy best album in 2012\\\",ElasticIndex.notStemmed,100 );\\n System.out.println(\\\"*****************************\\\");\\n\\n\\t\\t//manager.keywordQuery(\\\"Disney movies\\\");\\n\\t}\",\n \"public static ArrayList<Result> findMatches(Query query, DataManager myVocab){\\n\\n\\t\\t//Uncomment this for logging in this class\\t\\n//\\t\\tmyLogger.setLevel(Level.INFO); \\n\\n\\t\\t// get the term we're going to search for and\\n\\t\\t// take out any leading or trailing whitespaces\\n\\t\\tString querystr = query.getQuery();\\n\\t\\tquerystr = querystr.trim();\\n\\t\\tString uncleaned = querystr;\\n\\t\\t\\n\\t\\t// This is in case of numeric entries. Google Refine doesn't seem\\n\\t\\t// to have int cell types, instead it adds an invisible .0 to all\\n\\t\\t// numbers. This fixes that issue, as it sometimes causes false negatives.\\n\\t\\tif (querystr.endsWith(\\\".0\\\")){\\n\\t\\t Pattern p = Pattern.compile(\\\"[^0-9\\\\\\\\.]+\\\");\\n\\t\\t Matcher m = p.matcher(querystr);\\n\\t\\t boolean result = m.find();\\n\\t\\t if (!result){\\n\\t\\t \\t querystr = querystr.substring(0, querystr.length()-2);\\n\\t\\t }\\n\\t\\t}\\n\\t\\t// see if it's in the synonyms map, if it is\\n\\t\\t// replace it with the appropriate term, if it's\\n\\t\\t// not, don't do anything. \\n\\n\\t\\tif (myVocab.subMap.get(querystr)!=null){\\n\\t\\t\\tquerystr = myVocab.subMap.get(querystr);\\n\\t\\t\\tquery.setQuery(querystr);\\n\\t\\t}\\n\\t\\t\\n\\t\\t// Clean up the query string if it isn't case/punctuation sensitive\\n\\t\\tif (!myVocab.capsSensitive()){\\t\\t\\n\\t\\t\\tquerystr = querystr.toLowerCase();\\n\\t\\t}\\n\\t\\tif (! myVocab.punctSensitive()){\\t\\t\\n\\t\\t\\tquerystr = querystr.replaceAll(\\\"[\\\\\\\\W_]\\\", \\\"\\\");\\n\\t\\t}\\n\\t\\t\\n\\t\\t// see if it's in the synonyms map, if it is\\n\\t\\t// replace it with the appropriate term, if it's\\n\\t\\t// not, don't do anything. \\n\\t\\tif(myVocab.subMap.get(querystr)!=null){\\n\\t\\t\\tquerystr = myVocab.subMap.get(querystr);\\n\\t\\t\\tquery.setQuery(querystr);\\n\\t\\t}\\n\\n\\t\\tString type = query.getType();\\n\\n\\t\\t// This ArrayList is the results that are going to be returned. \\n\\t\\tArrayList<Result> results = getDirectMatches(myVocab, querystr, uncleaned, type);\\n\\t\\t\\n\\t\\t// If there's a perfect match return it.\\n\\t\\tif (results.size() == 1 && results.get(0).match){\\n\\t\\t\\treturn results;\\n\\t\\t}else{\\n\\t\\t\\t// Otherwise, add the initial ones and try matching\\n\\t\\t\\t// based on distance to vocabulary terms.\\n\\t\\t\\tresults.addAll(distanceMatching(query, myVocab));\\n\\t\\t\\t\\n\\t\\t\\t// Split the original query term by space and non-alphanumeric characters \\n\\t\\t\\t// to find how many words there are.\\n\\t\\t\\t//querystr = query.getQuery().replaceAll(\\\"[\\\\\\\\W_]\\\", \\\" \\\");\\n\\t\\t\\tString [] termList = querystr.split(\\\" \\\");\\n\\t\\t\\t\\n\\t\\t\\t// if there's more than one, run bagOfWords\\n\\t\\t\\t// which tries to find a match for each of the words.\\n\\t\\t\\tif (termList.length > 1){\\n\\t\\t\\t\\tresults.addAll(bagOfWords(query, myVocab));\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\t\\n\\t\\t// Clean the results: no duplicates\\n\\t\\t// no extra results to return, and sorted\\n\\t\\t// them by score before returning them\\n\\t\\tresults = removeDuplicates(results);\\n\\t\\t\\n\\t\\t// They do not need to be reduced in \\n\\t\\t// number if there are fewer than \\n\\t\\t// the max results.\\n\\t\\t// The pruneResults sorts them\\n\\t\\t// by score already.\\n\\t\\tif(query.getLimit()!=null){\\n\\t\\t\\tresults = pruneResults(results,Integer.parseInt(query.getLimit()));\\n\\t\\t}else{\\n\\t\\t\\tresults = pruneResults(results,MAX_RESULTS);\\n\\t\\t}\\n\\t\\t\\t\\n\\t\\tresults = sortByScore(results);\\n\\t\\tfor (int i = 0; i< results.size(); i++){\\n//\\t\\t\\tmyLogger.log(Level.SEVERE,results.get(i).getScore()+ \\\" is bigger than 100?\\\");\\n\\t\\t\\tif(results.get(i).getScore() > (double)100){\\n\\t\\t\\t\\tresults.get(i).setScore((double)100 - (results.get(i).getScore()-(double)100));\\n//\\t\\t\\t\\tmyLogger.log(Level.SEVERE,results.get(i).getScore()+\\\" is bigger than 100! and was set to \\\"+\\n//\\t\\t\\t\\t\\t\\t((double)100 - (results.get(i).getScore()-(double)100)));\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\treturn results;\\n\\t}\",\n \"protected HashMap<String,Double> rank(ArrayList<String> queryPostingLines, ArrayList<String> query){\\n HashMap<String,HashMap<String,Integer>> queryWordsTFPerDoc = computeTFForQueryWords(queryPostingLines);\\n ArrayList<String> retrievedDocuments = new ArrayList<>(queryWordsTFPerDoc.keySet());\\n HashMap<String,Double> rankedDocs = new HashMap<>();\\n\\n for(String doc : retrievedDocuments){\\n HashMap<String,Integer> docTFs = queryWordsTFPerDoc.get(doc);\\n double rank = 0.3*rankByBM25(query,doc,docTFs) + 0.7*rankByPosition(query,doc,queryPostingLines);// - rankByCosSim(query,doc,docTFs);\\n rankedDocs.put(doc,rank);\\n }\\n rankedDocs = sortByValue(rankedDocs);\\n ArrayList<String> docsAfterSort = new ArrayList<>(rankedDocs.keySet());\\n HashMap<String,Double> docsToRetrieve = new HashMap<>();\\n int i=0;\\n for(String doc: docsAfterSort){\\n docsToRetrieve.put(documentDetails.get(doc)[0],rankedDocs.get(doc));\\n i++;\\n if(i == 50)\\n break;\\n }\\n return docsToRetrieve;\\n }\",\n \"public void relevanceFeedback(PostingsList results, boolean[] docIsRelevant, Indexer indexer ) {\\r\\n// results contain the ranked list from the current search\\r\\n// docIsRelevant contains the users feedback on which of the 10 first hits are relevant\\r\\n\\tdouble gamma = 0.0; // används ej, de orelevanta dokumenterna. städa upp queryn. Vad innehller de orelevanta dokumenterna för termer\\r\\n// dess termer tar vi bort från den relebanta.)\\r\\n\\r\\n\\tdouble alfa = 0.8; // hur mycket litar på det gamla sökning innan feedback\\r\\n\\tdouble beta = 0.6; // hur mycket hänsyn du ska ta till nya sökningen efter feedback \\r\\n\\r\\n\\r\\n\\t/* \\r\\n\\r\\n\\tAlgorithm: \\r\\n\\tThe Rocchio algorithm is based on a method of relevance \\r\\n\\tfeedback found in information retrieval systems\\r\\n\\tThe algorithm is based on the assumption that most users \\r\\n\\thave a general conception of which documents should be denoted \\r\\n\\tas relevant or non-relevant.[1] Therefore, the user's search \\r\\n\\tquery is revised to include an arbitrary percentage of relevant \\r\\n\\tand non-relevant documents as a means of increasing the search \\r\\n\\tengine's recall, and possibly the precision as well. The number \\r\\n\\tof relevant and non-relevant documents allowed to enter a query \\r\\n\\tis dictated by the weights of the a, b.\\r\\n\\tthe associated weights (a, b) are responsible for shaping the \\r\\n\\tmodified vector in a direction closer, or farther away, from the \\r\\n\\toriginal query, related documents, and non-related documents.\\r\\n\\r\\n\\r\\n\\r\\n\\tLimitations of rocchio:\\r\\n\\t\\tTherefore the two queries of \\\"Burma\\\" and \\\"Myanmar\\\" will \\r\\n\\t\\tappear much farther apart in the vector space model, \\r\\n\\t\\tthough they both contain similar origins\\r\\n\\tWhy not use non-relevant documents:\\r\\n\\t\\tThough there are benefits to ranking documents as not-relevant, \\r\\n\\t\\ta relevant document ranking will result in more precise documents \\r\\n\\t\\tbeing made available to the user. \\r\\n\\t\\r\\n\\r\\n\\r\\n\\tRoccio algoritmen: \\r\\n\\t\\talfa = Original query weight \\r\\n\\t\\tbeta = related document weight\\r\\n\\t\\t\\r\\n\\t\\thigher alpha means that we give more focus to the original query terms\\r\\n\\t\\thigher beta means that we give more focus to the new search feedback. i.e new terms.\\r\\n\\r\\n\\t\\tTar en org query\\r\\n\\t\\tTar den gamla gånnger en viss vikt \\r\\n\\t\\tvikt är alfa + beta (entill vektor) plus att den kollar på original vektor, q0 \\r\\n\\t\\t\\thögre alfa mer fokus på original queryn \\r\\n\\t\\t\\thögra beta skiftar till mer fokus på de nya termerna. \\r\\n\\t\\tdvs utökas med ord/termer från dokument vektorerna som var relevanta. \\r\\n\\r\\n\\tVanligtvis har man väldigt häg alfa och beta lite under för att det är standard. man tycker att den \\r\\n\\tförsta queryn är väldigt bra.\\r\\n\\r\\n\\t\\r\\n\\t*/\\r\\n\\r\\n\\tPostingsList related_doc_vector = new PostingsList();\\r\\n\\tHashMap<String, Double> qm = new HashMap<String, Double>(); // spara termer och weights.\\r\\n\\t// normalize weights\\r\\n\\tfor(Double w : weights){\\r\\n\\t\\tw = w/weights.size();\\r\\n\\t}\\r\\n\\r\\n\\tIterator<PostingsEntry> it = results.iterator();\\r\\n\\tfor(int i = 0; i < docIsRelevant.length; i++){\\r\\n\\t\\tif(docIsRelevant[i] == true){\\r\\n\\t\\t\\trelated_doc_vector.list.add(results.get(i));\\r\\n\\t\\t} \\r\\n\\t}\\r\\n\\r\\n\\t// apply Rocchio algorithm.\\r\\n\\tfor(int i = 0; i < terms.size(); i++){\\r\\n\\t\\tdouble new_weigt = weights.get(i) * alfa;\\r\\n\\t\\tqm.put(terms.get(i), new_weigt);\\r\\n\\t}\\r\\n\\r\\n\\tfor(int i = 0; i < related_doc_vector.size(); i++){\\r\\n\\t\\tIterator<PostingsEntry> ite = related_doc_vector.iterator();\\r\\n\\t\\twhile(ite.hasNext()){\\r\\n\\t\\t\\tPostingsEntry postingsentry = ite.next();\\r\\n\\t\\t\\tint docID = postingsentry.docID;\\r\\n\\t\\t\\tString filename = indexer.index.docIDs.get(Integer.toString(docID)); // hämtar filnamnet\\r\\n\\t\\t\\tString path = \\\"/Users/monadadoun/Desktop/ir/lab/davisWiki/\\\" + filename; \\r\\n\\t\\t\\tFile file = new File(path);\\r\\n\\t\\t\\tHashSet<String> hs = new HashSet<>();\\r\\n\\t\\t\\t// lägger till alla ord som finns till mitt hashet\\r\\n\\t\\t\\ttry (Reader reader = new InputStreamReader( new FileInputStream(file), StandardCharsets.UTF_8 )){\\r\\n\\t\\t\\t\\tTokenizer tok = new Tokenizer( reader, true, false, true, indexer.patterns_file );\\r\\n\\t\\t\\t\\twhile (tok.hasMoreTokens()) {\\r\\n\\t\\t\\t\\t\\ths.add(tok.nextToken());\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t} catch (IOException e) {\\r\\n\\t\\t\\t\\te.printStackTrace();\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\t\\r\\n\\t\\t\\tIterator<String> iter = hs.iterator();\\r\\n\\t\\t\\twhile(iter.hasNext()){\\r\\n\\t\\t\\t\\tString s = iter.next();\\r\\n\\t\\t\\t\\tif(qm.containsKey(s)){\\r\\n\\t\\t\\t\\t\\tDouble tmp = qm.get(s);\\r\\n\\t\\t\\t\\t\\tqm.put(s, tmp + beta * postingsentry.score);\\r\\n\\t\\t\\t\\t} else {\\r\\n\\t\\t\\t\\t\\tqm.put(s, beta * postingsentry.score);\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t}\\r\\n\\t\\t}\\r\\n\\t}\\r\\n\\tLinkedList<String> term = new LinkedList<>();\\r\\n\\tLinkedList<Double> weight = new LinkedList<>();\\r\\n\\tList<Map.Entry<String,Double>> answer = new ArrayList<Map.Entry<String,Double>>(qm.entrySet());\\r\\n\\tanswer.sort((e1,e2) -> e2.getValue().compareTo(e1.getValue())); // sorterar efter värde så att orden med högst score ligger först\\r\\n\\tfor (int i = 0; i < answer.size(); i++) {\\r\\n\\t\\tterm.add(answer.get(i).getKey());\\r\\n\\t\\tweight.add(answer.get(i).getValue()/answer.size());\\r\\n\\t}\\r\\n\\r\\n\\tterms = term;\\r\\n\\tweights = weight;\\r\\n\\t}\",\n \"public List<Document> retrieveQuery( Query aQuery, int TopN ) throws IOException {\\n\\t\\t// NT: you will find our IndexingLucene.Myindexreader provides method: docLength()\\n\\t\\t// implement your retrieval model here, and for each input query, return the topN retrieved documents\\n\\t\\t// sort the documents based on their relevance score, from high to low\\n\\n\\t\\tHashMap<Integer, HashMap<String,Integer>> idTokenDocFrequencyMap = new HashMap<>();\\t//docid - (token - document frequency) map\\n\\t\\tHashMap<String, Long> tokenColFrequencyMap = new HashMap<>();\\t// token - collection frequency map\\n\\t\\tString content = aQuery.GetQueryContent();\\n\\t\\tString[] tokens = content.split(\\\" \\\");\\n\\n\\t\\tfor(String token : tokens){\\n\\t\\t\\ttokenColFrequencyMap.put(token, indexReader.CollectionFreq(token)); \\t// update the second map\\n\\t\\t\\tint [][]postingList = indexReader.getPostingList(token);\\n\\t\\t\\tif(postingList == null) continue;\\n\\t\\t\\tfor(int i = 0; i < postingList.length; i++){\\n\\t\\t\\t\\tint docid = postingList[i][0];\\n\\t\\t\\t\\tint freq = postingList[i][1];\\n\\t\\t\\t\\tif(idTokenDocFrequencyMap.containsKey(docid)){\\t\\t// update the first map\\n\\t\\t\\t\\t\\tidTokenDocFrequencyMap.get(docid).put(token,freq);\\n\\t\\t\\t\\t}else {\\n\\t\\t\\t\\t\\tHashMap<String,Integer> tokenFrequencyMap = new HashMap<>();\\n\\t\\t\\t\\t\\ttokenFrequencyMap.put(token,freq);\\n\\t\\t\\t\\t\\tidTokenDocFrequencyMap.put(docid,tokenFrequencyMap);\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\tdouble U = 2000.0;\\n\\t\\tList<Document> documentList = new ArrayList<>();\\n\\t\\t// if use a docidList, it will have some duplicates.\\n\\t\\tfor(Map.Entry<Integer, HashMap<String,Integer>> entry : idTokenDocFrequencyMap.entrySet()){\\n\\t\\t\\tdouble score = 1.0;\\t\\t\\t// each document have one score\\n\\t\\t\\tint docid = entry.getKey();\\n\\t\\t\\tint docLen = indexReader.docLength(docid);\\t// get document length\\n\\t\\t\\tHashMap<String,Integer> tokenDocFrequencyMap = idTokenDocFrequencyMap.get(docid);\\n\\t\\t\\tfor(String token : tokens){\\t\\t// for each token, not the token just exist in the document\\n\\t\\t\\t\\tlong colFreq = tokenColFrequencyMap.getOrDefault(token,0l);\\t// get collection frequency\\n\\t\\t\\t\\tif(colFreq != 0){\\n\\t\\t\\t\\t\\tint docFreq = 0;\\t// if this document don't have token, just set document frequency as 0\\n\\t\\t\\t\\t\\tif(tokenDocFrequencyMap.containsKey(token)){\\n\\t\\t\\t\\t\\t\\tdocFreq = tokenDocFrequencyMap.get(token);\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\tscore = score * (docFreq + U * ((double)colFreq / colLen)) / (docLen + U);\\t//equation\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t\\tDocument document = new Document(docid+\\\"\\\", indexReader.getDocno(docid),score);\\n\\t\\t\\tdocumentList.add(document);\\n\\t\\t}\\n\\n\\t\\tCollections.sort(documentList, new Comparator<Document>() {\\n\\t\\t\\t@Override\\n\\t\\t\\tpublic int compare(Document o1, Document o2) {\\n\\t\\t\\t\\treturn Double.compare(o2.score(),o1.score());\\n\\t\\t\\t}\\n\\t\\t});\\n\\t\\tList<Document> res = new ArrayList<>();\\n\\t\\tfor(int i = 0 ; i < TopN; i++){\\n\\t\\t\\tres.add(documentList.get(i));\\n\\t\\t}\\n\\t\\treturn res;\\n\\t}\",\n \"private static Query computeBooleanQueryNP(String textQuery){\\n\\t\\tBooleanQuery query = new BooleanQuery();\\n\\n\\t\\tHmmDecoder mPosTagger = null;\\n\\t\\tTokenizerFactory mTokenizerFactory = null;\\n\\t\\tPhraseChunker pChunker = new PhraseChunker(mPosTagger,mTokenizerFactory);\\n\\t\\tArrayList<String> pchuncker = new ArrayList<String>();\\n\\n\\t\\tpchuncker = pChunker.getCHunkNounPhrases(textQuery.toLowerCase());\\n\\n\\t\\tfor (int k = 0; k<= pchuncker.size()-1;k++ ){\\n\\t\\t\\tString wordInList = ((String) pchuncker.get(k));\\n\\t\\t\\twordInList = wordInList.toLowerCase().replaceAll(\\\"-\\\",\\\" \\\");\\n\\t\\t\\tString [] wordInListSplit = wordInList.split(\\\" \\\");\\n\\t\\t\\tfor (String word: wordInListSplit){\\n\\n\\t\\t\\t\\tquery.add(new TermQuery(new Term(\\\"content\\\", word)), Occur.SHOULD );\\n\\t\\t\\t}\\n\\n\\t\\t}\\n\\n\\t\\t/* String[] tQuery = textQuery.split(\\\" \\\");\\n\\t\\t for(String s: tQuery )\\n\\t\\t\\t query.add(new TermQuery(new Term(\\\"text\\\", s)), Occur.SHOULD);*/\\n\\n\\t\\treturn query;\\n\\t}\",\n \"private static ArrayList<Result> bagOfWords(Query query, DataManager myVocab) {\\n\\t\\tString queryname = query.getQuery();\\n\\t\\t// split on space and punctuation\\n\\t\\tString[] termList = queryname.split(\\\" \\\");\\n\\t\\tArrayList<Result> bagResults = new ArrayList<Result>();\\n\\t\\tfor (int i=0; i<termList.length; i++){\\n\\t\\t\\tQuery newQuery = new Query(termList[i], query.getLimit(), query.getType(), query.getTypeStrict(), query.properties()) ;\\n\\t\\t\\tArrayList<Result> tempResults = new ArrayList<Result>(findMatches(newQuery, myVocab));\\n\\t\\t\\tfor(int j=0; j<tempResults.size(); j++){\\n\\n\\t\\t\\t\\ttempResults.get(j).setMatch(false);\\n\\t\\t\\t\\ttempResults.get(j).decreaseScore(termList.length);\\n\\t\\t\\t\\tif(tempResults.get(j).getScore()>100){\\n\\t\\t\\t\\t\\ttempResults.get(j).setScore(99.0);\\n\\t\\t\\t\\t}else if (tempResults.get(j).getScore()<1){\\n\\t\\t\\t\\t\\ttempResults.get(j).setScore(tempResults.get(j).getScore()*10);\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t\\tbagResults.addAll(tempResults);\\n\\t\\t}\\n\\t\\treturn bagResults;\\n\\t}\",\n \"public double getTfIdf(){ return tf_idf; }\",\n \"public void updateUnseenTermInThisQuery(int relevanceFeedbackMethod) {\\n System.out.println(\\\"Nomor Query Lama : \\\" + listDocumentRetrievedForThisQuery.getQuery().getIndex());\\n System.out.println(\\\"Isi Query Lama : \\\" + listDocumentRetrievedForThisQuery.getQuery().getQueryContent());\\n int thisQueryIndex = listDocumentRetrievedForThisQuery.getQuery().getIndex();\\n for (Map.Entry m : invertedFile.getListTermWeights().entrySet()) {\\n String keyTerm = (String) m.getKey();\\n if (!isTermAppearInQuery(keyTerm)) {\\n double newWeight = computeNewWeightTerm(relevanceFeedbackMethod,keyTerm,0.0);\\n if (newWeight > 0) {\\n String filteredWord = \\\"\\\";\\n if (invertedFile.isStemmingApplied()) {\\n filteredWord = invertedFile.getMappingStemmedTermToNormalTerm().get(keyTerm);\\n } else {\\n filteredWord = keyTerm;\\n }\\n newQueryComposition.put(filteredWord,newWeight);\\n invertedFileQuery.insertRowTable(keyTerm,thisQueryIndex,newWeight);\\n normalFileQuery.insertElement(thisQueryIndex,keyTerm);\\n }\\n }\\n }\\n System.out.println(\\\"Nomor Query Baru : \\\" + convertNewQueryComposition().getIndex());\\n System.out.println(\\\"Isi Query Baru : \\\" + convertNewQueryComposition().getQueryContent());\\n }\",\n \"@Test\\n public void testCombineRankZeroPageRankWeight() {\\n Iterator<Pair<Document, Double>> resultIterator = icsSearchEngine.searchQuery(Arrays.asList(\\\"anteater\\\"),\\n 100, 0.0);\\n ImmutableList<Pair<Document, Double>> resultListCombined = ImmutableList.copyOf(resultIterator);\\n\\n Iterator<Pair<Document, Double>> resultIteratorTfIdf = invertedIndexManager.searchTfIdf(Arrays.asList(\\\"anteater\\\"), 100);\\n ImmutableList<Pair<Document, Double>> resultListTfIdf = ImmutableList.copyOf(resultIteratorTfIdf);\\n\\n Assert.assertEquals(resultListTfIdf, resultListCombined);\\n }\",\n \"private Node estimateRelevance(Node original) throws Exception {\\n Node combineNode = new Node(\\\"combine\\\", new NodeParameters(), original.getInternalNodes(), original.getPosition());\\n\\n // Only get as many as we need\\n Parameters localParameters = retrieval.getGlobalParameters().clone();\\n int fbDocs = (int) retrieval.getGlobalParameters().get(\\\"fbDocs\\\", 10);\\n localParameters.set(\\\"requested\\\", fbDocs);\\n\\n // transform and run\\n Node transformedCombineNode = retrieval.transformQuery(combineNode, localParameters);\\n List<ScoredDocument> initialResults = retrieval.executeQuery(transformedCombineNode, localParameters).scoredDocuments;\\n \\n // Gather content\\n ArrayList<String> names = new ArrayList<String>();\\n for (ScoredDocument sd : initialResults) {\\n names.add(sd.documentName);\\n }\\n List<Document> docs = getDocuments(names);\\n\\n // Now the maps from the different information sources\\n // Each of these is a term -> field -> score double-mapping\\n HashMap<String, TObjectDoubleHashMap<String>> uCFSs = null;\\n double ucfw = p.get(\\\"ucfw\\\", 1.0);\\n if (ucfw != 0.0) {\\n uCFSs = getUnigramCollFieldScores();\\n }\\n\\n HashMap<String, TObjectDoubleHashMap<String>> bCFSs = null;\\n double bcfw = p.get(\\\"bcfw\\\", 1.0);\\n if (bcfw != 0.0) {\\n bCFSs = getBigramCollFieldScores();\\n }\\n\\n HashMap<String, TObjectDoubleHashMap<String>> uPRFSs = null;\\n double uprfw = p.get(\\\"uprfw\\\", 1.0);\\n if (uprfw != 0.0) {\\n uPRFSs = getUnigramPRFScores(docs);\\n }\\n\\n HashMap<String, TObjectDoubleHashMap<String>> bPRFSs = null;\\n double bprfw = p.get(\\\"bprfw\\\", 1.0);\\n if (bprfw != 0.0) {\\n bPRFSs = getBigramPRFScores(docs);\\n }\\n\\n // We can now construct term-field weights using our supplied lambdas\\n // and scores\\n Node termNodes = new Node(\\\"combine\\\", new NodeParameters(), new ArrayList<Node>(), 0);\\n termNodes.getNodeParameters().set(\\\"norm\\\", false);\\n TObjectDoubleHashMap<String> weights = new TObjectDoubleHashMap<String>();\\n for (String term : queryTerms) {\\n weights.clear();\\n for (String field : fields) {\\n double sum = 0.0;\\n if (uCFSs != null) {\\n sum += (ucfw * uCFSs.get(term).get(field));\\n }\\n\\n if (bCFSs != null) {\\n TObjectDoubleHashMap<String> termMap = bCFSs.get(term);\\n if (termMap != null) {\\n sum += (bcfw * termMap.get(field));\\n }\\n }\\n\\n if (uPRFSs != null) {\\n sum += (uprfw * uPRFSs.get(term).get(field));\\n }\\n\\n if (bPRFSs != null) {\\n TObjectDoubleHashMap<String> termMap = bPRFSs.get(term);\\n if (termMap != null) {\\n sum += (bprfw * termMap.get(field));\\n }\\n }\\n weights.put(field, sum);\\n }\\n termNodes.addChild(createTermFieldNodes(term, weights));\\n }\\n return termNodes;\\n }\",\n \"public static String tfidf(String str) throws Exception{\\n\\t\\tIndexReader r = IndexReader.open(FSDirectory.open(new File(\\\"index\\\")));\\r\\n\\r\\n\\t\\t// this code takes care of calculating idf for each term\\r\\n\\r\\n\\t\\tHashMap<String, Double> idf_map = new HashMap<String, Double>();\\r\\n\\t\\tTermEnum t = r.terms();\\r\\n\\t\\tdouble docs_count = r.maxDoc();\\r\\n\\t\\twhile (t.next()) {\\r\\n\\t\\t\\tTerm te = new Term(\\\"contents\\\", t.term().text());\\r\\n\\t\\t\\tdouble idf = Math.log(docs_count / r.docFreq(te));\\r\\n\\t\\t\\tidf_map.put(t.term().text(), idf);\\r\\n\\t\\t}\\r\\n\\r\\n\\t\\t// This code is a test stub to get the term with lowest IDF value\\r\\n\\r\\n\\t\\t/*\\r\\n\\t\\t * double minVal = Collections.min(idf_map.values()); for(Entry<String,\\r\\n\\t\\t * Double> entry:idf_map.entrySet()){ if(entry.getValue() == minVal){\\r\\n\\t\\t * System.out.println(\\\"Term with lowest idf is: \\\"+entry.getKey()); } }\\r\\n\\t\\t */\\r\\n\\r\\n\\t\\tlong t1, t2;\\r\\n\\t\\tlong start = System.currentTimeMillis();\\r\\n\\r\\n\\t\\t// code to get |d| for every document\\r\\n\\r\\n\\t\\tHashMap<Integer, HashMap<String, Integer>> hmap = new HashMap<Integer, HashMap<String, Integer>>();\\r\\n\\t\\tTermEnum trm = r.terms();\\r\\n\\t\\twhile (trm.next()) {\\r\\n\\t\\t\\tTerm te1 = new Term(\\\"contents\\\", trm.term().text());\\r\\n\\t\\t\\tTermDocs td1 = r.termDocs(te1);\\r\\n\\r\\n\\t\\t\\twhile (td1.next()) {\\r\\n\\t\\t\\t\\tHashMap<String, Integer> a1 = hmap.get(td1.doc());\\r\\n\\t\\t\\t\\tif (a1 == null) {\\r\\n\\t\\t\\t\\t\\ta1 = new HashMap<String, Integer>();\\r\\n\\t\\t\\t\\t\\ta1.put(trm.term().text(), td1.freq());\\r\\n\\t\\t\\t\\t\\thmap.put(td1.doc(), a1);\\r\\n\\t\\t\\t\\t} else {\\r\\n\\t\\t\\t\\t\\ta1.put(trm.term().text(), td1.freq());\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t}\\r\\n\\t\\t}\\r\\n\\r\\n\\t\\t// compute magnitude of each document vector and store it in array\\r\\n\\r\\n\\t\\tArrayList<Double> doc_magnitude = new ArrayList<Double>();\\r\\n\\t\\tHashMap<String, Integer> val = new HashMap<String, Integer>();\\r\\n\\t\\tSet<Entry<Integer, HashMap<String, Integer>>> entrySet = hmap.entrySet();\\r\\n\\r\\n\\t\\tjava.util.Iterator<Entry<Integer, HashMap<String, Integer>>> it = entrySet.iterator();\\r\\n\\t\\twhile (it.hasNext()) { // foreach document id\\r\\n\\t\\t\\tdouble square_sum = 0.0;\\r\\n\\t\\t\\tMap.Entry<Integer, HashMap<String, Integer>> me = (Entry<Integer, HashMap<String, Integer>>) it.next();\\r\\n\\t\\t\\tval = me.getValue();\\r\\n\\t\\t\\tSet<Map.Entry<String, Integer>> entry = val.entrySet();\\r\\n\\t\\t\\tjava.util.Iterator<Map.Entry<String, Integer>> iterator = entry.iterator();\\r\\n\\t\\t\\twhile (iterator.hasNext()) { // foreach term\\r\\n\\t\\t\\t\\tMap.Entry<String, Integer> mp = iterator.next();\\r\\n\\t\\t\\t\\tsquare_sum += mp.getValue() * mp.getValue();\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\tdouble root = Math.sqrt(square_sum);\\r\\n\\t\\t\\tdoc_magnitude.add(me.getKey(), root);\\r\\n\\t\\t}\\r\\n\\r\\n\\t\\t// long end = System.currentTimeMillis();\\r\\n\\t\\t// double diff = end - start;\\r\\n\\t\\t// System.out.println(\\\"Time taken to compute norms(in seconds): \\\" + diff\\r\\n\\t\\t// / 1000 + \\\"\\\\n\\\");\\r\\n\\r\\n\\t\\t// get the query and find similarity with the documents\\r\\n\\t\\tHashMap<Integer, Double> similarity_map = new HashMap<Integer, Double>();\\r\\n\\t\\tSet<Entry<Integer, HashMap<String, Integer>>> entrySet1 = hmap.entrySet();\\r\\n\\t\\tjava.util.Iterator<Entry<Integer, HashMap<String, Integer>>> it1 = entrySet1.iterator();\\r\\n\\t\\t\\r\\n\\t\\t\\r\\n\\t\\t\\r\\n\\t\\tHashMap<Integer, Double> dot_product_map = new HashMap<Integer, Double>();\\r\\n\\r\\n\\t\\t\\r\\n\\t\\t\\tdot_product_map.clear();\\r\\n\\t\\t\\tsimilarity_map.clear();\\r\\n\\r\\n\\t\\t\\tString[] terms = str.split(\\\"\\\\\\\\s+\\\");\\r\\n\\t\\t\\tint cnt = 0;\\r\\n\\r\\n\\t\\t\\tlong result_st = System.currentTimeMillis();\\r\\n\\t\\t\\tt1 = System.nanoTime();\\r\\n\\r\\n\\t\\t\\t// for each term get the documents containing the corresponding term\\r\\n\\t\\t\\tfor (String word : terms) // foreach term in query\\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\tTerm te = new Term(\\\"contents\\\", word);\\r\\n\\t\\t\\t\\tTermDocs tdocs = r.termDocs(te);\\r\\n\\t\\t\\t\\twhile (tdocs.next() /* && tdocs.doc() < number */) {\\r\\n\\t\\t\\t\\t\\t// Map.Entry<Integer, HashMap<String, Integer>> me =\\r\\n\\t\\t\\t\\t\\t// (Entry<Integer, HashMap<String, Integer>>) it1.next();\\r\\n\\t\\t\\t\\t\\tdouble freq = hmap.get(tdocs.doc()).get(word);\\r\\n\\t\\t\\t\\t\\tDouble temp = dot_product_map.get(tdocs.doc());\\r\\n\\t\\t\\t\\t\\tif (temp == null) {\\r\\n\\t\\t\\t\\t\\t\\tdot_product_map.put(tdocs.doc(), freq * idf_map.get(word));\\r\\n\\t\\t\\t\\t\\t} else {\\r\\n\\t\\t\\t\\t\\t\\tdot_product_map.put(tdocs.doc(), dot_product_map.get(tdocs.doc()) + freq * idf_map.get(word));\\r\\n\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\tcnt++;\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\tSet<Entry<Integer, Double>> se = dot_product_map.entrySet();\\r\\n\\t\\t\\tjava.util.Iterator<Entry<Integer, Double>> iter = se.iterator();\\r\\n\\t\\t\\twhile (iter.hasNext()) {\\r\\n\\t\\t\\t\\tMap.Entry<Integer, Double> me = (Entry<Integer, Double>) iter.next();\\r\\n\\t\\t\\t\\tsimilarity_map.put(me.getKey(), me.getValue() / (Math.sqrt(cnt) * doc_magnitude.get(me.getKey())));\\r\\n\\t\\t\\t}\\r\\n\\r\\n\\t\\t\\t// Normalize the map\\r\\n\\t\\t\\tdouble sum = 0;\\r\\n\\t\\t\\tfor (int i : similarity_map.keySet()) {\\r\\n\\t\\t\\t\\tsum += similarity_map.get(i);\\r\\n\\t\\t\\t}\\r\\n\\r\\n\\t\\t\\tfor (int i : similarity_map.keySet()) {\\r\\n\\t\\t\\t\\tdouble temp = similarity_map.get(i) / sum;\\r\\n\\t\\t\\t\\tsimilarity_map.put(i, temp);\\r\\n\\t\\t\\t}\\r\\n\\r\\n\\t\\t\\tString result=\\\"\\\";\\r\\n\\r\\n\\t\\t\\tList<Integer> l1 = new ArrayList<Integer>();\\r\\n\\t\\t\\tHashMap<Integer, Double> sim_map = sortMap(similarity_map, r);\\r\\n\\t\\t\\tfor(Integer i:sim_map.keySet()){\\r\\n\\t\\t\\t\\tl1.add(i);\\r\\n\\t\\t\\t\\tDocument d1 = r.document(i);\\r\\n\\t\\t\\t\\tString url = d1.getFieldable(\\\"path\\\").stringValue();\\r\\n\\t\\t\\t\\t//String snippet = getSnippet(hmap.get(i));\\r\\n\\t\\t\\t\\turl = url.replace(\\\"%%\\\", \\\"/\\\");\\r\\n\\t\\t\\t\\tString snippet = Snippet.getContent(url,terms[0]); //read the content of url\\r\\n\\t\\t\\t\\tresult +=/*i+\\\" \\\"+*/url+\\\"\\\\n\\\";\\r\\n\\t\\t\\t\\tresult +=snippet+\\\"\\\\n\\\\n\\\\n\\\";\\r\\n\\t\\t\\t\\t//result += snippet+\\\"\\\\n\\\\n\\\";\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\treturn result;\\r\\n\\t\\t\\t\\r\\n}\",\n \"public void analyzequery(JSONObject json) {\\n\\t\\ttry {\\n\\t\\t\\t\\n\\t\\t\\tJSONArray jarray = json.getJSONArray(\\\"Reviews\\\");\\n\\t\\t\\t\\n\\t\\t\\tfor (int i = 0; i < jarray.length(); i++) {\\n\\t\\t\\t\\t\\n\\t\\t\\t\\tPost review = new Post(jarray.getJSONObject(i));\\n\\t\\t\\t\\tSystem.out.println(\\\"55\\\");\\n\\t\\t\\t\\tString content = review.getContent();\\n\\t\\t\\t\\t\\n\\t\\t\\t\\t\\n\\t\\t\\t\\t\\n\\n\\t\\t\\t\\tHashMap<String, Integer> querytf = new HashMap<String, Integer>();\\n\\n\\t\\t\\t\\tHashSet<String> biminiset = new HashSet<String>();\\n\\n\\t\\t\\t\\tArrayList uniquery = new ArrayList();\\n\\n\\t\\t\\t\\tfor (String token : tokenizer.tokenize(content)) {\\n\\t\\t\\t\\t\\tif (m_stopwords.contains(token))\\n\\t\\t\\t\\t\\t\\tcontinue;\\n\\t\\t\\t\\t\\tif (token.isEmpty())\\n\\t\\t\\t\\t\\t\\tcontinue;\\n\\n\\t\\t\\t\\t\\tuniquery.add(PorterStemmingDemo(SnowballStemmingDemo(NormalizationDemo(token))));\\n\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\tfor (int k = 0; k < uniquery.size(); k++) {\\n\\n\\t\\t\\t\\t\\tif (querytf.containsKey(uniquery.get(i).toString())) {\\n\\t\\t\\t\\t\\t\\tquerytf.put(uniquery.get(i).toString(),\\n\\t\\t\\t\\t\\t\\t\\t\\tquerytf.get(uniquery.get(i).toString()) + 1);\\n\\t\\t\\t\\t\\t} else {\\n\\t\\t\\t\\t\\t\\tquerytf.put(uniquery.get(i).toString(), 1);\\n\\t\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\tArrayList<String> N_gram = new ArrayList<String>();\\n\\n\\t\\t\\t\\tfor (String token : tokenizer.tokenize(content)) {\\n\\n\\t\\t\\t\\t\\ttoken = PorterStemmingDemo(SnowballStemmingDemo(NormalizationDemo(token)));\\n\\t\\t\\t\\t\\tif (token.isEmpty()) {\\n\\n\\t\\t\\t\\t\\t\\tcontinue;\\n\\t\\t\\t\\t\\t} else {\\n\\n\\t\\t\\t\\t\\t\\tN_gram.add(token);\\n\\t\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\tString[] fine = new String[N_gram.size()];\\n\\n\\t\\t\\t\\tfor (int p = 0; p < N_gram.size() - 1; p++) {\\n\\t\\t\\t\\t\\tif (m_stopwords.contains(N_gram.get(p)))\\n\\t\\t\\t\\t\\t\\tcontinue;\\n\\t\\t\\t\\t\\tif (m_stopwords.contains(N_gram.get(p + 1)))\\n\\t\\t\\t\\t\\t\\tcontinue;\\n\\n\\t\\t\\t\\t\\tfine[p] = N_gram.get(p) + \\\"-\\\" + N_gram.get(p + 1);\\n\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\t\\n\\t\\t\\t\\tfor (String str2 : fine) {\\n\\n\\t\\t\\t\\t\\tif (querytf.containsKey(str2)) {\\n\\t\\t\\t\\t\\t\\tquerytf.put(str2, querytf.get(str2) + 1);\\n\\t\\t\\t\\t\\t} else {\\n\\t\\t\\t\\t\\t\\tquerytf.put(str2, 1);\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\tfor (String key : querytf.keySet()) {\\n\\t\\t\\t\\t\\tif (m_stats.containsKey(key)) {\\n\\t\\t\\t\\t\\t\\tdouble df = (double) m_stats.get(key);\\n\\n\\t\\t\\t\\t\\t\\tdouble idf = (1 + Math.log(102201 / df));\\n\\n\\t\\t\\t\\t\\t\\tdouble tf = querytf.get(key);\\n\\n\\t\\t\\t\\t\\t\\tdouble result = tf * idf;\\n\\n\\t\\t\\t\\t\\t\\tquery_idf.put(key, result);\\n\\t\\t\\t\\t\\t} else {\\n\\t\\t\\t\\t\\t\\tquery_idf.put(key, 0.0);\\n\\t\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\n\\t\\t\\t\\t\\n\\t\\t\\t}\\n\\t\\t\\t\\n\\t\\t\\t\\n\\t\\t}\\n\\t\\tcatch (JSONException e) {\\n\\t\\t\\te.printStackTrace();\\n\\t\\t}\\n\\t\\t\\n\\t\\t}\",\n \"public void ComputeSimilarity() {\\n\\t\\t\\n\\t\\t//first construct the vector space representations for these five reviews\\n\\t\\t// the our smaples vector, finally get the similarity metric \\n\\t\\tanalyzequery(LoadJson(\\\"./data/samples/query.json\\\"));\\n\\t\\n\\t\\t\\n\\t\\tHashMap<String, Double> Similarity = new HashMap<String, Double>();\\n\\n\\t\\tfor (int i = 0; i < m_reviews.size(); i++) {\\n\\t\\t\\tString content = m_reviews.get(i).getContent();\\n\\n\\t\\t\\tHashMap<String, Integer> conunttf = new HashMap<String, Integer>();\\n\\n\\t\\t\\tHashSet<String> biminiset = new HashSet<String>();\\n \\n\\t\\t\\t//danci means word unit: one or two words\\n\\t\\t\\tArrayList danci = new ArrayList();\\n\\n\\t\\t\\tfor (String token : tokenizer.tokenize(content)) {\\n\\t\\t\\t\\tif (m_stopwords.contains(token))\\n\\t\\t\\t\\t\\tcontinue;\\n\\t\\t\\t\\tif (token.isEmpty())\\n\\t\\t\\t\\t\\tcontinue;\\n\\n\\t\\t\\t\\tdanci.add(PorterStemmingDemo(SnowballStemmingDemo(NormalizationDemo(token))));\\n\\n\\t\\t\\t}\\n \\n\\t\\t\\t//get word count in a document\\n\\t\\t\\tfor (int k = 0; k < danci.size(); k++) {\\n\\n\\t\\t\\t\\tif (conunttf.containsKey(danci.get(k).toString())) {\\n\\t\\t\\t\\t\\tconunttf.put(danci.get(k).toString(),\\n\\t\\t\\t\\t\\t\\t\\tconunttf.get(danci.get(k).toString()) + 1);\\n\\t\\t\\t\\t} else {\\n\\t\\t\\t\\t\\tconunttf.put(danci.get(k).toString(), 1);\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t}\\n\\n\\t\\t\\tArrayList<String> N_gram = new ArrayList<String>();\\n\\n\\t\\t\\tfor (String token : tokenizer.tokenize(content)) {\\n\\n\\t\\t\\t\\ttoken = PorterStemmingDemo(SnowballStemmingDemo(NormalizationDemo(token)));\\n\\t\\t\\t\\tif (token.isEmpty()) {\\n\\n\\t\\t\\t\\t\\tcontinue;\\n\\t\\t\\t\\t} else {\\n\\n\\t\\t\\t\\t\\tN_gram.add(token);\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t}\\n\\n\\t\\t\\tString[] fine = new String[N_gram.size()];\\n \\n\\t\\t\\t//get rid of stopwords\\n\\t\\t\\tfor (int p = 0; p < N_gram.size() - 1; p++) {\\n\\t\\t\\t\\tif (m_stopwords.contains(N_gram.get(p)))\\n\\t\\t\\t\\t\\tcontinue;\\n\\t\\t\\t\\tif (m_stopwords.contains(N_gram.get(p + 1)))\\n\\t\\t\\t\\t\\tcontinue;\\n\\n\\t\\t\\t\\tfine[p] = N_gram.get(p) + \\\"-\\\" + N_gram.get(p + 1);\\n\\n\\t\\t\\t}\\n\\n\\t\\t\\t\\n\\t\\t\\tfor (String str2 : fine) {\\n\\n\\t\\t\\t\\tif (conunttf.containsKey(str2)) {\\n\\t\\t\\t\\t\\tconunttf.put(str2, conunttf.get(str2) + 1);\\n\\t\\t\\t\\t} else {\\n\\t\\t\\t\\t\\tconunttf.put(str2, 1);\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n \\n\\t\\t\\t//compute tf * idf for each document\\n\\t\\t\\tfor (String key : conunttf.keySet()) {\\n\\t\\t\\t\\tif (m_stats.containsKey(key)) {\\n\\t\\t\\t\\t\\tdouble df = (double) m_stats.get(key);\\n\\n\\t\\t\\t\\t\\tdouble idf = (1 + Math.log(102201 / df));\\n\\n\\t\\t\\t\\t\\tdouble tf = conunttf.get(key);\\n\\n\\t\\t\\t\\t\\tdouble result = tf * idf;\\n\\n\\t\\t\\t\\t\\tm_idf.put(key, result);\\n\\t\\t\\t\\t} else {\\n\\t\\t\\t\\t\\tm_idf.put(key, 0.0);\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t}\\n\\n\\t\\t\\t\\n\\n\\t\\t\\tHashMap<String, Double> query = new HashMap<String, Double>();\\n\\t\\t\\tHashMap<String, Double> test = new HashMap<String, Double>();\\n \\n\\t\\t\\t//If query contains this word, store it for future computation \\n\\t\\t\\tfor (Map.Entry<String, Double> entry : m_idf.entrySet()) {\\n\\t\\t\\t\\tString key = entry.getKey();\\n\\t\\t\\t\\tif (query_idf.containsKey(key)) {\\n\\t\\t\\t\\t\\tquery.put(key, query_idf.get(key));\\n\\t\\t\\t\\t\\ttest.put(key, m_idf.get(key));\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\n\\t\\t\\tdouble dotProduct = 0.00;\\n\\t\\t\\tdouble magnitude1 = 0.0;\\n\\t\\t\\tdouble magnitude2 = 0.0;\\n\\t\\t\\tdouble magnitude3 = 0.0;\\n\\t\\t\\tdouble magnitude4 = 0.0;\\n\\t\\t\\tdouble cosineSimilarity = 0;\\n \\n\\t\\t\\t\\n\\t\\t\\t//compute Compute similarity between query document and each document in file\\n\\t\\t\\tfor (String cal : test.keySet()) {\\n\\t\\t\\t\\tdotProduct += query.get(cal) * test.get(cal); // a.b\\n\\t\\t\\t\\tmagnitude1 += Math.pow(query.get(cal), 2); // (a^2)\\n\\t\\t\\t\\tmagnitude2 += Math.pow(test.get(cal), 2); // (b^2)\\n\\n\\t\\t\\t\\tmagnitude3 = Math.sqrt(magnitude1);// sqrt(a^2)\\n\\t\\t\\t\\tmagnitude4 = Math.sqrt(magnitude2);// sqrt(b^2)\\n\\t\\t\\t}\\n\\n\\t\\t\\tif (magnitude3 != 0.0 | magnitude4 != 0.0)\\n\\t\\t\\t\\tcosineSimilarity = dotProduct / (magnitude3 * magnitude4);\\n\\n\\t\\t\\telse\\n\\t\\t\\t\\tcosineSimilarity = 0;\\n\\n\\t\\t\\tSimilarity.put(content, cosineSimilarity);\\n\\n\\t\\t\\t\\t\\t\\n\\n\\t\\t}\\n\\n\\t\\t// sort output to get 3 reviews with the highest similarity with query review\\n\\t\\tList<Map.Entry<String, Double>> infoIds = new ArrayList<Map.Entry<String, Double>>(\\n\\t\\t\\t\\tSimilarity.entrySet());\\n\\n\\t\\tCollections.sort(infoIds, new Comparator<Map.Entry<String, Double>>() {\\n\\t\\t\\tpublic int compare(Map.Entry<String, Double> o1,\\n\\t\\t\\t\\t\\tMap.Entry<String, Double> o2) {\\n\\t\\t\\t\\treturn (int) (o1.getValue() - o2.getValue());\\n\\t\\t\\t}\\n\\t\\t});\\n\\n\\t\\tfor (int i = infoIds.size() - 1; i > infoIds.size() - 4; i--) {\\n\\t\\t\\tEntry<String, Double> ent = infoIds.get(i);\\n\\t\\t\\tSystem.out.println(ent.getValue()+\\\"++\\\"+ent.getKey()+\\\"\\\\n\\\");\\n\\n\\t\\t}\\n\\n\\t}\",\n \"private ScoreDoc[] searchExec (Query query) {\\n\\n ScoreDoc[] hits = null;\\n\\n try {\\n IndexReader reader = DirectoryReader.open(indexDir);\\n IndexSearcher searcher = new IndexSearcher(reader);\\n TopDocs docs = searcher.search(query, hitsPerPage, new Sort(SortField.FIELD_SCORE)); //search(query, docs);\\n hits = docs.scoreDocs;\\n } catch (IOException e) {\\n e.printStackTrace();\\n }\\n\\n return hits;\\n }\",\n \"private static String addQueryEntry(String query) throws IOException {\\n\\t\\t\\t\\t\\n\\t\\tString submittedQuery=null;\\n\\t\\tString queryParts[]=query.split(\\\"&\\\"); // get parameters from query\\t\\t\\n\\t\\tboolean isNextPage=false;\\n\\t\\tString key=null;\\n\\t\\tInteger value=null;\\n\\t\\tboolean docsProcessed=false; // identifies if 'docs' occurs more than once in the query\\t\\t\\n\\t\\tboolean termsProcessed=false; // identifies if 'terms' occurs more than once in the query\\n\\t\\t\\n\\t\\t// identify if it is a next page\\n\\t\\tfor (int i=0;i<queryParts.length;i++) { // verifies if it is a next page\\n\\t\\t\\tString queryPartsFields[]=queryParts[i].split(\\\"=\\\",2);\\t\\t\\t\\n\\t\\t\\tqueryPartsFields[0]=queryPartsFields[0].trim();\\n\\t\\t\\tif (queryPartsFields.length>1) {\\n\\t\\t\\t\\tqueryPartsFields[1]=queryPartsFields[1].trim();\\n\\t\\t\\t}\\n\\t\\t\\t\\n\\t\\t\\tif (queryPartsFields[0].equals(DOCS_KEY) && queryPartsFields.length>1 && !queryPartsFields[1].equals(\\\"\\\")) {\\t\\t\\t\\n\\t\\t\\t\\tint ipage;\\n\\t\\t\\t\\ttry {\\n\\t\\t\\t\\t\\tipage=Integer.parseInt(queryPartsFields[1]);\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\tcatch (NumberFormatException e) {\\n\\t\\t\\t\\t\\tipage=0;\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\n\\t\\t\\t\\tif (ipage!=0) { // regist only pages>0 \\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\tisNextPage=true;\\t\\t\\t\\n\\t\\t\\t\\t\\tif (ipage%RESULTS_PER_PAGE!=0) {\\n\\t\\t\\t\\t\\t\\tSystem.err.println(\\\"Page results not multiple of \\\"+RESULTS_PER_PAGE+\\\": \\\"+ipage);\\n\\t\\t\\t\\t\\t\\tipage+=ipage%RESULTS_PER_PAGE;\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\tif (!docsProcessed) {\\n\\t\\t\\t\\t\\t\\tint index=ipage/RESULTS_PER_PAGE>pagesViewedDistAux.length-1 ? pagesViewedDistAux.length-1 : ipage/RESULTS_PER_PAGE;\\t\\t\\t\\n\\t\\t\\t\\t\\t\\tif (index==0) { // sanity check\\n\\t\\t\\t\\t\\t\\t throw new IOException(\\\"Error of index=0 on a next page. ipage:\\\"+ipage);\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\tpagesViewedDistAux[index]++;\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\tdocsProcessed=true;\\t\\t\\t\\t\\n\\t\\t\\t\\t}\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t}\\n\\t\\t\\telse if (queryPartsFields[0].equals(QUERY_KEY)) {\\n\\t\\t\\t\\ttermsProcessed=true;\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\t// check wrong entries\\n\\t\\tif (docsProcessed && !termsProcessed) {\\n\\t\\t\\tSystem.err.println(\\\"Error of query with docs without terms: \\\"+query);\\n\\t\\t\\treturn null;\\n\\t\\t}\\t\\t\\t\\t\\n\\t\\tif (isNextPage) {\\n\\t\\t\\treturn null;\\n\\t\\t}\\n\\t\\t\\n\\t\\t// count only first page\\n\\t\\tdocsProcessed=false;\\n\\t\\tfor (int i=0;i<queryParts.length;i++) {\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\tString queryPartsFields[]=queryParts[i].split(\\\"=\\\",2);\\t\\t\\t\\n\\t\\t\\tqueryPartsFields[0]=queryPartsFields[0].trim();\\n\\t\\t\\t\\n\\t\\t\\tif (!queryPartsFields[0].equals(QUERY_KEY) || queryPartsFields.length!=2) {\\n\\t\\t\\t\\tcontinue;\\n\\t\\t\\t}\\n\\t\\t\\t\\n\\t\\t\\t// normalize query\\t\\t\\t\\n\\t\\t\\ttry {\\n\\t\\t\\t\\tqueryPartsFields[1]=decodeStrings(decodeNCR(java.net.URLDecoder.decode(queryPartsFields[1],\\\"ISO8859-1\\\").toLowerCase()));\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t}\\n\\t\\t\\tcatch(IllegalArgumentException e) {\\n\\t\\t\\t\\tqueryPartsFields[1]=decodeStrings(decodeNCR(queryPartsFields[1].toLowerCase()));\\n\\t\\t\\t}\\n\\t\\t\\t// remove spaces\\n\\t\\t\\tString terms[]=queryPartsFields[1].split(\\\"\\\\\\\\s\\\");\\n\\t\\t\\tqueryPartsFields[1]=\\\"\\\";\\n\\t\\t\\tfor (int j=0,k=0;j<terms.length;j++) {\\t\\t\\t\\t\\t\\n\\t\\t\\t\\tif (terms[j].equals(\\\"\\\")) {\\n\\t\\t\\t\\t\\tcontinue;\\n\\t\\t\\t\\t}\\t\\t\\t\\t\\t\\n\\t\\t\\t\\tif (k>0) {\\n\\t\\t\\t\\t\\tqueryPartsFields[1]+=\\\" \\\";\\t\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\tqueryPartsFields[1]+=terms[j];\\t\\t\\t\\t\\t\\n\\t\\t\\t\\tk++;\\n\\t\\t\\t}\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t// filter queries\\t\\t\\t\\t\\t\\n\\t\\t\\tif (queryFiltersMap.containsKey(queryPartsFields[1]) || queryPartsFields[1].startsWith(\\\"cache%3\\\") || queryPartsFields[1].equals(\\\"\\\")) {\\t\\t\\t\\t\\n\\t\\t\\t\\tcontinue;\\n\\t\\t\\t}\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t// set first page viewed\\n\\t\\t\\tif (!docsProcessed) {\\n\\t\\t\\t\\tpagesViewedDistAux[0]++;\\n\\t\\t\\t\\tdocsProcessed=true;\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t}\\n\\t\\t\\t\\n\\t\\t\\t//key=queryPartsFields[0]+\\\" \\\"+queryPartsFields[1];\\n\\t\\t\\tkey=NEW_QUERY_KEY+\\\" \\\"+queryPartsFields[1];\\t\\t\\t\\n\\t\\t\\tif ((value=queryPartsMap.get(key))==null) {\\n\\t\\t\\t\\tqueryPartsMap.put(key,1);\\n\\t\\t\\t}\\n\\t\\t\\telse {\\n\\t\\t\\t\\tqueryPartsMap.put(key,value+1);\\n\\t\\t\\t}\\n\\t\\t\\t\\n\\t\\t\\t// set submitted query\\n\\t\\t\\tif (submittedQuery!=null) { // sanity check\\n\\t\\t\\t\\tthrow new IOException(\\\"Submitted query already set.\\\");\\n\\t\\t\\t}\\n\\t\\t\\tsubmittedQuery=queryPartsFields[1];\\n\\t\\t\\t\\t\\n\\t\\t\\t// count queries per session\\t\\n\\t\\t\\tnQueriesSession++;\\n\\t\\t}\\n\\t\\treturn submittedQuery;\\n\\t}\",\n \"public Set<String> calculateDistance() throws IOException {\\n booleanSearch();\\n\\n Set<String> words = invertedIndexForQuerryWords.keySet();\\n Map<String, Double> tfidfQuerry = new TreeMap<>();\\n\\n //load idf\\n char c='a';\\n char prC = 'v';\\n for (String word : words){\\n c = word.charAt(0);\\n if(c != prC) {\\n String path = Constants.PATH_TO_IDF + c + \\\"IDF.idf\\\";\\n prC = c;\\n idfMap.putAll(objectMapper.readValue(new File(path), new TypeReference<TreeMap<String, Double>>(){}));\\n }\\n }\\n\\n Map<String, Double> distanceMap = new HashMap<>();\\n double sum = 0.0;\\n //calculez norma interogarii\\n for(String word:words){\\n double idf, tf;\\n if(idfMap.containsKey(word)) {\\n idf = idfMap.get(word);\\n tf = 1.0 / words.size();\\n tfidfQuerry.put(word, tf * idf);\\n\\n sum += (tf * idf) * (tf * idf);\\n } else {\\n sum += 0.0;\\n }\\n }\\n\\n double normQuerry = Math.sqrt(sum);\\n\\n //iau toate documentele rezultate din boolean search\\n Set<String> docs = new TreeSet<>();\\n for(List<MyPair> list : invertedIndexForQuerryWords.values()) {\\n if (list != null) {\\n docs.addAll(list.stream().map(p -> p.getKey()).collect(Collectors.toSet()));\\n }\\n }\\n\\n List<File> documents = FileLoader.getFilesForInternalPath(\\\"Norms\\\", \\\".norm\\\");\\n\\n Map<String, Double> norms = new HashMap<>();\\n for(File file : documents) {\\n norms.putAll(objectMapper.readValue(file, new TypeReference<TreeMap<String, Double>>(){}));\\n }\\n\\n //pentru fiecare document din boolean search calculez distanta cosinus\\n for(String doc : docs) {\\n\\n String fileName = Paths.get(doc).getFileName().toString();\\n\\n String filePath = Constants.PATH_TO_TF + fileName.replaceFirst(\\\"[.][^.]+$\\\", \\\".tf\\\");\\n\\n Map<String, Double> tf = objectMapper.readValue(new File(filePath), new TypeReference<TreeMap<String, Double>>(){});\\n double wordTF, wordIDF;\\n double vectorialProduct = 0.0;\\n double tfidfForQueryWord;\\n\\n for(String word : words) {\\n if (tf.containsKey(word)) {\\n wordTF = tf.get(word);\\n wordIDF = idfMap.get(word);\\n tfidfForQueryWord = tfidfQuerry.get(word);\\n\\n vectorialProduct += tfidfForQueryWord * wordIDF * wordTF;\\n }\\n }\\n\\n double normProduct = normQuerry * norms.get(Paths.get(doc).getFileName().toString());\\n\\n distanceMap.put(doc, vectorialProduct / normProduct);\\n }\\n\\n //sortare distance map\\n distanceMap = distanceMap.entrySet().stream()\\n .sorted(Map.Entry.comparingByValue(Collections.reverseOrder()))\\n .collect(Collectors.toMap(\\n Map.Entry::getKey,\\n Map.Entry::getValue,\\n (e1, e2) -> e1,\\n LinkedHashMap::new));\\n\\n// System.out.println(\\\"Cos distance:\\\");\\n// for(Map.Entry entry : distanceMap.entrySet()){\\n// System.out.println(entry);\\n// }\\n\\n return distanceMap.keySet();\\n }\",\n \"public static void calcuTFIDF() throws IOException {\\n\\n\\t\\tHashtable<String, Double> idf = new Hashtable<String, Double>();\\n\\t\\tArrayList<String> terms = new ArrayList<String>();\\n\\t\\tdouble fileCount = 0.0;\\n\\t\\tString featurePath = \\\"./corpus/features\\\";\\n\\t\\tString featureWeight = \\\"./corpus/featureWeight\\\";\\n\\t\\tString trainPath = \\\"./corpus/trainData\\\";\\n\\t\\tString testPath = \\\"./corpus/testData\\\";\\n\\t\\tString stopPath = \\\"./corpus/english.stop\\\";\\n\\t\\tString trainOutPath = \\\"./corpus/trainVectors\\\";\\n\\t\\tString testOutPath = \\\"./corpus/testVectors\\\";\\n\\t\\tBufferedReader br = new BufferedReader(new FileReader(featurePath));\\n\\t\\tBufferedWriter featureWriter = new BufferedWriter(new FileWriter(\\n\\t\\t\\t\\tfeatureWeight));\\n\\t\\tBufferedReader trainReader = new BufferedReader(new FileReader(\\n\\t\\t\\t\\ttrainPath));\\n\\t\\tBufferedReader testReader = new BufferedReader(new FileReader(testPath));\\n\\t\\tBufferedReader br2 = new BufferedReader(new FileReader(stopPath));\\n\\t\\tBufferedWriter writer = new BufferedWriter(new FileWriter(trainOutPath));\\n\\t\\tBufferedWriter testWriter = new BufferedWriter(new FileWriter(\\n\\t\\t\\t\\ttestOutPath));\\n\\t\\tString oneline;\\n\\t\\tArrayList<String> as = new ArrayList<String>();\\n\\t\\twhile ((oneline = br2.readLine()) != null) {\\n\\t\\t\\tas.add(oneline);\\n\\t\\t}\\n\\t\\tString[] stopWords = new String[as.size()];\\n\\t\\tas.toArray(stopWords);\\n\\t\\tAnalyzer analyzer = new SnowballAnalyzer(\\\"English\\\", stopWords);\\n\\n\\t\\twhile ((oneline = br.readLine()) != null) {\\n\\t\\t\\tidf.put(oneline, 0.0);\\n\\t\\t\\tterms.add(oneline);\\n\\t\\t}\\n\\n\\t\\twhile ((oneline = trainReader.readLine()) != null) {\\n\\n\\t\\t\\tint pos = oneline.indexOf(\\\"\\\\t\\\");\\n\\t\\t\\tString topic = oneline.substring(0, pos);\\n\\t\\t\\tString content = oneline.substring(pos + 1);\\n\\t\\t\\tfileCount++;\\n\\t\\t\\tHashtable<String, Integer> termList = new Hashtable<String, Integer>();\\n\\t\\t\\tTokenStream stream = analyzer.tokenStream(\\\"\\\", new StringReader(\\n\\t\\t\\t\\t\\tcontent));\\n\\t\\t\\twhile (true) {\\n\\t\\t\\t\\tToken token = stream.next();\\n\\t\\t\\t\\tif (token == null)\\n\\t\\t\\t\\t\\tbreak;\\n\\t\\t\\t\\tString tmp = token.termText();\\n\\t\\t\\t\\tif (!termList.containsKey(tmp))\\n\\t\\t\\t\\t\\ttermList.put(tmp, new Integer(1));\\n\\t\\t\\t}\\n\\t\\t\\tSet<String> keys = termList.keySet();\\n\\t\\t\\tfor (String tmp : keys) {\\n\\t\\t\\t\\tif (idf.containsKey(tmp)) {\\n\\t\\t\\t\\t\\tDouble num = idf.get(tmp);\\n\\t\\t\\t\\t\\tidf.put(tmp, num + 1);\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t}\\n\\n\\t\\tfor (String term : terms) {\\n\\n\\t\\t\\tdouble weightOfTerm = Math.log((double) fileCount / idf.get(term)\\n\\t\\t\\t\\t\\t+ 0.01);\\n\\t\\t\\tfeatureWriter.write(term + \\\" \\\" + weightOfTerm);\\n\\t\\t\\tfeatureWriter.newLine();\\n\\t\\t\\tidf.put(term, weightOfTerm);\\n\\n\\t\\t}\\n\\t\\tfeatureWriter.flush();\\n\\t\\tfeatureWriter.close();\\n\\n\\t\\ttrainReader = new BufferedReader(new FileReader(trainPath));\\n\\t\\twhile ((oneline = trainReader.readLine()) != null) {\\n\\n\\t\\t\\tint pos = oneline.indexOf(\\\"\\\\t\\\");\\n\\t\\t\\tString topic = oneline.substring(0, pos);\\n\\t\\t\\tString content = oneline.substring(pos + 1);\\n\\t\\t\\tHashtable<String, Integer> termFrequent = new Hashtable<String, Integer>();\\n\\t\\t\\tTokenStream stream = analyzer.tokenStream(\\\"\\\", new StringReader(\\n\\t\\t\\t\\t\\tcontent));\\n\\t\\t\\twhile (true) {\\n\\t\\t\\t\\tToken token = stream.next();\\n\\t\\t\\t\\tif (token == null)\\n\\t\\t\\t\\t\\tbreak;\\n\\t\\t\\t\\tString tmp = token.termText();\\n\\t\\t\\t\\tif (!termFrequent.containsKey(tmp))\\n\\t\\t\\t\\t\\ttermFrequent.put(tmp, new Integer(1));\\n\\t\\t\\t\\telse {\\n\\t\\t\\t\\t\\tInteger num = termFrequent.get(tmp);\\n\\t\\t\\t\\t\\ttermFrequent.put(tmp, num + 1);\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t\\tdouble weights[] = new double[terms.size()];\\n\\t\\t\\tdouble denominator = 0.0;\\n\\t\\t\\tint i = 0;\\n\\t\\t\\tfor (String term : terms) {\\n\\t\\t\\t\\tdouble count;\\n\\t\\t\\t\\tif (termFrequent.containsKey(term)) {\\n\\t\\t\\t\\t\\tcount = termFrequent.get(term);\\n\\t\\t\\t\\t} else {\\n\\t\\t\\t\\t\\tcount = 0;\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\tdouble tmp = count * idf.get(term);\\n\\t\\t\\t\\tdenominator += tmp;\\n\\t\\t\\t\\tweights[i++] = tmp;\\n\\t\\t\\t}\\n\\t\\t\\tdenominator = Math.sqrt(denominator);\\n\\t\\t\\twriter.write(topic);\\n\\t\\t\\tfor (int j = 1; j <= weights.length; j++) {\\n\\t\\t\\t\\tdouble tmp = weights[j - 1];\\n\\t\\t\\t\\tif (tmp > 0.0) {\\n\\t\\t\\t\\t\\ttmp = Math.sqrt(tmp) / denominator;\\n\\t\\t\\t\\t\\twriter.write(\\\" \\\" + j + \\\":\\\" + tmp);\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t\\twriter.newLine();\\n\\t\\t}\\n\\n\\t\\twhile ((oneline = testReader.readLine()) != null) {\\n\\n\\t\\t\\tint pos = oneline.indexOf(\\\"\\\\t\\\");\\n\\t\\t\\tString topic = oneline.substring(0, pos);\\n\\t\\t\\tString content = oneline.substring(pos + 1);\\n\\t\\t\\tHashtable<String, Integer> termFrequent = new Hashtable<String, Integer>();\\n\\t\\t\\tTokenStream stream = analyzer.tokenStream(\\\"\\\", new StringReader(\\n\\t\\t\\t\\t\\tcontent));\\n\\t\\t\\twhile (true) {\\n\\t\\t\\t\\tToken token = stream.next();\\n\\t\\t\\t\\tif (token == null)\\n\\t\\t\\t\\t\\tbreak;\\n\\t\\t\\t\\tString tmp = token.termText();\\n\\t\\t\\t\\tif (!termFrequent.containsKey(tmp))\\n\\t\\t\\t\\t\\ttermFrequent.put(tmp, new Integer(1));\\n\\t\\t\\t\\telse {\\n\\t\\t\\t\\t\\tInteger num = termFrequent.get(tmp);\\n\\t\\t\\t\\t\\ttermFrequent.put(tmp, num + 1);\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t\\tdouble weights[] = new double[terms.size()];\\n\\t\\t\\tdouble denominator = 0.0;\\n\\t\\t\\tint i = 0;\\n\\t\\t\\tfor (String term : terms) {\\n\\t\\t\\t\\tdouble count;\\n\\t\\t\\t\\tif (termFrequent.containsKey(term)) {\\n\\t\\t\\t\\t\\tcount = termFrequent.get(term);\\n\\t\\t\\t\\t} else {\\n\\t\\t\\t\\t\\tcount = 0;\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\tdouble tmp = count * idf.get(term);\\n\\t\\t\\t\\tdenominator += tmp;\\n\\t\\t\\t\\tweights[i++] = tmp;\\n\\t\\t\\t}\\n\\t\\t\\tdenominator = Math.sqrt(denominator);\\n\\t\\t\\ttestWriter.write(topic);\\n\\t\\t\\tfor (int j = 1; j <= weights.length; j++) {\\n\\t\\t\\t\\tdouble tmp = weights[j - 1];\\n\\t\\t\\t\\tif (tmp > 0.0) {\\n\\t\\t\\t\\t\\ttmp = Math.sqrt(tmp) / denominator;\\n\\t\\t\\t\\t\\ttestWriter.write(\\\" \\\" + j + \\\":\\\" + tmp);\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t\\ttestWriter.newLine();\\n\\t\\t}\\n\\t\\twriter.close();\\n\\t\\ttestWriter.close();\\n\\t}\",\n \"public void makeQueryTermList() {\\n for (int i = 0; i < this.stemmed_query.size(); i++) {\\n boolean added = false;\\n String curTerm = this.stemmed_query.get(i);\\n for (int j = 0; j < this.query_terms_list.size(); j++) {\\n if (this.query_terms_list.get(j).strTerm.compareTo(curTerm) == 0) {\\n this.query_terms_list.get(j).timeOccur++;\\n added = true;\\n break;\\n }\\n }\\n if (added == false) {\\n this.query_terms_list.add(new QueryTerm(curTerm));\\n }\\n }\\n }\",\n \"public interface Query {\\n\\n\\t/**\\n\\t * @return ID of the given query\\n\\t */\\n\\tint queryID();\\n\\t\\n\\t/**\\n\\t * @return given query\\n\\t */\\n\\tString query();\\n\\t\\n\\t/**\\n\\t * @return list of relevant documents to the corresponding query\\n\\t */\\n\\tList<RelevanceInfo> listOfRelevantDocuments();\\n\\t\\n\\t/**\\n\\t * @return list of results to the corresponding query after running one of the retrieval models\\n\\t */\\n\\tList<Result> resultList();\\n\\t\\n\\t/**\\n\\t * @param resultList\\n\\t * @Effects adds results to the result list of the corresponding query\\n\\t */\\n\\tvoid putResultList(List<Result> resultList);\\n}\",\n \"private ArrayList<WordDocument> executeAdvancedQuery(){\\n ArrayList<WordDocument> documents = customDijkstrasTwoStack(this.query.split(\\\" \\\"));\\n ArrayList<WordDocument> result = new ArrayList<WordDocument>();\\n\\n try{\\n String[] orderByPart = query.substring(query.indexOf(\\\"ORDERBY\\\")).trim().toLowerCase().split(\\\" \\\");\\n if(isOrderByCommand(orderByPart[0]))\\n result = orderBy(documents, orderByPart[1], orderByPart[2]);\\n }catch (StringIndexOutOfBoundsException ex){\\n result = documents;\\n }\\n\\n return result;\\n }\",\n \"public List<Integer> processRelatedDocs(Query query) {\\r\\n List<Integer> result = new ArrayList<>();\\r\\n\\r\\n if (query.isTerm()) {\\r\\n\\r\\n result = this.processRelatedDocsQuery(query.getText());\\r\\n\\r\\n } else {\\r\\n\\r\\n //query.getNodes().keySet()\\r\\n for (BooleanClause.Occur key : new BooleanClause.Occur[] {\\r\\n BooleanClause.Occur.MUST,\\r\\n BooleanClause.Occur.SHOULD,\\r\\n BooleanClause.Occur.MUST_NOT }) {\\r\\n\\r\\n List<Query> nodes = query.getNodes().get(key);\\r\\n\\r\\n // no-op\\r\\n if(nodes.isEmpty()) continue;\\r\\n\\r\\n switch (key) {\\r\\n /* AND */ case MUST:\\r\\n for (Query node : nodes) {\\r\\n List<Integer> rel = this.processRelatedDocs(node);\\r\\n result = this.operator.and(result, rel);\\r\\n }\\r\\n break;\\r\\n /* OR */ case SHOULD:\\r\\n for (Query node : nodes) {\\r\\n List<Integer> rel = this.processRelatedDocs(node);\\r\\n result = this.operator.or(result, rel);\\r\\n }\\r\\n break;\\r\\n /* NOT */ case MUST_NOT:\\r\\n for (Query node : nodes) {\\r\\n List<Integer> rel = this.processRelatedDocs(node);\\r\\n result = this.operator.not(result, rel);\\r\\n }\\r\\n break;\\r\\n }\\r\\n }\\r\\n }\\r\\n\\r\\n return result;\\r\\n }\",\n \"@Override\\n public synchronized Long count(String query) {\\n long count = 0L;\\n String nQuery = normalizeQuery(query);\\n Set<String> keys = suggestIndex.getKeys();\\n Map index = suggestIndex.getIndex();\\n LinkedHashSet<Long> result = new LinkedHashSet<Long>();\\n\\n logger.debug(\\\"IN SEARCH: query={}, keys={}\\\", query, keys);\\n\\n StringBuilder patternBuilder;\\n List<Pattern> patterns = new ArrayList<Pattern>();\\n for (String keyPart : nQuery.split(\\\" \\\")) {\\n patternBuilder = new StringBuilder(\\\"^(?iu)\\\");\\n patternBuilder.append(ALLOWED_CHARS_REGEXP);\\n keyPart = Normalizer.normalize(keyPart, Normalizer.Form.NFD);\\n patternBuilder.append(keyPart)\\n .append(ALLOWED_CHARS_REGEXP)\\n .append('$');\\n patterns.add(Pattern.compile(patternBuilder.toString()));\\n }\\n\\n for (String key : keys) {\\n for (Pattern pattern : patterns) {\\n\\n if (pattern.matcher(key).matches()) {\\n result.addAll((LinkedHashSet<Long>) index.get(key));\\n count += ((LinkedHashSet<Long>) index.get(key)).size();\\n }\\n }\\n }\\n return Long.valueOf(result.size());\\n }\",\n \"CampusSearchQuery generateQuery();\",\n \"public void set_graph() throws ParseException, IOException {\\n \\tg = new WeightedUndirectedGraph(words.length);\\n //g = new WeightedUndirectedGraph(most_important_terms.size());\\n \\n Directory dir = new SimpleFSDirectory(new File(\\\".\\\\\\\\data\\\\\\\\lucene_index_r_r\\\"));\\n Analyzer analyzer = new StandardAnalyzer(LUCENE_41);\\n \\n // creat a map that stores, for each word (in the cluster), a set of all the documents that contain that word\\n HashMap<String,HashSet<Integer>> word_to_docs_map = new HashMap<String,HashSet<Integer>>();\\n int n_strings = words.length; \\n \\n // for each word...\\n for (int idx = 0; idx < n_strings; idx++) {\\n // query the index with that given word and retrieve all the documents that contains that word\\n String query = words[idx]; \\n QueryParser parser = new QueryParser(Version.LUCENE_41, \\\"text\\\", analyzer); \\n Query q = parser.parse(query); \\n\\n IndexReader reader = DirectoryReader.open(dir);\\n IndexSearcher searcher = new IndexSearcher(reader);\\n TopDocs docs = searcher.search(q, reader.numDocs());\\n ScoreDoc[] hits = docs.scoreDocs;\\n \\n // update map from word to docs it appears in \\n //HashSet<Integer> tmp = null;\\n // tmp is the set of all the document ids in which the current word is contained\\n HashSet<Integer> tmp = new HashSet<>();\\n //word_to_docs_map.put(query, tmp);\\n \\n // for each document, retrieved from the query\\n for(Integer i=0;i<hits.length;i++) {\\n Integer docId = hits[i].doc;\\n // tmp = word_to_docs_map.get(query); \\n // if the document is a document written by an user of interest \\n if(indices.contains(docId)) {\\n tmp.add(docId);\\n }\\n //word_to_docs_map.put(query, tmp); \\n }\\n word_to_docs_map.put(query, tmp);\\n\\t }\\n\\t \\n\\t // add edges: iterate over possible term pairs ...\\n\\t for(int idx_1 = 0; idx_1 < n_strings - 1; idx_1++) {\\n\\t \\n\\t for(int idx_2 = idx_1 + 1 ; idx_2 < n_strings ; idx_2 ++ ) {\\n\\t \\n\\t // extract document sets associated with the considered terms \\n\\t HashSet<Integer> set_a = word_to_docs_map.get(words[idx_1]); \\n\\t HashSet<Integer> set_b = word_to_docs_map.get(words[idx_2]); \\n\\t \\n\\t // compute set intersection \\n\\t int n = intersectionSize(set_a, set_b);\\n\\t \\n\\t // if the terms appear in at least one common document\\n\\t if(n>0) {\\n\\t // add edge \\n\\t g.testAndAdd(idx_1, idx_2 , n); \\n\\t }\\n\\t } \\n\\t }\\n\\t}\",\n \"@Override\\n public boolean onQueryTextSubmit(String query) {\\n prepareBooks(engine.search(query.toLowerCase(),filter));\\n return false;\\n }\",\n \"public static List<String> query_intersect(List<String> queryWords) throws IOException {\\n\\t\\tif (!initialized) initialize();\\n\\t\\tList<PostingList> pls = new ArrayList<PostingList> ();\\n\\t\\tfor (String queryWord : queryWords) {\\n\\t\\t\\tqueryWord = queryWord.toLowerCase();\\n\\t\\t\\tif (!termDict.containsKey(queryWord)) {\\n\\t\\t\\t\\tpls.clear();\\n\\t\\t\\t\\tbreak;\\n\\t\\t\\t}\\n\\t\\t\\tPostingList pl = readPosting(fc, termDict.get(queryWord));\\n\\t\\t\\tif (pl == null) {\\n\\t\\t\\t\\tpls.clear();\\n\\t\\t\\t\\tbreak;\\n\\t\\t\\t}\\n\\t\\t\\tpls.add(readPosting(fc, termDict.get(queryWord)));\\n\\t\\t}\\n\\t\\tCollections.sort(pls, new Comparator<PostingList>(){\\n\\t\\t public int compare(PostingList p1, PostingList p2) {\\n\\t\\t return p1.size() - p2.size(); // assumes you want biggest to smallest\\n\\t\\t }\\n\\t\\t});\\n\\t\\tif (pls.size() == 0) {\\n\\t\\t\\treturn null;\\n\\t\\t} else {\\n\\t\\t\\tList<Integer> current = pls.get(0).getList();\\n\\t\\t\\tfor (int i = 1; i < pls.size(); i++) {\\n\\t\\t\\t\\tList<Integer> toBeAdd = pls.get(i).getList();\\n\\t\\t\\t\\tcurrent = intersect(current, toBeAdd);\\n\\t\\t\\t}\\n\\t\\t\\tif (current.size() == 0) {\\n\\t\\t\\t\\treturn null;\\n\\t\\t\\t} else {\\n\\t\\t\\t\\tList<String> result = new ArrayList<String>();\\n\\t\\t\\t\\tfor (int docId : current) {\\n\\t\\t\\t\\t\\tresult.add(docDict.get(docId));\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\treturn result;\\n\\t\\t\\t}\\n\\t\\t}\\n\\t}\",\n \"public void calculateTermWeights() {\\n\\t\\tfor (String termString : terms.keySet()) {\\n\\t\\t\\tTerm t = terms.get(termString);\\n\\t\\t\\tMap<Integer, TermDoc> posting = t.getPostings();\\n\\n\\t\\t\\t// Iterate through the docs in which the selected term is found.\\n\\t\\t\\tfor (Integer docId : posting.keySet()) {\\n\\n\\t\\t\\t\\tTermDoc td = posting.get(docId);\\n\\t\\t\\t\\tDocument doc = this.getDocument(docId);\\n\\n\\t\\t\\t\\tfinal double a = 0.4;\\n\\t\\t\\t\\tdouble ntf = a + (1 - a) * (double) td.getFreq() / (double) doc.getMaxTermFreq();\\n\\t\\t\\t\\tdouble idf = Math.log((double) documents.size() / (1 + (double) t.getDocFreq()));\\n\\t\\t\\t\\tdoc.addWeight(termString, ntf * idf);\\n\\t\\t\\t}\\n\\t\\t}\\n\\n\\t\\tfor (Document doc : documents.values())\\n\\t\\t\\tdoc.setEuclideanDistance();\\n\\t}\",\n \"public void parseAndRankQuery(String stringNumber) throws Exception {\\n\\n if (this.semantics) { //if the user choose semantic\\n semantic=new ArrayList<>();\\n Word2VecModel model = Word2VecModel.fromTextFile(new File(\\\"word2vec.c.output.model.txt\\\"));\\n com.medallia.word2vec.Searcher semanticSearchrt = model.forSearch();\\n int num = 10;\\n String[] semanQuery = query.split(\\\" \\\");\\n for (String s : semanQuery)\\n {\\n try {\\n List<com.medallia.word2vec.Searcher.Match> matches = semanticSearchrt.getMatches(s.toLowerCase(), num);\\n for (com.medallia.word2vec.Searcher.Match match : matches) {\\n match.match();\\n }\\n if(matches.get(0).equals(s)) {\\n query = query + \\\" \\\" + matches.get(1);\\n String dd=\\\"\\\"+matches.get(1);\\n semantic.add(dd);\\n }\\n else {\\n query = query + \\\" \\\" + matches.get(0); //add to query the high semantics 3 top words score\\n String dd=\\\"\\\"+matches.get(0);\\n semantic.add(dd);\\n }\\n } catch(com.medallia.word2vec.Searcher.UnknownWordException e){\\n }\\n }\\n }\\n\\n ranker = new Ranker(this.indexer,stringNumber,path,originalString); // new ranker\\n ArrayList<String> cleanQuery;\\n ArrayList<String> parsedQueryList;\\n ReadFile rd=new ReadFile();\\n cleanQuery=rd.cleanLine(stemming,query); //clean the query from dots and other signs\\n HashMap<String, Pair<Integer,String>> parsedQuery=new HashMap<>();\\n parsedQuery=parser.Tokenizer(cleanQuery,\\\"\\\",stemming); //parse the query\\n Iterator it = parsedQuery.entrySet().iterator();\\n parsedQueryList=new ArrayList<>();\\n while (it.hasNext()) {\\n Map.Entry pair = (Map.Entry)it.next();\\n parsedQueryList.add((String)pair.getKey());\\n it.remove(); // avoids a ConcurrentModificationException\\n }\\n ranker.setParseredQuery(parsedQueryList);\\n try {\\n ranker.orgByPostFile();\\n } catch (FileNotFoundException e) {\\n e.printStackTrace();\\n }\\n }\",\n \"public void testAdvancedQuery() {\\n\\t\\t//manager.advancedQuery(ElasticIndex.analyzed, \\\"metropolitan areas\\\", \\\"sports clubs\\\");\\n\\t\\t//manager.advancedQuery(ElasticIndex.analyzed, \\\"\\\", \\\"Award\\\");\\n\\n\\t//manager.advancedQuery(ElasticIndex.analyzed,\\\"american actor\\\", \\\"list of movies starring Sean Connery\\\");\\n//\\tmanager.categorySearch(\\\"Sportspeople\\\", \\\"tennis\\\",ElasticIndex.analyzed,30);\\n\\t//manager.advancedQuery(ElasticIndex.analyzed,\\\"Broadway musicals\\\", \\\"Grammy Award\\\");\\n\\t//manager.advancedQuery(ElasticIndex.analyzed,\\\"musical movies\\\", \\\"Tony Award\\\");\\n\\t//manager.advancedQuery(ElasticIndex.analyzed,\\\"Top level football leagues\\\", \\\"teams\\\");\\n\\t//manager.advancedQuery(ElasticIndex.analyzed,\\\"american movies\\\", \\\"directed by Woody Allen\\\");\\n\\t//manager.advancedQuery(ElasticIndex.analyzed,\\\"United states\\\", \\\"professional sports teams\\\");\\n\\t\\t//manager.advancedQuery(\\\"musical movies\\\", \\\"tony award\\\");\\n\\t\\t//manager.advancedQuery(\\\"grammy\\\", \\\"best album in 2012\\\"); \\n\\t\\t//manager.advancedQuery(\\\"american movies\\\", \\\"directed by Woody Allen\\\"); \\n\\t\\t//Canceled manager.advancedQuery(\\\"tennis\\\", \\\"international players\\\"); \\n\\t\\t// canceled manager.advancedQuery(\\\"tennis\\\", \\\"french open\\\"); \\n\\t\\t// canceled manager.advancedQuery(\\\"film movie\\\", \\\"1933\\\"); \\n//\\t\\tmanager.advancedQuery(\\\"United states\\\", \\\"professional sports teams \\\");\\n//\\t\\t manager.advancedQuery(\\\"computer games\\\", \\\"developed by Ubisoft\\\");\\n//\\t\\tmanager.advancedQuery(\\\"movies\\\", \\\"academy award nominations\\\");\\n //manager.advancedQuery(\\\"movies\\\", \\\"starring Dustin Hoffman\\\");\\n // manager.advancedQuery(\\\"movies\\\", \\\"best costume design\\\");\\n // manager.advancedQuery(\\\"concert tours\\\", \\\"england\\\");\\n // manager.advancedQuery(\\\"sport\\\", \\\"Francesco\\\");\\n\\t\\t//System.out.println(\\\"******* advanced query *******\\\");\\n\\t\\t//manager.advancedQuery(\\\"sportspeople\\\", \\\"tennis\\\");\\n//\\t\\tmanager.advancedQuery(ElasticIndex.analyzed, \\\"Broadway musicals\\\", \\\"Grammy Award\\\");\\n //System.out.println(\\\"*****************************\\\");\\n\\n\\n\\t\\t\\n\\t\\t//manager.advancedQuery(\\\"football\\\", \\\"italian championship\\\");\\n\\t\\t//manager.advancedQuery(\\\"american basketball\\\", \\\"team\\\");\\n\\t\\t //manager.advancedQuery(\\\"Goya Award\\\", \\\"Winner and nominees from FRA\\\");\\n\\t\\t//manager.advancedQuery(\\\"films\\\", \\\"american comedy \\\");\\n\\t\\t//manager.advancedQuery(\\\"films\\\", \\\"american Adventure directed by James P. Hogan\\\");\\n\\t\\t//manager.advancedQuery(\\\"NCAA Division\\\", \\\"american universities in Arkansas\\\");\\n\\t\\t//manager.advancedQuery(\\\"Academy award\\\", \\\"winners and nominees in acting in 2011\\\");\\n\\t\\t//manager.advancedQuery(\\\"canadian soccer\\\", \\\"Alain Rochat position \\\");\\n\\n\\t}\",\n \"public Vector mapDocument(BOW bow) {\\n //logger.info(\\\"lsm.mapDocument\\\");\\n SparseVector vector = new SparseVector();\\n\\n Iterator<String> it = bow.termSet().iterator();\\n String term = null;\\n int index = 0;\\n //int tf = 0;\\n float tfIdf;\\n for (int i = 0; it.hasNext(); i++) {\\n //logger.info(i + \\\" \\\" + t[i]);\\n term = it.next();\\n index = termIndex.get(term);\\n\\n if (index != -1) {\\n //tf = bow.getFrequency(term);\\n //tfIdf = (float) (log2(tf)) * Iidf[index];\\n //tfIdf = (float) bow.augmentedFrequency(term) * Iidf[index];\\n tfIdf = (float) bow.tf(term) * Iidf[index];\\n //logger.info(term + \\\" ==> \\\" + index + \\\", tf.idf = \\\" + tf + \\\"(\\\" + (log2(tf)) + \\\") * \\\" + Iidf[index] + \\\" = \\\" + tfIdf);\\n vector.add(index, tfIdf);\\n\\n }\\n } // end for\\n\\n return vector;\\n }\",\n \"public void updateTermInThisQuery(int relevanceFeedbackMethod) {\\n query thisQuery = listDocumentRetrievedForThisQuery.getQuery();\\n StringTokenizer token = new StringTokenizer(thisQuery.getQueryContent(), \\\" %&\\\\\\\"*#@$^_<>|`+=-1234567890'(){}[]/.:;?!,\\\\n\\\");\\n while (token.hasMoreTokens()) {\\n String keyTerm = token.nextToken();\\n String filteredWord;\\n if (invertedFileQuery.isStemmingApplied()) {\\n filteredWord = StemmingPorter.stripAffixes(keyTerm);\\n } else {\\n filteredWord = keyTerm;\\n }\\n try {\\n termWeightingDocument relation = invertedFileQuery.getListTermWeights().get(filteredWord);\\n if (relation.getDocumentWeightCounterInOneTerm().get(thisQuery.getIndex()) != null) {\\n double oldWeight = relation.getDocumentWeightCounterInOneTerm().get(thisQuery.getIndex()).getWeight();\\n double newWeight = computeNewWeightTerm(relevanceFeedbackMethod,filteredWord,oldWeight);\\n if (newWeight > 0) {\\n newQueryComposition.put(keyTerm, newWeight);\\n relation.getDocumentWeightCounterInOneTerm().get(thisQuery.getIndex()).setWeight(newWeight);\\n } else {\\n relation.getDocumentWeightCounterInOneTerm().get(thisQuery.getIndex()).setWeight(0.0);\\n }\\n }\\n } catch (Exception e) {\\n\\n }\\n }\\n }\",\n \"public List<Classes.Document> RetrieveQuery(Classes.Query cQuery, int TopN, int TopK, double alpha) throws Exception { \\r\\n\\t\\t// Get P(token|feedback model)\\r\\n\\t\\tHashMap<String, Double> TokenRFScore = GetTokenRFScore(cQuery, TopK);\\r\\n\\r\\n\\t\\t// Store sorted top N results (from most relevant to least)\\r\\n\\t\\tList<Classes.Document> rankedList = new ArrayList<>();\\r\\n\\t\\t\\r\\n\\t\\t// Get query's content as input into retrieval model\\r\\n\\t\\tString[] tokens = cQuery.getQueryContent().split(\\\" \\\");\\r\\n\\t\\tList<DocScore> docScoreList = new ArrayList<>();\\r\\n\\t\\tqueryResult.forEach((luceneID, tfMap) -> {\\r\\n\\t\\t int doclen = 0;\\r\\n\\t\\t double score = 1.0;\\r\\n\\t\\t try {\\r\\n\\t\\t doclen = myireader.docLength(luceneID);\\r\\n\\t\\t } catch (Exception e) {\\r\\n\\t\\t \\t e.printStackTrace();\\r\\n\\t\\t };\\r\\n\\t\\t \\r\\n\\t\\t /**\\r\\n\\t\\t\\t * Dirichlet Prior Smoothing:\\r\\n\\t\\t\\t * p(w|D) = (|D|/(|D|+MU))*(c(w,D)/|D|) + (MU/(|D|+MU))*p(w|REF)\\r\\n\\t\\t * score = λ*p_doc + (1-λ)*p_ref\\r\\n\\t\\t * = c1*p_doc + c2*p_ref\\r\\n\\t\\t\\t */\\r\\n\\t\\t double c1 = doclen / (doclen + MU);\\r\\n\\t\\t double c2 = MU / (doclen + MU);\\r\\n\\t\\t for(String token : tokens) {\\r\\n\\t\\t \\t long cf = termFreq.get(token);\\r\\n\\t\\t \\t if(cf == 0) {\\t\\r\\n\\t\\t \\t\\t continue;\\r\\n\\t\\t \\t }\\r\\n\\t\\t \\r\\n\\t\\t \\t int tf = tfMap.getOrDefault(token, 0);\\r\\n\\t\\t \\t double p_doc = (double) tf / doclen; // c(w, D)\\r\\n\\t\\t \\t double p_ref = (double) cf / CORPUS_SIZE; // p(w|REF)\\r\\n\\t\\t \\t \\r\\n\\t\\t \\t // Get the final probability of each token with pseudo RF score\\r\\n\\t\\t \\t score *= alpha * (c1 * p_doc + c2 * p_ref) + (1 - alpha) * TokenRFScore.get(token);\\r\\n\\t\\t }\\r\\n\\t\\t \\r\\n\\t\\t DocScore docScore = new DocScore(luceneID, score);\\r\\n\\t\\t docScoreList.add(docScore);\\r\\n\\t\\t}); // The end of forEach loop block\\r\\n\\r\\n\\t\\t// Sort the result List \\r\\n\\t\\tCollections.sort(docScoreList, new Comparator<DocScore>() {\\r\\n\\t\\t\\t@Override\\r\\n\\t\\t\\tpublic int compare(DocScore ds1, DocScore ds2) {\\r\\n\\t\\t\\t\\tif(ds1.score != ds2.score) {\\r\\n\\t\\t\\t\\t\\treturn ds1.score < ds2.score ? 1 : -1;\\r\\n\\t\\t\\t\\t} else {\\r\\n\\t\\t\\t\\t\\treturn 1;\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t}\\r\\n\\t\\t});\\r\\n\\r\\n\\t\\t// Put all documents into result list\\r\\n\\t\\tfor(int n = 0; n < TopN; n++) {\\r\\n\\t\\t DocScore docScore = docScoreList.get(n);\\r\\n\\t\\t Classes.Document doc = null;\\r\\n\\t\\t try {\\r\\n\\t\\t \\t int luceneID = docScore.getId(); // Get Lucene id\\r\\n\\t\\t \\t doc = new Document(Integer.toString(luceneID), \\r\\n\\t\\t \\t\\t\\t \\t\\t\\tmyireader.getDocno(luceneID), \\r\\n\\t\\t \\t\\t\\t docScore.getScore(),\\r\\n\\t\\t \\t\\t\\t dreader.document(luceneID).get(\\\"restName\\\"),\\r\\n\\t\\t \\t\\t\\t dreader.document(luceneID).get(\\\"restUrl\\\"),\\r\\n\\t\\t \\t\\t\\t dreader.document(luceneID).get(\\\"originalContent\\\"));\\r\\n\\t\\t } catch(Exception e) {\\r\\n\\t\\t \\t e.printStackTrace();\\r\\n\\t\\t };\\r\\n\\t\\t \\r\\n\\t\\t rankedList.add(doc);\\r\\n\\t\\t}\\r\\n\\r\\n\\t\\treturn rankedList;\\r\\n\\t}\",\n \"public static void docWtgArray() {\\n int docCount = 0;\\n\\n while(docCount<totaldocument) {\\n List<Double> pass = new ArrayList();\\n for(Entry<String,List<Double>> entry : wtgMap.entrySet()) {\\n List<Double> docList = new ArrayList();\\n docList = entry.getValue();\\n double temp = docList.get(docCount);\\n pass.add(temp);\\n }\\n\\n double answer = CosineSimilarity(pass,query);\\n if(answer >= alpha) {\\n DocID.put(docCount,answer);\\n }\\n docCount++;\\n }\\n }\",\n \"protected Query newTermQuery(Term term, float boost) {\\n Query q = new TermQuery(term);\\n if (boost == DEFAULT_BOOST) {\\n return q;\\n }\\n return new BoostQuery(q, boost);\\n }\",\n \"@Override\\r\\n\\t\\t\\tpublic List<ScoredDocument> search(Query query, long maxNumberOfDocuments) {\\n\\t\\t\\t\\treturn null;\\r\\n\\t\\t\\t}\",\n \"public ArrayList<String> getResults(String query) {\\r\\n\\t\\t// TODO: Add code here\\r\\n\\t\\tHashMap<String,Double> map=new HashMap<>();\\r\\n\\t\\tArrayList<String> urls=wordIndex.get(query);\\r\\n\\t\\tif(urls==null){\\r\\n\\t\\t\\treturn new ArrayList<>();\\r\\n\\t\\t}\\r\\n\\t\\tfor(String url:urls){\\r\\n\\t\\t\\tmap.put(url,internet.getPageRank(url));\\r\\n\\t\\t}\\r\\n\\t\\treturn Sorting.fastSort(map);\\r\\n\\t}\",\n \"public void actionPerformed(ActionEvent e) {\\n displayInfoText(\\\" \\\");\\n // Turn the search string into a Query\\n String queryString = queryWindow.getText().toLowerCase().trim();\\n query = new Query(queryString);\\n // Take relevance feedback from the user into account (assignment 3)\\n // Check which documents the user has marked as relevant.\\n if (box != null) {\\n boolean[] relevant = new boolean[box.length];\\n for (int i = 0; i < box.length; i++) {\\n if (box[i] != null)\\n relevant[i] = box[i].isSelected();\\n }\\n query.relevanceFeedback(results, relevant, engine);\\n }\\n // Search and print results. Access to the index is synchronized since\\n // we don't want to search at the same time we're indexing new files\\n // (this might corrupt the index).\\n long startTime = System.currentTimeMillis();\\n synchronized (engine.indexLock) {\\n results = engine.searcher.search(query, queryType, rankingType);\\n }\\n long elapsedTime = System.currentTimeMillis() - startTime;\\n // Display the first few results + a button to see all results.\\n //\\n // We don't want to show all results directly since the displaying itself\\n // might take a long time, if there are many results.\\n if (results != null) {\\n displayResults(MAX_RESULTS, elapsedTime / 1000.0);\\n } else {\\n displayInfoText(\\\"Found 0 matching document(s)\\\");\\n\\n if (engine.speller != null) {\\n startTime = System.currentTimeMillis();\\n SpellingOptionsDialog dialog = new SpellingOptionsDialog(50);\\n String[] corrections = engine.speller.check(query, 10);\\n elapsedTime = System.currentTimeMillis() - startTime;\\n System.err.println(\\\"It took \\\" + elapsedTime / 1000.0 + \\\"s to check spelling\\\");\\n if (corrections != null && corrections.length > 0) {\\n String choice = dialog.show(corrections, corrections[0]);\\n if (choice != null) {\\n queryWindow.setText(choice);\\n queryWindow.grabFocus();\\n\\n this.actionPerformed(e);\\n }\\n }\\n }\\n }\\n }\",\n \"public QueryController(String[] args){\\n // Parse Args\\n QueryArgs queryArgs = new QueryArgs();\\n try {\\n queryArgs.parseArgs(args);\\n } catch (FileNotFoundException e) {\\n //e.printStackTrace();\\n System.err.println(\\\"Invalid Arguments received. Please check your arguments passed to ./search\\\");\\n return;\\n }\\n\\n // Run the Term Normaliser\\n TermNormalizer normalizer = new TermNormalizer();\\n String[] queryTerms = normalizer.transformedStringToTerms(queryArgs.queryString);\\n\\n //create the model\\n Model model = new Model();\\n model.loadCollectionFromMap(queryArgs.mapPath);\\n model.loadLexicon(queryArgs.lexiconPath);\\n model.loadInvertedList(queryArgs.invlistPath);\\n if(queryArgs.stopListEnabled)\\n {\\n model.loadStopList(queryArgs.stopListPath);\\n }\\n if(queryArgs.printSummary && queryArgs.collectionPath != \\\"\\\")\\n {\\n model.setPathToCollection(queryArgs.collectionPath);\\n }\\n\\n\\n //fetch the top results from the query module\\n QueryModule queryModule = new QueryModule();\\n queryModule.doQuery(queryTerms, model, queryArgs.bm25Enabled);\\n List<QueryResult> topResults = queryModule.getTopResult(queryArgs.maxResults);\\n\\n\\n\\n ResultsView resultsView = new ResultsView();\\n if(queryArgs.printSummary)\\n {\\n\\n DocSummary docSummary = new DocSummary();\\n for(QueryResult result:topResults)\\n {\\n // retrieve the actualy text from the document collection\\n result.setDoc(model.getDocumentCollection().getDocumentByIndex(result.getDoc().getIndex(), true));\\n\\n //set the summary on the result object by fetching it from the docSummary object\\n result.setSummaryNQB(docSummary.getNonQueryBiasedSummary(result.getDoc(), model.getStopListModule()));\\n result.setSummaryQB(docSummary.getQueryBiasedSummary(result.getDoc(), model.getStopListModule(), Arrays.asList(queryTerms)));\\n }\\n resultsView.printResultsWithSummary(topResults,queryArgs.queryLabel);\\n }else\\n {\\n resultsView.printResults(topResults,queryArgs.queryLabel);\\n }\\n\\n }\",\n \"@Test\\n public void testPhrase() {\\n assertQ(req(\\\"q\\\",\\\"text:now-cow\\\", \\\"indent\\\",\\\"true\\\")\\n ,\\\"//*[@numFound='1']\\\"\\n );\\n // should generate a query of (now OR cow) and match both docs\\n assertQ(req(\\\"q\\\",\\\"text_np:now-cow\\\", \\\"indent\\\",\\\"true\\\")\\n ,\\\"//*[@numFound='2']\\\"\\n );\\n }\",\n \"public Vector mapDocument(MultiSet<String> bow) {\\n //logger.info(\\\"lsm.mapDocument\\\");\\n SparseVector vector = new SparseVector();\\n\\n Iterator<String> it = bow.iterator();\\n String term = null;\\n int index = 0;\\n int tf = 0;\\n float tfIdf;\\n for (int i = 0; it.hasNext(); i++) {\\n //logger.info(i + \\\" \\\" + t[i]);\\n term = it.next();\\n index = termIndex.get(term);\\n\\n if (index != -1) {\\n tf = bow.getFrequency(term);\\n tfIdf = (float) (log2(tf)) * Iidf[index];\\n\\n //logger.info(term + \\\" ==> \\\" + index + \\\", tf.idf = \\\" + tf + \\\"(\\\" + (log2(tf)) + \\\") * \\\" + Iidf[index] + \\\" = \\\" + tfIdf);\\n vector.add(index, tfIdf);\\n\\n }\\n } // end for\\n\\n return vector;\\n }\",\n \"public SortedSet<LabeledVector> query(double[] queryVector) {\\n SortedSet<LabeledVector> sortedSet = new TreeSet<LabeledVector>(new LabeledVectorCompare(queryVector));\\n for (int i = 0; i < vectors.length; i++) {\\n boolean addedDoc = sortedSet.add(new LabeledVector(i, vectors[i]));\\n assert(addedDoc);\\n }\\n return sortedSet;\\n }\",\n \"public Utwor search2(String query) {\\n for (Utwor utwor : utwory) {\\n if (utwor.getTitle().equals(query)) {\\n return utwor;\\n }\\n }\\n return null;\\n }\",\n \"@Override\\n public void postInserts() \\n {\\n for(IndexObject i: myIndex.values())\\n {\\n i.tfidf(documentData);\\n }\\n }\",\n \"public abstract double score(double tf, double docLength);\",\n \"public ArrayList<String> top5search(String kw1, String kw2) {\\n\\t\\t/** COMPLETE THIS METHOD **/\\n\\t\\tArrayList<String> results = new ArrayList<String>();\\n\\t\\tArrayList<Occurrence> ocArr1 = new ArrayList<Occurrence>();\\n\\t\\tArrayList<Occurrence> ocArr2 = new ArrayList<Occurrence>();\\n\\t\\tArrayList<Occurrence> combined = new ArrayList<Occurrence>();\\n\\t\\t\\n\\t\\tif (keywordsIndex.containsKey(kw1))\\n\\t\\t\\tocArr1 = keywordsIndex.get(kw1);\\n\\t\\t\\n\\t\\tif (keywordsIndex.containsKey(kw2))\\n\\t\\t\\tocArr2 = keywordsIndex.get(kw2);\\n\\t\\t\\n\\t\\tcombined.addAll(ocArr1);\\n\\t\\tcombined.addAll(ocArr2);\\n\\t\\t\\n\\t\\tif (!(ocArr1.isEmpty()) && !(ocArr2.isEmpty()))\\n\\t\\t{\\n\\t\\t\\t// Sort with preference for ocArr1\\n\\t\\t\\tfor (int x = 0; x < combined.size()-1; x++)\\n\\t\\t\\t{\\n\\t\\t\\t\\tfor (int y = 1; y < combined.size()-x; y++)\\n\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\tif (combined.get(y-1).frequency < combined.get(y).frequency)\\n\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\tOccurrence temp = combined.get(y-1);\\n\\t\\t\\t\\t\\t\\tcombined.set(y-1, combined.get(y));\\n\\t\\t\\t\\t\\t\\tcombined.set(y, temp);\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\n\\t\\t\\t// Remove duplicates\\n\\t\\t\\tfor (int x = 0; x < combined.size()-1; x++)\\n\\t\\t\\t{\\n\\t\\t\\t\\tfor (int y = x + 1; y < combined.size(); y++)\\n\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\tif (combined.get(x).document == combined.get(y).document)\\n\\t\\t\\t\\t\\t\\tcombined.remove(y);\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t}\\n\\n\\t\\t// Top 5\\n\\t\\twhile (combined.size() > 5)\\n\\t\\t\\tcombined.remove(combined.size()-1);\\n\\t\\t\\n\\t\\t//System.out.println(combined);\\n\\t\\t\\n\\t\\tfor (Occurrence oc : combined)\\n\\t\\t\\tresults.add(oc.document);\\n\\n\\t\\treturn results;\\n\\t\\n\\t\\t\\n\\t\\t// following line is a placeholder to make the program compile\\n\\t\\t// you should modify it as needed when you write your code\\n\\t\\n\\t}\",\n \"private static void printTable(int numberOfDocs) {\\n \\n Gson gs = new Gson();\\n String json = gs.toJson(wor);\\n // System.out.println(json);\\n \\n List<String> queryWords = new ArrayList();\\n //to test it for other query word you can change the following two words\\n //queryWords.add(\\\"carpet\\\");\\n //queryWords.add(\\\"hous\\\");\\n queryWords.add(\\\"the\\\");\\n queryWords.add(\\\"crystallin\\\");\\n queryWords.add(\\\"len\\\");\\n queryWords.add(\\\"vertebr\\\");\\n queryWords.add(\\\"includ\\\");\\n \\n \\n FrequencySummary frequencySummary = new FrequencySummary();\\n frequencySummary.getSummary(json,docName, queryWords);\\n \\n System.exit(0);\\n \\n Hashtable<Integer,Integer> g = new Hashtable<>();\\n \\n /* wor.entrySet().forEach((wordToDocument) -> {\\n String currentWord = wordToDocument.getKey();\\n Map<String, Integer> documentToWordCount = wordToDocument.getValue();\\n freq.set(0);\\n df.set(0);\\n documentToWordCount.entrySet().forEach((documentToFrequency) -> {\\n String document = documentToFrequency.getKey();\\n Integer wordCount = documentToFrequency.getValue();\\n freq.addAndGet(wordCount);\\n System.out.println(\\\"Word \\\" + currentWord + \\\" found \\\" + wordCount +\\n \\\" times in document \\\" + document);\\n \\n if(g.getOrDefault(currentWord.hashCode(), null)==null){\\n g.put(currentWord.hashCode(),1);\\n \\n }else {\\n System.out.println(\\\"Hello\\\");\\n \\n int i = g.get(currentWord.hashCode());\\n System.out.println(\\\"i \\\"+i);\\n g.put(currentWord.hashCode(), i++);\\n }\\n // System.out.println(currentWord+\\\" \\\"+ g.get(currentWord.hashCode()));\\n // g.put(currentWord.hashCode(), g.getOrDefault(currentWord.hashCode(), 0)+wordCount);\\n \\n });\\n // System.out.println(freq.doubleValue());\\n \\n // System.out.println(\\\"IDF for this word: \\\"+Math.log10( (double)(counter/freq.doubleValue())));\\n });\\n // System.out.println(g.get(\\\"plai\\\".hashCode()));\\n //System.out.println(\\\"IDF for this word: \\\"+Math.log10( (double)(counter/(double)g.get(\\\"plai\\\".hashCode()))));\\n */\\n }\",\n \"public ArrayList<String> top5search(String kw1, String kw2) {\\n // COMPLETE THIS METHOD\\n ArrayList<Occurrence> Res1 = keywordsIndex.get(getKeyWord(kw1));\\n ArrayList<Occurrence> res2 = keywordsIndex.get(getKeyWord(kw1));\\n ArrayList<String> arrayList = new ArrayList<String>();\\n\\n while (arrayList.size() < 6) {\\n Occurrence aa = null;\\n Occurrence b = null;\\n {\\n if (Res1 != null) {\\n for (Occurrence occr : Res1) {\\n if (!arrayList.contains(occr.document)) {\\n aa = occr;\\n }\\n }\\n } if(Res1 == null){\\n aa = new Occurrence(null, 0);\\n }\\n else aa = new Occurrence(null,0);\\n }\\n {\\n if(res2 != null){\\n for(Occurrence occr : res2){\\n if(!arrayList.contains(occr.document)){\\n b = occr;\\n }\\n }\\n }\\n if(res2 == null){\\n b = new Occurrence(null,0);\\n }\\n else b = new Occurrence(null,0);\\n }\\n Occurrence[] a = {aa,b};//{search(arrayList, Res1), search(arrayList, res2)};\\n Occurrence m = null;\\n if (a[0].frequency < a[1].frequency) {\\n m = a[1];\\n } else m = a[0];\\n if (m.document != null) {\\n arrayList.add(m.document);\\n } else break;\\n }\\n return arrayList;\\n }\",\n \"private static String handleNonPhraseToken(String stringPart) {\\r\\n // Set of final terms to be used (no empty elements, right syntax of index fields)\\r\\n ArrayList <String> terms = new ArrayList <String> ();\\r\\n \\r\\n /** Case Index field **/\\r\\n if(stringPart.contains(\\\"[\\\") | stringPart.contains(\\\"[\\\")){ // at least an Index field contained here\\r\\n //separate brackets for term with one space (extra spaces dont matter, trim() is used later)\\r\\n stringPart = stringPart.replace(\\\"[\\\", \\\" [\\\");\\r\\n stringPart = stringPart.replace(\\\"]\\\", \\\"] \\\");\\r\\n }\\r\\n\\r\\n /** Case Bag of terms **/\\r\\n //replace space with AND (change default operator to match pubMed's)\\r\\n // No need for this if setDefaultOperator(QueryParser.Operator.AND) is used\\r\\n \\r\\n String[] tokens = stringPart.split(\\\"\\\\\\\\s\\\");\\r\\n if(tokens.length > 0){ \\r\\n for(int i = 1 ; i < tokens.length ; i++){\\r\\n tokens[i] = tokens[i].trim();\\r\\n /* Case index field [fieldName] */\\r\\n if(tokens[i].startsWith(\\\"[\\\") & tokens[i].endsWith(\\\"]\\\")){\\r\\n tokens[i] = tokens[i].replace(\\\"[\\\",\\\"\\\");// clean field name from brackets\\r\\n tokens[i] = tokens[i].replace(\\\"]\\\",\\\"\\\");// clean field name from brackets\\r\\n //Add index field as prefix to previus (not empty) term (as opening index fields handled separately, this index field should not be the first term of string part)\\r\\n int tmp = i-1;\\r\\n boolean perviusTermFound = false;\\r\\n while(!perviusTermFound & tmp >= 0){\\r\\n if(!tokens[tmp].equals(\\\"\\\")){\\r\\n perviusTermFound = true;\\r\\n //TO DO : handle wrong syntax (e.g. ... AND [ArticleTitle])\\r\\n String luceneField = supportedIndexFields.get(tokens[i]);\\r\\n if(luceneField != null){\\r\\n tokens[tmp] = luceneField + \\\":\\\" + tokens[tmp];\\r\\n } // else : Lucene counterpart not found, unsupported field - do nothing\\r\\n } else {\\r\\n tmp--;\\r\\n }\\r\\n }\\r\\n //Empty field to not be added as a search term in query\\r\\n tokens[i] = \\\"\\\";\\r\\n } \\r\\n \\r\\n /*\\r\\n \\r\\n else if(!tokens[i].equals(\\\"AND\\\") & !tokens[i].equals(\\\"\\\")) {\\r\\n terms.add(tokens[i]);\\r\\n }\\r\\n */\\r\\n }\\r\\n }\\r\\n \\r\\n String luceneQueryPart = \\\"\\\";\\r\\n boolean notWaiting = false;\\r\\n boolean orWaiting = false;\\r\\n for(int i = 0 ; i < tokens.length ; i++){\\r\\n\\r\\n if(!tokens[i].equals(\\\"AND\\\") & !tokens[i].equals(\\\"\\\")){\\r\\n //in case of AND nothing should happen, it is the default operator\\r\\n //empty elements are also ignored as useless\\r\\n \\r\\n if(!tokens[i].equals(\\\"NOT\\\") & !tokens[i].equals(\\\"OR\\\") ){ // it's not an operator, it's a term\\r\\n \\r\\n if(!luceneQueryPart.endsWith(\\\" OR \\\") & !luceneQueryPart.endsWith(\\\" -\\\") ) { \\r\\n luceneQueryPart += \\\" +\\\"; \\r\\n } \\r\\n luceneQueryPart += tokens[i];\\r\\n } else {\\r\\n if(tokens[i].equals(\\\"NOT\\\")) {\\r\\n luceneQueryPart += \\\" -\\\";\\r\\n }\\r\\n if(tokens[i].equals(\\\"OR\\\")){\\r\\n luceneQueryPart += \\\" OR \\\";\\r\\n }\\r\\n \\r\\n } \\r\\n } \\r\\n }\\r\\n \\r\\n return luceneQueryPart;\\r\\n }\",\n \"public Query getQuery(String[] values, Collection<String> termCollector) {\\n Query result = null;\\n\\n String[] termValues = values;\\n if (values != null){\\n if(isOffByOne()){\\n for(int i = 0; i < values.length; i++){\\n termValues[i] = String.valueOf(Integer.parseInt(values[i]) - 1);\\n }\\n }\\n }\\n\\n if (index == Field.Index.ANALYZED || normalizer == null) {\\n result = LuceneUtils.toQuery(getAnalyzer(), label, termValues, termCollector);\\n }\\n else {\\n if (termValues != null && termValues.length > 0) {\\n if (termValues.length == 1) {\\n result = LuceneUtils.tokensToQuery(label, tokenize(termValues[0]), termCollector);\\n }\\n else {\\n final PhraseQuery phraseQuery = new PhraseQuery();\\n for (String value : termValues) {\\n final String[] tokens = tokenize(value);\\n if (tokens != null && tokens.length > 0) {\\n for (String token : tokens) {\\n phraseQuery.add(new Term(label, token));\\n if (termCollector != null) termCollector.add(token);\\n }\\n }\\n }\\n result = phraseQuery;\\n }\\n }\\n }\\n\\n return result;\\n }\",\n \"public ArrayList<String> tokeniseQuery(String query) {\\n ArrayList<String> tokens;\\n\\n tokens = this.tokeniseString(query);\\n\\n // Normalise the tokens\\n tokens = this.normaliseTokens(tokens);\\n\\n // Remove commas\\n tokens = this.removeCommas(tokens);\\n\\n // Remove the stopwords\\n this.removeStopwords(tokens);\\n\\n // Remove empty tokens that resulted from normalisation\\n this.removeEmptyTokens(tokens);\\n\\n // Stem the tokens\\n tokens = this.stemTokens(tokens);\\n\\n return tokens;\\n }\",\n \"SearchResult getBestResult(List<SearchResult> results, SearchQuery query);\",\n \"public DocFile[] searchResponse(ScoreDoc[] results, Query query) {\\n\\n DocFile[] result = new DocFile[results.length];\\n FastVectorHighlighter highlighter = new FastVectorHighlighter(true,true);\\n FieldQuery highlightQuery = highlighter.getFieldQuery(query); \\n\\n try {\\n IndexReader reader = DirectoryReader.open(indexDir);\\n IndexSearcher searcher = new IndexSearcher(reader);\\n\\n for (int i = 0; i < results.length; i++) {\\n int docId = results[i].doc;\\n Document document = searcher.doc(docId);\\n \\n //Highlight the best Content context from each Doc\\n String contextString = highlighter.getBestFragment(highlightQuery, \\n searcher.getIndexReader(), results[i].doc,Constants.INDEX_KEY_CONTENT,140);\\n \\n DocFile toAdd = new DocFile(\\n document.get(Constants.INDEX_KEY_FILENAME),\\n document.get(Constants.INDEX_KEY_TITLE),\\n document.get(Constants.INDEX_KEY_OWNER),\\n document.get(Constants.INDEX_KEY_PATH),\\n document.get(Constants.INDEX_KEY_STATUS).equalsIgnoreCase(\\\"true\\\"));\\n \\n if (contextString != null) {\\n toAdd.setContextString(contextString);\\n }\\n \\n toAdd.setId(document.get(Constants.INDEX_KEY_ID));\\n toAdd.setPermissions(Integer.parseInt(document.get(Constants.INDEX_KEY_PERMISSION)));\\n toAdd.setCourseCode(document.get(Constants.INDEX_KEY_COURSE));\\n result[i] = toAdd;\\n\\n }\\n } catch (Exception e) {\\n e.printStackTrace();\\n }\\n\\n return result;\\n }\",\n \"public VSM(String[] docs) {\\n\\t\\tmyDocs = docs;\\n\\t\\ttermList = new ArrayList<String>();\\n\\t\\tdocLists = new ArrayList<ArrayList<Doc>>();\\n\\t\\tArrayList<Doc> docList;\\n\\t\\t// parse the documents to construct the index and collect the raw\\n\\t\\t// frequencies.\\n\\t\\tfor (int i = 0; i < myDocs.length; i++) {\\n\\t\\t\\tString[] tokens = myDocs[i].split(\\\" \\\");\\n\\t\\t\\tString token;\\n\\t\\t\\tfor (int j = 0; j < tokens.length; j++) {\\n\\t\\t\\t\\ttoken = tokens[j];\\n\\t\\t\\t\\tif (!termList.contains(token)) {\\n\\t\\t\\t\\t\\ttermList.add(token);\\n\\t\\t\\t\\t\\tdocList = new ArrayList<Doc>();\\n\\t\\t\\t\\t\\tDoc doc = new Doc(i, 1); // initial raw frequency is 1\\n\\t\\t\\t\\t\\tdocList.add(doc);\\n\\t\\t\\t\\t\\tdocLists.add(docList);\\n\\t\\t\\t\\t} else {\\n\\t\\t\\t\\t\\tint index = termList.indexOf(token);\\n\\t\\t\\t\\t\\tdocList = docLists.get(index);\\n\\t\\t\\t\\t\\tint k = 0;\\n\\t\\t\\t\\t\\tboolean match = false;\\n\\n\\t\\t\\t\\t\\t// search the postings list for a document id, if match,\\n\\t\\t\\t\\t\\t// insert a new position number to the document id\\n\\t\\t\\t\\t\\tfor (Doc doc : docList) {\\n\\t\\t\\t\\t\\t\\tif (doc.docId == i) {\\n\\t\\t\\t\\t\\t\\t\\tdoc.tw++; // increase word count\\n\\t\\t\\t\\t\\t\\t\\tmatch = true;\\n\\t\\t\\t\\t\\t\\t\\tbreak;\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\tk++;\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t// if no match, add a new document id along with the\\n\\t\\t\\t\\t\\t// position number\\n\\t\\t\\t\\t\\tif (!match) {\\n\\t\\t\\t\\t\\t\\tDoc doc = new Doc(i, 1);\\n\\t\\t\\t\\t\\t\\tdocList.add(doc);\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t}\\n\\t\\t\\t}//\\n\\t\\t}// end with parsing\\n\\n\\t\\t// compute the tf-idf term weights and the doc lengths\\n\\t\\tint N = myDocs.length;\\n\\t\\tdocLength = new double[N];\\n\\t\\tfor (int i = 0; i < termList.size(); i++) {\\n\\t\\t\\tdocList = docLists.get(i);\\n\\t\\t\\tint df = docList.size();\\n\\t\\t\\tDoc doc;\\n\\t\\t\\tfor (int j = 0; j < docList.size(); j++) {\\n\\t\\t\\t\\tdoc = docList.get(j);\\n\\t\\t\\t\\tdouble tfidf = (1 + Math.log(doc.tw))\\n\\t\\t\\t\\t\\t\\t* Math.log(N / (df * 1.0));\\n\\t\\t\\t\\tdocLength[doc.docId] += Math.pow(tfidf, 2);\\n\\t\\t\\t\\tdoc.tw = tfidf;\\n\\t\\t\\t\\tdocList.set(j, doc);\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\t// update the length\\n\\t\\tfor (int i = 0; i < N; i++) {\\n\\t\\t\\tdocLength[i] = Math.sqrt(docLength[i]);\\n\\t\\t}\\n\\n\\t}\",\n \"public void onSearchSubmit(String queryTerm);\",\n \"static AnalysisResult analyseQuery(String query) {\\n for (String attack : commonAttacks) {\\n attack = attack.toLowerCase();\\n if (trim(query.toLowerCase()).contains(trim(attack))) {\\n return new AnalysisResult(true, null, attack, true);\\n }\\n }\\n return new AnalysisResult(false, null, null, true);\\n }\",\n \"private IDictionary<URI, IDictionary<String, Double>> computeAllDocumentTfIdfVectors(ISet<Webpage> pages) {\\n // Hint: this method should use the idfScores field and\\n // call the computeTfScores(...) method.\\n\\t\\tdocumentTfIdfVectors = new ChainedHashDictionary<URI, IDictionary<String, Double>>();\\n\\t\\t\\n\\t\\t// Iterates through the given set of webpages\\n\\t\\tfor (Webpage page: pages) {\\n\\t\\t\\tIDictionary<String, Double> tfIdfScores = new ChainedHashDictionary<String, Double>();\\n\\t\\t\\tIDictionary<String, Double> tfScores = computeTfScores(page.getWords());\\n\\t\\t\\t\\n\\t\\t\\t// Computes TfIdf scores\\n\\t\\t\\tfor (KVPair<String, Double> pair: tfScores) {\\n\\t\\t\\t\\tDouble tfIdfScore = pair.getValue() * idfScores.get(pair.getKey());\\n\\t\\t\\t\\ttfIdfScores.put(pair.getKey(), tfIdfScore);\\n\\t\\t\\t}\\n\\t\\t\\tdocumentTfIdfVectors.put(page.getUri(), tfIdfScores);\\n\\t\\t}\\n\\t\\treturn documentTfIdfVectors;\\n }\",\n \"@Test\\n void testAndFilterWithoutExplicitIndex() {\\n Query q = newQueryFromEncoded(\\\"?query=trump\\\" +\\n \\\"&model.type=all\\\" +\\n \\\"&model.defaultIndex=text\\\" +\\n \\\"&filter=%2B%28filterTerm%29\\\");\\n assertEquals(\\\"AND text:trump |text:filterTerm\\\",\\n q.getModel().getQueryTree().toString());\\n }\",\n \"public static String getAllEvaluationAsString(String query, Vector<String> retrievalResults, Map<String, DocumentRelevances> judgments) throws IOException{\\n double precisionAt1 = precisionAtK(retrievalResults, 1, judgments);\\n double precisionAt5 = precisionAtK(retrievalResults, 5, judgments);\\n double precisionAt10 = precisionAtK(retrievalResults, 10, judgments);\\n double recallAt1 = recallAtK(retrievalResults, 1, judgments);\\n double recallAt5 = recallAtK(retrievalResults, 5, judgments);\\n double recallAt10 = recallAtK(retrievalResults, 10, judgments);\\n double F05At1 = F05AtK(retrievalResults, 1, judgments);\\n double F05At5 = F05AtK(retrievalResults, 5, judgments);\\n double F05At10 = F05AtK(retrievalResults, 10, judgments);\\n double[] precisionsAtRecalls = precisionAtRecall(retrievalResults, judgments);\\n double averagePrecision = averagePrecision(retrievalResults, judgments);\\n double NDCGAt1 = NDCGAtK(retrievalResults, 1, judgments);\\n double NDCGAt5 = NDCGAtK(retrievalResults, 5, judgments);\\n double NDCGAt10 = NDCGAtK(retrievalResults, 10, judgments);\\n double reciprocalRank = reciprocalRank(retrievalResults, judgments);\\n \\n String output = query+\\\"\\\\n\\\"+\\n \\t\\t \\\"Precision at 1: \\\"+Double.toString(precisionAt1)+\\\"\\\\n\\\"+\\n \\t\\t \\\"Precision at 5: \\\"+Double.toString(precisionAt5)+\\\"\\\\n\\\"+\\n \\t\\t \\\"Precision at 10: \\\"+Double.toString(precisionAt10)+\\\"\\\\n\\\"+\\n \\t\\t \\\"Recall at 1: \\\"+Double.toString(recallAt1)+\\\"\\\\n\\\"+\\n \\t\\t \\\"Recall at 5: \\\"+Double.toString(recallAt5)+\\\"\\\\n\\\"+\\n \\t\\t \\\"Recall at 10: \\\"+Double.toString(recallAt10)+\\\"\\\\n\\\"+\\n \\t\\t \\\"F05 at 1: \\\"+Double.toString(F05At1)+\\\"\\\\n\\\"+\\n \\t\\t \\\"F05 at 5: \\\"+Double.toString(F05At5)+\\\"\\\\n\\\"+\\n \\t\\t \\\"F05 at 10: \\\"+Double.toString(F05At10)+\\\"\\\\n\\\"+\\n \\t\\t \\\"Precision at Recall 0.0: \\\"+Double.toString(precisionsAtRecalls[0])+\\\"\\\\n\\\"+\\n \\t\\t \\\"Precision at Recall 0.1: \\\"+Double.toString(precisionsAtRecalls[1])+\\\"\\\\n\\\"+\\n \\t\\t \\\"Precision at Recall 0.2: \\\"+Double.toString(precisionsAtRecalls[2])+\\\"\\\\n\\\"+\\n \\t\\t \\\"Precision at Recall 0.3: \\\"+Double.toString(precisionsAtRecalls[3])+\\\"\\\\n\\\"+\\n \\t\\t \\\"Precision at Recall 0.4: \\\"+Double.toString(precisionsAtRecalls[4])+\\\"\\\\n\\\"+\\n \\t\\t \\\"Precision at Recall 0.5: \\\"+Double.toString(precisionsAtRecalls[5])+\\\"\\\\n\\\"+\\n \\t\\t \\\"Precision at Recall 0.6: \\\"+Double.toString(precisionsAtRecalls[6])+\\\"\\\\n\\\"+\\n \\t\\t \\\"Precision at Recall 0.7: \\\"+Double.toString(precisionsAtRecalls[7])+\\\"\\\\n\\\"+\\n \\t\\t \\\"Precision at Recall 0.8: \\\"+Double.toString(precisionsAtRecalls[8])+\\\"\\\\n\\\"+\\n \\t\\t \\\"Precision at Recall 0.9: \\\"+Double.toString(precisionsAtRecalls[9])+\\\"\\\\n\\\"+\\n \\t\\t \\\"Precision at Recall 1.0: \\\"+Double.toString(precisionsAtRecalls[10])+\\\"\\\\n\\\"+\\n \\t\\t \\\"Average precision: \\\"+Double.toString(averagePrecision)+\\\"\\\\n\\\"+\\n \\t\\t \\\"NDCG at 1: \\\"+Double.toString(NDCGAt1)+\\\"\\\\n\\\"+\\n \\t\\t \\\"NDCG at 5: \\\"+Double.toString(NDCGAt5)+\\\"\\\\n\\\"+\\n \\t\\t \\\"NDCG at 10: \\\"+Double.toString(NDCGAt10)+\\\"\\\\n\\\"+\\n \\t\\t \\\"Reciprocal rank: \\\"+Double.toString(reciprocalRank);\\n\\t\\t\\t\\t\\t\\t\\t\\t\\n return output;\\n }\",\n \"@Override\\n\\tpublic String toString() {\\n\\t\\treturn weight + \\\"\\\\t\\\" + query;\\n\\t}\",\n \"public void doSearch(String query)\\n \\t{\\n \\t\\tlistener.onQueryTextSubmit(query);\\n \\t}\",\n \"public void splitQuery(){\\n for (int i=0;i<stemmed_query.size();i++){\\n String stemmed_term = stemmed_query.get(i);\\n for (int j=0;j<num_slave_client_threads;j++){\\n if (stemmed_term.compareTo(ServerThread.start_terms[j]) >= 0 && stemmed_term.compareTo(ServerThread.end_terms[j]) <= 0){\\n slave_queries.set(j, slave_queries.get(j)+\\\" \\\"+stemmed_term);\\n break;\\n }\\n }\\n }\\n }\",\n \"@Override\\n public void init(SearchHits hits) { \\n\\n \\tint numFbDocs = 50;\\n \\tint numFbTerms = 20;\\n \\tdouble lambda = 1.0;\\n \\tdouble alpha = 5.0;\\n \\t\\n if (paramTable.get(FB_DOCS) != null ) \\n \\tnumFbDocs = paramTable.get(FB_DOCS).intValue();\\n if (paramTable.get(FB_TERMS) != null ) \\n \\tnumFbTerms = paramTable.get(FB_TERMS).intValue();\\n if (paramTable.get(LAMBDA) != null ) \\n \\tlambda = paramTable.get(LAMBDA).doubleValue();\\n if (paramTable.get(ALPHA) != null ) \\n \\talpha = paramTable.get(ALPHA).doubleValue(); \\n \\n if (hits.size() < numFbDocs) \\n \\tnumFbDocs = hits.size();\\n \\n SearchHits fbDocs = new SearchHits(hits.hits().subList(0, numFbDocs));\\n FeedbackRelevanceModel rm = new FeedbackRelevanceModel();\\n rm.setDocCount(numFbDocs);\\n rm.setTermCount(numFbTerms);\\n rm.setIndex(index);\\n rm.setStopper(null);\\n rm.setRes(fbDocs);\\n rm.build(); \\n \\n FeatureVector rmVector = rm.asFeatureVector();\\n rmVector.clip(numFbTerms);\\n rmVector.normalize();\\n \\n TermTimeSeries ts = new TermTimeSeries(startTime, endTime, interval, \\n \\t\\trm.asFeatureVector().getFeatures());\\n \\n for (SearchHit hit: hits.hits()) {\\n \\t\\tlong docTime = TemporalScorer.getTime(hit);\\n \\t\\tdouble score = hit.getScore();\\n \\t\\tts.addDocument(docTime, score, hit.getFeatureVector());\\n }\\n \\n RUtil rutil = new RUtil();\\n \\n double sdps =0;\\n for (String term: rmVector.getFeatures()) {\\n \\tdouble[] tsw = ts.getTermFrequencies(term);\\n \\tif (sum(tsw) > 0) {\\n \\t\\ttry {\\n \\t\\t\\tsdps += rutil.dps(tsw);\\n \\t\\t} catch (Exception e) {\\n \\t\\t\\te.printStackTrace();\\n \\t\\t}\\n \\t}\\n } \\n \\n FeatureVector tsfv = new FeatureVector(null);\\n for (String term: rmVector.getFeatures()) {\\n \\tdouble[] termts = ts.getTermFrequencies(term);\\n \\ttry {\\n \\t\\tdouble dps = rutil.dps(termts)/sdps;\\n \\t\\t\\n \\tdouble weight = Math.pow(dps, alpha) * Math.pow(rmVector.getFeatureWeight(term), (1-alpha));\\n tsfv.addTerm(term, weight);\\n \\n \\t} catch (Exception e) {\\n \\t\\te.printStackTrace();\\n \\t}\\n }\\n tsfv.normalize();\\n\\n gQuery.getFeatureVector().normalize();\\n FeatureVector fv =\\n \\t\\tFeatureVector.interpolate(gQuery.getFeatureVector(), tsfv, lambda);\\n gQuery.setFeatureVector(fv);\\n \\n System.out.println(rmVector.toString(10));\\n System.out.println(tsfv.toString(10));\\n System.out.println(fv.toString(10));\\n rutil.close();\\n \\n }\",\n \"private void addQueries(String query){\\n ArrayList <String> idsFullSet = new ArrayList <String>(searchIDs);\\n while(idsFullSet.size() > 0){\\n ArrayList <String> idsSmallSet = new ArrayList <String>(); \\n if(debugMode) {\\n System.out.println(\\\"\\\\t Pmids not used in query available : \\\" + idsFullSet.size());\\n }\\n idsSmallSet.addAll(idsFullSet.subList(0,Math.min(getSearchIdsLimit(), idsFullSet.size())));\\n idsFullSet.removeAll(idsSmallSet);\\n String idsConstrain =\\\"\\\";\\n idsConstrain = idsConstrain(idsSmallSet);\\n addQuery(query,idsConstrain);\\n }\\n }\",\n \"public byte filter(Manager m, SearchRequest q, ResultSet rs, int DocAtNumber, int DocNo)\\n\\t{\\t\\t\\n\\t\\tString originalQuery = q.getOriginalQuery();\\n\\t\\t//highlight query terms only for the queries, \\n\\t\\t//which are not about finding related documents\\n\\t\\t//this check may be removed, because the preparation of the \\n\\t\\t//query terms for highlighting takes into account\\n\\t\\t//the related: operator\\n\\t\\tboolean highlightQueryTerms = true;\\n\\t\\tif (originalQuery.matches(\\\"\\\\\\\\brelated:\\\\\\\\d+\\\\\\\\b\\\") || //check if the query uses the related: operator \\n\\t\\t\\t!enableQueryTermsHighlight || //check if the highlighting of terms is enabled\\n\\t\\t\\thighlight.pattern().equals(\\\"(\\\\\\\\b)()(\\\\\\\\b)\\\")) //check if there are no query terms to highlight\\n\\t\\t\\thighlightQueryTerms = false;\\n\\t\\t\\n\\t\\tString[] qTerms = q.getOriginalQuery().replaceAll(\\\" \\\\\\\\w+\\\\\\\\p{Punct}\\\\\\\\w+ \\\",\\\" \\\").toLowerCase().split(\\\" \\\");\\n\\t\\t\\n\\t\\tString[] metadata = null;\\n\\t\\tint tmpSentence;\\n\\t\\tdouble tmpScore;\\n\\t\\tsynchronized(metaCache) {\\n\\t\\t\\ttry {\\n\\t\\t\\t\\tInteger DocNoObject = new Integer(DocNo);\\n\\t\\t\\t\\tif (metaCache.containsKey(DocNoObject))\\n\\t\\t\\t\\t\\t\\tmetadata = (String[]) metaCache.get(DocNoObject);\\n\\t\\t\\t\\telse {\\n\\t\\t\\t\\t\\tmetadata = metaIndex.getItems(keys, DocNo);\\n\\t\\t\\t\\t\\tmetaCache.put(DocNoObject,metadata);\\n\\t\\t\\t\\t}\\n\\t\\t\\t} catch(IOException ioe) {} \\n\\t\\t}\\n\\t\\n\\t\\tif (show_snippet)\\n\\t\\t{\\n\\t\\t\\tString extract = metadata[1];\\n\\t\\t\\tString[] sentences = sentencePattern.split(extract, 50); //use 50 sentences at most\\n\\t\\t\\tdouble[] sentenceScores = new double[sentences.length]; \\n\\t\\t\\tint frsSentence = -1;\\n\\t\\t\\tint sndSentence = -1;\\n\\t\\t\\tint top1Sentence = 0;\\n\\t\\t\\tint top2Sentence = 0;\\n\\t\\t\\tdouble max1Score = -1;\\n\\t\\t\\tdouble max2Score = 0;\\n\\t\\t\\tfinal int qTermsLength = qTerms.length;\\n\\t\\t\\tfor (int i=0; i<qTermsLength; i++) {\\n\\t\\t\\t\\tqTerms[i] = removeEndings.matcher(qTerms[i]).replaceAll(\\\"\\\");\\n\\t\\t\\t}\\n\\t\\t\\tString lowerCaseSentence;\\n\\t\\t\\tint sentenceLength;\\n\\t\\t\\tfinal int sentencesLength = sentences.length;\\n\\n\\t\\t\\tfor (int i=0; i<sentencesLength; i++) {\\n\\t\\t\\t\\t\\n\\t\\t\\t\\tlowerCaseSentence = sentences[i].toLowerCase();\\n\\t\\t\\t\\tsentenceLength=sentences[i].length();\\n\\t\\t\\t\\tif (sentenceLength < 20 || sentenceLength > 250) {\\n\\t\\t\\t\\t\\tfor (int j=0; j<qTermsLength; j++) {\\n\\t\\t\\t\\t\\t\\tif (lowerCaseSentence.indexOf(qTerms[j])>=0) {\\n\\t\\t\\t\\t\\t\\t\\tsentenceScores[i]+=1.0d + sentenceLength / (20.0d + sentenceLength);\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t} else {\\n\\t\\t\\t\\t\\tfor (int j=0; j<qTermsLength; j++) {\\n\\t\\t\\t\\t\\t\\tif (lowerCaseSentence.indexOf(qTerms[j])>=0) {\\n\\t\\t\\t\\t\\t\\t\\tsentenceScores[i]+=qTerms[j].length() + sentenceLength / (1.0d + sentenceLength);\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t}\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t//do your best to get at least a second sentence for the snippet, \\n\\t\\t\\t\\t//after having found the first one\\n\\t\\t\\t\\tif (frsSentence > -1 && sndSentence == -1 && sentenceLength > 5) {\\n\\t\\t\\t\\t\\tsndSentence = i;\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\t//do your best to get at least one sentence for the snippet\\n\\t\\t\\t\\tif (frsSentence == -1 && sentenceLength > 5) { \\n\\t\\t\\t\\t\\tfrsSentence = i;\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\tif (max2Score < sentenceScores[i]) {\\n\\t\\t\\t\\t\\tmax2Score = sentenceScores[i];\\n\\t\\t\\t\\t\\ttop2Sentence = i;\\n\\t\\t\\t\\t\\t//logger.debug(\\\"top 2 sentence is \\\" + i);\\n\\t\\t\\t\\t\\tif (max2Score > max1Score) {\\n\\t\\t\\t\\t\\t\\ttmpScore = max1Score; max1Score = max2Score; max2Score = tmpScore;\\n\\t\\t\\t\\t\\t\\ttmpSentence = top1Sentence; top1Sentence = top2Sentence; top2Sentence = tmpSentence;\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t}\\n\\t\\t\\tint lastIndexOfSpace = -1;\\n\\t\\t\\tString sentence=\\\"\\\";\\n\\t\\t\\tString secondSentence=\\\"\\\";\\n\\t\\t\\tString snippet = \\\"\\\";\\n\\t\\t\\tif (max1Score == -1) {\\n\\t\\t\\t\\tif (frsSentence>=0) {\\n\\t\\t\\t\\t\\tsentence = sentences[frsSentence];\\n\\t\\t\\t\\t\\tif (sentence.length() > 100) {\\n\\t\\t\\t\\t\\t\\tlastIndexOfSpace = sentence.substring(0, 100).lastIndexOf(\\\" \\\");\\n\\t\\t\\t\\t\\t\\tsentence = sentence.substring(0, lastIndexOfSpace > 0 ? lastIndexOfSpace : 100);\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\n\\t\\t\\t\\tif (sndSentence>=0) {\\n\\t\\t\\t\\t\\tsecondSentence = sentences[sndSentence];\\n\\t\\t\\t\\t\\tif (secondSentence.length() > 100) {\\n\\t\\t\\t\\t\\t\\tlastIndexOfSpace = secondSentence.substring(0, 100).lastIndexOf(\\\" \\\");\\n\\t\\t\\t\\t\\t\\tsecondSentence = secondSentence.substring(0, lastIndexOfSpace>0 ? lastIndexOfSpace : 100);\\n\\t\\t\\t\\t\\t}\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\n\\t\\t\\t\\tif (frsSentence >=0 && sndSentence >= 0) \\n\\t\\t\\t\\t\\tsnippet = sentence.trim() + \\\"...\\\" + secondSentence.trim();\\n\\t\\t\\t\\telse if (frsSentence >= 0 && sndSentence<0) \\n\\t\\t\\t\\t\\tsnippet = sentence.trim();\\n\\t\\t\\t\\t\\n\\t\\t\\t} else if (sentences[top1Sentence].length()<100 && top1Sentence!=top2Sentence) {\\n\\t\\t\\t\\tsentence = sentences[top1Sentence];\\n\\t\\t\\t\\tif (sentence.length() > 100) {\\n\\t\\t\\t\\t\\tlastIndexOfSpace = sentence.substring(0, 100).lastIndexOf(\\\" \\\");\\n\\t\\t\\t\\t\\tsentence = sentence.substring(0, lastIndexOfSpace > 0 ? lastIndexOfSpace : 100);\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\tsecondSentence = sentences[top2Sentence];\\n\\t\\t\\t\\tif (secondSentence.length() > 100) {\\n\\t\\t\\t\\t\\tlastIndexOfSpace = secondSentence.substring(0, 100).lastIndexOf(\\\" \\\");\\n\\t\\t\\t\\t\\tsecondSentence = secondSentence.substring(0, lastIndexOfSpace>0 ? lastIndexOfSpace : 100);\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\tsnippet = sentence.trim() + \\\"...\\\" + secondSentence.trim();\\n\\t\\t\\t} else {\\n\\t\\t\\t\\tsentence = sentences[top1Sentence];\\n\\t\\t\\t\\tif (sentence.length()>200) {\\n\\t\\t\\t\\t\\tlastIndexOfSpace = sentence.substring(0, 200).lastIndexOf(\\\" \\\");\\n\\t\\t\\t\\t\\tsentence = sentence.substring(0, lastIndexOfSpace > 0 ? lastIndexOfSpace : 200);\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\tsnippet = sentence.trim();\\n\\t\\t\\t}\\n\\t\\t\\t\\n\\t\\t\\t//checking and removing any control characters\\n\\t\\t\\tcontrolNonVisibleCharactersMatcher.reset(snippet);\\n\\t\\t\\tsnippet = controlNonVisibleCharactersMatcher.replaceAll(\\\"\\\");\\n\\t\\t\\t\\n\\t\\t\\t//String escapedSnippet = StringEscapeUtils.escapeHtml(snippet);\\n\\t\\t\\t//if (highlightQueryTerms)\\n\\t\\t\\t//\\tescapedSnippet = highlight.matcher(escapedSnippet).replaceAll(\\\"$1<b>$2</b>$3\\\");\\n\\t\\t\\tif (highlightQueryTerms)\\n\\t\\t\\t\\tsnippet = highlight.matcher(snippet).replaceAll(\\\"$1<b>$2</b>$3\\\");\\n\\t\\t\\t//else \\n\\t\\t\\t//\\tsnippet = StringEscapeUtils.escapeHtml(snippet);\\n\\t\\t\\t\\n\\t\\t\\t//change by Vassilis, 20/09/2006\\n\\t\\t\\t//disabling the xml escaping in order to move the data into ![CDATA[ ]]\\n\\t\\t\\t//the code was:\\n\\t\\t\\t//rs.addMetaItem(\\\"snippet\\\", DocAtNumber, StringEscapeUtils.escapeXml(snippet));\\n\\t\\t\\t//and now it is:\\n\\t\\t\\t//snippet.replaceAll(\\\"[^\\\\\\\\u0009\\\\\\\\u000A\\\\\\\\u000D\\\\\\\\u0020-\\\\\\\\uD7FF\\\\\\\\uE000-\\\\\\\\uFFFD\\\\\\\\u10000-\\\\\\\\u10FFFF]\\\",\\\"\\\");\\n\\t\\t\\trs.addMetaItem(\\\"snippet\\\", DocAtNumber, snippet);\\n\\t\\t\\t\\n\\t\\t}\\n\\t\\tif (show_title)\\n\\t\\t{\\n\\t\\t\\tString title = metadata[2];\\n\\t\\t\\t\\n\\t\\t\\t//checking and removing any control characters\\n\\t\\t\\tcontrolNonVisibleCharactersMatcher.reset(title);\\n\\t\\t\\ttitle = controlNonVisibleCharactersMatcher.replaceAll(\\\"\\\");\\n\\t\\t\\ttitle = (highlightQueryTerms)\\n\\t\\t\\t\\t ? highlight.matcher(metadata[2]).replaceAll(\\\"$1<b>$2</b>$3\\\") \\n\\t\\t\\t\\t : metadata[2];\\n\\t\\t\\t\\n\\t\\t\\t\\n\\t\\t\\t//String escapedTitle = StringEscapeUtils.escapeHtml(metadata[2]);\\n\\t\\t\\t//String title = (highlightQueryTerms)\\n\\t\\t\\t//\\t\\t\\t ? highlight.matcher(escapedTitle).replaceAll(\\\"$1<b>$2</b>$3\\\") \\n\\t\\t\\t//\\t\\t\\t : escapedTitle;\\n\\t\\t\\t//String title = (highlightQueryTerms) \\n\\t\\t\\t//\\t\\t? highlight.matcher(metadata[2]).replaceAll(\\\"$1<b>$2</b>$3\\\") \\n\\t\\t\\t//\\t\\t: metadata[2];\\n\\n\\t\\t\\t//change by Vassilis, 20/09/2006\\n\\t\\t\\t//disabling the xml escaping in order to move the data into ![CDATA[ ]]\\n\\t\\t\\t//the code was:\\n\\t\\t\\t//rs.addMetaItem(\\\"title\\\", DocAtNumber, StringEscapeUtils.escapeXml(title));\\n\\t\\t\\t//and now is:\\n\\t\\t\\t//title.replaceAll(\\\"[^\\\\\\\\u0009\\\\\\\\u000A\\\\\\\\u000D\\\\\\\\u0020-\\\\\\\\uD7FF\\\\\\\\uE000-\\\\\\\\uFFFD\\\\\\\\u10000-\\\\\\\\u10FFFF]\\\",\\\"\\\");\\n\\t\\t\\trs.addMetaItem(\\\"title\\\", DocAtNumber, title);\\n\\t\\t\\t\\n\\t\\t}\\n\\t\\tif (!show_docid_early && show_docid)\\n\\t\\t{\\n\\t\\t\\trs.addMetaItem(\\\"docid\\\", DocAtNumber, docIndex.getDocumentNumber(DocNo));\\n\\t\\t}\\n\\t\\tif (!show_url_early && show_url)\\n\\t\\t{\\n\\n\\t\\t\\trs.addMetaItem(\\\"url\\\", DocAtNumber, StringEscapeUtils.escapeXml(metadata[0]));\\n\\t\\t}\\n\\t\\t\\n\\t\\treturn FILTER_OK;\\n\\t}\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.713265","0.67490345","0.6708787","0.6570831","0.65290445","0.65091664","0.6301124","0.62564147","0.62462723","0.62303966","0.6121615","0.6092577","0.60881495","0.6067615","0.6061933","0.60572237","0.6025526","0.59403056","0.5899081","0.58948946","0.5887808","0.5887068","0.5864838","0.58580875","0.5853241","0.58524257","0.5845645","0.5837921","0.5837022","0.5825521","0.58220243","0.5820077","0.5803137","0.5726654","0.5679536","0.5675475","0.56683815","0.564162","0.56369144","0.56121457","0.5604361","0.5595679","0.55587804","0.5549475","0.55488926","0.55241674","0.5520853","0.55040574","0.5493972","0.5485638","0.5479736","0.5455311","0.543085","0.5424341","0.5389106","0.5379557","0.53745854","0.5352378","0.53452796","0.533532","0.5317884","0.5313038","0.52934","0.5284727","0.52823675","0.5276282","0.5265649","0.52643824","0.52623487","0.52522624","0.5248299","0.52344877","0.522835","0.5220491","0.5213272","0.5203328","0.5188717","0.51854587","0.517874","0.5167496","0.51624376","0.51594985","0.5156694","0.5149749","0.51480454","0.51459414","0.5144377","0.513359","0.5132872","0.5131469","0.5130192","0.51292807","0.5125858","0.51187575","0.5116828","0.5114698","0.5110938","0.5104272","0.5102763","0.51016533"],"string":"[\n \"0.713265\",\n \"0.67490345\",\n \"0.6708787\",\n \"0.6570831\",\n \"0.65290445\",\n \"0.65091664\",\n \"0.6301124\",\n \"0.62564147\",\n \"0.62462723\",\n \"0.62303966\",\n \"0.6121615\",\n \"0.6092577\",\n \"0.60881495\",\n \"0.6067615\",\n \"0.6061933\",\n \"0.60572237\",\n \"0.6025526\",\n \"0.59403056\",\n \"0.5899081\",\n \"0.58948946\",\n \"0.5887808\",\n \"0.5887068\",\n \"0.5864838\",\n \"0.58580875\",\n \"0.5853241\",\n \"0.58524257\",\n \"0.5845645\",\n \"0.5837921\",\n \"0.5837022\",\n \"0.5825521\",\n \"0.58220243\",\n \"0.5820077\",\n \"0.5803137\",\n \"0.5726654\",\n \"0.5679536\",\n \"0.5675475\",\n \"0.56683815\",\n \"0.564162\",\n \"0.56369144\",\n \"0.56121457\",\n \"0.5604361\",\n \"0.5595679\",\n \"0.55587804\",\n \"0.5549475\",\n \"0.55488926\",\n \"0.55241674\",\n \"0.5520853\",\n \"0.55040574\",\n \"0.5493972\",\n \"0.5485638\",\n \"0.5479736\",\n \"0.5455311\",\n \"0.543085\",\n \"0.5424341\",\n \"0.5389106\",\n \"0.5379557\",\n \"0.53745854\",\n \"0.5352378\",\n \"0.53452796\",\n \"0.533532\",\n \"0.5317884\",\n \"0.5313038\",\n \"0.52934\",\n \"0.5284727\",\n \"0.52823675\",\n \"0.5276282\",\n \"0.5265649\",\n \"0.52643824\",\n \"0.52623487\",\n \"0.52522624\",\n \"0.5248299\",\n \"0.52344877\",\n \"0.522835\",\n \"0.5220491\",\n \"0.5213272\",\n \"0.5203328\",\n \"0.5188717\",\n \"0.51854587\",\n \"0.517874\",\n \"0.5167496\",\n \"0.51624376\",\n \"0.51594985\",\n \"0.5156694\",\n \"0.5149749\",\n \"0.51480454\",\n \"0.51459414\",\n \"0.5144377\",\n \"0.513359\",\n \"0.5132872\",\n \"0.5131469\",\n \"0.5130192\",\n \"0.51292807\",\n \"0.5125858\",\n \"0.51187575\",\n \"0.5116828\",\n \"0.5114698\",\n \"0.5110938\",\n \"0.5104272\",\n \"0.5102763\",\n \"0.51016533\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.7497625"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":13889,"cells":{"query":{"kind":"string","value":"Which terms should be considered? Based on Index elimination theory, idfthresholding!"},"document":{"kind":"string","value":"public Set<String> queryTermsConsidered(Query query, double idf_threshold){\n double idf, nDocs = this.docIDs.size();\n String term;\n\n Set<String> termsToConsider = new HashSet<String>();\n\n Iterator<String> it = query.terms.iterator();\n while(it.hasNext()){\n term = it.next();\n idf = -1;\n if(this.idfMap.containsKey(term))\n idf = Math.log(nDocs/new Double(this.idfMap.get(term)));\n if (idf >= idf_threshold){\n termsToConsider.add(term);\n }\n /*else{\n System.err.println(term + \" not considered since idf = \" + idf);\n }*/\n }\n\n return termsToConsider;\n\n }"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["public abstract int numberOfTerms();","int DF(String term) {\n for (int i = 0; i < count1; i++) {\n if (economydocument[i].contains(term)) {\n df++;\n }\n }\n for (int i = 0; i < count2; i++) {\n if (educationdocument[i].contains(term)) {\n df++;\n }\n }\n for (int i = 0; i < count3; i++) {\n if (sportdocument[i].contains(term)) {\n df++;\n }\n }\n for (int i = 0; i < count4; i++) {\n if (culturedocument[i].contains(term)) {\n df++;\n }\n }\n for (int i = 0; i < count5; i++) {\n if (accedentdocument[i].contains(term)) {\n df++;\n }\n }\n for (int i = 0; i < count6; i++) {\n if (environmntaldocument[i].contains(term)) {\n df++;\n }\n }\n for (int i = 0; i < count7; i++) {\n if (foreign_affairdocument[i].contains(term)) {\n df++;\n }\n }\n for (int i = 0; i < count8; i++) {\n if (law_justicedocument[i].contains(term)) {\n df++;\n }\n }\n for (int i = 0; i < count9; i++) {\n if (agriculture[i].contains(term)) {\n df++;\n }\n }\n for (int i = 0; i < count10; i++) {\n if (politicsdocument[i].contains(term)) {\n df++;\n }\n }\n for (int i = 0; i < count12; i++) {\n if (science_technologydocument[i].contains(term)) {\n df++;\n }\n }\n for (int i = 0; i < count13; i++) {\n if (healthdocument[i].contains(term)) {\n df++;\n }\n }\n for (int i = 0; i < count14; i++) {\n if (army[i].contains(term)) {\n df++;\n }\n }\n return df;\n }","public int getTermIndex() {return termIndex;}","private void termQuerySearch(String[] terms) {\n for (String term : terms) {\n LinkedList<TermPositions> postingLists = indexMap.get(analyzeTerm(term));\n if (postingLists != null) {\n for (TermPositions matches : postingLists) {\n double score = (double) 1 + Math.log((double) matches.getPositionList().size()) *\n Math.log((double) N / (double) postingLists.size());\n resultsCollector.add(new DocCollector(matches.getDocId(), score));\n }\n }\n }\n }","static void returnTfIdfResults() {\n\t\tSet<String> specificWords = findKeywords();\n\n\t\t// for every phrase\n\t\tfor (String word : specificWords) {\n\t\t\t// get the total number of documents\n\t\t\tdouble totalSize = size;\n\n\t\t\t// get the collection of documents containing that word\n\t\t\tCollection<File> containingWordSet = invertedMap.getValues(word);\n\n\t\t\t// makes a new one if null (for ease of code)\n\t\t\tif (containingWordSet == null) {\n\t\t\t\tcontainingWordSet = new HashSet<File>();\n\t\t\t}\n\n\t\t\t// the number containing the word\n\t\t\tdouble numContainingWord = containingWordSet.size();\n\n\t\t\t// get the idf (log(total/(1 + |# contain word|)\n\t\t\t// it is normalize with 1 to prevent division by 0\n\t\t\tdouble idf = Math.log(totalSize / (1 + numContainingWord));\n\n\t\t\t// System.out.println(\"------------------\");\n\t\t\t// System.out.println(word + \" totalSize \" + totalSize);\n\t\t\t// System.out.println(word + \" numContainingWord \" +\n\t\t\t// numContainingWord);\n\t\t\t// System.out.println(word + \" idf \" + idf);\n\t\t\t// System.out.println(\"------------------\");\n\n\t\t\t// set the wordscore to 0\n\t\t\tdouble wordScore = 0;\n\n\t\t\t// for all of the files with the word\n\t\t\tfor (File file : containingWordSet) {\n\t\t\t\tString fileName = file.getName();\n\n\t\t\t\t// get the phrase count for this document\n\t\t\t\tInteger phraseCount = phraseCountMap.get(fileName);\n\t\t\t\tdouble numPhrases = phraseCount.doubleValue();\n\n\t\t\t\t// get the word frequency map for this page\n\t\t\t\tHashMap<String, Integer> docFreqMap = wordFreqMap.get(fileName);\n\t\t\t\tInteger freq = docFreqMap.get(word);\n\n\t\t\t\t// otherwise, get the tf\n\t\t\t\tdouble tf;\n\t\t\t\tif (freq == null) {\n\t\t\t\t\t// if it's not present, it's 0\n\t\t\t\t\ttf = 0;\n\t\t\t\t} else {\n\t\t\t\t\t// otherwise, it's the value\n\t\t\t\t\ttf = freq / numPhrases;\n\t\t\t\t\t// System.out.println(tf);\n\t\t\t\t}\n\n\t\t\t\t// multiply for this score\n\t\t\t\tdouble score = tf * idf;\n\n\t\t\t\t// add it to the page score\n\t\t\t\twordScore += score;\n\t\t\t}\n\n\t\t\t// make a node with the sum of tf-idf for all relevant phrases and\n\t\t\t// add to pq\n\t\t\tWordNode w = new WordNode(word, wordScore);\n\t\t\tpq.add(w);\n\t\t}\n\t}","@Override\n public int getTermFrequency(String term) {\n return 0;\n }","private double idf(String term) {\n return 1 + Math.log(this.numberOfDocuments / (double) termToDocumentsContainingTerm.get(term).size());\n }","void documentFrequncy(Set<String> features,\n int index,\n int troush\n ) {\n for (String str : features) {\n switch (index) {\n case 1:\n for (int i = 0; i < count1; i++) {\n if (economydocument[i].contains(str)) {\n e++;\n }\n }\n if (e > troush) {\n documntfrequencyeco.put(str, e);\n }\n e = 0;\n break;\n case 2:\n for (int i = 0; i < count2; i++) {\n if (educationdocument[i].contains(str)) {\n e++;\n }\n }\n if (e > troush) {\n documntfrequencyedu.put(str, e);\n }\n e = 0;\n break;\n case 3:\n for (int i = 0; i < count3; i++) {\n if (sportdocument[i].contains(str)) {\n e++;\n }\n }\n if (e > troush) {\n documntfrequencyspo.put(str, e);\n }\n e = 0;\n break;\n case 4:\n for (int i = 0; i < count4; i++) {\n if (culturedocument[i].contains(str)) {\n e++;\n }\n }\n if (e > troush) {\n documntfrequencycul.put(str, e);\n }\n e = 0;\n break;\n case 5:\n for (int i = 0; i < count5; i++) {\n if (accedentdocument[i].contains(str)) {\n e++;\n }\n }\n if (e > troush) {\n documntfrequencyaccid.put(str, e);\n }\n e = 0;\n break;\n case 6:\n for (int i = 0; i < count6; i++) {\n if (environmntaldocument[i].contains(str)) {\n e++;\n }\n }\n if (e > troush) {\n documntfrequencyenv.put(str, e);\n }\n e = 0;\n break;\n case 7:\n for (int i = 0; i < count7; i++) {\n if (foreign_affairdocument[i].contains(str)) {\n e++;\n }\n }\n if (e > troush) {\n documntfrequencydep.put(str, e);\n }\n e = 0;\n break;\n case 8:\n for (int i = 0; i < count8; i++) {\n if (law_justicedocument[i].contains(str)) {\n e++;\n }\n }\n if (e > troush) {\n documntfrequencylaw.put(str, e);\n }\n e = 0;\n break;\n case 9:\n for (int i = 0; i < count9; i++) {\n if (agriculture[i].contains(str)) {\n e++;\n }\n }\n if (e > troush) {\n documntfrequencyagri.put(str, e);\n }\n e = 0;\n break;\n case 10:\n for (int i = 0; i < count10; i++) {\n if (politicsdocument[i].contains(str)) {\n e++;\n }\n }\n if (e > troush) {\n documntfrequencypoltics.put(str, e);\n }\n e = 0;\n break;\n// case 11:\n//\n// for (int i = 0; i < count11; i++) {\n// if (social_affairsdocument[i].contains(str)) {\n// e++;\n// }\n// }\n// if (e > troush) {\n// documntfrequencysocial.put(str, e);\n// }\n// e = 0;\n// break;\n case 11:\n for (int i = 0; i < count12; i++) {\n if (science_technologydocument[i].contains(str)) {\n e++;\n }\n }\n\n if (e > troush) {\n documntfrequencysci.put(str, e);\n }\n e = 0;\n break;\n case 12:\n for (int i = 0; i < count13; i++) {\n if (healthdocument[i].contains(str)) {\n e++;\n }\n }\n if (e > troush) {\n documntfrequencyhel.put(str, e);\n }\n e = 0;\n break;\n case 13:\n for (int i = 0; i < count14; i++) {\n if (army[i].contains(str)) {\n e++;\n }\n }\n\n if (e > troush) {\n documntfrequencyarmy.put(str, e);\n }\n e = 0;\n break;\n default:\n break;\n }\n\n }\n }","public ComputeTermFrequencies() { super(); }","public double numTerms()\r\n\t{\r\n\t\treturn unionAll.size();\r\n\t}","abstract public int docFreq(Term t) throws IOException;","@Override\n public int getIndexByTerm(String term) {\n return 0;\n }","public static void calcuTFIDF() throws IOException {\n\n\t\tHashtable<String, Double> idf = new Hashtable<String, Double>();\n\t\tArrayList<String> terms = new ArrayList<String>();\n\t\tdouble fileCount = 0.0;\n\t\tString featurePath = \"./corpus/features\";\n\t\tString featureWeight = \"./corpus/featureWeight\";\n\t\tString trainPath = \"./corpus/trainData\";\n\t\tString testPath = \"./corpus/testData\";\n\t\tString stopPath = \"./corpus/english.stop\";\n\t\tString trainOutPath = \"./corpus/trainVectors\";\n\t\tString testOutPath = \"./corpus/testVectors\";\n\t\tBufferedReader br = new BufferedReader(new FileReader(featurePath));\n\t\tBufferedWriter featureWriter = new BufferedWriter(new FileWriter(\n\t\t\t\tfeatureWeight));\n\t\tBufferedReader trainReader = new BufferedReader(new FileReader(\n\t\t\t\ttrainPath));\n\t\tBufferedReader testReader = new BufferedReader(new FileReader(testPath));\n\t\tBufferedReader br2 = new BufferedReader(new FileReader(stopPath));\n\t\tBufferedWriter writer = new BufferedWriter(new FileWriter(trainOutPath));\n\t\tBufferedWriter testWriter = new BufferedWriter(new FileWriter(\n\t\t\t\ttestOutPath));\n\t\tString oneline;\n\t\tArrayList<String> as = new ArrayList<String>();\n\t\twhile ((oneline = br2.readLine()) != null) {\n\t\t\tas.add(oneline);\n\t\t}\n\t\tString[] stopWords = new String[as.size()];\n\t\tas.toArray(stopWords);\n\t\tAnalyzer analyzer = new SnowballAnalyzer(\"English\", stopWords);\n\n\t\twhile ((oneline = br.readLine()) != null) {\n\t\t\tidf.put(oneline, 0.0);\n\t\t\tterms.add(oneline);\n\t\t}\n\n\t\twhile ((oneline = trainReader.readLine()) != null) {\n\n\t\t\tint pos = oneline.indexOf(\"\\t\");\n\t\t\tString topic = oneline.substring(0, pos);\n\t\t\tString content = oneline.substring(pos + 1);\n\t\t\tfileCount++;\n\t\t\tHashtable<String, Integer> termList = new Hashtable<String, Integer>();\n\t\t\tTokenStream stream = analyzer.tokenStream(\"\", new StringReader(\n\t\t\t\t\tcontent));\n\t\t\twhile (true) {\n\t\t\t\tToken token = stream.next();\n\t\t\t\tif (token == null)\n\t\t\t\t\tbreak;\n\t\t\t\tString tmp = token.termText();\n\t\t\t\tif (!termList.containsKey(tmp))\n\t\t\t\t\ttermList.put(tmp, new Integer(1));\n\t\t\t}\n\t\t\tSet<String> keys = termList.keySet();\n\t\t\tfor (String tmp : keys) {\n\t\t\t\tif (idf.containsKey(tmp)) {\n\t\t\t\t\tDouble num = idf.get(tmp);\n\t\t\t\t\tidf.put(tmp, num + 1);\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\n\t\tfor (String term : terms) {\n\n\t\t\tdouble weightOfTerm = Math.log((double) fileCount / idf.get(term)\n\t\t\t\t\t+ 0.01);\n\t\t\tfeatureWriter.write(term + \" \" + weightOfTerm);\n\t\t\tfeatureWriter.newLine();\n\t\t\tidf.put(term, weightOfTerm);\n\n\t\t}\n\t\tfeatureWriter.flush();\n\t\tfeatureWriter.close();\n\n\t\ttrainReader = new BufferedReader(new FileReader(trainPath));\n\t\twhile ((oneline = trainReader.readLine()) != null) {\n\n\t\t\tint pos = oneline.indexOf(\"\\t\");\n\t\t\tString topic = oneline.substring(0, pos);\n\t\t\tString content = oneline.substring(pos + 1);\n\t\t\tHashtable<String, Integer> termFrequent = new Hashtable<String, Integer>();\n\t\t\tTokenStream stream = analyzer.tokenStream(\"\", new StringReader(\n\t\t\t\t\tcontent));\n\t\t\twhile (true) {\n\t\t\t\tToken token = stream.next();\n\t\t\t\tif (token == null)\n\t\t\t\t\tbreak;\n\t\t\t\tString tmp = token.termText();\n\t\t\t\tif (!termFrequent.containsKey(tmp))\n\t\t\t\t\ttermFrequent.put(tmp, new Integer(1));\n\t\t\t\telse {\n\t\t\t\t\tInteger num = termFrequent.get(tmp);\n\t\t\t\t\ttermFrequent.put(tmp, num + 1);\n\t\t\t\t}\n\t\t\t}\n\t\t\tdouble weights[] = new double[terms.size()];\n\t\t\tdouble denominator = 0.0;\n\t\t\tint i = 0;\n\t\t\tfor (String term : terms) {\n\t\t\t\tdouble count;\n\t\t\t\tif (termFrequent.containsKey(term)) {\n\t\t\t\t\tcount = termFrequent.get(term);\n\t\t\t\t} else {\n\t\t\t\t\tcount = 0;\n\t\t\t\t}\n\n\t\t\t\tdouble tmp = count * idf.get(term);\n\t\t\t\tdenominator += tmp;\n\t\t\t\tweights[i++] = tmp;\n\t\t\t}\n\t\t\tdenominator = Math.sqrt(denominator);\n\t\t\twriter.write(topic);\n\t\t\tfor (int j = 1; j <= weights.length; j++) {\n\t\t\t\tdouble tmp = weights[j - 1];\n\t\t\t\tif (tmp > 0.0) {\n\t\t\t\t\ttmp = Math.sqrt(tmp) / denominator;\n\t\t\t\t\twriter.write(\" \" + j + \":\" + tmp);\n\t\t\t\t}\n\t\t\t}\n\t\t\twriter.newLine();\n\t\t}\n\n\t\twhile ((oneline = testReader.readLine()) != null) {\n\n\t\t\tint pos = oneline.indexOf(\"\\t\");\n\t\t\tString topic = oneline.substring(0, pos);\n\t\t\tString content = oneline.substring(pos + 1);\n\t\t\tHashtable<String, Integer> termFrequent = new Hashtable<String, Integer>();\n\t\t\tTokenStream stream = analyzer.tokenStream(\"\", new StringReader(\n\t\t\t\t\tcontent));\n\t\t\twhile (true) {\n\t\t\t\tToken token = stream.next();\n\t\t\t\tif (token == null)\n\t\t\t\t\tbreak;\n\t\t\t\tString tmp = token.termText();\n\t\t\t\tif (!termFrequent.containsKey(tmp))\n\t\t\t\t\ttermFrequent.put(tmp, new Integer(1));\n\t\t\t\telse {\n\t\t\t\t\tInteger num = termFrequent.get(tmp);\n\t\t\t\t\ttermFrequent.put(tmp, num + 1);\n\t\t\t\t}\n\t\t\t}\n\t\t\tdouble weights[] = new double[terms.size()];\n\t\t\tdouble denominator = 0.0;\n\t\t\tint i = 0;\n\t\t\tfor (String term : terms) {\n\t\t\t\tdouble count;\n\t\t\t\tif (termFrequent.containsKey(term)) {\n\t\t\t\t\tcount = termFrequent.get(term);\n\t\t\t\t} else {\n\t\t\t\t\tcount = 0;\n\t\t\t\t}\n\t\t\t\tdouble tmp = count * idf.get(term);\n\t\t\t\tdenominator += tmp;\n\t\t\t\tweights[i++] = tmp;\n\t\t\t}\n\t\t\tdenominator = Math.sqrt(denominator);\n\t\t\ttestWriter.write(topic);\n\t\t\tfor (int j = 1; j <= weights.length; j++) {\n\t\t\t\tdouble tmp = weights[j - 1];\n\t\t\t\tif (tmp > 0.0) {\n\t\t\t\t\ttmp = Math.sqrt(tmp) / denominator;\n\t\t\t\t\ttestWriter.write(\" \" + j + \":\" + tmp);\n\t\t\t\t}\n\t\t\t}\n\t\t\ttestWriter.newLine();\n\t\t}\n\t\twriter.close();\n\t\ttestWriter.close();\n\t}","private void calculateIdf(){\r\n\t\tIdf = new HashMap<>();\r\n\t\tOcc = new HashMap<>();\r\n\t\t\r\n\t\tfor (Entry<String, Document> doc : Docs.entrySet()){\r\n\t\t\tdoc.getValue().wordSet.forEach(word -> {\r\n\t\t\t\tdouble count = Idf.containsKey(word) ? Idf.get(word) : 0;\r\n \tIdf.put(word, count+1);\r\n\t\t\t});\r\n\t\t\t\r\n\t\t\tdoc.getValue().words.forEach((w, o) -> words.add(w));\r\n\t\t\t\r\n\t\t}\r\n\t\t\r\n\t\tfor (Entry<String, Double> e : new HashMap<>(Idf).entrySet()){\r\n\t\t\tIdf.put(e.getKey(),\r\n\t\t\t\t\tMath.log(Idf.keySet().size() / e.getValue()));\r\n\t\t}\r\n\t}","public List<OWLObject> search(OWLObject queryObj) {\n\t\tList<OWLObject> hits = new ArrayList<OWLObject>(maxHits);\n\t\tSystem.out.println(\"gettings atts for \"+queryObj+\" -- \"+simEngine.comparisonProperty);\n\t\tSet<OWLObject> atts = simEngine.getAttributeClosureFor(queryObj);\n\t\tSystem.out.println(\"all atts: \"+atts.size());\n\t\tif (atts.size() == 0)\n\t\t\treturn hits;\n\t\t\n\t\t// only compare using significant atts;\n\t\t// we don't do the same test on candidates as these will be removed by the\n\t\t// intersection operation. they will have a small effect on the score, as\n\t\t// we don't divide by the union, but instead the sum of sizes\n\t\tatts = filterNonSignificantAttributes(atts);\n\t\tSystem.out.println(\"filtered atts: \"+atts.size());\n\n\t\t//bloomFilter = new BloomFilter<OWLObject>(0.05, atts.size());\n\t\t//bloomFilter.addAll(atts);\n\t\t\t\t\n\t\tSortedMap<Integer,Set<OWLObject>> scoreCandidateMap = new TreeMap<Integer,Set<OWLObject>>();\n\t\t\n\t\tfor (OWLObject candidate : getCandidates()) {\n\t\t\tif (candidate.equals(queryObj))\n\t\t\t\tcontinue;\n\t\t\tSet<OWLObject> iAtts = simEngine.getAttributeClosureFor(candidate);\n\t\t\t//Set<OWLObject> iAtts = simEngine.getGraph().getAncestors(candidate);\n\n\t\t\tif (iAtts.size() == 0)\n\t\t\t\tcontinue;\n\t\t\tint cAttsSize = iAtts.size();\n\t\n\t\t\tiAtts.retainAll(atts);\n\t\t\t//Collection<OWLObject> iAtts = bloomFilter.intersection(cAtts);\n\t\t\t\n\t\t\t// simJ, one-sided, scaled by 1000\n\t\t\t// negate to ensure largest first\n\t\t\t//Integer score = - (iAtts.size() * 1000 / cAttsSize);\n\t\t\t\n\t\t\t// this biases us towards genes with large numbers of annotations,\n\t\t\t// but it is better at finding the models that share all features\n\t\t\tInteger score = - iAtts.size();\n\t\t\tif (!scoreCandidateMap.containsKey(score)) \n\t\t\t\tscoreCandidateMap.put(score, new HashSet<OWLObject>());\n\t\t\tscoreCandidateMap.get(score).add(candidate);\n\t\t\treporter.report(this,\"query_candidate_overlap_total\",queryObj,candidate,iAtts.size(),cAttsSize);\n\t\t}\n\t\t\n\t\tint n = 0;\n\t\tfor (Set<OWLObject> cs : scoreCandidateMap.values()) {\n\t\t\tn += cs.size();\n\t\t\thits.addAll(cs);\n\t\t}\n\t\t\n\t\tn = 0;\n\t\tfor (OWLObject hit : hits) {\n\t\t\tn++;\n\t\t\treporter.report(this,\"query_hit_rank_threshold\",queryObj,hit,n,maxHits);\n\t\t}\n\t\tif (hits.size() > maxHits)\n\t\t\thits = hits.subList(0, maxHits);\n\t\t\n\n\n\t\treturn hits;\n\t}","public void calculateTermWeights() {\n\t\tfor (String termString : terms.keySet()) {\n\t\t\tTerm t = terms.get(termString);\n\t\t\tMap<Integer, TermDoc> posting = t.getPostings();\n\n\t\t\t// Iterate through the docs in which the selected term is found.\n\t\t\tfor (Integer docId : posting.keySet()) {\n\n\t\t\t\tTermDoc td = posting.get(docId);\n\t\t\t\tDocument doc = this.getDocument(docId);\n\n\t\t\t\tfinal double a = 0.4;\n\t\t\t\tdouble ntf = a + (1 - a) * (double) td.getFreq() / (double) doc.getMaxTermFreq();\n\t\t\t\tdouble idf = Math.log((double) documents.size() / (1 + (double) t.getDocFreq()));\n\t\t\t\tdoc.addWeight(termString, ntf * idf);\n\t\t\t}\n\t\t}\n\n\t\tfor (Document doc : documents.values())\n\t\t\tdoc.setEuclideanDistance();\n\t}","@Override\n public double score(Document document) {\n Set<String> allDocTerms = documentsTerms.termsExtractedFromDocument(document).allTerms();\n\n //keeping only the query terms that are in the document\n Collection<String> relevantTerms = new LinkedHashSet<>(query);\n relevantTerms.retainAll(allDocTerms);\n\n //compute score using a sum formula on each query term\n int docLength = termsOccurences.get(document).totalNumberOfOccurences();\n double score = 0.0;\n for (String term : relevantTerms) {\n double termIDF = idf.weight(term);\n double termTF = tf.weight(term, document);\n\n score += termIDF * (termTF * (k1 + 1)) / (termTF + k1 * (1 - b + b * (docLength / averageDocLength)));\n }\n\n return score;\n }","SwiftScoredSet getTfIdf(String text,ASTNode n,boolean kgram)\n{\n Map<String,Integer> words = null;\n Map<String,Integer> totals = null;\n double tot = 0;\n if (kgram){\n words = buildKgramCounts(text,n);\n totals = kgram_counts;\n tot = total_kdocuments;\n } \n else {\n words = handleDocumentText(text);\n totals = document_counts;\n tot = total_documents;\n }\n double termtot = 1;\n \n for (Integer iv : words.values()) {\n termtot += iv;\n }\n \n SwiftScoredSet rslt = new SwiftScoredSet();\n for (Map.Entry<String,Integer> ent : words.entrySet()) {\n String wd = ent.getKey();\n double ct = ent.getValue();\n Integer docs = totals.get(wd);\n double docct = 0;\n if (docs != null) docct = docs;\n double idf = Math.log(tot/(1+docct));\n double tf = ct/termtot;\n double tfidf = tf*idf;\n rslt.add(wd,tfidf);\n }\n rslt.normalize();\n \n return rslt;\n}","private void doBayesianClassification() {\n\t\tList<MutualInformation> mutualInformationList = new ArrayList<MutualInformation>();\r\n\t\tint k = 5;\r\n\t\tSystem.out.println(\"k = \" + k);\r\n\t\tdouble N = fileNames.size();\r\n\t\t\r\n\t\tList<Set<String>> classifiedDocsList = new ArrayList<Set<String>>();\r\n\t\tclassifiedDocsList.add(setOfHamiltonDocs);\r\n\t\tclassifiedDocsList.add(setOfMadisonDocs);\r\n\t\tclassifiedDocsList.add(setOfJayDocs);\r\n\t\t\r\n\t\tfor (String term : corpusVocab) {\r\n\r\n\t\t\t// All docs containing this term\r\n\t\t\tSet<String> matchingDocs = new HashSet<String>();\r\n\t\t\t\r\n\t\t\tfor (PositionalPosting posting : pInvertedIndex.getPostings(term)) {\r\n\t\t\t\tmatchingDocs.add(fileNames.get(posting.getDocumentId()));\r\n\t\t\t}\r\n\t\t\t\r\n\t\t\t// iterate through all classes (Hamilton, Madison, Jay)\r\n\t\t\tfor (int i = 0; i < classifiedDocsList.size(); i++) {\r\n\t\t\t\t\r\n\t\t\t\tSet<String> classifiedDocs = classifiedDocsList.get(i);\r\n\t\t\t\t\r\n\t\t\t\tSet<String> intersection = new HashSet<String>(matchingDocs);\r\n\t\t\t\tintersection.retainAll(classifiedDocs);\r\n\t\t\t\tdouble N11 = intersection.size();\r\n\t\t\t\t\r\n\t\t\t\tSet<String> difference = new HashSet<String>(matchingDocs);\r\n\t\t\t\tdifference.removeAll(classifiedDocs);\r\n\t\t\t\tdouble N10 = difference.size();\r\n\t\t\t\t\r\n\t\t\t\tdouble N01 = classifiedDocs.size() - N11;\r\n\t\t\t\tdouble N00 = fileNames.size() - classifiedDocs.size() - N10;\r\n\r\n\t\t\t\t// Calculate I(t,c)\r\n\t\t\t\tdouble Itc = (N11 / N) * log2((N * N11) / ((N11 + N10) * (N11 + N01)))\r\n\t\t\t\t\t\t+ (N01 / N) * log2((N * N01) / ((N01 + N00) * (N11 + N01)))\r\n\t\t\t\t\t\t+ (N10 / N) * log2((N * N10) / ((N11 + N10) * (N10 + N00)))\r\n\t\t\t\t\t\t+ (N00 / N) * log2((N * N00) / ((N01 + N00) * (N10 + N00)));\r\n\t\t\t\tif (!Double.isNaN(Itc)) {\r\n\t\t\t\t\tmutualInformationList.add(new MutualInformation(term, Itc));\r\n\t\t\t\t}\r\n\t\t\t}\r\n\t\t}\r\n\t\t\r\n\t\t// Build Discriminating Set of vocab terms by sorting mutual information\r\n\t\t// list and keep the first k values\r\n\t\tSet<String> terms = new HashSet<String>();\r\n\t\tCollections.sort(mutualInformationList, Collections.reverseOrder());\r\n\t\tfor (int i = 0; i < k; i++) {\r\n\t\t\tterms.add(mutualInformationList.get(i).getTerm());\r\n\t\t}\r\n\t\t\r\n\t\t// get term counts in classified (trainer) docs\t\t\r\n\t\tint[] classifiedDocsTermFreq = new int[classifiedDocsList.size()];\r\n\t\t\r\n\t\tclassifiedDocsTermFreq[0] = getTermFreq(hamiltonDocs, terms);\r\n\t\tclassifiedDocsTermFreq[1] = getTermFreq(madisonDocs, terms);\r\n\t\tclassifiedDocsTermFreq[2] = getTermFreq(jayDocs, terms);\r\n\t\t\r\n\t\t// Calculate p(t|c)\r\n\t\t// maps term to list of p(t|c) for each class\r\n\t\tMap<String, List<Double>> ptc = new HashMap<String, List<Double>>();\r\n\t\t\r\n\t\tfor (String term : terms) {\r\n\t\t\tptc.put(term, new ArrayList<Double>());\r\n\t\t\tfor (int i = 0; i < classifiedDocsList.size(); i++) {\r\n\t\t\t\t\r\n\t\t\t\tint ftc = 0;\r\n\t\t\t\tfor (PositionalPosting posting : pInvertedIndex.getPostings(term)) {\r\n\t\t\t\t\tif (classifiedDocsList.get(i).contains(fileNames.get(posting.getDocumentId()))) {\r\n\t\t\t\t\t\tftc += posting.getPositions().size();\r\n\t\t\t\t\t}\r\n\t\t\t\t}\r\n\t\t\t\tptc.get(term).add((double) (ftc + 1) / (double) (classifiedDocsTermFreq[i] + terms.size()));\r\n\t\t\t}\r\n\t\t}\r\n\t\t\r\n\t\t// visit each unclassified document\r\n\t\ttry {\r\n\t\t\tPath currentWorkingPath = Paths.get(toBeClassified).toAbsolutePath();\r\n\t\t\t// This is our standard \"walk through all .txt files\" code.\r\n\t\t\tFiles.walkFileTree(currentWorkingPath, new SimpleFileVisitor<Path>() {\r\n\r\n\t\t\t\tpublic FileVisitResult preVisitDirectory(Path dir, BasicFileAttributes attrs) {\r\n\t\t\t\t\t// make sure we only process the current working directory\r\n\t\t\t\t\tif (currentWorkingPath.equals(dir)) {\r\n\t\t\t\t\t\treturn FileVisitResult.CONTINUE;\r\n\t\t\t\t\t}\r\n\t\t\t\t\treturn FileVisitResult.SKIP_SUBTREE;\r\n\t\t\t\t}\r\n\r\n\t\t\t\tpublic FileVisitResult visitFile(Path file, BasicFileAttributes attrs) {\r\n\r\n\t\t\t\t\tif (file.toString().endsWith(\".txt\")) {\r\n\r\n\t\t\t\t\t\tTokenStream tokenStream = null;\r\n\t\t\t\t\t\t// terms in this document\r\n\t\t\t\t\t\tSet<String> docTerms = new HashSet<String>();\r\n\t\t\t\t\t\ttry {\r\n\t\t\t\t\t\t\ttokenStream = Utils.getTokenStreams(file.toFile());\r\n\t\t\t\t\t\t} catch (FileNotFoundException e) {\r\n\t\t\t\t\t\t\te.printStackTrace();\r\n\t\t\t\t\t\t}\r\n\r\n\t\t\t\t\t\twhile (tokenStream.hasNextToken()) {\r\n\t\t\t\t\t\t\tString token = Utils.processWord(tokenStream.nextToken().trim(), false);\r\n\t\t\t\t\t\t\tdocTerms.add(token);\r\n\t\t\t\t\t\t}\r\n\t\t\t\t\t\t// only keep terms in discriminating set\r\n\t\t\t\t\t\tdocTerms.retainAll(terms);\r\n\t\t\t\t\t\t\r\n\t\t\t\t\t\t// calculate log(p(c) + sum(log(p(ti|c))) for each class\r\n\t\t\t\t\t\tdouble[] pce = new double[classifiedDocsList.size()];\r\n\t\t\t\t\t\tfor (int i = 0; i < classifiedDocsList.size(); i++) {\r\n\t\t\t\t\t\t\tdouble sum = 0;\r\n\t\t\t\t\t\t\tfor (String term : docTerms) {\r\n\t\t\t\t\t\t\t\tsum += Math.log(ptc.get(term).get(i));\r\n\t\t\t\t\t\t\t}\r\n\t\t\t\t\t\t\t\r\n\t\t\t\t\t\t\tpce[i] = Math.log(classifiedDocsTermFreq[i] / terms.size()) + sum;\r\n\t\t\t\t\t\t}\r\n\t\t\t\t\t\t\r\n\t\t\t\t\t\tif (pce[0] > pce[1] && pce[0] > pce[2]) {\r\n\t\t\t\t\t\t\tSystem.out.println(\"Document : \" + file.getFileName().toString() + \" : belongs to Hamilton\");\r\n\t\t\t\t\t\t} else if (pce[1] > pce[0] && pce[1] > pce[2]) {\r\n\t\t\t\t\t\t\tSystem.out.println(\"Document : \" + file.getFileName().toString() + \" : belongs to Madison\");\r\n\t\t\t\t\t\t} else if (pce[2] > pce[0] && pce[2] > pce[1]) {\r\n\t\t\t\t\t\t\tSystem.out.println(\"Document : \" + file.getFileName().toString() + \" : belongs to Jay\");\r\n\t\t\t\t\t\t} else {\r\n\t\t\t\t\t\t\tSystem.out.println(\"I don't know whom document : \" + file.getFileName().toString() + \" : belongs to.\");\r\n\t\t\t\t\t\t}\r\n\t\t\t\t\t}\r\n\t\t\t\t\treturn FileVisitResult.CONTINUE;\r\n\t\t\t\t}\r\n\r\n\t\t\t\t// don't throw exceptions if files are locked/other errors occur\r\n\t\t\t\tpublic FileVisitResult visitFileFailed(Path file, IOException e) {\r\n\t\t\t\t\treturn FileVisitResult.CONTINUE;\r\n\t\t\t\t}\r\n\t\t\t});\r\n\t\t} catch (IOException e) {\r\n\t\t\te.printStackTrace();\r\n\t\t}\r\n\t}","public static String tfidf(String str) throws Exception{\n\t\tIndexReader r = IndexReader.open(FSDirectory.open(new File(\"index\")));\r\n\r\n\t\t// this code takes care of calculating idf for each term\r\n\r\n\t\tHashMap<String, Double> idf_map = new HashMap<String, Double>();\r\n\t\tTermEnum t = r.terms();\r\n\t\tdouble docs_count = r.maxDoc();\r\n\t\twhile (t.next()) {\r\n\t\t\tTerm te = new Term(\"contents\", t.term().text());\r\n\t\t\tdouble idf = Math.log(docs_count / r.docFreq(te));\r\n\t\t\tidf_map.put(t.term().text(), idf);\r\n\t\t}\r\n\r\n\t\t// This code is a test stub to get the term with lowest IDF value\r\n\r\n\t\t/*\r\n\t\t * double minVal = Collections.min(idf_map.values()); for(Entry<String,\r\n\t\t * Double> entry:idf_map.entrySet()){ if(entry.getValue() == minVal){\r\n\t\t * System.out.println(\"Term with lowest idf is: \"+entry.getKey()); } }\r\n\t\t */\r\n\r\n\t\tlong t1, t2;\r\n\t\tlong start = System.currentTimeMillis();\r\n\r\n\t\t// code to get |d| for every document\r\n\r\n\t\tHashMap<Integer, HashMap<String, Integer>> hmap = new HashMap<Integer, HashMap<String, Integer>>();\r\n\t\tTermEnum trm = r.terms();\r\n\t\twhile (trm.next()) {\r\n\t\t\tTerm te1 = new Term(\"contents\", trm.term().text());\r\n\t\t\tTermDocs td1 = r.termDocs(te1);\r\n\r\n\t\t\twhile (td1.next()) {\r\n\t\t\t\tHashMap<String, Integer> a1 = hmap.get(td1.doc());\r\n\t\t\t\tif (a1 == null) {\r\n\t\t\t\t\ta1 = new HashMap<String, Integer>();\r\n\t\t\t\t\ta1.put(trm.term().text(), td1.freq());\r\n\t\t\t\t\thmap.put(td1.doc(), a1);\r\n\t\t\t\t} else {\r\n\t\t\t\t\ta1.put(trm.term().text(), td1.freq());\r\n\t\t\t\t}\r\n\t\t\t}\r\n\t\t}\r\n\r\n\t\t// compute magnitude of each document vector and store it in array\r\n\r\n\t\tArrayList<Double> doc_magnitude = new ArrayList<Double>();\r\n\t\tHashMap<String, Integer> val = new HashMap<String, Integer>();\r\n\t\tSet<Entry<Integer, HashMap<String, Integer>>> entrySet = hmap.entrySet();\r\n\r\n\t\tjava.util.Iterator<Entry<Integer, HashMap<String, Integer>>> it = entrySet.iterator();\r\n\t\twhile (it.hasNext()) { // foreach document id\r\n\t\t\tdouble square_sum = 0.0;\r\n\t\t\tMap.Entry<Integer, HashMap<String, Integer>> me = (Entry<Integer, HashMap<String, Integer>>) it.next();\r\n\t\t\tval = me.getValue();\r\n\t\t\tSet<Map.Entry<String, Integer>> entry = val.entrySet();\r\n\t\t\tjava.util.Iterator<Map.Entry<String, Integer>> iterator = entry.iterator();\r\n\t\t\twhile (iterator.hasNext()) { // foreach term\r\n\t\t\t\tMap.Entry<String, Integer> mp = iterator.next();\r\n\t\t\t\tsquare_sum += mp.getValue() * mp.getValue();\r\n\t\t\t}\r\n\t\t\tdouble root = Math.sqrt(square_sum);\r\n\t\t\tdoc_magnitude.add(me.getKey(), root);\r\n\t\t}\r\n\r\n\t\t// long end = System.currentTimeMillis();\r\n\t\t// double diff = end - start;\r\n\t\t// System.out.println(\"Time taken to compute norms(in seconds): \" + diff\r\n\t\t// / 1000 + \"\\n\");\r\n\r\n\t\t// get the query and find similarity with the documents\r\n\t\tHashMap<Integer, Double> similarity_map = new HashMap<Integer, Double>();\r\n\t\tSet<Entry<Integer, HashMap<String, Integer>>> entrySet1 = hmap.entrySet();\r\n\t\tjava.util.Iterator<Entry<Integer, HashMap<String, Integer>>> it1 = entrySet1.iterator();\r\n\t\t\r\n\t\t\r\n\t\t\r\n\t\tHashMap<Integer, Double> dot_product_map = new HashMap<Integer, Double>();\r\n\r\n\t\t\r\n\t\t\tdot_product_map.clear();\r\n\t\t\tsimilarity_map.clear();\r\n\r\n\t\t\tString[] terms = str.split(\"\\\\s+\");\r\n\t\t\tint cnt = 0;\r\n\r\n\t\t\tlong result_st = System.currentTimeMillis();\r\n\t\t\tt1 = System.nanoTime();\r\n\r\n\t\t\t// for each term get the documents containing the corresponding term\r\n\t\t\tfor (String word : terms) // foreach term in query\r\n\t\t\t{\r\n\t\t\t\tTerm te = new Term(\"contents\", word);\r\n\t\t\t\tTermDocs tdocs = r.termDocs(te);\r\n\t\t\t\twhile (tdocs.next() /* && tdocs.doc() < number */) {\r\n\t\t\t\t\t// Map.Entry<Integer, HashMap<String, Integer>> me =\r\n\t\t\t\t\t// (Entry<Integer, HashMap<String, Integer>>) it1.next();\r\n\t\t\t\t\tdouble freq = hmap.get(tdocs.doc()).get(word);\r\n\t\t\t\t\tDouble temp = dot_product_map.get(tdocs.doc());\r\n\t\t\t\t\tif (temp == null) {\r\n\t\t\t\t\t\tdot_product_map.put(tdocs.doc(), freq * idf_map.get(word));\r\n\t\t\t\t\t} else {\r\n\t\t\t\t\t\tdot_product_map.put(tdocs.doc(), dot_product_map.get(tdocs.doc()) + freq * idf_map.get(word));\r\n\t\t\t\t\t}\r\n\t\t\t\t}\r\n\t\t\t\tcnt++;\r\n\t\t\t}\r\n\t\t\tSet<Entry<Integer, Double>> se = dot_product_map.entrySet();\r\n\t\t\tjava.util.Iterator<Entry<Integer, Double>> iter = se.iterator();\r\n\t\t\twhile (iter.hasNext()) {\r\n\t\t\t\tMap.Entry<Integer, Double> me = (Entry<Integer, Double>) iter.next();\r\n\t\t\t\tsimilarity_map.put(me.getKey(), me.getValue() / (Math.sqrt(cnt) * doc_magnitude.get(me.getKey())));\r\n\t\t\t}\r\n\r\n\t\t\t// Normalize the map\r\n\t\t\tdouble sum = 0;\r\n\t\t\tfor (int i : similarity_map.keySet()) {\r\n\t\t\t\tsum += similarity_map.get(i);\r\n\t\t\t}\r\n\r\n\t\t\tfor (int i : similarity_map.keySet()) {\r\n\t\t\t\tdouble temp = similarity_map.get(i) / sum;\r\n\t\t\t\tsimilarity_map.put(i, temp);\r\n\t\t\t}\r\n\r\n\t\t\tString result=\"\";\r\n\r\n\t\t\tList<Integer> l1 = new ArrayList<Integer>();\r\n\t\t\tHashMap<Integer, Double> sim_map = sortMap(similarity_map, r);\r\n\t\t\tfor(Integer i:sim_map.keySet()){\r\n\t\t\t\tl1.add(i);\r\n\t\t\t\tDocument d1 = r.document(i);\r\n\t\t\t\tString url = d1.getFieldable(\"path\").stringValue();\r\n\t\t\t\t//String snippet = getSnippet(hmap.get(i));\r\n\t\t\t\turl = url.replace(\"%%\", \"/\");\r\n\t\t\t\tString snippet = Snippet.getContent(url,terms[0]); //read the content of url\r\n\t\t\t\tresult +=/*i+\" \"+*/url+\"\\n\";\r\n\t\t\t\tresult +=snippet+\"\\n\\n\\n\";\r\n\t\t\t\t//result += snippet+\"\\n\\n\";\r\n\t\t\t}\r\n\t\t\treturn result;\r\n\t\t\t\r\n}","boolean hasFreq();","private static String handleNonPhraseToken(String stringPart) {\r\n // Set of final terms to be used (no empty elements, right syntax of index fields)\r\n ArrayList <String> terms = new ArrayList <String> ();\r\n \r\n /** Case Index field **/\r\n if(stringPart.contains(\"[\") | stringPart.contains(\"[\")){ // at least an Index field contained here\r\n //separate brackets for term with one space (extra spaces dont matter, trim() is used later)\r\n stringPart = stringPart.replace(\"[\", \" [\");\r\n stringPart = stringPart.replace(\"]\", \"] \");\r\n }\r\n\r\n /** Case Bag of terms **/\r\n //replace space with AND (change default operator to match pubMed's)\r\n // No need for this if setDefaultOperator(QueryParser.Operator.AND) is used\r\n \r\n String[] tokens = stringPart.split(\"\\\\s\");\r\n if(tokens.length > 0){ \r\n for(int i = 1 ; i < tokens.length ; i++){\r\n tokens[i] = tokens[i].trim();\r\n /* Case index field [fieldName] */\r\n if(tokens[i].startsWith(\"[\") & tokens[i].endsWith(\"]\")){\r\n tokens[i] = tokens[i].replace(\"[\",\"\");// clean field name from brackets\r\n tokens[i] = tokens[i].replace(\"]\",\"\");// clean field name from brackets\r\n //Add index field as prefix to previus (not empty) term (as opening index fields handled separately, this index field should not be the first term of string part)\r\n int tmp = i-1;\r\n boolean perviusTermFound = false;\r\n while(!perviusTermFound & tmp >= 0){\r\n if(!tokens[tmp].equals(\"\")){\r\n perviusTermFound = true;\r\n //TO DO : handle wrong syntax (e.g. ... AND [ArticleTitle])\r\n String luceneField = supportedIndexFields.get(tokens[i]);\r\n if(luceneField != null){\r\n tokens[tmp] = luceneField + \":\" + tokens[tmp];\r\n } // else : Lucene counterpart not found, unsupported field - do nothing\r\n } else {\r\n tmp--;\r\n }\r\n }\r\n //Empty field to not be added as a search term in query\r\n tokens[i] = \"\";\r\n } \r\n \r\n /*\r\n \r\n else if(!tokens[i].equals(\"AND\") & !tokens[i].equals(\"\")) {\r\n terms.add(tokens[i]);\r\n }\r\n */\r\n }\r\n }\r\n \r\n String luceneQueryPart = \"\";\r\n boolean notWaiting = false;\r\n boolean orWaiting = false;\r\n for(int i = 0 ; i < tokens.length ; i++){\r\n\r\n if(!tokens[i].equals(\"AND\") & !tokens[i].equals(\"\")){\r\n //in case of AND nothing should happen, it is the default operator\r\n //empty elements are also ignored as useless\r\n \r\n if(!tokens[i].equals(\"NOT\") & !tokens[i].equals(\"OR\") ){ // it's not an operator, it's a term\r\n \r\n if(!luceneQueryPart.endsWith(\" OR \") & !luceneQueryPart.endsWith(\" -\") ) { \r\n luceneQueryPart += \" +\"; \r\n } \r\n luceneQueryPart += tokens[i];\r\n } else {\r\n if(tokens[i].equals(\"NOT\")) {\r\n luceneQueryPart += \" -\";\r\n }\r\n if(tokens[i].equals(\"OR\")){\r\n luceneQueryPart += \" OR \";\r\n }\r\n \r\n } \r\n } \r\n }\r\n \r\n return luceneQueryPart;\r\n }","public abstract void addFeatures(Collection<Double> indices,Predicate pred, Word arg,boolean allWords);","public void setTerms(Term[] terms) { this.terms = terms; }","public float computeTermScore(int term, int dl, int tf, GlobalStats stats);","public double getTfIdf(){ return tf_idf; }","private Float weightTermUniqeness(String term) throws IOException{\n\t\tFloat result = null;\n\t\t\n\t\tLong docCnt\t\t= this.elasticClient.getDocCount();\n\t\tLong termDocCnt = this.elasticClient.getDocCount(term);\n\t\t\n\t\tresult = ((Long)(docCnt / termDocCnt)).floatValue();\n\t\t\n\t\treturn result;\n\t}","@Override\n protected float score(BasicStats stats, float termFreq, float docLength) {\n double s = 0.75;\n\n long N = stats.getNumberOfDocuments();\n long df = stats.getDocFreq();\n float cwd = termFreq;\n float cwq = 1; //assume that the query term frequency is always one\n float n = docLength;\n float navg = stats.getAvgFieldLength();\n\n double p1 = (1+Math.log(1+Math.log(cwd)))/(1-s+s*n/navg);\n float ans = (float) (p1 * cwq * Math.log((N+1)/df));\n\n return ans;\n }","public HashMap<String, Double> search(String query) {\n // ===================================================\n // 1. Fetch all inverted lists corresponding to terms\n // in the query.\n // ===================================================\n String[] terms = query.split(\" \");\n HashMap<String, Integer> qf = new HashMap<String, Integer>();\n // Calculate term frequencies in the query\n for (String term : terms) {\n if (qf.containsKey(term))\n qf.put(term, qf.get(term) + 1);\n else\n qf.put(term, 1);\n }\n HashMap<String, Double> docScore = new HashMap<String, Double>();\n for (Entry<String, Integer> termEntry : qf.entrySet()) {\n String term = termEntry.getKey();\n int qfi = termEntry.getValue();\n\n // ===================================================\n // 2. Compute BM25 scores for documents in the lists.\n // Make a score list for documents in the inverted\n // lists. Assume that no relevance information is \n // available. For parameters, use k1=1.2, b=0.75, \n // k2=100.\n // ===================================================\n double k1 = 1.2;\n double b = 0.75;\n double k2 = 100;\n int ni = invIndex.get(term).size();\n\n\n for (Entry<String, IndexEntry> invListEntry : invIndex.get(term).entrySet()) {\n String docID = invListEntry.getKey();\n double bm25Score;\n if (docScore.containsKey(docID))\n bm25Score = docScore.get(docID);\n else\n bm25Score = 0;\n\n // length of the document\n int dl = docStat.get(docID);\n // frequency of the term in the document\n int fi = invListEntry.getValue().getTf();\n double K = k1 * ((1 - b) + b * ((double) dl / avdl));\n\n // ===================================================\n // 3. Accumulate scores for each term in a query\n // on the score list.\n // ===================================================\n bm25Score += Math.log((N - ni + 0.5) / (ni + 0.5))\n * (((k1 + 1) * fi * (k2 + 1) * qfi) / ((K + fi) * (k2 + qfi)));\n docScore.put(docID, bm25Score);\n }\n }\n\n return docScore;\n }","public Term[] getTerms() { return terms; }","@Override\n protected float score(BasicStats stats, float termFreq, float docLength) {\n float k1 = (float)1.2;\n float k2 = 750;\n float b = (float)0.75;\n float N = stats.getNumberOfDocuments();\n float df = stats.getDocFreq();\n float qtermFreq = 1;\n float score = (float)Math.log((N - df + 0.5)/df+0.5);\n score*=((k1+1)*termFreq)/(k1*(1-b+b*(docLength/stats.getAvgFieldLength()))+termFreq);\n score*=((k2+1)*qtermFreq)/(k2+qtermFreq);\n return score; }","public /*TreeMap<String, Float>*/void getTopnTermsOverlapWithQuery() throws IOException, ParseException{\n\t\tString outputfile = \"./output/score/test3.txt\";\n\n\t\tFileOutputStream out = new FileOutputStream(outputfile);\n\t\tPrintStream ps = new PrintStream(out);\n\t\t/*-------------------------------------------------------------------------------*/\n\n\t\tTreeMap<String,Float> termsscoressorted = null;\n\t\tCollectionReader reader = new CollectionReader(indexDir); \n\t\tIndexReader ir = reader.getIndexReader();\t\t\n\n\t\tTopicsInMemory topics = new TopicsInMemory(\"data/CLEF-IP-2010/PAC_test/topics/PAC_topics-test2.xml\"/*omit-PAC-1094.xml\"*/);\n\t\tfor(Map.Entry<String, PatentDocument> topic : topics.getTopics().entrySet()){\n\t\t\tString qUcid = topic.getValue().getUcid();\n\t\t\tString queryid = topic.getKey();\n\t\t\tString queryName = topic.getKey() + \"_\" + topic.getValue().getUcid();\n\t\t\tString queryfile = topic.getKey() + \"_\" + topic.getValue().getUcid() + \".xml\";\n\n\t\t\t/*System.out.println(\"=========================================\");\n\t\t\tSystem.out.println(queryName);\n\t\t\tSystem.out.println(\"=========================================\");*/\n\t\t\t/*int docid = reader.getDocId(\"UN-EP-0663270\", PatentDocument.FileName);\n\t\t\tir.getTermVector(docid, field) getTermVectors(b);*/\n\n\t\t\tEvaluateResults er = new EvaluateResults();\n\t\t\tArrayList<String> tps = er.evaluatePatents(queryid, \"TP\");\n\t\t\tArrayList<String> fps = er.evaluatePatents(queryid, \"FP\");\n\t\t\tHashMap<String, Float> /*TFreqs*/ termsscores = new HashMap<>();\n\n\n\t\t\t/*--------------------------------- Query Words -------------------------------*/\n\t\t\t//\t\t\tHashMap<String, Integer> query_termsfreqspair = reader.gettermfreqpair(qUcid, PatentDocument.Description);\n\t\t\tHashSet<String> query_terms = reader.getDocTerms(qUcid, PatentDocument.Description);\n\t\t\t//\t\t\tSystem.out.println(query_termsfreqspair.size() +\"\\t\"+ query_termsfreqspair);\n//\t\t\tSystem.out.println(query_terms.size() + \"\\t\" + query_terms);\n\t\t\t/*-----------------------------------------------------------------------------*/\t\t\t\n\n\n\t\t\t//\t\t\tSystem.out.println(\"-----TPs----\");\n\t\t\tfor (String tp : tps) {\n\t\t\t\t/*System.out.println(\"---------\");\n\t\t\t\tSystem.out.println(tp);*/\n\t\t\t\tHashMap<String, Integer> termsfreqsTP = reader.gettermfreqpairAllsecs(\"UN-\" + tp);\n\n\t\t\t\tfor(Entry<String, Integer> tfTP:termsfreqsTP.entrySet()){\n\t\t\t\t\tif(termsscores.containsKey(tfTP.getKey())){\n\t\t\t\t\t\ttermsscores.put(tfTP.getKey(), termsscores.get(tfTP.getKey()) + (float)tfTP.getValue()/tps.size());\n\t\t\t\t\t}else{\n\t\t\t\t\t\t//\t\t\t\t\t\tfloat test = (float)t.getValue()/tps.size();\n\t\t\t\t\t\t//\t\t\t\t\t\tSystem.out.println(test);\n\t\t\t\t\t\ttermsscores.put(tfTP.getKey(), (float)tfTP.getValue()/tps.size());\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t\t//\t\t\t\tSystem.out.println(termsscores.size() + \" \" + termsscores);\t\t\t\t\t\n\t\t\t}\n\n\t\t\t/*System.out.println();\n\t\t\tSystem.out.println(\"-----FNs----\");*/\n\t\t\tfor (String fp : fps) {\n\t\t\t\t/*System.out.println(\"---------\");\n\t\t\t\tSystem.out.println(fp);*/\n\t\t\t\tHashMap<String, Integer> termsfreqsFP = reader.gettermfreqpairAllsecs(\"UN-\" + fp);\n\n\t\t\t\tfor(Entry<String, Integer> t:termsfreqsFP.entrySet()){\n\t\t\t\t\tif(termsscores.containsKey(t.getKey())){\n\t\t\t\t\t\ttermsscores.put(t.getKey(), termsscores.get(t.getKey()) - (float)t.getValue()/fps.size());\n\t\t\t\t\t}else{\t\t\t\t\t\t\n\t\t\t\t\t\ttermsscores.put(t.getKey(), -(float)t.getValue()/fps.size());\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t\t//\t\t\t\tSystem.out.println(TFreqs.size() + \" \" + TFreqs);\n\t\t\t}\n\t\t\t//\t\t\tSystem.out.println(termsscores.size() + \" \" + termsscores);\n\t\t\tValueComparator bvc = new ValueComparator(termsscores);\n\t\t\ttermsscoressorted = new TreeMap<String,Float>(bvc);\t\t\t\n\t\t\ttermsscoressorted.putAll(termsscores);\n\t\t\tSystem.out.println(queryid + \"\\t\"+ termsscoressorted.size() + \"\\t\" + termsscoressorted/*.keySet()*/);\n\t\t\tint overlap = 0;\n\t\t\tint i = 0;\n\t\t\tfor(Entry<String, Float> scoresorted:termsscoressorted.entrySet()){\n\t\t\t\ti++;\n\t\t\t\tif(i<=100){\n\t\t\t\t\tif(query_terms.contains(scoresorted.getKey())){\n\t\t\t\t\t\toverlap++;\n\t\t\t\t\t}\t\t\t\t\t\n\t\t\t\t}\n\t\t\t}\t\n\t\t\tSystem.out.println(queryName + \"\\t\"+overlap);\n//\t\t\tps.println(queryName + \"\\t\"+overlap);\n\t\t}\n\t}","private Double getSentenceTfIdf(String sentence, Article article) {\n Double sentenceTfIdf = 0.0;\n PriorityQueue<Double> topFiveWords = new PriorityQueue<>(Collections.reverseOrder());\n Set<String> alreadyConsideredWords = new HashSet<>();\n\n // Split the words in a sentence\n String[] sentenceTerms = sentence.split(\"\\\\s+\");\n\n for (String term: sentenceTerms) {\n // format the raw term to remove non-alphanumeric characters\n term = term.replaceAll(\"[^a-zA-Z\\\\d]\", \"\").toLowerCase().trim();\n\n if (!term.isEmpty()) {\n // lookup term in unigrams map to get its TF.IDF score\n Unigram correspondingUnigram = article.unigrams.get(term);\n\n if (correspondingUnigram != null && !alreadyConsideredWords.contains(term)) {\n topFiveWords.add(correspondingUnigram.getTf_idf());\n alreadyConsideredWords.add(term);\n }\n }\n }\n\n int limit = Math.min(5, topFiveWords.size());\n for (int i = 0; i < limit; i++) {\n sentenceTfIdf += topFiveWords.poll();\n }\n\n return sentenceTfIdf;\n }","public void relevanceFeedback(PostingsList results, boolean[] docIsRelevant, Indexer indexer ) {\r\n// results contain the ranked list from the current search\r\n// docIsRelevant contains the users feedback on which of the 10 first hits are relevant\r\n\tdouble gamma = 0.0; // används ej, de orelevanta dokumenterna. städa upp queryn. Vad innehller de orelevanta dokumenterna för termer\r\n// dess termer tar vi bort från den relebanta.)\r\n\r\n\tdouble alfa = 0.8; // hur mycket litar på det gamla sökning innan feedback\r\n\tdouble beta = 0.6; // hur mycket hänsyn du ska ta till nya sökningen efter feedback \r\n\r\n\r\n\t/* \r\n\r\n\tAlgorithm: \r\n\tThe Rocchio algorithm is based on a method of relevance \r\n\tfeedback found in information retrieval systems\r\n\tThe algorithm is based on the assumption that most users \r\n\thave a general conception of which documents should be denoted \r\n\tas relevant or non-relevant.[1] Therefore, the user's search \r\n\tquery is revised to include an arbitrary percentage of relevant \r\n\tand non-relevant documents as a means of increasing the search \r\n\tengine's recall, and possibly the precision as well. The number \r\n\tof relevant and non-relevant documents allowed to enter a query \r\n\tis dictated by the weights of the a, b.\r\n\tthe associated weights (a, b) are responsible for shaping the \r\n\tmodified vector in a direction closer, or farther away, from the \r\n\toriginal query, related documents, and non-related documents.\r\n\r\n\r\n\r\n\tLimitations of rocchio:\r\n\t\tTherefore the two queries of \"Burma\" and \"Myanmar\" will \r\n\t\tappear much farther apart in the vector space model, \r\n\t\tthough they both contain similar origins\r\n\tWhy not use non-relevant documents:\r\n\t\tThough there are benefits to ranking documents as not-relevant, \r\n\t\ta relevant document ranking will result in more precise documents \r\n\t\tbeing made available to the user. \r\n\t\r\n\r\n\r\n\tRoccio algoritmen: \r\n\t\talfa = Original query weight \r\n\t\tbeta = related document weight\r\n\t\t\r\n\t\thigher alpha means that we give more focus to the original query terms\r\n\t\thigher beta means that we give more focus to the new search feedback. i.e new terms.\r\n\r\n\t\tTar en org query\r\n\t\tTar den gamla gånnger en viss vikt \r\n\t\tvikt är alfa + beta (entill vektor) plus att den kollar på original vektor, q0 \r\n\t\t\thögre alfa mer fokus på original queryn \r\n\t\t\thögra beta skiftar till mer fokus på de nya termerna. \r\n\t\tdvs utökas med ord/termer från dokument vektorerna som var relevanta. \r\n\r\n\tVanligtvis har man väldigt häg alfa och beta lite under för att det är standard. man tycker att den \r\n\tförsta queryn är väldigt bra.\r\n\r\n\t\r\n\t*/\r\n\r\n\tPostingsList related_doc_vector = new PostingsList();\r\n\tHashMap<String, Double> qm = new HashMap<String, Double>(); // spara termer och weights.\r\n\t// normalize weights\r\n\tfor(Double w : weights){\r\n\t\tw = w/weights.size();\r\n\t}\r\n\r\n\tIterator<PostingsEntry> it = results.iterator();\r\n\tfor(int i = 0; i < docIsRelevant.length; i++){\r\n\t\tif(docIsRelevant[i] == true){\r\n\t\t\trelated_doc_vector.list.add(results.get(i));\r\n\t\t} \r\n\t}\r\n\r\n\t// apply Rocchio algorithm.\r\n\tfor(int i = 0; i < terms.size(); i++){\r\n\t\tdouble new_weigt = weights.get(i) * alfa;\r\n\t\tqm.put(terms.get(i), new_weigt);\r\n\t}\r\n\r\n\tfor(int i = 0; i < related_doc_vector.size(); i++){\r\n\t\tIterator<PostingsEntry> ite = related_doc_vector.iterator();\r\n\t\twhile(ite.hasNext()){\r\n\t\t\tPostingsEntry postingsentry = ite.next();\r\n\t\t\tint docID = postingsentry.docID;\r\n\t\t\tString filename = indexer.index.docIDs.get(Integer.toString(docID)); // hämtar filnamnet\r\n\t\t\tString path = \"/Users/monadadoun/Desktop/ir/lab/davisWiki/\" + filename; \r\n\t\t\tFile file = new File(path);\r\n\t\t\tHashSet<String> hs = new HashSet<>();\r\n\t\t\t// lägger till alla ord som finns till mitt hashet\r\n\t\t\ttry (Reader reader = new InputStreamReader( new FileInputStream(file), StandardCharsets.UTF_8 )){\r\n\t\t\t\tTokenizer tok = new Tokenizer( reader, true, false, true, indexer.patterns_file );\r\n\t\t\t\twhile (tok.hasMoreTokens()) {\r\n\t\t\t\t\ths.add(tok.nextToken());\r\n\t\t\t\t}\r\n\t\t\t} catch (IOException e) {\r\n\t\t\t\te.printStackTrace();\r\n\t\t\t}\r\n\t\t\t\r\n\t\t\tIterator<String> iter = hs.iterator();\r\n\t\t\twhile(iter.hasNext()){\r\n\t\t\t\tString s = iter.next();\r\n\t\t\t\tif(qm.containsKey(s)){\r\n\t\t\t\t\tDouble tmp = qm.get(s);\r\n\t\t\t\t\tqm.put(s, tmp + beta * postingsentry.score);\r\n\t\t\t\t} else {\r\n\t\t\t\t\tqm.put(s, beta * postingsentry.score);\r\n\t\t\t\t}\r\n\t\t\t}\r\n\t\t}\r\n\t}\r\n\tLinkedList<String> term = new LinkedList<>();\r\n\tLinkedList<Double> weight = new LinkedList<>();\r\n\tList<Map.Entry<String,Double>> answer = new ArrayList<Map.Entry<String,Double>>(qm.entrySet());\r\n\tanswer.sort((e1,e2) -> e2.getValue().compareTo(e1.getValue())); // sorterar efter värde så att orden med högst score ligger först\r\n\tfor (int i = 0; i < answer.size(); i++) {\r\n\t\tterm.add(answer.get(i).getKey());\r\n\t\tweight.add(answer.get(i).getValue()/answer.size());\r\n\t}\r\n\r\n\tterms = term;\r\n\tweights = weight;\r\n\t}","public TermToVertexCount[] getSubTermVertexMappings(String term)\n {\n /* String is not valid as-is.\n * \n * Replace and split words into parts.\n */\n term = term.replace('-', ' ');\n String [] arr = term.split(\" \");\n\n /* Remove common words */\n for(int i = 0; i < arr.length; i++)\n {\n if(arr[i].equals(\"and\"))\n {\n arr[i] = \"\";\n }\n else if(arr[i].equals(\"or\"))\n {\n arr[i] = \"\";\n }\n else if(arr[i].equals(\"to\"))\n {\n arr[i] = \"\";\n }\n else if(arr[i].equals(\"be\"))\n {\n arr[i] = \"\";\n }\n else if(arr[i].equals(\"the\"))\n {\n arr[i] = \"\";\n }\n else if(arr[i].equals(\"a\"))\n {\n arr[i] = \"\";\n }\n else if(arr[i].equals(\"of\"))\n {\n arr[i] = \"\";\n }\n else if(arr[i].equals(\"on\"))\n {\n arr[i] = \"\";\n }\n else if(arr[i].equals(\"in\"))\n {\n arr[i] = \"\";\n }\n else if(arr[i].equals(\"for\"))\n {\n arr[i] = \"\";\n }\n else if(arr[i].equals(\"with\"))\n {\n arr[i] = \"\";\n }\n else if(arr[i].equals(\"by\"))\n {\n arr[i] = \"\";\n }\n else if(arr[i].equals(\"into\"))\n {\n arr[i] = \"\";\n }\n else if(arr[i].equals(\"an\"))\n {\n arr[i] = \"\";\n }\n else if(arr[i].equals(\"is\"))\n {\n arr[i] = \"\";\n }\n else if(arr[i].equals(\"no\"))\n {\n arr[i] = \"\";\n }\n }//end: for(i)\n\n /* Create String array without common terms */\n int size = 0;\n for(int i = 0; i < arr.length; i++)\n {\n if(!arr[i].equals(\"\") && stem)\n { // Stem if required\n arr[i] = PorterStemmerTokenizerFactory.stem(arr[i]);\n }\n \n // Check for valid term\n if(!arr[i].equals(\"\") && getVertexMappings(arr[i]) != null)\n {\n size++;\n }\n }//end: for(i)\n \n if(size == 0)\n { /* No valid terms found */\n return null;\n }\n \n /* At least one valid term was found */\n TermToVertexCount[] words = new TermToVertexCount[size];\n int pos = 0;\n \n for(int i = 0; i < arr.length; i++)\n {\n // Check for valid term\n if(!arr[i].equals(\"\"))\n {\n // Get mappings for sub-term\n TermToVertexCount[] temp = getVertexMappings(arr[i]);\n \n if(temp != null)\n {\n words[pos] = temp[0];\n pos++;\n }//end: if(temp)\n \n }//end: if(!arr[i])\n }//end: for(i)\n \n return words; \n }","private static void statsForQuery(String query) {\n\t\tHashMap<String,Integer> oldTerms=newTerms; // record the terms to analyze modified queries\n\t\tnewTerms=new HashMap<String,Integer>();\n\t\t\t\t\n\t\tString terms[]=query.split(\"\\\\s\");\t\t\t\t\n\t\tint matchingTerms=0;\n\t\tint matchingTermsStopwords=0;\n\t\tint matchingTermsOrder=0;\n\t\tfor (int j=0;j<terms.length;j++) {\n\t\t\tif (!terms[j].equals(\"\")) {\n\t\t\t \tif (oldTerms.containsKey(terms[j])) {\n\t\t\t \t\tmatchingTerms++;\t\t\t\t\t \n\t\t\t \t\tif (stopwordsMap.containsKey(terms[j])) { // match if it is stopword\n\t\t\t \t\t\tmatchingTermsStopwords++;\n\t\t\t \t\t}\n\t\t\t \t\tif (oldTerms.get(terms[j])==j) { // match if it has the same order\n\t\t\t \t\t\tmatchingTermsOrder++;\n\t\t\t \t\t}\n\t\t\t \t}\n\t\t\t \tnewTerms.put(terms[j],j);\n\t\t\t}\n\t\t}\t\n\n\t\tif (newTerms.size()==oldTerms.size() && matchingTerms==oldTerms.size() && matchingTerms>0) { // the queries have the same terms\n\t\t totalEqualTermsQueries++;\n\t\t\t\t \t\t\t\t \t\t\t\t\t\t \t\t\t\t \t\t\t\t \n\t\t if (matchingTermsStopwords==oldTerms.size()) {\n\t\t \ttotalEqualTermsStopwordsQueries++;\n\t\t }\n\t\t if (matchingTermsOrder==oldTerms.size()) {\n\t\t \ttotalEqualTermsOrderQueries++;\n\t\t }\n\t\t if (query.equals(oldQuery)) {\n\t\t \ttotalIdenticalQueries++;\n\t\t }\n\t\t if (sessionQueries.contains(query)) {\n\t\t \ttotalIdenticalSessionQueries++;\n\t\t }\n\t\t}\n\t\telse if (matchingTerms-matchingTermsStopwords>0) { // the queries have at least one term equal and diferent from a stopword\n\t\t totalModifiedQueries++;\n\t\t int index=newTerms.size()-oldTerms.size()+N_MODIFIED_TERMS_RANGE/2;\n\t\t if (index<0) {\n\t\t \tindex=0;\n\t\t }\n\t\t else if (index>N_MODIFIED_TERMS_RANGE-1) {\n\t\t \tindex=N_MODIFIED_TERMS_RANGE-1;\n\t\t }\n\t\t nModifiedTerms[index]++;\n\t\t}\n\t\toldQuery=query; \n\t\t\t\t\t\t\n\t\t// store session query\n\t\tsessionQueries.add(query);\n\t}","abstract public TermEnum terms(Term t) throws IOException;","public int getNatureFilter();","@Override\n public int getDocumentFrequencyByTerm(String term) {\n return 0;\n }","int getSimilarityThreshold(final int field);","private double getTermOccurrence(String term, ClassificationClass classificationClass) {\n int termOccurrence = 0;\n\n for (Document document : documents) {\n if (document.getClassificationClasses().contains(classificationClass)) {\n if (document.getFeatures().containsKey(term)) {\n termOccurrence += document.getFeatures().get(term);\n }\n }\n }\n\n return termOccurrence;\n }","@Override\n\t\tpublic int hashCode() {\n\t\t\treturn mTerm.hashCode();\n\t\t}","private HashMap<String,HashMap<String,Integer>> computeTFForQueryWords(ArrayList<String> queryPostingLines) {\n HashMap<String,HashMap<String,Integer>> queryWordsTF = new HashMap<>();\n HashMap<String,HashMap<String,Integer>> queryWordsTFPerDoc = new HashMap<>();\n String docID,term;\n Integer tf;\n HashSet<String> docIDs = new HashSet<>();\n for(String postingLine : queryPostingLines){\n HashMap<String,Integer> frequenciesInDocuments = new HashMap<>();\n term = postingLine.substring(0,postingLine.indexOf(\"|\"));\n postingLine = postingLine.substring(postingLine.indexOf(\"|\")+1);\n while(!postingLine.equals(\"\")) {\n docID = postingLine.substring(0, postingLine.indexOf(\":\"));\n docIDs.add(docID);\n postingLine = postingLine.substring(postingLine.indexOf(\"_\") + 1);\n tf = Integer.valueOf(postingLine.substring(0, postingLine.indexOf(\"_\")));\n postingLine = postingLine.substring(postingLine.indexOf(\"_\") + 1);\n frequenciesInDocuments.put(docID,tf);\n }\n queryWordsTF.put(term,frequenciesInDocuments);\n }\n\n ArrayList<String> allTermsInQuery = new ArrayList<>(queryWordsTF.keySet());\n for(String doc : docIDs){\n HashMap<String,Integer> tfsInDoc = new HashMap<>();\n for(String termInQuery : allTermsInQuery){\n HashMap<String,Integer> termsTFInDoc = queryWordsTF.get(termInQuery);\n if(termsTFInDoc.containsKey(doc)){\n tfsInDoc.put(termInQuery,termsTFInDoc.get(doc));\n }\n }\n queryWordsTFPerDoc.put(doc,tfsInDoc);\n }\n return queryWordsTFPerDoc;\n }","public abstract List<LambdaTerm> containedLambdaTerms(LambdaTerm P);","public void theDude() {\n\t\ttotal_targets = 0;\n\t\ttotal = 0;\n\t\tint target_count = 0;\n\t\tresult.clear();\n\t\t\n\t\tfor(int k=0; k<input.getWords().size();k++) {\n\t\t\tWord currentWordStat = input.getWordStatistics().get(k);\n\t\t\ttarget_count = 0;\n\t\t\t\n\t\t\tfor(int i=0;i<input.getWords().get(k).length();i++) {\n\t\t\t\tif(target.contains(input.getWords().get(k).charAt(i))) {\n\t\t\t\t\ttarget_count++;\n\t\t\t\t\ttotal_targets++;\n\t\t\t\t}\n\t\t\t\ttotal++;\n\t\t\t}\n\t\t\t\n\t\t\tif(result.containsKey(currentWordStat)) {\n\t\t\t\tresult.put(currentWordStat, result.get(currentWordStat)+target_count);\n\t\t\t}\n\t\t\telse {\n\t\t\t\tresult.put(currentWordStat, target_count);\n\t\t\t}\n\t\t}\t\n\t}","public float getTFIDF(Index index, String word) {\n long docCount = index.getDocuments().stream().filter(document -> document.hasWord(word)).count();\n return (float) getWordOccurrence(word) * (float) Math.log((float) index.getDocuments().size() / (float) docCount);\n }","public int getDocFreq(Term t){\n\t\tint freq = 0;\r\n\t\tfor (Map.Entry<String, IndexedDoc> set : index.entrySet()){\r\n\t\t\tif (set.getValue().containsTerm(t)){\r\n\t\t\t\tfreq++;\r\n\t\t\t}\r\n\t\t}\r\n\t\treturn freq;\r\n\t}","private Map<String,List<Invertedindex>> collecting() //\r\n {\r\n Map<String,List<Invertedindex>> maps = new TreeMap<>();\r\n for (Core pon:pondred){\r\n for(Map.Entry<String,Double> term:pon.allTerms.entrySet()){\r\n if (maps.containsKey(term.getKey())){\r\n List<Invertedindex> index = maps.get(term.getKey());\r\n index.add(new Invertedindex(pon.m_cle,term.getValue(),pon.getBalise(term.getKey())));\r\n maps.put(term.getKey(), index);\r\n }else {\r\n List<Invertedindex> index = new ArrayList<>();\r\n index.add(new Invertedindex(pon.m_cle,term.getValue(),pon.getBalise(term.getKey())));\r\n maps.put(term.getKey(), index);\r\n }\r\n if(cleFreq.containsKey(pon.m_cle))\r\n cleFreq.put(pon.m_cle,cleFreq.get(pon.m_cle)+term.getValue());\r\n else cleFreq.put(pon.m_cle,term.getValue());\r\n\r\n }\r\n }\r\n return maps;\r\n }","@Override\n protected QueryProcessor computeResult(ResultComputingContext<? extends TermsIndexingEquipment> context) {\n final TermWeight idf = context.preliminaryResult(CalculatingInvertedTermFrequency.getInstance());\n final TermDocumentWeight tf = context.preliminaryResult(context.equipment().termFrequencyCalculation());\n //for obtaining set of terms in each document.\n final EachDocumentTermsExtraction documentsTerms = context.preliminaryResult(ExtractingEachDocumentTerms.getInstance());\n //for obtaining document length\n final Map<Document, TermsOccurences> termsOccurences = context.preliminaryResult(CountingTermsOccurencesInEachDocument.getInstance());\n final double averageDocLength = context.preliminaryResult(ComputingAverageDocumentLength.getInstance());\n\n QueryProcessor res = new QueryProcessor() {\n @Override\n public DocumentRanker rankForQuery(final Collection<String> query) {\n return new DocumentRanker() {\n @Override\n public double score(Document document) {\n /*\n * BM25 score is calculated here\n */\n\n //obtaining the set of terms in the document\n Set<String> allDocTerms = documentsTerms.termsExtractedFromDocument(document).allTerms();\n\n //keeping only the query terms that are in the document\n Collection<String> relevantTerms = new LinkedHashSet<>(query);\n relevantTerms.retainAll(allDocTerms);\n\n //compute score using a sum formula on each query term\n int docLength = termsOccurences.get(document).totalNumberOfOccurences();\n double score = 0.0;\n for (String term : relevantTerms) {\n double termIDF = idf.weight(term);\n double termTF = tf.weight(term, document);\n\n score += termIDF * (termTF * (k1 + 1)) / (termTF + k1 * (1 - b + b * (docLength / averageDocLength)));\n }\n\n return score;\n }\n };\n\n }\n };\n\n logger.log(Level.INFO, \"Just created a BM25 query processor with parameters : \" + \"k1={0}, b={1}\", new Object[]{k1, b});\n\n return res;\n }","String legalTerms();","void collectLeastFrequent(FrequencyTable fq);","public Taxonomy getInterests();","@Override\n protected double getTFDocument(BasicStats stats, float termFreq, float docLength) {\n return ((k1 + 1) * termFreq / (k1 * (1 - b +\n b * docLength / stats.getAvgFieldLength()) + termFreq));\n }","public abstract void addFeatures(Collection<Integer> indices,Predicate pred,Word arg,Integer offset,boolean allWords);","@Override\r\n\t\t\tpublic long getDocumentFrequency(String term) {\n\t\t\t\treturn 0;\r\n\t\t\t}","public static HashMap<String, Double> getTFIDF(String inputStr) throws IOException{\n\t\tHashMap<String, Double> result = new HashMap<String, Double>();\n\t\tHashMap<String, Integer> termsMap = new HashMap<String, Integer>();\t\t\n\t\tArrayList<String> inputTerms = getTerms(inputStr);\n\t\t\n\t\tfor(String s : inputTerms){\n\t\t\tif(termsMap.containsKey(s) != true){\n\t\t\t\ttermsMap.put(s, 1);\n\t\t\t}else{\n\t\t\t\ttermsMap.put(s, termsMap.get(s)+1);\n\t\t\t}\n\t\t}\n\t\t\n\t\tfor(String term : termsMap.keySet()){\n\t\t\tdouble TF;\n\t\t\t//System.out.println(term + \" \" + termsMap.get(term));\t\t\t\t\n\t\t\tTF = (double)termsMap.get(term)/inputTerms.size();\n\t\t\tresult.put(term, TF*cal_IDF(term));\n\t\t}\n\t\t\n\t\treturn result;\n\t}","public static void main(String[] args) throws Exception {\n\t\tint i;\r\n\t\tint [][]preci_recall = new int [5][6]; \r\n\r\n\t\tNGRAM ngram = new NGRAM();\r\n\t\t\r\n\t\tfor(i=0; i<5; i++) {\r\n\t\t\t\r\n\t\t\tSystem.out.println((i+1) + \" th FOLD IS A TEST SET\");\r\n\t\t\t\r\n\t\t\tdouble[][] test_ngram_features = ngram.feature(i,1);\r\n\t\t\tdouble[][] train_ngram_features = ngram.feature(i,0);\r\n\t\t\t\r\n\t\t\tSystem.out.println(\"NGRAM FEATURES...OK\");\r\n\t\r\n//\t\t\t\r\n//\t\t\tLIWC liwc = new LIWC();\r\n//\t\t\t\r\n//\t\t\tdouble[][] test_liwc_features = liwc.feature(i,1,test_ngram_features.length);\r\n//\t\t\tdouble[][] train_liwc_features = liwc.feature(i,0,train_ngram_features.length);\r\n//\r\n//\t\t\tSystem.out.println(\"LIWC FEATURES..OK\");\r\n//\t\t\t\r\n//\t\t\tCOMBINE combine = new COMBINE();\r\n//\t\t\tdouble[][] train_features = combine.sum(train_liwc_features,train_ngram_features);\r\n//\t\t\tdouble[][] test_features = combine.sum(test_liwc_features,test_ngram_features);\r\n//\t\t\t\r\n//\t\t\tSystem.out.println(\"COMBINE...OK\");\r\n\t\t\r\n\t\t\tSVMLIGHT svmlight = new SVMLIGHT();\r\n\t\t\tpreci_recall[i]=svmlight.calcc(train_ngram_features, test_ngram_features);\r\n\r\n\t\t}\r\n\t\t\r\n//\t 0 : truthful TP\r\n//\t 1 : truthful TP+FP\r\n//\t 2 : truthful TP+FN\r\n//\t 3 : deceptive TP\r\n//\t 4 : deceptive TP+FP\r\n//\t 5 : deceptive TP+FN\r\n\t\t\r\n\t\tint truthful_TP_sum=0,truthful_TPFP_sum=0,truthful_TPFN_sum=0;\r\n\t\tint deceptive_TP_sum=0,deceptive_TPFP_sum=0,deceptive_TPFN_sum=0;\r\n\t\t\r\n\t\tfor(i=0;i<5;i++) {\r\n\t\t\ttruthful_TP_sum+=preci_recall[i][0];\r\n\t\t\ttruthful_TPFP_sum+=preci_recall[i][1];\r\n\t\t\ttruthful_TPFN_sum+=preci_recall[i][2];\r\n\t\t\t\r\n\t\t\tdeceptive_TP_sum+=preci_recall[i][3];\r\n\t\t\tdeceptive_TPFP_sum+=preci_recall[i][4];\r\n\t\t\tdeceptive_TPFN_sum+=preci_recall[i][5];\r\n\t\t}\r\n\t\t\t\t\r\n\t\tSystem.out.println(\"\\n\\nTRUTHFUL_TP_SUM : \" + truthful_TP_sum);\r\n\t\tSystem.out.println(\"TRUTHFUL_TPFP_SUM : \" + truthful_TPFP_sum);\r\n\t\tSystem.out.println(\"TRUTHFUL_TPFN_SUM : \" + truthful_TPFN_sum);\r\n\t\t\r\n\t\tSystem.out.println(\"DECEPTIVE_TP_SUM : \" + deceptive_TP_sum);\r\n\t\tSystem.out.println(\"DECEPTIVE_TPFP_SUM : \" + deceptive_TPFP_sum);\r\n\t\tSystem.out.println(\"DECEPTIVE_TPFN_SUM : \" + deceptive_TPFN_sum);\r\n\t\t\r\n\t\tSystem.out.println(\"\\nTRUTHFUL PRECISION : \" + (double)(truthful_TP_sum)/(double)(truthful_TPFP_sum));\r\n\t\tSystem.out.println(\"TRUTHFUL RECALL : \" + (double)(truthful_TP_sum)/(double)(truthful_TPFN_sum));\r\n\t\t\r\n\t\tSystem.out.println(\"DECEPTIVE PRECISION : \" + (double)(deceptive_TP_sum)/(double)(deceptive_TPFP_sum));\r\n\t\tSystem.out.println(\"DECEPTIVE RECALL : \" + (double)(deceptive_TP_sum)/(double)(deceptive_TPFN_sum));\r\n\t\t\r\n\r\n\t}","public int getTermTotal(){\n\t\tint total = 0;\r\n\t\tfor (Map.Entry<String, IndexedDoc> set : index.entrySet()){\r\n\t\t\ttotal += set.getValue().getTotalTerms();\r\n\t\t}\r\n\t\treturn total;\r\n\t}","private boolean classify(FeatureVector<? extends Number> wd) {\n\t\tfloat sum = 0;\n\t\t// Scalar Product\n\t\tfor (int i = 0; i < this.getDimensionality(); ++i) {\n\t\t\t// TODO check the type of the vector\n\t\t\tsum += wd.getValue(i).doubleValue()\n\t\t\t\t\t* this.getValue(i).doubleValue();\n\t\t}\n\n\t\t// sign binary function\n\t\tif (sum <= 0) {\n\t\t\treturn false;\n\t\t} else {\n\t\t\treturn true;\n\t\t}\n\t}","public void fillHandBuilt(Indexer index, String [] terms) {\n\t\tindex.addPosition(terms[0], 3, 1); // ar Term, docID, pos\n\t\tindex.addPosition(terms[1], 2, 4); // british\n\t\tindex.addPosition(terms[2], 3, 3); // dog\n\t\tindex.addPosition(terms[2], 4, 0); // dog\n\t\tindex.addPosition(terms[2], 4, 3); // dog\n\t\tindex.addPosition(terms[3], 4, 1); // enjoi\n\t\tindex.addPosition(terms[4], 0, 6); // enjoy\n\t\tindex.addPosition(terms[5], 1, 5); // in, potential error\n\t\tindex.addPosition(terms[5], 3, 4); // in\n\t\tindex.addPosition(terms[6], 1, 4); // is, potential error\n\t\tindex.addPosition(terms[7], 1, 1); // known\n\t\tindex.addPosition(terms[8], 3, 2); // mani\n\t\tindex.addPosition(terms[9], 0, 1); // monument\n\t\tindex.addPosition(terms[9], 1, 3); // monument potential error\n\t\tindex.addPosition(terms[10], 0, 3); // on\n\t\tindex.addPosition(terms[10], 2, 2); // on\n\t\tindex.addPosition(terms[11], 0, 4); // park\n\t\tindex.addPosition(terms[11], 4, 4); // park\n\t\tindex.addPosition(terms[12], 0, 2); // raid\n\t\tindex.addPosition(terms[12], 2, 1); // raid\n\t\tindex.addPosition(terms[13], 3, 5); // seattl\n\t\tindex.addPosition(terms[14], 0, 0); // the\n\t\tindex.addPosition(terms[14], 1, 0); // the\n\t\tindex.addPosition(terms[14], 2, 3); // the\n\t\tindex.addPosition(terms[14], 4, 2); // the\n\t\tindex.addPosition(terms[15], 3, 0); // there\n\t\tindex.addPosition(terms[16], 0, 5); // wa\n\t\tindex.addPosition(terms[17], 1, 2); // washington potential error\n\t\tindex.addPosition(terms[17], 2, 6); // washington potential error\n\t\tindex.addPosition(terms[17], 2, 0); // washington\n\t\tindex.addPosition(terms[17], 3, 6); // washington\n\t\tindex.addPosition(terms[18], 1, 1); // well potential error\n\t\tindex.addPosition(terms[18], 2, 6); // well \n\t\tindex.addPosition(terms[19], 1, 1); // wellknown\n\t\tindex.addPosition(terms[20], 2, 6); // went\n\t}","int indexOfFeature(Feature feature);","private static void banFeature(ArrayList t) {\n\t\tSet setKeys = Utility.vocabHM.keySet();\n\t\tIterator i = setKeys.iterator();\n\t\tSystem.out.print(\"Word cut : [\");\n\t\tint idx = 0;\n\t\twhile (i.hasNext()) {\n\t\t\tString s = (String) i.next();\n\t\t\tInteger df = (Integer) Utility.vocabHM.get(s);\n\n\t\t\tif (t.contains(s)){\n\t\t\t\tSystem.out.print(s+\", \");\n\t\t\t\ti.remove();\n\t\t\t\tidx++;\n\t\t\t}\n\t\t}\n\t\tSystem.out.println(\"]\\n ::banned::\"+idx+\" feature.\");\n\t}","public void translate() {\n\t\tif(!init)\r\n\t\t\treturn; \r\n\t\ttermPhraseTranslation.clear();\r\n\t\t// document threshold: number of terms / / 8\r\n//\t\tdocThreshold = (int) (wordKeyList.size() / computeAvgTermNum(documentTermRelation) / 8.0);\r\n\t\t//\t\tuseDocFrequency = true;\r\n\t\tint minFrequency=1;\r\n\t\temBkgCoefficient=0.5;\r\n\t\tprobThreshold=0.001;//\r\n\t\titerationNum = 20;\r\n\t\tArrayList<Token> tokenList;\r\n\t\tToken curToken;\r\n\t\tint j,k;\r\n\t\t//p(w|C)\r\n\r\n\t\tint[] termValues = termIndexList.values;\r\n\t\tboolean[] termActive = termIndexList.allocated;\r\n\t\ttotalCollectionCount = 0;\r\n\t\tfor(k=0;k<termActive.length;k++){\r\n\t\t\tif(!termActive[k])\r\n\t\t\t\tcontinue;\r\n\t\t\ttotalCollectionCount +=termValues[k];\r\n\t\t}\r\n\t\t\r\n\t\t// for each phrase\r\n\t\tint[] phraseFreqKeys = phraseFrequencyIndex.keys;\r\n\t\tint[] phraseFreqValues = phraseFrequencyIndex.values;\r\n\t\tboolean[] states = phraseFrequencyIndex.allocated;\r\n\t\tfor (int phraseEntry = 0;phraseEntry<states.length;phraseEntry++){\r\n\t\t\tif(!states[phraseEntry]){\r\n\t\t\t\tcontinue;\r\n\t\t\t}\r\n\t\t\tif (phraseFreqValues[phraseEntry] < minFrequency)\r\n\t\t\t\tcontinue;\r\n\t\t\ttokenList=genSignatureTranslation(phraseFreqKeys[phraseEntry]); // i is phrase number\r\n\t\t\tfor (j = 0; j <tokenList.size(); j++) {\r\n\t\t\t\tcurToken=(Token)tokenList.get(j);\r\n\t\t\t\tif(termPhraseTranslation.containsKey(curToken.getIndex())){\r\n\t\t\t\t\tIntFloatOpenHashMap old = termPhraseTranslation.get(curToken.getIndex());\r\n\t\t\t\t\tif(old.containsKey(phraseFreqKeys[phraseEntry])){\r\n\t\t\t\t\t\tSystem.out.println(\"aha need correction\");\r\n\t\t\t\t\t}\r\n\t\t\t\t\told.put(phraseFreqKeys[phraseEntry], (float) curToken.getWeight()); //phrase, weight\r\n\t\t\t\t}\r\n\t\t\t\telse {\r\n\t\t\t\t\tIntFloatOpenHashMap newPhrase = new IntFloatOpenHashMap();\r\n\t\t\t\t\tnewPhrase.put(phraseFreqKeys[phraseEntry], (float) curToken.getWeight());\r\n\t\t\t\t\ttermPhraseTranslation.put(curToken.getIndex(), newPhrase);\r\n\t\t\t\t}\r\n\t\t\t\t//\t\t\t\toutputTransMatrix.add(i,curToken.getIndex(),curToken.getWeight());\r\n\t\t\t\t//\t\t\t\toutputTransTMatrix.add(curToken.getIndex(), i, curToken.getWeight());\r\n\t\t\t\t//TODO termPhrase exists, create PhraseTerm\r\n\t\t\t}\r\n\t\t\ttokenList.clear();\r\n\t\t}\r\n\r\n\t}","private void calculateIDF2Values() throws IOException {\n\t\tfor (int i = 0; i < getTfMapArrayIDF().size(); i++) {\n\t\t\tList<Map<String, List<Double>>> gestureDocument = getTfMapArrayIDF()\n\t\t\t\t\t.get(i);\n\t\t\tMap<String, Double> idf2PerDocument = getTfMapArrayIDF2().get(i);\n\n\t\t\tfor (int j = 0; j < gestureDocument.size(); j++) {\n\t\t\t\tMap<String, List<Double>> tempMap = gestureDocument.get(j);\n\t\t\t\tIterator<Entry<String, List<Double>>> it = tempMap.entrySet()\n\t\t\t\t\t\t.iterator();\n\t\t\t\twhile (it.hasNext()) {\n\t\t\t\t\tMap.Entry<String, List<Double>> pairs = (Map.Entry) it\n\t\t\t\t\t\t\t.next();\n\t\t\t\t\tDouble inverse = (new Double(getTfMapArrayIDF().get(0)\n\t\t\t\t\t\t\t.size()) / idf2PerDocument.get(pairs.getKey())); // already\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t// inversse\n\t\t\t\t\tList<Double> tf = pairs.getValue();\n\t\t\t\t\ttf.set(2,Math.log(inverse));\n\t\t\t\t\ttf.set(3,tf.get(0) * tf.get(1)); //tf-idf\n\t\t\t\t\tidfValues.add(tf.get(1));\n\t\t\t\t\ttf.set(4,tf.get(0) * tf.get(2)); //tf-idf2\n\t\t\t\t\tidf2Values.add(tf.get(2));\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}","private void evaluationLogic() {\n // setup for logic:\n // if distToClosestEstimate[i][0] is smaller than threshold, we have a Tp\n // if distToClosestEstimate[i][0] is larger than threshold, we have a Fn\n // all estimatedFeatures that are not assigned Tp are therefore Fp\n for (int i = 0; i < groundTruthInstant.size(); ++i) {\n if (distToClosestEstimate[i][0] < truePositiveThreshold) {\n ++truePositiveCount;\n int assignedEstimatedFeature = (int) distToClosestEstimate[i][1];\n assignedEstimatedFeatures[assignedEstimatedFeature] = true;\n } else\n ++falseNegativeCount;\n }\n for (int i = 0; i < estimatedInstant.size(); ++i)\n if (!assignedEstimatedFeatures[i])\n ++falsePositiveCount;\n }","static double binarySearchForBuckets (double[] splits, double feature, boolean keepInvalid) { throw new RuntimeException(); }","abstract public TermEnum terms() throws IOException;","public abstract double score(double tf, double docLength, double precomp);","boolean isIndexed();","boolean isIndexed();","@Override\n public double classify(String[] words) {\n if (words == null || words.length == 0) {\n throw new IllegalArgumentException(\"words must not be null or empty\");\n }\n return Activation.SIGMOID.apply(bias + dotProduct(words));\n }","public Map<Integer, Boolean> testCategorization(String topic, String[] features) {\n\n\t\tint n = trainingSet.size(); // Count docs.\n\n\t\t// Count docs in class.\n\t\tint nc = 0;\n\t\tfor (Integer id : trainingSet) {\n\t\t\tboolean inClass = this.getDocument(id).getTopics().contains(topic);\n\t\t\tif (inClass)\n\t\t\t\tnc++;\n\t\t}\n\n\t\tdouble prior_c = nc / (double) n;\n\t\tdouble prior_cbar = (n - nc) / (double) n;\n\n\t\tMap<String, Double> condProb_c = new HashMap<String, Double>();\n\t\tMap<String, Double> condProb_cbar = new HashMap<String, Double>();\n\n\t\t// Count docs in class containing term.\n\t\tfor (String term : features) {\n\t\t\tSet<Integer> postings = terms.get(term).getPostings().keySet();\n\t\t\tint nct_c = 0, nct_cbar = 0;\n\t\t\tfor (Integer id : trainingSet) {\n\t\t\t\tboolean inClass = this.getDocument(id).getTopics().contains(topic);\n\t\t\t\tif (postings.contains(id)) { // document contains the term\n\t\t\t\t\tif (inClass)\n\t\t\t\t\t\tnct_c++;\n\t\t\t\t\telse\n\t\t\t\t\t\tnct_cbar++;\n\t\t\t\t}\n\t\t\t}\n\t\t\t// And calculate conditional probabilities.\n\t\t\tcondProb_c.put(term, (nct_c + 1) / (double) (nc + 2));\n\t\t\tcondProb_cbar.put(term, (nct_cbar + 1) / (double) ((n - nc) + 2));\n\t\t}\n\n\t\t// ---APPLY BERNOULLI----\n\n\t\tMap<Integer, Boolean> marked = new HashMap<Integer, Boolean>();\n\t\tfor (Integer id : testSet) {\n\t\t\tdouble score_c = Math.log(prior_c);\n\t\t\tdouble score_cbar = Math.log(prior_cbar);\n\t\t\tfor (String term : features) {\n\t\t\t\tSet<Integer> postings = terms.get(term).getPostings().keySet();\n\t\t\t\tif (postings.contains(id)) {\n\t\t\t\t\tscore_c += Math.log(condProb_c.get(term));\n\t\t\t\t\tscore_cbar += Math.log(condProb_cbar.get(term));\n\t\t\t\t} else {\n\t\t\t\t\tscore_c += Math.log(1 - condProb_c.get(term));\n\t\t\t\t\tscore_cbar += Math.log(1 - condProb_cbar.get(term));\n\t\t\t\t}\n\t\t\t}\n\t\t\tif (score_c > score_cbar)\n\t\t\t\tmarked.put(id, true);\n\t\t\telse\n\t\t\t\tmarked.put(id, false);\n\t\t}\n\t\treturn marked;\n\t}","public Object eval(Individual ind)\r\n {\r\n BinaryIndividual bi = (BinaryIndividual)ind;\r\n int partialFitness = 0;\r\n int distance = 0;\r\n double fitness = 0.0;\r\n\r\n\t for (int i=0; i<100; i++){\r\n\r\n\t distance = 0;\r\n\r\n\t for (int j=0; j<100; j++){\r\n\t if (!((BinaryIndividual)target[i]).getBooleanAllele(j)^bi.getBooleanAllele(j)) { \r\n\t\t distance++;\r\n\t }\r\n \r\n\t if (distance > partialFitness) {\r\n\t partialFitness = distance;\r\n\t }\r\n\t }\r\n }\r\n\r\n fitness = (double)partialFitness/100.0;\r\n return new Double(fitness);\r\n \r\n\r\n }","private static List<SearchData> booleanSearchFrequency(Query query, Indexer si) {\n Tokenizer tkn = new SimpleTokenizer();\n tkn.tokenize(query.getStr(), \"[a-zA-Z]{3,}\", true, true);\n List<SearchData> searchList = new ArrayList<>();\n LinkedList<Token> wordsList = tkn.getTokens();\n Iterator<Token> wordsIt = wordsList.iterator();\n HashMap<String, LinkedList<Posting>> indexer = si.getIndexer();\n int idx;\n SearchData searched_doc;\n\n while (wordsIt.hasNext()) {\n String word = wordsIt.next().getSequence();\n if (indexer.containsKey(word)) {\n\n LinkedList<Posting> posting = indexer.get(word);\n\n for (Posting pst : posting) {\n\n SearchData sd = new SearchData(query, pst.getDocId());\n\n if (!searchList.contains(sd)) {\n sd.setScore(pst.getTermFreq());\n searchList.add(sd);\n } else {\n idx = searchList.indexOf(sd);\n searched_doc = searchList.get(idx);\n searched_doc.setScore(searched_doc.getScore() + pst.getTermFreq());\n }\n }\n }\n }\n\n Collections.sort(searchList);\n\n return searchList;\n }","public int getIDFScore(String term) { \r\n\t\tif (map.containsKey(term) == false)\r\n\t\t\treturn 0;\r\n\t\treturn map.get(term).size();\r\n\t}","public interface Term {\n\t\n\t/**\n\t * Get the coefficient of a term\n\t * @return the coefficient \n\t */\n\tpublic double getCoefficient();\n\t\n\t/**\n\t * Get the exponent of a term\n\t * @return the exponent\n\t */\n\tpublic int getExponent();\n\t\n\t/**\n\t * Evaluate a term by a given value. c = constant, a(c)^n \n\t * @param x The value to be evaluated \n\t * @return The result of the evaluated term \n\t */\n\tpublic double evaluate(double x);\n\t\n}","public void setTerm(java.lang.Integer value) {\n this.term = value;\n }","public double idfCalculator(String targetWord, List<List<String>> tokenizedDescriptionCollection) {\n // indicator if the List<String> uniqueWordCollection contains the String targetWord\n // indicator can only be 1 or 0\n // 1: indicates List<String> uniqueWordCollection contains the target word\n // 0: indicates List<String> uniqueWordCollection does not contain the target word\n double totalCount = 0.0;\n for (List<String> uniqueWordCollection : tokenizedDescriptionCollection) {\n double indicator = 0.0;\n for (String word : uniqueWordCollection) {\n if (word.equals(targetWord)) {\n indicator++;\n break; // break statement is needed since indicator is either 0 or 1\n }\n }\n totalCount += indicator;\n }\n return Math.log10( (1 + tokenizedDescriptionCollection.size()) / (1 + totalCount) ) + 1;\n }","public static void main(String[] args) throws Exception \n\t{\n\t\tList<String> stopWords = new ArrayList<String>();\n\t\tstopWords = stopWordsCreation();\n\n\n\t\t\n\t\tHashMap<Integer, String> hmap = new HashMap<Integer, String>();\t//Used in tittle, all terms are unique, and any dups become \" \"\n\t\n\t\t\n\t\tList<String> uniqueTerms = new ArrayList<String>();\n\t\tList<String> allTerms = new ArrayList<String>();\n\t\t\t\t\n\t\t\n\t\tHashMap<Integer, String> hmap2 = new HashMap<Integer, String>();\n\t\tHashMap<Integer, String> allValues = new HashMap<Integer, String>();\n\t\tHashMap<Integer, Double> docNorms = new HashMap<Integer, Double>();\n\t\t\n\t\t\n\t\t\n\t\t\n\t\tMap<Integer, List<String>> postingsFileListAllWords = new HashMap<>();\t\t\n\t\tMap<Integer, List<String>> postingsFileList = new HashMap<>();\n\t\t\n\t\tMap<Integer, List<StringBuilder>> docAndTitles = new HashMap<>();\n\t\tMap<Integer, List<StringBuilder>> docAndAbstract = new HashMap<>();\n\t\tMap<Integer, List<StringBuilder>> docAndAuthors = new HashMap<>();\n\t\t\n\t\t\n\t\tMap<Integer, List<Double>> termWeights = new HashMap<>();\n\t\t\n\t\tList<Integer> docTermCountList = new ArrayList<Integer>();\n\t\t\n\t\tBufferedReader br = null;\n\t\tFileReader fr = null;\n\t\tString sCurrentLine;\n\n\t\tint documentCount = 0;\n\t\tint documentFound = 0;\n\t\tint articleNew = 0;\n\t\tint docTermCount = 0;\n\t\t\n\t\t\n\t\tboolean abstractReached = false;\n\n\t\ttry {\n\t\t\tfr = new FileReader(FILENAME);\n\t\t\tbr = new BufferedReader(fr);\n\n\t\t\t// Continues to get 1 line from document until it reaches the end of EVERY doc\n\t\t\twhile ((sCurrentLine = br.readLine()) != null) \n\t\t\t{\n\t\t\t\t// sCurrentLine now contains the 1 line from the document\n\n\t\t\t\t// Take line and split each word and place them into array\n\t\t\t\tString[] arr = sCurrentLine.split(\" \");\n\n\n\t\t\t\t//Go through the entire array\n\t\t\t\tfor (String ss : arr) \n\t\t\t\t{\n\t\t\t\t\t\n\t\t\t\t\t/*\n\t\t\t\t\t * This section takes the array and checks to see if it has reached a new\n\t\t\t\t\t * document or not. If the current line begins with an .I, then it knows that a\n\t\t\t\t\t * document has just started. If it incounters another .I, then it knows that a\n\t\t\t\t\t * new document has started.\n\t\t\t\t\t */\n\t\t\t\t\t//System.out.println(\"Before anything: \"+sCurrentLine);\n\t\t\t\t\tif (arr[0].equals(\".I\")) \n\t\t\t\t\t{\t\t\t\t\t\t\n\t\t\t\t\t\tif (articleNew == 0) \n\t\t\t\t\t\t{\n\t\t\t\t\t\t\tarticleNew = 1;\n\t\t\t\t\t\t\tdocumentFound = Integer.parseInt(arr[1]);\n\t\t\t\t\t\t} \n\t\t\t\t\t\telse if (articleNew == 1) \n\t\t\t\t\t\t{\n\t\t\t\t\t\t\tarticleNew = 0;\n\t\t\t\t\t\t\tdocumentFound = Integer.parseInt(arr[1]);\n\t\t\t\t\t\t}\t\t\t\n\t\t\t\t\t\t//System.out.println(documentFound);\n\t\t\t\t\t\t//count++;\n\t\t\t\t\t\tbreak;\n\t\t\t\t\t}\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t/* This section detects that after a document has entered,\n\t\t\t\t\t * it has to gather all the words contained in the title \n\t\t\t\t\t * section.\n\t\t\t\t\t */\n\t\t\t\t\tif (arr[0].equals(\".T\") ) \n\t\t\t\t\t{\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t// Go to line UNDER .T since that is where tittle is located\n\t\t\t\t\t\t//sCurrentLine = br.readLine();\n\t\t\t\t\t\tdocAndTitles.put(documentFound, new ArrayList<StringBuilder>());\n\t\t\t\t\t\t//System.out.println(\"docAndTitles.get(documentCount+1): \" +docAndTitles.get(documentFound));\n\t\t\t\t\t\t//System.out.println(\"Docs and titles: \"+docAndTitles);\n\t\t\t\t\t\tStringBuilder title = new StringBuilder();\n\t\t\t\t\t\t\n\t\t\t\t\t\twhile ( !(sCurrentLine = br.readLine()).matches(\".B|.A|.N|.X|.K|.C\") )\n\t\t\t\t\t\t{\t\t\t\t\n\t\t\t\t\t\t\t/* In this section, there are 2 lists being made. One list\n\t\t\t\t\t\t\t * is for all the unique words in every title in the document (hmap).\n\t\t\t\t\t\t\t * Hmap contains all unique words, and anytime a duplicate word is \n\t\t\t\t\t\t\t * found, it is replaced with an empty space in the map.\n\t\t\t\t\t\t\t * All Values \n\t\t\t\t\t\t\t * \n\t\t\t\t\t\t\t */\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t//postingsFileList.put(documentFound - 1, new ArrayList<String>());\n\t\t\t\t\t\t\t//postingsFileList.get(documentFound - 1).add(term2);\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t//System.out.println(\"current line: \"+sCurrentLine);\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\tString[] tittle = sCurrentLine.split(\" \");\n\t\t\t\t\t\t\tif (tittle[0].equals(\".W\") )\n\t\t\t\t\t\t\t{\t\t\n\t\t\t\t\t\t\t\tabstractReached = true;\n\t\t\t\t\t\t\t\tbreak;\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\ttitle.append(sCurrentLine);\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\tfor (String tittleWords : tittle)\n\t\t\t\t\t\t\t{\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\ttittleWords = tittleWords.toLowerCase();\n\t\t\t\t\t\t\t\ttittleWords = tittleWords.replaceAll(\"[-&^%'{}*|$+\\\\/\\\\?!<>=.,;_:()\\\\[\\\\]\\\"\\\\d]\", \"\");\n\t\t\t\t\t\t\t\ttittleWords = tittleWords.replaceAll(\"[-&^%'*{}|$+\\\\/\\\\?!<>=.,;_:()\\\\[\\\\]\\\"\\\\d]\", \"\");\n\t\t\t\t\t\t\t\ttittleWords = tittleWords.replaceAll(\"[-&^%'{}*|$+\\\\/\\\\?!<>=.,;_:()\\\\[\\\\]\\\"\\\\d]\", \"\");\n\t\t\t\t\t\t\t\t//System.out.println(tittleWords);\n\t\t\t\t\t\t\t\tif (hmap.containsValue(tittleWords)) \n\t\t\t\t\t\t\t\t{\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\thmap.put(documentCount, \" \");\n\t\t\t\t\t\t\t\t\tallValues.put(documentCount, tittleWords);\n\t\t\t\t\t\t\t\t\tallTerms.add(tittleWords);\n\t\t\t\t\t\t\t\t\tdocumentCount++;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\telse \n\t\t\t\t\t\t\t\t{\n\t\t\t\t\t\t\t\t\tallTerms.add(tittleWords);\n\t\t\t\t\t\t\t\t\tallValues.put(documentCount, tittleWords);\n\t\t\t\t\t\t\t\t\thmap.put(documentCount, tittleWords);\n\t\t\t\t\t\t\t\t\tif (!(uniqueTerms.contains(tittleWords)))\n\t\t\t\t\t\t\t\t\t{\n\t\t\t\t\t\t\t\t\t\tif ((stopWordsSetting && !(stopWords.contains(tittleWords))))\n\t\t\t\t\t\t\t\t\t\t\tuniqueTerms.add(tittleWords);\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tdocumentCount++;\n\t\t\t\t\t\t\t\t}\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t//docAndTitles.get(documentCount).add(\" \");\n\t\t\t\t\t\t\ttitle.append(\"\\n\");\n\t\t\t\t\t\t}\n\t\t\t\t\t\t//System.out.println(\"Title: \"+title);\n\t\t\t\t\t\t//System.out.println(\"docAndTitles.get(documentCount+1): \" +docAndTitles.get(documentFound));\n\t\t\t\t\t\tdocAndTitles.get(documentFound).add(title);\n\t\t\t\t\t\t//System.out.println(\"Done!: \"+ docAndTitles);\n\t\t\t\t\t}\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\tif (arr[0].equals(\".A\") ) \n\t\t\t\t\t{\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t// Go to line UNDER .T since that is where tittle is located\n\t\t\t\t\t\t//sCurrentLine = br.readLine();\n\t\t\t\t\t\tdocAndAuthors.put(documentFound, new ArrayList<StringBuilder>());\n\t\t\t\t\t\t//System.out.println(\"docAndTitles.get(documentCount+1): \" +docAndTitles.get(documentFound));\n\t\t\t\t\t\t//System.out.println(\"Docs and titles: \"+docAndTitles);\n\t\t\t\t\t\tStringBuilder author = new StringBuilder();\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\twhile ( !(sCurrentLine = br.readLine()).matches(\".N|.X|.K|.C\") )\n\t\t\t\t\t\t{\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t/* In this section, there are 2 lists being made. One list\n\t\t\t\t\t\t\t * is for all the unique words in every title in the document (hmap).\n\t\t\t\t\t\t\t * Hmap contains all unique words, and anytime a duplicate word is \n\t\t\t\t\t\t\t * found, it is replaced with an empty space in the map.\n\t\t\t\t\t\t\t * All Values \n\t\t\t\t\t\t\t * \n\t\t\t\t\t\t\t */\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t//postingsFileList.put(documentFound - 1, new ArrayList<String>());\n\t\t\t\t\t\t\t//postingsFileList.get(documentFound - 1).add(term2);\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t//System.out.println(\"current line: \"+sCurrentLine);\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\tString[] tittle = sCurrentLine.split(\" \");\n\t\t\t\t\t\t\tif (tittle[0].equals(\".W\") )\n\t\t\t\t\t\t\t{\t\t\n\t\t\t\t\t\t\t\tabstractReached = true;\n\t\t\t\t\t\t\t\tbreak;\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\tauthor.append(sCurrentLine);\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t//docAndTitles.get(documentCount).add(\" \");\n\t\t\t\t\t\t\tauthor.append(\"\\n\");\n\t\t\t\t\t\t}\n\t\t\t\t\t\t//System.out.println(\"Title: \"+title);\n\t\t\t\t\t\t//System.out.println(\"docAndTitles.get(documentCount+1): \" +docAndTitles.get(documentFound));\n\t\t\t\t\t\tdocAndAuthors.get(documentFound).add(author);\n\t\t\t\t\t\t//System.out.println(\"Done!: \"+ docAndTitles);\n\t\t\t\t\t}\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t/* Since there may or may not be an asbtract after\n\t\t\t\t\t * the title, we need to check what the next section\n\t\t\t\t\t * is. We know that every doc has a publication date,\n\t\t\t\t\t * so it can end there, but if there is no abstract,\n\t\t\t\t\t * then it will keep scanning until it reaches the publication\n\t\t\t\t\t * date. If abstract is empty (in tests), it will also finish instantly\n\t\t\t\t\t * since it's blank and goes straight to .B (the publishing date).\n\t\t\t\t\t * Works EXACTLY like Title \t\t \n\t\t\t\t\t */\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\tif (abstractReached) \n\t\t\t\t\t{\t\n\t\t\t\t\t\t//System.out.println(\"\\n\");\n\t\t\t\t\t\t//System.out.println(\"REACHED ABSTRACT and current line is: \" +sCurrentLine);\n\t\t\t\t\t\tdocAndAbstract.put(documentFound, new ArrayList<StringBuilder>());\n\t\t\t\t\t\tStringBuilder totalAbstract = new StringBuilder();\n\t\t\t\t\t\t\n\t\t\t\t\t\twhile ( !(sCurrentLine = br.readLine()).matches(\".T|.I|.A|.N|.X|.K|.C\") )\n\t\t\t\t\t\t{\t\n\t\t\t\t\t\t\tString[] abstaract = sCurrentLine.split(\" \");\n\t\t\t\t\t\t\tif (abstaract[0].equals(\".B\") )\n\t\t\t\t\t\t\t{\t\t\t\n\t\t\t\t\t\t\t\tabstractReached = false;\n\t\t\t\t\t\t\t\tbreak;\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\ttotalAbstract.append(sCurrentLine);\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\tString[] misc = sCurrentLine.split(\" \");\n\t\t\t\t\t\t\tfor (String miscWords : misc) \n\t\t\t\t\t\t\t{\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tmiscWords = miscWords.toLowerCase(); \n\t\t\t\t\t\t\t\tmiscWords = miscWords.replaceAll(\"[-&^%'*$+|{}?!\\\\/<\\\\>=.,;_:()\\\\[\\\\]\\\"\\\\d]\", \"\");\n\t\t\t\t\t\t\t\tmiscWords = miscWords.replaceAll(\"[-&^%'*$+|?{}!\\\\/<\\\\>=.,;_:()\\\\[\\\\]\\\"\\\\d]\", \"\");\t\t\n\t\t\t\t\t\t\t\tmiscWords = miscWords.replaceAll(\"[-&^%'*$+|{}?!\\\\/<\\\\>=.,;_:()\\\\[\\\\]\\\"\\\\d]\", \"\");\t\t\n\t\t\t\t\t\t\t\t//System.out.println(miscWords);\n\t\t\t\t\t\t\t\tif (hmap.containsValue(miscWords)) \n\t\t\t\t\t\t\t\t{\n\t\t\t\t\t\t\t\t\thmap.put(documentCount, \" \");\n\t\t\t\t\t\t\t\t\tallValues.put(documentCount, miscWords);\n\t\t\t\t\t\t\t\t\tallTerms.add(miscWords);\n\t\t\t\t\t\t\t\t\tdocumentCount++;\n\t\n\t\t\t\t\t\t\t\t} \n\t\t\t\t\t\t\t\telse \n\t\t\t\t\t\t\t\t{\n\t\t\t\t\t\t\t\t\tallTerms.add(miscWords);\n\t\t\t\t\t\t\t\t\thmap.put(documentCount, miscWords);\n\t\t\t\t\t\t\t\t\tallValues.put(documentCount, miscWords);\n\t\t\t\t\t\t\t\t\tif (!(uniqueTerms.contains(miscWords)))\n\t\t\t\t\t\t\t\t\t{\n\t\t\t\t\t\t\t\t\t\tif ((stopWordsSetting && !(stopWords.contains(miscWords))))\n\t\t\t\t\t\t\t\t\t\t\tuniqueTerms.add(miscWords);\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tdocumentCount++;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\t\n\t\t\t\t\t\t\ttotalAbstract.append(\"\\n\");\n\t\t\t\t\t\t}\n\t\t\t\t\t\tdocAndAbstract.get(documentFound).add(totalAbstract);\n\t\t\t\t\t}\n\t\t\t\t\t\n\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t}\t\n\t\t\t\t\n\t\t\t\t//Once article is found, we enter all of of it's title and abstract terms \n\t\t\t\tif (articleNew == 0) \n\t\t\t\t{\n\t\t\t\t\t\n\t\t\t\t\tdocumentFound = documentFound - 1;\n\t\t\t\t\t//System.out.println(\"Words found in Doc: \" + documentFound);\n\t\t\t\t\t//System.out.println(\"Map is\" +allValues);\n\t\t\t\t\tSet set = hmap.entrySet();\n\t\t\t\t\tIterator iterator = set.iterator();\n\n\t\t\t\t\tSet set2 = allValues.entrySet();\n\t\t\t\t\tIterator iterator2 = set2.iterator();\n\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\tpostingsFileList.put(documentFound - 1, new ArrayList<String>());\n\t\t\t\t\tpostingsFileListAllWords.put(documentFound - 1, new ArrayList<String>());\n\t\t\t\t\twhile (iterator.hasNext()) {\n\t\t\t\t\t\tMap.Entry mentry = (Map.Entry) iterator.next();\n\t\t\t\t\t\t// (\"key is: \"+ mentry.getKey() + \" & Value is: \" + mentry.getValue());\n\t\t\t\t\t\t// (\"Value is: \" + mentry.getValue());\n\t\t\t\t\t\t// );\n\t\t\t\t\t\tString term = mentry.getValue().toString();\n\t\t\t\t\t\t// //\"This is going to be put in doc3: \"+ (documentFound-1));\n\t\t\t\t\t\tpostingsFileList.get(documentFound - 1).add(term);\n\t\t\t\t\t\t// if ( !((mentry.getValue()).equals(\" \")) )\n\t\t\t\t\t\tdocTermCount++;\n\t\t\t\t\t}\n\t\t\t\t\t// \"BEFORE its put in, this is what it looks like\" + hmap);\n\t\t\t\t\thmap2.putAll(hmap);\n\t\t\t\t\thmap.clear();\n\t\t\t\t\tarticleNew = 1;\n\n\t\t\t\t\tdocTermCountList.add(docTermCount);\n\t\t\t\t\tdocTermCount = 0;\n\n\t\t\t\t\twhile (iterator2.hasNext()) {\n\t\t\t\t\t\tMap.Entry mentry2 = (Map.Entry) iterator2.next();\n\t\t\t\t\t\t// (\"key is: \"+ mentry.getKey() + \" & Value is: \" + mentry.getValue());\n\t\t\t\t\t\t// (\"Value2 is: \" + mentry2.getValue());\n\t\t\t\t\t\t// );\n\t\t\t\t\t\tString term = mentry2.getValue().toString();\n\t\t\t\t\t\t// //\"This is going to be put in doc3: \"+ (documentFound-1));\n\t\t\t\t\t\tpostingsFileListAllWords.get(documentFound - 1).add(term);\n\t\t\t\t\t\t// if ( !((mentry.getValue()).equals(\" \")) )\n\t\t\t\t\t\t// docTermCount++;\n\t\t\t\t\t}\n\n\t\t\t\t\tallValues.clear();\t\t\t\t\t\n\t\t\t\t\tdocumentFound = Integer.parseInt(arr[1]);\n\n\t\t\t\t\t// \"MEANWHILE THESE ARE ALL VALUES\" + postingsFileListAllWords);\n\n\t\t\t\t}\t\t\t\t\t\t\t\n\t\t\t}\n\t\t\t\n\t\t\t\n\t\t\t\n\t\t\t//System.out.println(\"Looking at final doc!\");\n\t\t\t//Final loop for last sets\n\t\t\tSet set = hmap.entrySet();\n\t\t\tIterator iterator = set.iterator();\n\n\t\t\tSet setA = allValues.entrySet();\n\t\t\tIterator iteratorA = setA.iterator();\n\t\t\tpostingsFileList.put(documentFound - 1, new ArrayList<String>());\n\t\t\tpostingsFileListAllWords.put(documentFound - 1, new ArrayList<String>());\n\t\t\twhile (iterator.hasNext()) {\n\t\t\t\tMap.Entry mentry = (Map.Entry) iterator.next();\n\t\t\t\t// (\"key is: \"+ mentry.getKey() + \" & Value is: \" + mentry.getValue());\n\t\t\t\t// (\"Value is: \" + mentry.getValue());\n\t\t\t\t// //);\n\t\t\t\t// if ( !((mentry.getValue()).equals(\" \")) )\n\t\t\t\tString term2 = mentry.getValue().toString();\n\t\t\t\tpostingsFileList.get(documentFound - 1).add(term2);\n\n\t\t\t\tdocTermCount++;\n\t\t\t}\n\t\t\t//System.out.println(\"Done looking at final doc!\");\n\t\t\t\n\t\t\t\n\t\t\t//System.out.println(\"Sorting time!\");\n\t\t\twhile (iteratorA.hasNext()) {\n\t\t\t\tMap.Entry mentry2 = (Map.Entry) iteratorA.next();\n\t\t\t\t// (\"key is: \"+ mentry.getKey() + \" & Value is: \" + mentry.getValue());\n\t\t\t\t// (\"Value2 is: \" + mentry2.getValue());\n\t\t\t\t// //);\n\t\t\t\tString term = mentry2.getValue().toString();\n\t\t\t\t// //\"This is going to be put in doc3: \"+ (documentFound-1));\n\t\t\t\tpostingsFileListAllWords.get(documentFound - 1).add(term);\n\t\t\t\t// if ( !((mentry.getValue()).equals(\" \")) )\n\t\t\t\t// docTermCount++;\n\t\t\t}\n\n\t\t\thmap2.putAll(hmap);\n\t\t\thmap.clear();\n\t\t\tdocTermCountList.add(docTermCount);\n\t\t\tdocTermCount = 0;\n\n\n\t\t\t\n\t\t\n\t\t\t// END OF LOOKING AT ALL DOCS\n\t\t\t\n\t\t\t//System.out.println(\"Docs and titles: \"+docAndTitles);\n\t\t\t\n\t\t\t//System.out.println(\"All terms\" +allTerms);\n\t\t\tString[] sortedArray = allTerms.toArray(new String[0]);\n\t\t\tString[] sortedArrayUnique = uniqueTerms.toArray(new String[0]);\n\t\t\t//System.out.println(Arrays.toString(sortedArray));\n\t\t\t\n\t\t\tArrays.sort(sortedArray);\n\t\t\tArrays.sort(sortedArrayUnique);\n\t\t\t\n\t\t\t\n\t\t\t\n\t\t\t//Sortings \n\t\t\tSet set3 = hmap2.entrySet();\n\t\t\tIterator iterator3 = set3.iterator();\n\n\t\t\t// Sorting the map\n\t\t\t//System.out.println(\"Before sorting \" +hmap2);\t\t\t\n\t\t\tMap<Integer, String> map = sortByValues(hmap2);\n\t\t\t//System.out.println(\"after sorting \" +map);\n\t\t\t// //\"After Sorting:\");\n\t\t\tSet set2 = map.entrySet();\n\t\t\tIterator iterator2 = set2.iterator();\n\t\t\tint docCount = 1;\n\t\t\twhile (iterator2.hasNext()) {\n\t\t\t\tMap.Entry me2 = (Map.Entry) iterator2.next();\n\t\t\t\t// (me2.getKey() + \": \");\n\t\t\t\t// //me2.getValue());\n\t\t\t}\n\t\t\t\n\t\t\t//System.out.println(\"Done sorting!\");\n\t\t\n\t\t\t\n\t\t\t\n\t\t\t\n\t\t\t//System.out.println(\"Posting starts \");\n\t\t\t//\"THIS IS START OF DICTIONARTY\" \n\t\t\tBufferedWriter bw = null;\n\t\t\tFileWriter fw = null;\n\t\t\t\n\t\t\t\n\t\t\t//System.out.println(\"Start making an array thats big as every doc total \");\n\t\t\tfor (int z = 1; z < documentFound+1; z++)\n\t\t\t{\n\t\t\t\ttermWeights.put(z, new ArrayList<Double>());\n\t\t\t}\n\t\t\t//System.out.println(\"Done making that large array Doc \");\n\t\t\t\n\t\t\t//System.out.println(\"Current Weights: \"+termWeights);\n\t\t\t\n\t\t\t//System.out.println(\"All terms\" +allTerms)\n\t\t\t//System.out.println(Arrays.toString(sortedArray));\n\t\t\t//System.out.println(Arrays.toString(sortedArrayUnique));\n\t\t\t//System.out.println(uniqueTerms);\n\t\t\t\n\t\t\t\n\t\t\t\n\t\t\t//\tSystem.out.println(\"Posting starts \");\n\t\t\t// \tPOSTING FILE STARTS \n\t\t\ttry {\n\t\t\t\t// Posting File\n\t\t\t\t//System.out.println(\"postingsFileListAllWords: \"+postingsFileListAllWords); //Contains every word including Dups, seperated per doc\n\t\t\t\t//System.out.println(\"postingsFileList: \"+postingsFileList); \t\t //Contains unique words, dups are \" \", seperated per doc\n\t\t\t\t//System.out.println(\"postingsFileListAllWords.size(): \" +postingsFileListAllWords.size()); //Total # of docs \n\t\t\t\t//System.out.println(\"Array size: \"+sortedArrayUnique.length);\n\n\t\t\t\tfw = new FileWriter(POSTING);\n\t\t\t\tbw = new BufferedWriter(fw);\n\t\t\t\tString temp = \" \";\n\t\t\t\tDouble termFreq = 0.0;\n\t\t\t\t// //postingsFileListAllWords);\n\t\t\t\tList<String> finalTermList = new ArrayList<String>();\n\t\t\t\t\n\t\t\t\t\n\t\t\t\n\t\t\t\t\t// //postingsFileList.get(i).size());\n\t\t\t\t\tfor (int j = 0; j < sortedArrayUnique.length; ++j)\t\t\t\t\t // go thru each word, CURRENT TERM\n\t\t\t\t\t{\n\t\t\t\t\t\t//System.out.println(\"Term is: \" + sortedArrayUnique[j]);\n\t\t\t\t\t\ttemp = sortedArrayUnique[j];\t\t\t\t\t\n\t\t\t\t\t\tif ((stopWordsSetting && stopWords.contains(temp))) \n\t\t\t\t\t\t{\t\t\t\t\t\t\n\t\t\t\t\t\t\tcontinue;\n\t\t\t\t\t\t}\n\n\t\t\t\t\t\tif (!(finalTermList.contains(temp))) \n\t\t\t\t\t\t{\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t//PART TO FIND DOCUMENT FREQ\t\t\t\t\t\t\t\n\t\t\t\t\t\t\tint docCountIDF = 0;\n\t\t\t\t\t\t\t//Start here for dictionary \n\t\t\t\t\t\t\tfor (int totalWords = 0; totalWords < sortedArray.length; totalWords++) \t\t\n\t\t\t\t\t\t\t{\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tif (temp.compareTo(\" \") == 0 || (stopWordsSetting && stopWords.contains(temp))) \n\t\t\t\t\t\t\t\t{\n\t\t\t\t\t\t\t\t\t//EITHER BLANK OR STOPWORD \n\t\t\t\t\t\t\t\t\t//System.out.println(\"fOUND STOP WORD\");\n\t\t\t\t\t\t\t\t\tcontinue;\n\t\t\t\t\t\t\t\t}\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tString temp2 = sortedArray[totalWords];\n\t\t\t\t\t\t\t\t\t//System.out.println(\"Compare: \"+temp+ \" with \" +temp2);\n\t\t\t\t\t\t\t\t\tif (temp.compareTo(temp2) == 0) {\n\t\t\t\t\t\t\t\t\t\t// (temp2+\" \");\t\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\tdocCountIDF++;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t//System.out.println(\"Total Number: \" +docCountIDF);\n\t\t\t\t\t\t\t//System.out.println(\"documentFound: \" +documentFound);\n\t\t\t\t\t\t\t//System.out.println(\"So its \" + documentFound + \" dividied by \" +docCountIDF);\n\t\t\t\t\t\t\t//docCountIDF = 1;\t\t\t\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\tdouble idf = (Math.log10(((double)documentFound/(double)docCountIDF)));\n\t\t\t\t\t\t\t//System.out.println(\"Calculated IDF: \"+idf);\n\t\t\t\t\t\t\tif (idf < 0.0)\n\t\t\t\t\t\t\t{\n\t\t\t\t\t\t\t\tidf = 0.0;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t//System.out.println(\"IDF is: \" +idf);\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t//System.out.println(\"Size of doc words: \" + postingsFileListAllWords.size());\n\t\t\t\t\t\t\tfor (int k = 0; k < postingsFileListAllWords.size(); k++) \t\t//Go thru each doc. Since only looking at 1 term, it does it once per doc\n\t\t\t\t\t\t\t{\n\t\t\t\t\t\t\t\t//System.out.println(\"Current Doc: \" +(k+1));\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\ttermFreq = 1 + (Math.log10(Collections.frequency(postingsFileListAllWords.get(k), temp)));\t\t\t\n\t\t\t\t\t\t\t\t\t//System.out.println(\"Freq is: \" +Collections.frequency(postingsFileListAllWords.get(k), temp));\n\t\t\t\t\t\t\t\t\t//System.out.println(termFreq + \": \" + termFreq.isInfinite());\n\t\t\t\t\t\t\t\t\tif (termFreq.isInfinite() || termFreq <= 0)\n\t\t\t\t\t\t\t\t\t{\n\t\t\t\t\t\t\t\t\t\ttermFreq = 0.0;\n\t\t\t\t\t\t\t\t\t}\t\t\t\t\n\t\t\t\t\t\t\t\t\t//System.out.println(\"termFreq :\" +termFreq); \n\t\t\t\t\t\t\t\t\t//System.out.println(\"idf: \" +idf);\n\t\t\t\t\t\t\t\t\ttermWeights.get(k+1).add( (idf*termFreq) );\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t//System.out.println(\"\");\n\t\t\t\t\t\t\tfinalTermList.add(temp);\t\t\t\t\t\t\t\n\t\t\t\t\t\t}\t\n\t\t\t\t\t\t//System.out.println(\"Current Weights: \"+termWeights);\n\t\t\t\t\t\t\n\t\t\t\t\t\t//FINALCOUNTER\n\t\t\t\t\t\t//System.out.println(\"Done looking at word: \" +j);\n\t\t\t\t\t\t//System.out.println(\"\");\n\t\t\t\t\t}\n\t\t\t\t\t\n\t\t\t\t\t//System.out.println(\"Current Weights: \"+termWeights);\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\twhile (true)\n\t\t\t\t {\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\tSystem.out.println(\"Enter a query: \");\n\t\t\t\t\t\n\t \tScanner scanner = new Scanner(System.in);\n\t \tString enterQuery = scanner.nextLine();\n\t \t\n\t \t\n\t\t\t\t\tList<Double> queryWeights = new ArrayList<Double>();\n\t\t\t\t\t\n\t\t\t\t\t// Query turn\t\t\t\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\tenterQuery = enterQuery.toLowerCase();\t\t\n\t\t\t\t\tenterQuery = enterQuery.replaceAll(\"[-&^%'*$+|{}?!\\\\/<\\\\>=.,;_:()\\\\[\\\\]\\\"]\", \"\");\n\t\t\t\t\t//System.out.println(\"Query is: \" + enterQuery);\n\t\t\t\t\t\n\t\t\t\t\tif (enterQuery.equals(\"exit\"))\n\t\t\t\t\t{\n\t\t\t\t\t\tbreak;\n\t\t\t\t\t}\n\t\t\t\t\tString[] queryArray = enterQuery.split(\" \");\n\t\t\t\t\tArrays.sort(queryArray);\n\t\t\t\t\t\n\t\t\t\t\t//Find the query weights for each term in vocab\n\t\t\t\t\tfor (int j = 0; j < sortedArrayUnique.length; ++j)\t\t\t\t\t // go thru each word, CURRENT TERM\n\t\t\t\t\t{\n\t\t\t\t\t\t//System.out.println(\"Term is: \" + sortedArrayUnique[j]);\n\t\t\t\t\t\ttemp = sortedArrayUnique[j];\t\t\t\t\t\n\t\t\t\t\t\tif ((stopWordsSetting && stopWords.contains(temp))) \n\t\t\t\t\t\t{\t\t\t\t\t\t\n\t\t\t\t\t\t\tcontinue;\n\t\t\t\t\t\t}\n\t\t\t\t\t\n\t\t\t\t\t\tint docCountDF = 0;\n\t\t\t\t\t\t//Start here for dictionary \n\t\t\t\t\t\tfor (int totalWords = 0; totalWords < queryArray.length; totalWords++) \t\t\n\t\t\t\t\t\t{\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\tif (temp.compareTo(\" \") == 0 || (stopWordsSetting && stopWords.contains(temp))) \n\t\t\t\t\t\t\t{\n\t\t\t\t\t\t\t\t//EITHER BLANK OR STOPWORD\n\t\t\t\t\t\t\t\tcontinue;\n\t\t\t\t\t\t\t}\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tString temp2 = queryArray[totalWords];\n\t\t\t\t\t\t\t\t//System.out.println(\"Compare: \"+temp+ \" with \" +temp2);\n\t\t\t\t\t\t\t\tif (temp.compareTo(temp2) == 0) {\n\t\t\t\t\t\t\t\t\t// (temp2+\" \");\t\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tdocCountDF++;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t\tDouble queryWeight = 1 + (Math.log10(docCountDF));\n\t\t\t\t\t\tif (queryWeight.isInfinite())\n\t\t\t\t\t\t{\n\t\t\t\t\t\t\tqueryWeight = 0.0;\n\t\t\t\t\t\t}\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\tqueryWeights.add(queryWeight);\n\t\t\t\t\t}\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t//System.out.println(\"Query WEights is: \"+queryWeights);\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t// Finding the norms for DOCS\t\t\t\t\t\n\t\t\t\t\tfor (int norms = 1; norms < documentFound+1; norms++)\n\t\t\t\t\t{\n\t\t\t\t\t\tdouble currentTotal = 0.0;\n\t\t\t\t\t\t\n\t\t\t\t\t\tfor (int weightsPerDoc = 0; weightsPerDoc < termWeights.get(norms).size(); weightsPerDoc++)\n\t\t\t\t\t\t{\t\t\t\t\t\t\n\t\t\t\t\t\t\tdouble square = Math.pow(termWeights.get(norms).get(weightsPerDoc), 2);\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t//System.out.println(\"Current square: \" + termWeights.get(norms).get(weightsPerDoc));\n\t\t\t\t\t\t\tcurrentTotal = currentTotal + square;\n\t\t\t\t\t\t\t//System.out.println(\"Current total: \" + currentTotal);\n\t\t\t\t\t\t}\n\t\t\t\t\t\t//System.out.println(\"About to square root this: \" +currentTotal);\n\t\t\t\t\t\tdouble root = Math.sqrt(currentTotal);\n\t\t\t\t\t\tdocNorms.put(norms, root);\n\t\t\t\t\t}\n\t\t\t\t\t//System.out.println(\"All of the docs norms: \"+docNorms);\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t//Finding the norm for the query\n\t\t\t\t\tdouble currentTotal = 0.0;\t\t\t\t\t\n\t\t\t\t\tfor (int weightsPerDoc = 0; weightsPerDoc < queryWeights.size(); weightsPerDoc++)\n\t\t\t\t\t{\t\t\t\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\tdouble square = Math.pow(queryWeights.get(weightsPerDoc), 2);\n\t\t\t\t\t\tcurrentTotal = currentTotal + square;\t\t\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t}\n\t\t\t\t\tdouble root = Math.sqrt(currentTotal);\n\t\t\t\t\tdouble queryNorm = root; \t\t\t\t\t\t\n\t\t\t\t\t//System.out.println(\"Query norm \" + queryNorm);\n\t\t\t\t\t\n\t\t\t\t\t//Finding the cosine sim\n\t\t\t\t\t//System.out.println(\"Term Weights \" + termWeights);\n\t\t\t\t\tHashMap<Integer, Double> cosineScore = new HashMap<Integer, Double>();\n\t\t\t\t\tfor (int cosineSim = 1; cosineSim < documentFound+1; cosineSim++)\n\t\t\t\t\t{\n\t\t\t\t\t\tdouble total = 0.0;\n\t\t\t\t\t\tfor (int docTerms = 0; docTerms < termWeights.get(cosineSim).size(); docTerms++)\n\t\t\t\t\t\t{\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\tdouble docTermWeight = termWeights.get(cosineSim).get(docTerms);\n\t\t\t\t\t\t\tdouble queryTermWeight = queryWeights.get(docTerms);\n\t\t\t\t\t\t\t//System.out.println(\"queryTermWeight \" + queryTermWeight);\n\t\t\t\t\t\t\t//System.out.println(\"docTermWeight \" + docTermWeight);\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\ttotal = total + (docTermWeight*queryTermWeight);\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t}\n\t\t\t\t\t\tdouble cosineSimScore = 0.0;\n\t\t\t\t\t\tif (!(total == 0.0 || (docNorms.get(cosineSim) * queryNorm) == 0))\n\t\t\t\t\t\t{\n\t\t\t\t\t\t\tcosineSimScore = total / (docNorms.get(cosineSim) * queryNorm);\n\t\t\t\t\t\t}\n\t\t\t\t\t\telse\n\t\t\t\t\t\t{\n\t\t\t\t\t\t\tcosineSimScore = 0.0;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t\n\t\t\t\t\t\tcosineScore.put(cosineSim, cosineSimScore);\n\t\t\t\t\t}\n\t\t\t\t\tcosineScore = sortByValues2(cosineScore);\t\t\t\t\t\n\t\t\t\t\t//System.out.println(\"This is the cosineScores: \" +cosineScore);\n\t\t\t\t\t\n\t\t\t\t\t//System.out.println(\"docAndTitles: \"+ docAndTitles);\n\t\t\t\t\tint topK = 0;\n\t\t\t\t\tint noValue = 0;\n\t\t\t\t\tfor (Integer name: cosineScore.keySet())\n\t\t\t\t\t{\n\t\t\t\t\t\tif (topK < 50)\n\t\t\t\t\t\t{\t\n\t\t\t\t\t\t\t\n\t\t\t\t String key =name.toString();\n\t\t\t\t //String value = cosineScore.get(name).toString(); \n\t\t\t\t if (!(cosineScore.get(name) <= 0))\n\t\t\t\t {\n\t\t\t\t \tSystem.out.println(\"Doc: \"+key);\t\t\t\t \t\t\t\t\t \t\t\t\t\t \t\n\t\t\t\t \t\n\t\t\t\t \tStringBuilder builder = new StringBuilder();\n\t\t\t\t \tfor (StringBuilder value : docAndTitles.get(name)) {\n\t\t\t\t \t builder.append(value);\n\t\t\t\t \t}\n\t\t\t\t \tString text = builder.toString();\t\t\t\t \t\n\t\t\t\t \t//System.out.println(\"Title:\\n\" +docAndTitles.get(name));\n\t\t\t\t \tSystem.out.println(\"Title: \" +text);\n\t\t\t\t \t\n\t\t\t\t \t\n\t\t\t\t \t\n\t\t\t\t \t\n\t\t\t\t \t\n\t\t\t\t \t//System.out.println(\"Authors:\\n\" +docAndAuthors.get(name));\n\t\t\t\t \t\n\t\t\t\t \tif (docAndAuthors.get(name) == null || docAndAuthors.get(name).toString().equals(\"\"))\n\t\t\t\t \t{\n\t\t\t\t \t\tSystem.out.println(\"Authors: N\\\\A\\n\");\n\t\t\t\t \t}\n\t\t\t\t \telse \n\t\t\t\t \t{\t\t\t\t \t\t\t\t\t\t \t\n\t\t\t\t\t \tStringBuilder builder2 = new StringBuilder();\n\t\t\t\t\t \tfor (StringBuilder value : docAndAuthors.get(name)) {\n\t\t\t\t\t \t builder2.append(value);\n\t\t\t\t\t \t}\n\t\t\t\t\t \tString text2 = builder2.toString();\t\t\t\t \t\n\t\t\t\t\t \t\n\t\t\t\t\t \tSystem.out.println(\"Authors found: \" +text2);\n\t\t\t\t \t}\t\n\t\t\t\t \t\n\t\t\t\t \t\n\t\t\t\t \t/* ABSTRACT \n\t\t\t\t \tif (docAndAbstract.get(name) == null)\n\t\t\t\t \t{\n\t\t\t\t \t\tSystem.out.println(\"Abstract: N\\\\A\\n\");\n\t\t\t\t \t}\n\t\t\t\t \telse \n\t\t\t\t \t{\t\t\t\t \t\t\t\t\t\t \t\n\t\t\t\t\t \tStringBuilder builder2 = new StringBuilder();\n\t\t\t\t\t \tfor (StringBuilder value : docAndAbstract.get(name)) {\n\t\t\t\t\t \t builder2.append(value);\n\t\t\t\t\t \t}\n\t\t\t\t\t \tString text2 = builder2.toString();\t\t\t\t \t\n\t\t\t\t\t \t\n\t\t\t\t\t \tSystem.out.println(\"Abstract: \" +text2);\n\t\t\t\t \t}\t\n\t\t\t\t \t*/\n\t\t\t\t \t\n\t\t\t\t \tSystem.out.println(\"\");\n\t\t\t\t }\n\t\t\t\t else {\n\t\t\t\t \tnoValue++;\n\t\t\t\t }\n\t\t\t\t topK++;\n\t\t\t\t \n\t\t\t\t\t\t}\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\tif (noValue == documentFound)\n\t\t\t\t\t\t{\n\t\t\t\t\t\t\tSystem.out.println(\"No documents contain query!\");\n\t\t\t\t\t\t}\n\t\t\t\t\t} \n\t\t\t\t\ttopK=0;\n\t\t\t\t\tnoValue = 0;\n\t\t\t\t }\n\t\t\t\t\n\t\t\t} finally {\n\t\t\t\ttry {\n\t\t\t\t\tif (bw != null)\n\t\t\t\t\t\tbw.close();\n\n\t\t\t\t\tif (fw != null)\n\t\t\t\t\t\tfw.close();\n\n\t\t\t\t} catch (IOException ex) {\n\n\t\t\t\t\tex.printStackTrace();\n\n\t\t\t\t}\n\n\t\t\t}\n\t\t\t\n\n\t\t} catch (IOException e) {\n\t\t\te.printStackTrace();\n\t\t} finally {\n\t\t\ttry {\n\t\t\t\tif (br != null)\n\t\t\t\t\tbr.close();\n\n\t\t\t\tif (fr != null)\n\t\t\t\t\tfr.close();\n\n\t\t\t} catch (IOException ex) {\n\n\t\t\t\tex.printStackTrace();\n\n\t\t\t}\n\n\t\t}\n\t\t\t\n\t\t\t\n\t\t\t\n\t\t\t\n\t\t\t\n\n\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\tint itemCount = uniqueTerms.size();\n\t\t\t//System.out.println(allValues);\n\t\t\tSystem.out.println(\"Total Terms BEFORE STEMING: \" +itemCount);\n\t\t\tSystem.out.println(\"Total Documents \" + documentFound);\n\t\t\t\t\t\t\n\t\t \n\t\t\t \n\t\t\t \n\t\t\t//END OF MAIN\n\t\t}","private int disjunctMatch( int ix0, int ix1 )\n {\n \tint n = 0;\n if( ix0 == ix1 ){\n // TODO: complain, this should never happen.\n return 0;\n }\n \n if( ix0>ix1 ){\n int h = ix0;\n ix0 = ix1;\n ix1 = h;\n }\n \twhile( (ix0+n)<ix1 && (text[ix0+n] == text[ix1+n]) && (text[ix0+n] != STOP) ){\n \t n++;\n \t}\n \treturn n;\n }","private void countOnePseudoDoc(int docIdx) {\n\t\tFeatureSequence fs = (FeatureSequence)documents.get(docIdx).getData();\n\t\tint[] tokens = fs.getFeatures();\n\t\tdouble[] tmpCounts = new double[numOfTerms];\n\t\tArrays.fill(tmpCounts, 0);\n\t\tfor(int i=0; i<tokens.length; i++) {\n\t\t\tint term = tokens[i];\n\t\t\ttmpCounts[term] += alpha * 1;\n\t\t}\n\t\t\n\t\tPairedInfo pairedDocs = pairs.links.get(docIdx);\n\t\tif(!pairedDocs.isEmpty()) {\n//\t\t\tSystem.out.println(docIdx + \":\" + Arrays.toString(tokens));\n\t\t\tint[] pIds = pairedDocs.getPairedIdsArray();\n//\t\t\tSystem.out.println(docIdx + \": \" + pairedDocs.getLength() + \":\" + Arrays.toString(pIds));\n\t\t\tdouble[] sims = pairedDocs.getPairedSimArray();\n\t\t\tsims = Util.reWeightVector(sims);\n\t\t\tfor(int p=0; p<pIds.length; p++) {\n\t\t\t\tfs = (FeatureSequence)documents.get(p).getData();\n\t\t\t\tint[] pTokens = fs.getFeatures();\n\t\t\t\tfor(int i=0; i<pTokens.length; i++) {\n\t\t\t\t\tint term = pTokens[i];\n\t\t\t\t\ttmpCounts[term] += (1-alpha) * sims[p];\n\t\t\t\t}\n\t\t\t\ttokens = ArrayUtils.append(tokens, fs.getFeatures());\n\t\t\t}\n//\t\t\tSystem.out.println(docIdx + \":\" + Arrays.toString(tokens));\n\t\t}\n\t\t\n\t\tint termNum = MalletTfidf.distinctNumbers(tokens);\n\t\tpseudoTermIndex[docIdx]= new int[termNum];\n\t\tpseudoTf[docIdx] = new double[termNum];\n\t\tint[] tmpTf = new int[termNum];\n\t\tMalletTfidf.countTf(tokens, pseudoTermIndex[docIdx], tmpTf); // count the tf frequency\n\t\tfor(int i=0; i<pseudoTermIndex[docIdx].length; i++) {\n\t\t\tint term = pseudoTermIndex[docIdx][i];\n\t\t\tpseudoTf[docIdx][i] = tmpCounts[term];\n\t\t}\n\t\tpseudoTermWeight[docIdx] = Util.reWeightVector(pseudoTf[docIdx]);\n\t}","int countTypedFeatures();","public java.lang.Integer getTerm() {\n return term;\n }","public abstract double score(double tf, double docLength);","boolean hasFixedHotwordGain();","public static float[] getVector(\n Map<String, Map<String, List<Integer>>> index,\n List<String> allTerms,\n Map<String, List<Integer>> docTerms,\n int docCount) {\n\n float[] vector = new float[allTerms.size()];\n\n for (int i = 0; i < allTerms.size(); i++) {\n String term = allTerms.get(i);\n\n // the number of documents in which the term appears\n int termDocCount = 0;\n if (index.containsKey(term)) {\n termDocCount = index.get(term).size();\n }\n\n if (docTerms.containsKey(term)) {\n vector[i] =\n (float)\n (Math.sqrt(docTerms.get(term).size())\n * Math.log10((double) docCount / termDocCount));\n }\n }\n\n return vector;\n }","@Override\n public void postInserts() \n {\n for(IndexObject i: myIndex.values())\n {\n i.tfidf(documentData);\n }\n }","@Override\n public double makePrediction(ParsedText text) {\n double pr = 0.0;\n\n /* FILL IN HERE */\n double productSpam = 0;\n double productNoSpam = 0;\n \n int i, tempSpam,tempNoSpam;\n int minSpam, minNoSpam ;\n \n \n for (String ng: text.ngrams) {\n \tminSpam = Integer.MAX_VALUE;\n \tminNoSpam = Integer.MAX_VALUE;\n \n\n \tfor (int h = 0;h < nbOfHashes; h++) {\n \t\ti = hash(ng,h);\n\n \t\ttempSpam = counts[1][h][i];\n \t\ttempNoSpam = counts[0][h][i];\n \t\t\n \t\t//System.out.print(tempSpam + \" \");\n\n \t\tminSpam = minSpam<tempSpam?minSpam:tempSpam; \n \t\tminNoSpam = minNoSpam<tempNoSpam?minNoSpam:tempNoSpam; \n \t\t\n \t}\n\n \t//System.out.println(minSpam + \"\\n\");\n \tproductSpam += Math.log(minSpam);\n \tproductNoSpam += Math.log(minNoSpam);\n }\n \n // size of set minus 1\n int lm1 = text.ngrams.size() - 1;\n \n //System.out.println((productNoSpam - productSpam ));\n //System.out.println((lm1*Math.log(this.classCounts[1]) - lm1*Math.log(this.classCounts[0])));\n\n //\n pr = 1 + Math.exp(productNoSpam - productSpam + lm1*(Math.log(classCounts[1]) - Math.log(classCounts[0])));\n // System.out.print(1.0/pr + \"\\n\");\n \n return 1.0 / pr;\n\n }","int countFeatures();","int countFeatures();","private IDictionary<URI, IDictionary<String, Double>> computeAllDocumentTfIdfVectors(ISet<Webpage> pages) {\n // Hint: this method should use the idfScores field and\n // call the computeTfScores(...) method.\n\t\tdocumentTfIdfVectors = new ChainedHashDictionary<URI, IDictionary<String, Double>>();\n\t\t\n\t\t// Iterates through the given set of webpages\n\t\tfor (Webpage page: pages) {\n\t\t\tIDictionary<String, Double> tfIdfScores = new ChainedHashDictionary<String, Double>();\n\t\t\tIDictionary<String, Double> tfScores = computeTfScores(page.getWords());\n\t\t\t\n\t\t\t// Computes TfIdf scores\n\t\t\tfor (KVPair<String, Double> pair: tfScores) {\n\t\t\t\tDouble tfIdfScore = pair.getValue() * idfScores.get(pair.getKey());\n\t\t\t\ttfIdfScores.put(pair.getKey(), tfIdfScore);\n\t\t\t}\n\t\t\tdocumentTfIdfVectors.put(page.getUri(), tfIdfScores);\n\t\t}\n\t\treturn documentTfIdfVectors;\n }","static boolean checkTerm() {\r\n // Checks if this is a complete term\r\n boolean complete = false;\r\n\r\n // simple_term (base case)\r\n if (token.equals(\"IDENTIFIER\") || token.equals(\"SIGNED_INTEGER\") || token.equals(\"UNSIGNED_INTEGER\")) {\r\n complete = true;\r\n lex();\r\n\r\n // simple_term op\r\n if (token.equals(\"PLUS\") || token.equals(\"MINUS\") || token.equals(\"STAR\") || token.equals(\"DIVOP\") || token.equals(\"MOD\")) {\r\n complete = false;\r\n lex();\r\n\r\n // simple_term op term\r\n if(checkTerm()) {\r\n complete = true;\r\n }\r\n }\r\n }\r\n\r\n // (\r\n else if (token.equals(\"LEFT_PAREN\")) {\r\n lex();\r\n\r\n // ( term\r\n if(checkTerm()) {\r\n\r\n // ( term )\r\n if (token.equals(\"RIGHT_PAREN\")) {\r\n complete = true;\r\n lex();\r\n\r\n // ( term ) op\r\n if (token.equals(\"PLUS\") || token.equals(\"MINUS\") || token.equals(\"STAR\") || token.equals(\"DIVOP\") || token.equals(\"MOD\")) {\r\n complete = false;\r\n lex();\r\n\r\n // ( term ) op term\r\n if (checkTerm()) {\r\n complete = true;\r\n }\r\n }\r\n }\r\n\r\n // ( term op\r\n else if (token.equals(\"PLUS\") || token.equals(\"MINUS\") || token.equals(\"STAR\") || token.equals(\"DIVOP\") || token.equals(\"MOD\")) {\r\n complete = false;\r\n lex();\r\n\r\n // ( term op term\r\n if(checkTerm()) {\r\n\r\n // ( term op term )\r\n if (token.equals(\"RIGHT_PAREN\")) {\r\n complete = true;\r\n lex();\r\n\r\n // ( term op term ) op\r\n if (token.equals(\"PLUS\") || token.equals(\"MINUS\") || token.equals(\"STAR\") || token.equals(\"DIVOP\") || token.equals(\"MOD\")) {\r\n complete = false;\r\n lex();\r\n\r\n // ( term op term ) op term\r\n if (checkTerm()) {\r\n complete = true;\r\n }\r\n }\r\n }\r\n }\r\n }\r\n }\r\n }\r\n return complete;\r\n }","public abstract double score(\n\t\tdouble tf,\n\t\tdouble docLength,\n\t\tdouble n_t,\n\t\tdouble F_t,\n\t\tdouble keyFrequency);","public double computeIDF(HashMap<String, Integer> termPostings, int documents) {\n // Document frequency is the number of postings\n int df = termPostings.size();\n\n return Math.log(((double) documents) / (df + 1));\n }","public Set<String> calculateDistance() throws IOException {\n booleanSearch();\n\n Set<String> words = invertedIndexForQuerryWords.keySet();\n Map<String, Double> tfidfQuerry = new TreeMap<>();\n\n //load idf\n char c='a';\n char prC = 'v';\n for (String word : words){\n c = word.charAt(0);\n if(c != prC) {\n String path = Constants.PATH_TO_IDF + c + \"IDF.idf\";\n prC = c;\n idfMap.putAll(objectMapper.readValue(new File(path), new TypeReference<TreeMap<String, Double>>(){}));\n }\n }\n\n Map<String, Double> distanceMap = new HashMap<>();\n double sum = 0.0;\n //calculez norma interogarii\n for(String word:words){\n double idf, tf;\n if(idfMap.containsKey(word)) {\n idf = idfMap.get(word);\n tf = 1.0 / words.size();\n tfidfQuerry.put(word, tf * idf);\n\n sum += (tf * idf) * (tf * idf);\n } else {\n sum += 0.0;\n }\n }\n\n double normQuerry = Math.sqrt(sum);\n\n //iau toate documentele rezultate din boolean search\n Set<String> docs = new TreeSet<>();\n for(List<MyPair> list : invertedIndexForQuerryWords.values()) {\n if (list != null) {\n docs.addAll(list.stream().map(p -> p.getKey()).collect(Collectors.toSet()));\n }\n }\n\n List<File> documents = FileLoader.getFilesForInternalPath(\"Norms\", \".norm\");\n\n Map<String, Double> norms = new HashMap<>();\n for(File file : documents) {\n norms.putAll(objectMapper.readValue(file, new TypeReference<TreeMap<String, Double>>(){}));\n }\n\n //pentru fiecare document din boolean search calculez distanta cosinus\n for(String doc : docs) {\n\n String fileName = Paths.get(doc).getFileName().toString();\n\n String filePath = Constants.PATH_TO_TF + fileName.replaceFirst(\"[.][^.]+$\", \".tf\");\n\n Map<String, Double> tf = objectMapper.readValue(new File(filePath), new TypeReference<TreeMap<String, Double>>(){});\n double wordTF, wordIDF;\n double vectorialProduct = 0.0;\n double tfidfForQueryWord;\n\n for(String word : words) {\n if (tf.containsKey(word)) {\n wordTF = tf.get(word);\n wordIDF = idfMap.get(word);\n tfidfForQueryWord = tfidfQuerry.get(word);\n\n vectorialProduct += tfidfForQueryWord * wordIDF * wordTF;\n }\n }\n\n double normProduct = normQuerry * norms.get(Paths.get(doc).getFileName().toString());\n\n distanceMap.put(doc, vectorialProduct / normProduct);\n }\n\n //sortare distance map\n distanceMap = distanceMap.entrySet().stream()\n .sorted(Map.Entry.comparingByValue(Collections.reverseOrder()))\n .collect(Collectors.toMap(\n Map.Entry::getKey,\n Map.Entry::getValue,\n (e1, e2) -> e1,\n LinkedHashMap::new));\n\n// System.out.println(\"Cos distance:\");\n// for(Map.Entry entry : distanceMap.entrySet()){\n// System.out.println(entry);\n// }\n\n return distanceMap.keySet();\n }","public void countTerm() throws IOException {\n\n long countBody = reader.getSumDocFreq(\"body\");\n long countTitle = reader.getSumDocFreq(\"title\");\n\n System.out.println(\"Body: \" + countBody);\n System.out.println(\"Title: \" + countTitle);\n System.out.println(\"Total count Terms: \" + (countTitle + countBody));\n\n }","public void computeTermTable(IndexReader reader) throws IOException {\n\t\t//MultiFields.getFields(reader).terms(field)\n\t\tint numDocs = reader.numDocs();\n\t\tfor (int docID =0 ; docID < numDocs; docID++) {\n\t\t\tTerms termVector = reader.getTermVector(docID, FieldName.METHOD_DESC.getName());\n\t\t\tif(termVector == null)\n\t\t\t\tcontinue;\n\t\t\tTermsEnum iterator = termVector.iterator(null);\n\t\t\tBytesRef next = iterator.next();\n\t\t\twhile (next != null) {\n\t\t\t\tint docFreq = reader.docFreq(FieldName.METHOD_DESC.getName(), next);\n\t\t\t\t\n\t\t\t\ttermTable.put(next.utf8ToString(), docFreq);\n\t\t\t\tnext = iterator.next();\n\t\t\t}\n\t\t\t\n\t\t}\n\t\t\n\t\tcomputeStatProperties(reader,termTable);\n\t}","public abstract Object[] getSimilarityFactors();","public static void InvertedDocFrequency() throws FileNotFoundException {\n //int totalDoc = totaldocument;\n int i = 0;\n for(Entry<String, List<Integer>> entry: dictionary.entrySet()) {\n List<Integer> docFrequency = new ArrayList<>();\n //\tList<Double> idfValue = new ArrayList<>();\n docFrequency = entry.getValue(); //again taking the list of word terms from the same dictionary hashmap\n int df = docFrequency.get(totaldocument+1); // it will save the idf of every word term at the 57th index\n double ans = Math.log10(df);\n ans /= totaldocument;\n\n idfFinal.add(i,ans); //updatin\n i++;\n }\n saveidf();\n }","default List<String> interestingConcepts(int topK, UnitLocation located,\n Set<Location> irrelevantSet){\n // collect frequent words outside the blacklist of locations\n final TokenIterator extractor = new TokenIterator(irrelevantSet);\n located.getUnitNode().accept(extractor);\n\n final WordCounter wordCounter = new WordCounter(extractor.getItems());\n\n return wordCounter.mostFrequent(topK);\n }"],"string":"[\n \"public abstract int numberOfTerms();\",\n \"int DF(String term) {\\n for (int i = 0; i < count1; i++) {\\n if (economydocument[i].contains(term)) {\\n df++;\\n }\\n }\\n for (int i = 0; i < count2; i++) {\\n if (educationdocument[i].contains(term)) {\\n df++;\\n }\\n }\\n for (int i = 0; i < count3; i++) {\\n if (sportdocument[i].contains(term)) {\\n df++;\\n }\\n }\\n for (int i = 0; i < count4; i++) {\\n if (culturedocument[i].contains(term)) {\\n df++;\\n }\\n }\\n for (int i = 0; i < count5; i++) {\\n if (accedentdocument[i].contains(term)) {\\n df++;\\n }\\n }\\n for (int i = 0; i < count6; i++) {\\n if (environmntaldocument[i].contains(term)) {\\n df++;\\n }\\n }\\n for (int i = 0; i < count7; i++) {\\n if (foreign_affairdocument[i].contains(term)) {\\n df++;\\n }\\n }\\n for (int i = 0; i < count8; i++) {\\n if (law_justicedocument[i].contains(term)) {\\n df++;\\n }\\n }\\n for (int i = 0; i < count9; i++) {\\n if (agriculture[i].contains(term)) {\\n df++;\\n }\\n }\\n for (int i = 0; i < count10; i++) {\\n if (politicsdocument[i].contains(term)) {\\n df++;\\n }\\n }\\n for (int i = 0; i < count12; i++) {\\n if (science_technologydocument[i].contains(term)) {\\n df++;\\n }\\n }\\n for (int i = 0; i < count13; i++) {\\n if (healthdocument[i].contains(term)) {\\n df++;\\n }\\n }\\n for (int i = 0; i < count14; i++) {\\n if (army[i].contains(term)) {\\n df++;\\n }\\n }\\n return df;\\n }\",\n \"public int getTermIndex() {return termIndex;}\",\n \"private void termQuerySearch(String[] terms) {\\n for (String term : terms) {\\n LinkedList<TermPositions> postingLists = indexMap.get(analyzeTerm(term));\\n if (postingLists != null) {\\n for (TermPositions matches : postingLists) {\\n double score = (double) 1 + Math.log((double) matches.getPositionList().size()) *\\n Math.log((double) N / (double) postingLists.size());\\n resultsCollector.add(new DocCollector(matches.getDocId(), score));\\n }\\n }\\n }\\n }\",\n \"static void returnTfIdfResults() {\\n\\t\\tSet<String> specificWords = findKeywords();\\n\\n\\t\\t// for every phrase\\n\\t\\tfor (String word : specificWords) {\\n\\t\\t\\t// get the total number of documents\\n\\t\\t\\tdouble totalSize = size;\\n\\n\\t\\t\\t// get the collection of documents containing that word\\n\\t\\t\\tCollection<File> containingWordSet = invertedMap.getValues(word);\\n\\n\\t\\t\\t// makes a new one if null (for ease of code)\\n\\t\\t\\tif (containingWordSet == null) {\\n\\t\\t\\t\\tcontainingWordSet = new HashSet<File>();\\n\\t\\t\\t}\\n\\n\\t\\t\\t// the number containing the word\\n\\t\\t\\tdouble numContainingWord = containingWordSet.size();\\n\\n\\t\\t\\t// get the idf (log(total/(1 + |# contain word|)\\n\\t\\t\\t// it is normalize with 1 to prevent division by 0\\n\\t\\t\\tdouble idf = Math.log(totalSize / (1 + numContainingWord));\\n\\n\\t\\t\\t// System.out.println(\\\"------------------\\\");\\n\\t\\t\\t// System.out.println(word + \\\" totalSize \\\" + totalSize);\\n\\t\\t\\t// System.out.println(word + \\\" numContainingWord \\\" +\\n\\t\\t\\t// numContainingWord);\\n\\t\\t\\t// System.out.println(word + \\\" idf \\\" + idf);\\n\\t\\t\\t// System.out.println(\\\"------------------\\\");\\n\\n\\t\\t\\t// set the wordscore to 0\\n\\t\\t\\tdouble wordScore = 0;\\n\\n\\t\\t\\t// for all of the files with the word\\n\\t\\t\\tfor (File file : containingWordSet) {\\n\\t\\t\\t\\tString fileName = file.getName();\\n\\n\\t\\t\\t\\t// get the phrase count for this document\\n\\t\\t\\t\\tInteger phraseCount = phraseCountMap.get(fileName);\\n\\t\\t\\t\\tdouble numPhrases = phraseCount.doubleValue();\\n\\n\\t\\t\\t\\t// get the word frequency map for this page\\n\\t\\t\\t\\tHashMap<String, Integer> docFreqMap = wordFreqMap.get(fileName);\\n\\t\\t\\t\\tInteger freq = docFreqMap.get(word);\\n\\n\\t\\t\\t\\t// otherwise, get the tf\\n\\t\\t\\t\\tdouble tf;\\n\\t\\t\\t\\tif (freq == null) {\\n\\t\\t\\t\\t\\t// if it's not present, it's 0\\n\\t\\t\\t\\t\\ttf = 0;\\n\\t\\t\\t\\t} else {\\n\\t\\t\\t\\t\\t// otherwise, it's the value\\n\\t\\t\\t\\t\\ttf = freq / numPhrases;\\n\\t\\t\\t\\t\\t// System.out.println(tf);\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\t// multiply for this score\\n\\t\\t\\t\\tdouble score = tf * idf;\\n\\n\\t\\t\\t\\t// add it to the page score\\n\\t\\t\\t\\twordScore += score;\\n\\t\\t\\t}\\n\\n\\t\\t\\t// make a node with the sum of tf-idf for all relevant phrases and\\n\\t\\t\\t// add to pq\\n\\t\\t\\tWordNode w = new WordNode(word, wordScore);\\n\\t\\t\\tpq.add(w);\\n\\t\\t}\\n\\t}\",\n \"@Override\\n public int getTermFrequency(String term) {\\n return 0;\\n }\",\n \"private double idf(String term) {\\n return 1 + Math.log(this.numberOfDocuments / (double) termToDocumentsContainingTerm.get(term).size());\\n }\",\n \"void documentFrequncy(Set<String> features,\\n int index,\\n int troush\\n ) {\\n for (String str : features) {\\n switch (index) {\\n case 1:\\n for (int i = 0; i < count1; i++) {\\n if (economydocument[i].contains(str)) {\\n e++;\\n }\\n }\\n if (e > troush) {\\n documntfrequencyeco.put(str, e);\\n }\\n e = 0;\\n break;\\n case 2:\\n for (int i = 0; i < count2; i++) {\\n if (educationdocument[i].contains(str)) {\\n e++;\\n }\\n }\\n if (e > troush) {\\n documntfrequencyedu.put(str, e);\\n }\\n e = 0;\\n break;\\n case 3:\\n for (int i = 0; i < count3; i++) {\\n if (sportdocument[i].contains(str)) {\\n e++;\\n }\\n }\\n if (e > troush) {\\n documntfrequencyspo.put(str, e);\\n }\\n e = 0;\\n break;\\n case 4:\\n for (int i = 0; i < count4; i++) {\\n if (culturedocument[i].contains(str)) {\\n e++;\\n }\\n }\\n if (e > troush) {\\n documntfrequencycul.put(str, e);\\n }\\n e = 0;\\n break;\\n case 5:\\n for (int i = 0; i < count5; i++) {\\n if (accedentdocument[i].contains(str)) {\\n e++;\\n }\\n }\\n if (e > troush) {\\n documntfrequencyaccid.put(str, e);\\n }\\n e = 0;\\n break;\\n case 6:\\n for (int i = 0; i < count6; i++) {\\n if (environmntaldocument[i].contains(str)) {\\n e++;\\n }\\n }\\n if (e > troush) {\\n documntfrequencyenv.put(str, e);\\n }\\n e = 0;\\n break;\\n case 7:\\n for (int i = 0; i < count7; i++) {\\n if (foreign_affairdocument[i].contains(str)) {\\n e++;\\n }\\n }\\n if (e > troush) {\\n documntfrequencydep.put(str, e);\\n }\\n e = 0;\\n break;\\n case 8:\\n for (int i = 0; i < count8; i++) {\\n if (law_justicedocument[i].contains(str)) {\\n e++;\\n }\\n }\\n if (e > troush) {\\n documntfrequencylaw.put(str, e);\\n }\\n e = 0;\\n break;\\n case 9:\\n for (int i = 0; i < count9; i++) {\\n if (agriculture[i].contains(str)) {\\n e++;\\n }\\n }\\n if (e > troush) {\\n documntfrequencyagri.put(str, e);\\n }\\n e = 0;\\n break;\\n case 10:\\n for (int i = 0; i < count10; i++) {\\n if (politicsdocument[i].contains(str)) {\\n e++;\\n }\\n }\\n if (e > troush) {\\n documntfrequencypoltics.put(str, e);\\n }\\n e = 0;\\n break;\\n// case 11:\\n//\\n// for (int i = 0; i < count11; i++) {\\n// if (social_affairsdocument[i].contains(str)) {\\n// e++;\\n// }\\n// }\\n// if (e > troush) {\\n// documntfrequencysocial.put(str, e);\\n// }\\n// e = 0;\\n// break;\\n case 11:\\n for (int i = 0; i < count12; i++) {\\n if (science_technologydocument[i].contains(str)) {\\n e++;\\n }\\n }\\n\\n if (e > troush) {\\n documntfrequencysci.put(str, e);\\n }\\n e = 0;\\n break;\\n case 12:\\n for (int i = 0; i < count13; i++) {\\n if (healthdocument[i].contains(str)) {\\n e++;\\n }\\n }\\n if (e > troush) {\\n documntfrequencyhel.put(str, e);\\n }\\n e = 0;\\n break;\\n case 13:\\n for (int i = 0; i < count14; i++) {\\n if (army[i].contains(str)) {\\n e++;\\n }\\n }\\n\\n if (e > troush) {\\n documntfrequencyarmy.put(str, e);\\n }\\n e = 0;\\n break;\\n default:\\n break;\\n }\\n\\n }\\n }\",\n \"public ComputeTermFrequencies() { super(); }\",\n \"public double numTerms()\\r\\n\\t{\\r\\n\\t\\treturn unionAll.size();\\r\\n\\t}\",\n \"abstract public int docFreq(Term t) throws IOException;\",\n \"@Override\\n public int getIndexByTerm(String term) {\\n return 0;\\n }\",\n \"public static void calcuTFIDF() throws IOException {\\n\\n\\t\\tHashtable<String, Double> idf = new Hashtable<String, Double>();\\n\\t\\tArrayList<String> terms = new ArrayList<String>();\\n\\t\\tdouble fileCount = 0.0;\\n\\t\\tString featurePath = \\\"./corpus/features\\\";\\n\\t\\tString featureWeight = \\\"./corpus/featureWeight\\\";\\n\\t\\tString trainPath = \\\"./corpus/trainData\\\";\\n\\t\\tString testPath = \\\"./corpus/testData\\\";\\n\\t\\tString stopPath = \\\"./corpus/english.stop\\\";\\n\\t\\tString trainOutPath = \\\"./corpus/trainVectors\\\";\\n\\t\\tString testOutPath = \\\"./corpus/testVectors\\\";\\n\\t\\tBufferedReader br = new BufferedReader(new FileReader(featurePath));\\n\\t\\tBufferedWriter featureWriter = new BufferedWriter(new FileWriter(\\n\\t\\t\\t\\tfeatureWeight));\\n\\t\\tBufferedReader trainReader = new BufferedReader(new FileReader(\\n\\t\\t\\t\\ttrainPath));\\n\\t\\tBufferedReader testReader = new BufferedReader(new FileReader(testPath));\\n\\t\\tBufferedReader br2 = new BufferedReader(new FileReader(stopPath));\\n\\t\\tBufferedWriter writer = new BufferedWriter(new FileWriter(trainOutPath));\\n\\t\\tBufferedWriter testWriter = new BufferedWriter(new FileWriter(\\n\\t\\t\\t\\ttestOutPath));\\n\\t\\tString oneline;\\n\\t\\tArrayList<String> as = new ArrayList<String>();\\n\\t\\twhile ((oneline = br2.readLine()) != null) {\\n\\t\\t\\tas.add(oneline);\\n\\t\\t}\\n\\t\\tString[] stopWords = new String[as.size()];\\n\\t\\tas.toArray(stopWords);\\n\\t\\tAnalyzer analyzer = new SnowballAnalyzer(\\\"English\\\", stopWords);\\n\\n\\t\\twhile ((oneline = br.readLine()) != null) {\\n\\t\\t\\tidf.put(oneline, 0.0);\\n\\t\\t\\tterms.add(oneline);\\n\\t\\t}\\n\\n\\t\\twhile ((oneline = trainReader.readLine()) != null) {\\n\\n\\t\\t\\tint pos = oneline.indexOf(\\\"\\\\t\\\");\\n\\t\\t\\tString topic = oneline.substring(0, pos);\\n\\t\\t\\tString content = oneline.substring(pos + 1);\\n\\t\\t\\tfileCount++;\\n\\t\\t\\tHashtable<String, Integer> termList = new Hashtable<String, Integer>();\\n\\t\\t\\tTokenStream stream = analyzer.tokenStream(\\\"\\\", new StringReader(\\n\\t\\t\\t\\t\\tcontent));\\n\\t\\t\\twhile (true) {\\n\\t\\t\\t\\tToken token = stream.next();\\n\\t\\t\\t\\tif (token == null)\\n\\t\\t\\t\\t\\tbreak;\\n\\t\\t\\t\\tString tmp = token.termText();\\n\\t\\t\\t\\tif (!termList.containsKey(tmp))\\n\\t\\t\\t\\t\\ttermList.put(tmp, new Integer(1));\\n\\t\\t\\t}\\n\\t\\t\\tSet<String> keys = termList.keySet();\\n\\t\\t\\tfor (String tmp : keys) {\\n\\t\\t\\t\\tif (idf.containsKey(tmp)) {\\n\\t\\t\\t\\t\\tDouble num = idf.get(tmp);\\n\\t\\t\\t\\t\\tidf.put(tmp, num + 1);\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t}\\n\\n\\t\\tfor (String term : terms) {\\n\\n\\t\\t\\tdouble weightOfTerm = Math.log((double) fileCount / idf.get(term)\\n\\t\\t\\t\\t\\t+ 0.01);\\n\\t\\t\\tfeatureWriter.write(term + \\\" \\\" + weightOfTerm);\\n\\t\\t\\tfeatureWriter.newLine();\\n\\t\\t\\tidf.put(term, weightOfTerm);\\n\\n\\t\\t}\\n\\t\\tfeatureWriter.flush();\\n\\t\\tfeatureWriter.close();\\n\\n\\t\\ttrainReader = new BufferedReader(new FileReader(trainPath));\\n\\t\\twhile ((oneline = trainReader.readLine()) != null) {\\n\\n\\t\\t\\tint pos = oneline.indexOf(\\\"\\\\t\\\");\\n\\t\\t\\tString topic = oneline.substring(0, pos);\\n\\t\\t\\tString content = oneline.substring(pos + 1);\\n\\t\\t\\tHashtable<String, Integer> termFrequent = new Hashtable<String, Integer>();\\n\\t\\t\\tTokenStream stream = analyzer.tokenStream(\\\"\\\", new StringReader(\\n\\t\\t\\t\\t\\tcontent));\\n\\t\\t\\twhile (true) {\\n\\t\\t\\t\\tToken token = stream.next();\\n\\t\\t\\t\\tif (token == null)\\n\\t\\t\\t\\t\\tbreak;\\n\\t\\t\\t\\tString tmp = token.termText();\\n\\t\\t\\t\\tif (!termFrequent.containsKey(tmp))\\n\\t\\t\\t\\t\\ttermFrequent.put(tmp, new Integer(1));\\n\\t\\t\\t\\telse {\\n\\t\\t\\t\\t\\tInteger num = termFrequent.get(tmp);\\n\\t\\t\\t\\t\\ttermFrequent.put(tmp, num + 1);\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t\\tdouble weights[] = new double[terms.size()];\\n\\t\\t\\tdouble denominator = 0.0;\\n\\t\\t\\tint i = 0;\\n\\t\\t\\tfor (String term : terms) {\\n\\t\\t\\t\\tdouble count;\\n\\t\\t\\t\\tif (termFrequent.containsKey(term)) {\\n\\t\\t\\t\\t\\tcount = termFrequent.get(term);\\n\\t\\t\\t\\t} else {\\n\\t\\t\\t\\t\\tcount = 0;\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\tdouble tmp = count * idf.get(term);\\n\\t\\t\\t\\tdenominator += tmp;\\n\\t\\t\\t\\tweights[i++] = tmp;\\n\\t\\t\\t}\\n\\t\\t\\tdenominator = Math.sqrt(denominator);\\n\\t\\t\\twriter.write(topic);\\n\\t\\t\\tfor (int j = 1; j <= weights.length; j++) {\\n\\t\\t\\t\\tdouble tmp = weights[j - 1];\\n\\t\\t\\t\\tif (tmp > 0.0) {\\n\\t\\t\\t\\t\\ttmp = Math.sqrt(tmp) / denominator;\\n\\t\\t\\t\\t\\twriter.write(\\\" \\\" + j + \\\":\\\" + tmp);\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t\\twriter.newLine();\\n\\t\\t}\\n\\n\\t\\twhile ((oneline = testReader.readLine()) != null) {\\n\\n\\t\\t\\tint pos = oneline.indexOf(\\\"\\\\t\\\");\\n\\t\\t\\tString topic = oneline.substring(0, pos);\\n\\t\\t\\tString content = oneline.substring(pos + 1);\\n\\t\\t\\tHashtable<String, Integer> termFrequent = new Hashtable<String, Integer>();\\n\\t\\t\\tTokenStream stream = analyzer.tokenStream(\\\"\\\", new StringReader(\\n\\t\\t\\t\\t\\tcontent));\\n\\t\\t\\twhile (true) {\\n\\t\\t\\t\\tToken token = stream.next();\\n\\t\\t\\t\\tif (token == null)\\n\\t\\t\\t\\t\\tbreak;\\n\\t\\t\\t\\tString tmp = token.termText();\\n\\t\\t\\t\\tif (!termFrequent.containsKey(tmp))\\n\\t\\t\\t\\t\\ttermFrequent.put(tmp, new Integer(1));\\n\\t\\t\\t\\telse {\\n\\t\\t\\t\\t\\tInteger num = termFrequent.get(tmp);\\n\\t\\t\\t\\t\\ttermFrequent.put(tmp, num + 1);\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t\\tdouble weights[] = new double[terms.size()];\\n\\t\\t\\tdouble denominator = 0.0;\\n\\t\\t\\tint i = 0;\\n\\t\\t\\tfor (String term : terms) {\\n\\t\\t\\t\\tdouble count;\\n\\t\\t\\t\\tif (termFrequent.containsKey(term)) {\\n\\t\\t\\t\\t\\tcount = termFrequent.get(term);\\n\\t\\t\\t\\t} else {\\n\\t\\t\\t\\t\\tcount = 0;\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\tdouble tmp = count * idf.get(term);\\n\\t\\t\\t\\tdenominator += tmp;\\n\\t\\t\\t\\tweights[i++] = tmp;\\n\\t\\t\\t}\\n\\t\\t\\tdenominator = Math.sqrt(denominator);\\n\\t\\t\\ttestWriter.write(topic);\\n\\t\\t\\tfor (int j = 1; j <= weights.length; j++) {\\n\\t\\t\\t\\tdouble tmp = weights[j - 1];\\n\\t\\t\\t\\tif (tmp > 0.0) {\\n\\t\\t\\t\\t\\ttmp = Math.sqrt(tmp) / denominator;\\n\\t\\t\\t\\t\\ttestWriter.write(\\\" \\\" + j + \\\":\\\" + tmp);\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t\\ttestWriter.newLine();\\n\\t\\t}\\n\\t\\twriter.close();\\n\\t\\ttestWriter.close();\\n\\t}\",\n \"private void calculateIdf(){\\r\\n\\t\\tIdf = new HashMap<>();\\r\\n\\t\\tOcc = new HashMap<>();\\r\\n\\t\\t\\r\\n\\t\\tfor (Entry<String, Document> doc : Docs.entrySet()){\\r\\n\\t\\t\\tdoc.getValue().wordSet.forEach(word -> {\\r\\n\\t\\t\\t\\tdouble count = Idf.containsKey(word) ? Idf.get(word) : 0;\\r\\n \\tIdf.put(word, count+1);\\r\\n\\t\\t\\t});\\r\\n\\t\\t\\t\\r\\n\\t\\t\\tdoc.getValue().words.forEach((w, o) -> words.add(w));\\r\\n\\t\\t\\t\\r\\n\\t\\t}\\r\\n\\t\\t\\r\\n\\t\\tfor (Entry<String, Double> e : new HashMap<>(Idf).entrySet()){\\r\\n\\t\\t\\tIdf.put(e.getKey(),\\r\\n\\t\\t\\t\\t\\tMath.log(Idf.keySet().size() / e.getValue()));\\r\\n\\t\\t}\\r\\n\\t}\",\n \"public List<OWLObject> search(OWLObject queryObj) {\\n\\t\\tList<OWLObject> hits = new ArrayList<OWLObject>(maxHits);\\n\\t\\tSystem.out.println(\\\"gettings atts for \\\"+queryObj+\\\" -- \\\"+simEngine.comparisonProperty);\\n\\t\\tSet<OWLObject> atts = simEngine.getAttributeClosureFor(queryObj);\\n\\t\\tSystem.out.println(\\\"all atts: \\\"+atts.size());\\n\\t\\tif (atts.size() == 0)\\n\\t\\t\\treturn hits;\\n\\t\\t\\n\\t\\t// only compare using significant atts;\\n\\t\\t// we don't do the same test on candidates as these will be removed by the\\n\\t\\t// intersection operation. they will have a small effect on the score, as\\n\\t\\t// we don't divide by the union, but instead the sum of sizes\\n\\t\\tatts = filterNonSignificantAttributes(atts);\\n\\t\\tSystem.out.println(\\\"filtered atts: \\\"+atts.size());\\n\\n\\t\\t//bloomFilter = new BloomFilter<OWLObject>(0.05, atts.size());\\n\\t\\t//bloomFilter.addAll(atts);\\n\\t\\t\\t\\t\\n\\t\\tSortedMap<Integer,Set<OWLObject>> scoreCandidateMap = new TreeMap<Integer,Set<OWLObject>>();\\n\\t\\t\\n\\t\\tfor (OWLObject candidate : getCandidates()) {\\n\\t\\t\\tif (candidate.equals(queryObj))\\n\\t\\t\\t\\tcontinue;\\n\\t\\t\\tSet<OWLObject> iAtts = simEngine.getAttributeClosureFor(candidate);\\n\\t\\t\\t//Set<OWLObject> iAtts = simEngine.getGraph().getAncestors(candidate);\\n\\n\\t\\t\\tif (iAtts.size() == 0)\\n\\t\\t\\t\\tcontinue;\\n\\t\\t\\tint cAttsSize = iAtts.size();\\n\\t\\n\\t\\t\\tiAtts.retainAll(atts);\\n\\t\\t\\t//Collection<OWLObject> iAtts = bloomFilter.intersection(cAtts);\\n\\t\\t\\t\\n\\t\\t\\t// simJ, one-sided, scaled by 1000\\n\\t\\t\\t// negate to ensure largest first\\n\\t\\t\\t//Integer score = - (iAtts.size() * 1000 / cAttsSize);\\n\\t\\t\\t\\n\\t\\t\\t// this biases us towards genes with large numbers of annotations,\\n\\t\\t\\t// but it is better at finding the models that share all features\\n\\t\\t\\tInteger score = - iAtts.size();\\n\\t\\t\\tif (!scoreCandidateMap.containsKey(score)) \\n\\t\\t\\t\\tscoreCandidateMap.put(score, new HashSet<OWLObject>());\\n\\t\\t\\tscoreCandidateMap.get(score).add(candidate);\\n\\t\\t\\treporter.report(this,\\\"query_candidate_overlap_total\\\",queryObj,candidate,iAtts.size(),cAttsSize);\\n\\t\\t}\\n\\t\\t\\n\\t\\tint n = 0;\\n\\t\\tfor (Set<OWLObject> cs : scoreCandidateMap.values()) {\\n\\t\\t\\tn += cs.size();\\n\\t\\t\\thits.addAll(cs);\\n\\t\\t}\\n\\t\\t\\n\\t\\tn = 0;\\n\\t\\tfor (OWLObject hit : hits) {\\n\\t\\t\\tn++;\\n\\t\\t\\treporter.report(this,\\\"query_hit_rank_threshold\\\",queryObj,hit,n,maxHits);\\n\\t\\t}\\n\\t\\tif (hits.size() > maxHits)\\n\\t\\t\\thits = hits.subList(0, maxHits);\\n\\t\\t\\n\\n\\n\\t\\treturn hits;\\n\\t}\",\n \"public void calculateTermWeights() {\\n\\t\\tfor (String termString : terms.keySet()) {\\n\\t\\t\\tTerm t = terms.get(termString);\\n\\t\\t\\tMap<Integer, TermDoc> posting = t.getPostings();\\n\\n\\t\\t\\t// Iterate through the docs in which the selected term is found.\\n\\t\\t\\tfor (Integer docId : posting.keySet()) {\\n\\n\\t\\t\\t\\tTermDoc td = posting.get(docId);\\n\\t\\t\\t\\tDocument doc = this.getDocument(docId);\\n\\n\\t\\t\\t\\tfinal double a = 0.4;\\n\\t\\t\\t\\tdouble ntf = a + (1 - a) * (double) td.getFreq() / (double) doc.getMaxTermFreq();\\n\\t\\t\\t\\tdouble idf = Math.log((double) documents.size() / (1 + (double) t.getDocFreq()));\\n\\t\\t\\t\\tdoc.addWeight(termString, ntf * idf);\\n\\t\\t\\t}\\n\\t\\t}\\n\\n\\t\\tfor (Document doc : documents.values())\\n\\t\\t\\tdoc.setEuclideanDistance();\\n\\t}\",\n \"@Override\\n public double score(Document document) {\\n Set<String> allDocTerms = documentsTerms.termsExtractedFromDocument(document).allTerms();\\n\\n //keeping only the query terms that are in the document\\n Collection<String> relevantTerms = new LinkedHashSet<>(query);\\n relevantTerms.retainAll(allDocTerms);\\n\\n //compute score using a sum formula on each query term\\n int docLength = termsOccurences.get(document).totalNumberOfOccurences();\\n double score = 0.0;\\n for (String term : relevantTerms) {\\n double termIDF = idf.weight(term);\\n double termTF = tf.weight(term, document);\\n\\n score += termIDF * (termTF * (k1 + 1)) / (termTF + k1 * (1 - b + b * (docLength / averageDocLength)));\\n }\\n\\n return score;\\n }\",\n \"SwiftScoredSet getTfIdf(String text,ASTNode n,boolean kgram)\\n{\\n Map<String,Integer> words = null;\\n Map<String,Integer> totals = null;\\n double tot = 0;\\n if (kgram){\\n words = buildKgramCounts(text,n);\\n totals = kgram_counts;\\n tot = total_kdocuments;\\n } \\n else {\\n words = handleDocumentText(text);\\n totals = document_counts;\\n tot = total_documents;\\n }\\n double termtot = 1;\\n \\n for (Integer iv : words.values()) {\\n termtot += iv;\\n }\\n \\n SwiftScoredSet rslt = new SwiftScoredSet();\\n for (Map.Entry<String,Integer> ent : words.entrySet()) {\\n String wd = ent.getKey();\\n double ct = ent.getValue();\\n Integer docs = totals.get(wd);\\n double docct = 0;\\n if (docs != null) docct = docs;\\n double idf = Math.log(tot/(1+docct));\\n double tf = ct/termtot;\\n double tfidf = tf*idf;\\n rslt.add(wd,tfidf);\\n }\\n rslt.normalize();\\n \\n return rslt;\\n}\",\n \"private void doBayesianClassification() {\\n\\t\\tList<MutualInformation> mutualInformationList = new ArrayList<MutualInformation>();\\r\\n\\t\\tint k = 5;\\r\\n\\t\\tSystem.out.println(\\\"k = \\\" + k);\\r\\n\\t\\tdouble N = fileNames.size();\\r\\n\\t\\t\\r\\n\\t\\tList<Set<String>> classifiedDocsList = new ArrayList<Set<String>>();\\r\\n\\t\\tclassifiedDocsList.add(setOfHamiltonDocs);\\r\\n\\t\\tclassifiedDocsList.add(setOfMadisonDocs);\\r\\n\\t\\tclassifiedDocsList.add(setOfJayDocs);\\r\\n\\t\\t\\r\\n\\t\\tfor (String term : corpusVocab) {\\r\\n\\r\\n\\t\\t\\t// All docs containing this term\\r\\n\\t\\t\\tSet<String> matchingDocs = new HashSet<String>();\\r\\n\\t\\t\\t\\r\\n\\t\\t\\tfor (PositionalPosting posting : pInvertedIndex.getPostings(term)) {\\r\\n\\t\\t\\t\\tmatchingDocs.add(fileNames.get(posting.getDocumentId()));\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\t\\r\\n\\t\\t\\t// iterate through all classes (Hamilton, Madison, Jay)\\r\\n\\t\\t\\tfor (int i = 0; i < classifiedDocsList.size(); i++) {\\r\\n\\t\\t\\t\\t\\r\\n\\t\\t\\t\\tSet<String> classifiedDocs = classifiedDocsList.get(i);\\r\\n\\t\\t\\t\\t\\r\\n\\t\\t\\t\\tSet<String> intersection = new HashSet<String>(matchingDocs);\\r\\n\\t\\t\\t\\tintersection.retainAll(classifiedDocs);\\r\\n\\t\\t\\t\\tdouble N11 = intersection.size();\\r\\n\\t\\t\\t\\t\\r\\n\\t\\t\\t\\tSet<String> difference = new HashSet<String>(matchingDocs);\\r\\n\\t\\t\\t\\tdifference.removeAll(classifiedDocs);\\r\\n\\t\\t\\t\\tdouble N10 = difference.size();\\r\\n\\t\\t\\t\\t\\r\\n\\t\\t\\t\\tdouble N01 = classifiedDocs.size() - N11;\\r\\n\\t\\t\\t\\tdouble N00 = fileNames.size() - classifiedDocs.size() - N10;\\r\\n\\r\\n\\t\\t\\t\\t// Calculate I(t,c)\\r\\n\\t\\t\\t\\tdouble Itc = (N11 / N) * log2((N * N11) / ((N11 + N10) * (N11 + N01)))\\r\\n\\t\\t\\t\\t\\t\\t+ (N01 / N) * log2((N * N01) / ((N01 + N00) * (N11 + N01)))\\r\\n\\t\\t\\t\\t\\t\\t+ (N10 / N) * log2((N * N10) / ((N11 + N10) * (N10 + N00)))\\r\\n\\t\\t\\t\\t\\t\\t+ (N00 / N) * log2((N * N00) / ((N01 + N00) * (N10 + N00)));\\r\\n\\t\\t\\t\\tif (!Double.isNaN(Itc)) {\\r\\n\\t\\t\\t\\t\\tmutualInformationList.add(new MutualInformation(term, Itc));\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t}\\r\\n\\t\\t}\\r\\n\\t\\t\\r\\n\\t\\t// Build Discriminating Set of vocab terms by sorting mutual information\\r\\n\\t\\t// list and keep the first k values\\r\\n\\t\\tSet<String> terms = new HashSet<String>();\\r\\n\\t\\tCollections.sort(mutualInformationList, Collections.reverseOrder());\\r\\n\\t\\tfor (int i = 0; i < k; i++) {\\r\\n\\t\\t\\tterms.add(mutualInformationList.get(i).getTerm());\\r\\n\\t\\t}\\r\\n\\t\\t\\r\\n\\t\\t// get term counts in classified (trainer) docs\\t\\t\\r\\n\\t\\tint[] classifiedDocsTermFreq = new int[classifiedDocsList.size()];\\r\\n\\t\\t\\r\\n\\t\\tclassifiedDocsTermFreq[0] = getTermFreq(hamiltonDocs, terms);\\r\\n\\t\\tclassifiedDocsTermFreq[1] = getTermFreq(madisonDocs, terms);\\r\\n\\t\\tclassifiedDocsTermFreq[2] = getTermFreq(jayDocs, terms);\\r\\n\\t\\t\\r\\n\\t\\t// Calculate p(t|c)\\r\\n\\t\\t// maps term to list of p(t|c) for each class\\r\\n\\t\\tMap<String, List<Double>> ptc = new HashMap<String, List<Double>>();\\r\\n\\t\\t\\r\\n\\t\\tfor (String term : terms) {\\r\\n\\t\\t\\tptc.put(term, new ArrayList<Double>());\\r\\n\\t\\t\\tfor (int i = 0; i < classifiedDocsList.size(); i++) {\\r\\n\\t\\t\\t\\t\\r\\n\\t\\t\\t\\tint ftc = 0;\\r\\n\\t\\t\\t\\tfor (PositionalPosting posting : pInvertedIndex.getPostings(term)) {\\r\\n\\t\\t\\t\\t\\tif (classifiedDocsList.get(i).contains(fileNames.get(posting.getDocumentId()))) {\\r\\n\\t\\t\\t\\t\\t\\tftc += posting.getPositions().size();\\r\\n\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\tptc.get(term).add((double) (ftc + 1) / (double) (classifiedDocsTermFreq[i] + terms.size()));\\r\\n\\t\\t\\t}\\r\\n\\t\\t}\\r\\n\\t\\t\\r\\n\\t\\t// visit each unclassified document\\r\\n\\t\\ttry {\\r\\n\\t\\t\\tPath currentWorkingPath = Paths.get(toBeClassified).toAbsolutePath();\\r\\n\\t\\t\\t// This is our standard \\\"walk through all .txt files\\\" code.\\r\\n\\t\\t\\tFiles.walkFileTree(currentWorkingPath, new SimpleFileVisitor<Path>() {\\r\\n\\r\\n\\t\\t\\t\\tpublic FileVisitResult preVisitDirectory(Path dir, BasicFileAttributes attrs) {\\r\\n\\t\\t\\t\\t\\t// make sure we only process the current working directory\\r\\n\\t\\t\\t\\t\\tif (currentWorkingPath.equals(dir)) {\\r\\n\\t\\t\\t\\t\\t\\treturn FileVisitResult.CONTINUE;\\r\\n\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\treturn FileVisitResult.SKIP_SUBTREE;\\r\\n\\t\\t\\t\\t}\\r\\n\\r\\n\\t\\t\\t\\tpublic FileVisitResult visitFile(Path file, BasicFileAttributes attrs) {\\r\\n\\r\\n\\t\\t\\t\\t\\tif (file.toString().endsWith(\\\".txt\\\")) {\\r\\n\\r\\n\\t\\t\\t\\t\\t\\tTokenStream tokenStream = null;\\r\\n\\t\\t\\t\\t\\t\\t// terms in this document\\r\\n\\t\\t\\t\\t\\t\\tSet<String> docTerms = new HashSet<String>();\\r\\n\\t\\t\\t\\t\\t\\ttry {\\r\\n\\t\\t\\t\\t\\t\\t\\ttokenStream = Utils.getTokenStreams(file.toFile());\\r\\n\\t\\t\\t\\t\\t\\t} catch (FileNotFoundException e) {\\r\\n\\t\\t\\t\\t\\t\\t\\te.printStackTrace();\\r\\n\\t\\t\\t\\t\\t\\t}\\r\\n\\r\\n\\t\\t\\t\\t\\t\\twhile (tokenStream.hasNextToken()) {\\r\\n\\t\\t\\t\\t\\t\\t\\tString token = Utils.processWord(tokenStream.nextToken().trim(), false);\\r\\n\\t\\t\\t\\t\\t\\t\\tdocTerms.add(token);\\r\\n\\t\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\t\\t// only keep terms in discriminating set\\r\\n\\t\\t\\t\\t\\t\\tdocTerms.retainAll(terms);\\r\\n\\t\\t\\t\\t\\t\\t\\r\\n\\t\\t\\t\\t\\t\\t// calculate log(p(c) + sum(log(p(ti|c))) for each class\\r\\n\\t\\t\\t\\t\\t\\tdouble[] pce = new double[classifiedDocsList.size()];\\r\\n\\t\\t\\t\\t\\t\\tfor (int i = 0; i < classifiedDocsList.size(); i++) {\\r\\n\\t\\t\\t\\t\\t\\t\\tdouble sum = 0;\\r\\n\\t\\t\\t\\t\\t\\t\\tfor (String term : docTerms) {\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tsum += Math.log(ptc.get(term).get(i));\\r\\n\\t\\t\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\t\\t\\t\\r\\n\\t\\t\\t\\t\\t\\t\\tpce[i] = Math.log(classifiedDocsTermFreq[i] / terms.size()) + sum;\\r\\n\\t\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\t\\t\\r\\n\\t\\t\\t\\t\\t\\tif (pce[0] > pce[1] && pce[0] > pce[2]) {\\r\\n\\t\\t\\t\\t\\t\\t\\tSystem.out.println(\\\"Document : \\\" + file.getFileName().toString() + \\\" : belongs to Hamilton\\\");\\r\\n\\t\\t\\t\\t\\t\\t} else if (pce[1] > pce[0] && pce[1] > pce[2]) {\\r\\n\\t\\t\\t\\t\\t\\t\\tSystem.out.println(\\\"Document : \\\" + file.getFileName().toString() + \\\" : belongs to Madison\\\");\\r\\n\\t\\t\\t\\t\\t\\t} else if (pce[2] > pce[0] && pce[2] > pce[1]) {\\r\\n\\t\\t\\t\\t\\t\\t\\tSystem.out.println(\\\"Document : \\\" + file.getFileName().toString() + \\\" : belongs to Jay\\\");\\r\\n\\t\\t\\t\\t\\t\\t} else {\\r\\n\\t\\t\\t\\t\\t\\t\\tSystem.out.println(\\\"I don't know whom document : \\\" + file.getFileName().toString() + \\\" : belongs to.\\\");\\r\\n\\t\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\treturn FileVisitResult.CONTINUE;\\r\\n\\t\\t\\t\\t}\\r\\n\\r\\n\\t\\t\\t\\t// don't throw exceptions if files are locked/other errors occur\\r\\n\\t\\t\\t\\tpublic FileVisitResult visitFileFailed(Path file, IOException e) {\\r\\n\\t\\t\\t\\t\\treturn FileVisitResult.CONTINUE;\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t});\\r\\n\\t\\t} catch (IOException e) {\\r\\n\\t\\t\\te.printStackTrace();\\r\\n\\t\\t}\\r\\n\\t}\",\n \"public static String tfidf(String str) throws Exception{\\n\\t\\tIndexReader r = IndexReader.open(FSDirectory.open(new File(\\\"index\\\")));\\r\\n\\r\\n\\t\\t// this code takes care of calculating idf for each term\\r\\n\\r\\n\\t\\tHashMap<String, Double> idf_map = new HashMap<String, Double>();\\r\\n\\t\\tTermEnum t = r.terms();\\r\\n\\t\\tdouble docs_count = r.maxDoc();\\r\\n\\t\\twhile (t.next()) {\\r\\n\\t\\t\\tTerm te = new Term(\\\"contents\\\", t.term().text());\\r\\n\\t\\t\\tdouble idf = Math.log(docs_count / r.docFreq(te));\\r\\n\\t\\t\\tidf_map.put(t.term().text(), idf);\\r\\n\\t\\t}\\r\\n\\r\\n\\t\\t// This code is a test stub to get the term with lowest IDF value\\r\\n\\r\\n\\t\\t/*\\r\\n\\t\\t * double minVal = Collections.min(idf_map.values()); for(Entry<String,\\r\\n\\t\\t * Double> entry:idf_map.entrySet()){ if(entry.getValue() == minVal){\\r\\n\\t\\t * System.out.println(\\\"Term with lowest idf is: \\\"+entry.getKey()); } }\\r\\n\\t\\t */\\r\\n\\r\\n\\t\\tlong t1, t2;\\r\\n\\t\\tlong start = System.currentTimeMillis();\\r\\n\\r\\n\\t\\t// code to get |d| for every document\\r\\n\\r\\n\\t\\tHashMap<Integer, HashMap<String, Integer>> hmap = new HashMap<Integer, HashMap<String, Integer>>();\\r\\n\\t\\tTermEnum trm = r.terms();\\r\\n\\t\\twhile (trm.next()) {\\r\\n\\t\\t\\tTerm te1 = new Term(\\\"contents\\\", trm.term().text());\\r\\n\\t\\t\\tTermDocs td1 = r.termDocs(te1);\\r\\n\\r\\n\\t\\t\\twhile (td1.next()) {\\r\\n\\t\\t\\t\\tHashMap<String, Integer> a1 = hmap.get(td1.doc());\\r\\n\\t\\t\\t\\tif (a1 == null) {\\r\\n\\t\\t\\t\\t\\ta1 = new HashMap<String, Integer>();\\r\\n\\t\\t\\t\\t\\ta1.put(trm.term().text(), td1.freq());\\r\\n\\t\\t\\t\\t\\thmap.put(td1.doc(), a1);\\r\\n\\t\\t\\t\\t} else {\\r\\n\\t\\t\\t\\t\\ta1.put(trm.term().text(), td1.freq());\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t}\\r\\n\\t\\t}\\r\\n\\r\\n\\t\\t// compute magnitude of each document vector and store it in array\\r\\n\\r\\n\\t\\tArrayList<Double> doc_magnitude = new ArrayList<Double>();\\r\\n\\t\\tHashMap<String, Integer> val = new HashMap<String, Integer>();\\r\\n\\t\\tSet<Entry<Integer, HashMap<String, Integer>>> entrySet = hmap.entrySet();\\r\\n\\r\\n\\t\\tjava.util.Iterator<Entry<Integer, HashMap<String, Integer>>> it = entrySet.iterator();\\r\\n\\t\\twhile (it.hasNext()) { // foreach document id\\r\\n\\t\\t\\tdouble square_sum = 0.0;\\r\\n\\t\\t\\tMap.Entry<Integer, HashMap<String, Integer>> me = (Entry<Integer, HashMap<String, Integer>>) it.next();\\r\\n\\t\\t\\tval = me.getValue();\\r\\n\\t\\t\\tSet<Map.Entry<String, Integer>> entry = val.entrySet();\\r\\n\\t\\t\\tjava.util.Iterator<Map.Entry<String, Integer>> iterator = entry.iterator();\\r\\n\\t\\t\\twhile (iterator.hasNext()) { // foreach term\\r\\n\\t\\t\\t\\tMap.Entry<String, Integer> mp = iterator.next();\\r\\n\\t\\t\\t\\tsquare_sum += mp.getValue() * mp.getValue();\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\tdouble root = Math.sqrt(square_sum);\\r\\n\\t\\t\\tdoc_magnitude.add(me.getKey(), root);\\r\\n\\t\\t}\\r\\n\\r\\n\\t\\t// long end = System.currentTimeMillis();\\r\\n\\t\\t// double diff = end - start;\\r\\n\\t\\t// System.out.println(\\\"Time taken to compute norms(in seconds): \\\" + diff\\r\\n\\t\\t// / 1000 + \\\"\\\\n\\\");\\r\\n\\r\\n\\t\\t// get the query and find similarity with the documents\\r\\n\\t\\tHashMap<Integer, Double> similarity_map = new HashMap<Integer, Double>();\\r\\n\\t\\tSet<Entry<Integer, HashMap<String, Integer>>> entrySet1 = hmap.entrySet();\\r\\n\\t\\tjava.util.Iterator<Entry<Integer, HashMap<String, Integer>>> it1 = entrySet1.iterator();\\r\\n\\t\\t\\r\\n\\t\\t\\r\\n\\t\\t\\r\\n\\t\\tHashMap<Integer, Double> dot_product_map = new HashMap<Integer, Double>();\\r\\n\\r\\n\\t\\t\\r\\n\\t\\t\\tdot_product_map.clear();\\r\\n\\t\\t\\tsimilarity_map.clear();\\r\\n\\r\\n\\t\\t\\tString[] terms = str.split(\\\"\\\\\\\\s+\\\");\\r\\n\\t\\t\\tint cnt = 0;\\r\\n\\r\\n\\t\\t\\tlong result_st = System.currentTimeMillis();\\r\\n\\t\\t\\tt1 = System.nanoTime();\\r\\n\\r\\n\\t\\t\\t// for each term get the documents containing the corresponding term\\r\\n\\t\\t\\tfor (String word : terms) // foreach term in query\\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\tTerm te = new Term(\\\"contents\\\", word);\\r\\n\\t\\t\\t\\tTermDocs tdocs = r.termDocs(te);\\r\\n\\t\\t\\t\\twhile (tdocs.next() /* && tdocs.doc() < number */) {\\r\\n\\t\\t\\t\\t\\t// Map.Entry<Integer, HashMap<String, Integer>> me =\\r\\n\\t\\t\\t\\t\\t// (Entry<Integer, HashMap<String, Integer>>) it1.next();\\r\\n\\t\\t\\t\\t\\tdouble freq = hmap.get(tdocs.doc()).get(word);\\r\\n\\t\\t\\t\\t\\tDouble temp = dot_product_map.get(tdocs.doc());\\r\\n\\t\\t\\t\\t\\tif (temp == null) {\\r\\n\\t\\t\\t\\t\\t\\tdot_product_map.put(tdocs.doc(), freq * idf_map.get(word));\\r\\n\\t\\t\\t\\t\\t} else {\\r\\n\\t\\t\\t\\t\\t\\tdot_product_map.put(tdocs.doc(), dot_product_map.get(tdocs.doc()) + freq * idf_map.get(word));\\r\\n\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\tcnt++;\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\tSet<Entry<Integer, Double>> se = dot_product_map.entrySet();\\r\\n\\t\\t\\tjava.util.Iterator<Entry<Integer, Double>> iter = se.iterator();\\r\\n\\t\\t\\twhile (iter.hasNext()) {\\r\\n\\t\\t\\t\\tMap.Entry<Integer, Double> me = (Entry<Integer, Double>) iter.next();\\r\\n\\t\\t\\t\\tsimilarity_map.put(me.getKey(), me.getValue() / (Math.sqrt(cnt) * doc_magnitude.get(me.getKey())));\\r\\n\\t\\t\\t}\\r\\n\\r\\n\\t\\t\\t// Normalize the map\\r\\n\\t\\t\\tdouble sum = 0;\\r\\n\\t\\t\\tfor (int i : similarity_map.keySet()) {\\r\\n\\t\\t\\t\\tsum += similarity_map.get(i);\\r\\n\\t\\t\\t}\\r\\n\\r\\n\\t\\t\\tfor (int i : similarity_map.keySet()) {\\r\\n\\t\\t\\t\\tdouble temp = similarity_map.get(i) / sum;\\r\\n\\t\\t\\t\\tsimilarity_map.put(i, temp);\\r\\n\\t\\t\\t}\\r\\n\\r\\n\\t\\t\\tString result=\\\"\\\";\\r\\n\\r\\n\\t\\t\\tList<Integer> l1 = new ArrayList<Integer>();\\r\\n\\t\\t\\tHashMap<Integer, Double> sim_map = sortMap(similarity_map, r);\\r\\n\\t\\t\\tfor(Integer i:sim_map.keySet()){\\r\\n\\t\\t\\t\\tl1.add(i);\\r\\n\\t\\t\\t\\tDocument d1 = r.document(i);\\r\\n\\t\\t\\t\\tString url = d1.getFieldable(\\\"path\\\").stringValue();\\r\\n\\t\\t\\t\\t//String snippet = getSnippet(hmap.get(i));\\r\\n\\t\\t\\t\\turl = url.replace(\\\"%%\\\", \\\"/\\\");\\r\\n\\t\\t\\t\\tString snippet = Snippet.getContent(url,terms[0]); //read the content of url\\r\\n\\t\\t\\t\\tresult +=/*i+\\\" \\\"+*/url+\\\"\\\\n\\\";\\r\\n\\t\\t\\t\\tresult +=snippet+\\\"\\\\n\\\\n\\\\n\\\";\\r\\n\\t\\t\\t\\t//result += snippet+\\\"\\\\n\\\\n\\\";\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\treturn result;\\r\\n\\t\\t\\t\\r\\n}\",\n \"boolean hasFreq();\",\n \"private static String handleNonPhraseToken(String stringPart) {\\r\\n // Set of final terms to be used (no empty elements, right syntax of index fields)\\r\\n ArrayList <String> terms = new ArrayList <String> ();\\r\\n \\r\\n /** Case Index field **/\\r\\n if(stringPart.contains(\\\"[\\\") | stringPart.contains(\\\"[\\\")){ // at least an Index field contained here\\r\\n //separate brackets for term with one space (extra spaces dont matter, trim() is used later)\\r\\n stringPart = stringPart.replace(\\\"[\\\", \\\" [\\\");\\r\\n stringPart = stringPart.replace(\\\"]\\\", \\\"] \\\");\\r\\n }\\r\\n\\r\\n /** Case Bag of terms **/\\r\\n //replace space with AND (change default operator to match pubMed's)\\r\\n // No need for this if setDefaultOperator(QueryParser.Operator.AND) is used\\r\\n \\r\\n String[] tokens = stringPart.split(\\\"\\\\\\\\s\\\");\\r\\n if(tokens.length > 0){ \\r\\n for(int i = 1 ; i < tokens.length ; i++){\\r\\n tokens[i] = tokens[i].trim();\\r\\n /* Case index field [fieldName] */\\r\\n if(tokens[i].startsWith(\\\"[\\\") & tokens[i].endsWith(\\\"]\\\")){\\r\\n tokens[i] = tokens[i].replace(\\\"[\\\",\\\"\\\");// clean field name from brackets\\r\\n tokens[i] = tokens[i].replace(\\\"]\\\",\\\"\\\");// clean field name from brackets\\r\\n //Add index field as prefix to previus (not empty) term (as opening index fields handled separately, this index field should not be the first term of string part)\\r\\n int tmp = i-1;\\r\\n boolean perviusTermFound = false;\\r\\n while(!perviusTermFound & tmp >= 0){\\r\\n if(!tokens[tmp].equals(\\\"\\\")){\\r\\n perviusTermFound = true;\\r\\n //TO DO : handle wrong syntax (e.g. ... AND [ArticleTitle])\\r\\n String luceneField = supportedIndexFields.get(tokens[i]);\\r\\n if(luceneField != null){\\r\\n tokens[tmp] = luceneField + \\\":\\\" + tokens[tmp];\\r\\n } // else : Lucene counterpart not found, unsupported field - do nothing\\r\\n } else {\\r\\n tmp--;\\r\\n }\\r\\n }\\r\\n //Empty field to not be added as a search term in query\\r\\n tokens[i] = \\\"\\\";\\r\\n } \\r\\n \\r\\n /*\\r\\n \\r\\n else if(!tokens[i].equals(\\\"AND\\\") & !tokens[i].equals(\\\"\\\")) {\\r\\n terms.add(tokens[i]);\\r\\n }\\r\\n */\\r\\n }\\r\\n }\\r\\n \\r\\n String luceneQueryPart = \\\"\\\";\\r\\n boolean notWaiting = false;\\r\\n boolean orWaiting = false;\\r\\n for(int i = 0 ; i < tokens.length ; i++){\\r\\n\\r\\n if(!tokens[i].equals(\\\"AND\\\") & !tokens[i].equals(\\\"\\\")){\\r\\n //in case of AND nothing should happen, it is the default operator\\r\\n //empty elements are also ignored as useless\\r\\n \\r\\n if(!tokens[i].equals(\\\"NOT\\\") & !tokens[i].equals(\\\"OR\\\") ){ // it's not an operator, it's a term\\r\\n \\r\\n if(!luceneQueryPart.endsWith(\\\" OR \\\") & !luceneQueryPart.endsWith(\\\" -\\\") ) { \\r\\n luceneQueryPart += \\\" +\\\"; \\r\\n } \\r\\n luceneQueryPart += tokens[i];\\r\\n } else {\\r\\n if(tokens[i].equals(\\\"NOT\\\")) {\\r\\n luceneQueryPart += \\\" -\\\";\\r\\n }\\r\\n if(tokens[i].equals(\\\"OR\\\")){\\r\\n luceneQueryPart += \\\" OR \\\";\\r\\n }\\r\\n \\r\\n } \\r\\n } \\r\\n }\\r\\n \\r\\n return luceneQueryPart;\\r\\n }\",\n \"public abstract void addFeatures(Collection<Double> indices,Predicate pred, Word arg,boolean allWords);\",\n \"public void setTerms(Term[] terms) { this.terms = terms; }\",\n \"public float computeTermScore(int term, int dl, int tf, GlobalStats stats);\",\n \"public double getTfIdf(){ return tf_idf; }\",\n \"private Float weightTermUniqeness(String term) throws IOException{\\n\\t\\tFloat result = null;\\n\\t\\t\\n\\t\\tLong docCnt\\t\\t= this.elasticClient.getDocCount();\\n\\t\\tLong termDocCnt = this.elasticClient.getDocCount(term);\\n\\t\\t\\n\\t\\tresult = ((Long)(docCnt / termDocCnt)).floatValue();\\n\\t\\t\\n\\t\\treturn result;\\n\\t}\",\n \"@Override\\n protected float score(BasicStats stats, float termFreq, float docLength) {\\n double s = 0.75;\\n\\n long N = stats.getNumberOfDocuments();\\n long df = stats.getDocFreq();\\n float cwd = termFreq;\\n float cwq = 1; //assume that the query term frequency is always one\\n float n = docLength;\\n float navg = stats.getAvgFieldLength();\\n\\n double p1 = (1+Math.log(1+Math.log(cwd)))/(1-s+s*n/navg);\\n float ans = (float) (p1 * cwq * Math.log((N+1)/df));\\n\\n return ans;\\n }\",\n \"public HashMap<String, Double> search(String query) {\\n // ===================================================\\n // 1. Fetch all inverted lists corresponding to terms\\n // in the query.\\n // ===================================================\\n String[] terms = query.split(\\\" \\\");\\n HashMap<String, Integer> qf = new HashMap<String, Integer>();\\n // Calculate term frequencies in the query\\n for (String term : terms) {\\n if (qf.containsKey(term))\\n qf.put(term, qf.get(term) + 1);\\n else\\n qf.put(term, 1);\\n }\\n HashMap<String, Double> docScore = new HashMap<String, Double>();\\n for (Entry<String, Integer> termEntry : qf.entrySet()) {\\n String term = termEntry.getKey();\\n int qfi = termEntry.getValue();\\n\\n // ===================================================\\n // 2. Compute BM25 scores for documents in the lists.\\n // Make a score list for documents in the inverted\\n // lists. Assume that no relevance information is \\n // available. For parameters, use k1=1.2, b=0.75, \\n // k2=100.\\n // ===================================================\\n double k1 = 1.2;\\n double b = 0.75;\\n double k2 = 100;\\n int ni = invIndex.get(term).size();\\n\\n\\n for (Entry<String, IndexEntry> invListEntry : invIndex.get(term).entrySet()) {\\n String docID = invListEntry.getKey();\\n double bm25Score;\\n if (docScore.containsKey(docID))\\n bm25Score = docScore.get(docID);\\n else\\n bm25Score = 0;\\n\\n // length of the document\\n int dl = docStat.get(docID);\\n // frequency of the term in the document\\n int fi = invListEntry.getValue().getTf();\\n double K = k1 * ((1 - b) + b * ((double) dl / avdl));\\n\\n // ===================================================\\n // 3. Accumulate scores for each term in a query\\n // on the score list.\\n // ===================================================\\n bm25Score += Math.log((N - ni + 0.5) / (ni + 0.5))\\n * (((k1 + 1) * fi * (k2 + 1) * qfi) / ((K + fi) * (k2 + qfi)));\\n docScore.put(docID, bm25Score);\\n }\\n }\\n\\n return docScore;\\n }\",\n \"public Term[] getTerms() { return terms; }\",\n \"@Override\\n protected float score(BasicStats stats, float termFreq, float docLength) {\\n float k1 = (float)1.2;\\n float k2 = 750;\\n float b = (float)0.75;\\n float N = stats.getNumberOfDocuments();\\n float df = stats.getDocFreq();\\n float qtermFreq = 1;\\n float score = (float)Math.log((N - df + 0.5)/df+0.5);\\n score*=((k1+1)*termFreq)/(k1*(1-b+b*(docLength/stats.getAvgFieldLength()))+termFreq);\\n score*=((k2+1)*qtermFreq)/(k2+qtermFreq);\\n return score; }\",\n \"public /*TreeMap<String, Float>*/void getTopnTermsOverlapWithQuery() throws IOException, ParseException{\\n\\t\\tString outputfile = \\\"./output/score/test3.txt\\\";\\n\\n\\t\\tFileOutputStream out = new FileOutputStream(outputfile);\\n\\t\\tPrintStream ps = new PrintStream(out);\\n\\t\\t/*-------------------------------------------------------------------------------*/\\n\\n\\t\\tTreeMap<String,Float> termsscoressorted = null;\\n\\t\\tCollectionReader reader = new CollectionReader(indexDir); \\n\\t\\tIndexReader ir = reader.getIndexReader();\\t\\t\\n\\n\\t\\tTopicsInMemory topics = new TopicsInMemory(\\\"data/CLEF-IP-2010/PAC_test/topics/PAC_topics-test2.xml\\\"/*omit-PAC-1094.xml\\\"*/);\\n\\t\\tfor(Map.Entry<String, PatentDocument> topic : topics.getTopics().entrySet()){\\n\\t\\t\\tString qUcid = topic.getValue().getUcid();\\n\\t\\t\\tString queryid = topic.getKey();\\n\\t\\t\\tString queryName = topic.getKey() + \\\"_\\\" + topic.getValue().getUcid();\\n\\t\\t\\tString queryfile = topic.getKey() + \\\"_\\\" + topic.getValue().getUcid() + \\\".xml\\\";\\n\\n\\t\\t\\t/*System.out.println(\\\"=========================================\\\");\\n\\t\\t\\tSystem.out.println(queryName);\\n\\t\\t\\tSystem.out.println(\\\"=========================================\\\");*/\\n\\t\\t\\t/*int docid = reader.getDocId(\\\"UN-EP-0663270\\\", PatentDocument.FileName);\\n\\t\\t\\tir.getTermVector(docid, field) getTermVectors(b);*/\\n\\n\\t\\t\\tEvaluateResults er = new EvaluateResults();\\n\\t\\t\\tArrayList<String> tps = er.evaluatePatents(queryid, \\\"TP\\\");\\n\\t\\t\\tArrayList<String> fps = er.evaluatePatents(queryid, \\\"FP\\\");\\n\\t\\t\\tHashMap<String, Float> /*TFreqs*/ termsscores = new HashMap<>();\\n\\n\\n\\t\\t\\t/*--------------------------------- Query Words -------------------------------*/\\n\\t\\t\\t//\\t\\t\\tHashMap<String, Integer> query_termsfreqspair = reader.gettermfreqpair(qUcid, PatentDocument.Description);\\n\\t\\t\\tHashSet<String> query_terms = reader.getDocTerms(qUcid, PatentDocument.Description);\\n\\t\\t\\t//\\t\\t\\tSystem.out.println(query_termsfreqspair.size() +\\\"\\\\t\\\"+ query_termsfreqspair);\\n//\\t\\t\\tSystem.out.println(query_terms.size() + \\\"\\\\t\\\" + query_terms);\\n\\t\\t\\t/*-----------------------------------------------------------------------------*/\\t\\t\\t\\n\\n\\n\\t\\t\\t//\\t\\t\\tSystem.out.println(\\\"-----TPs----\\\");\\n\\t\\t\\tfor (String tp : tps) {\\n\\t\\t\\t\\t/*System.out.println(\\\"---------\\\");\\n\\t\\t\\t\\tSystem.out.println(tp);*/\\n\\t\\t\\t\\tHashMap<String, Integer> termsfreqsTP = reader.gettermfreqpairAllsecs(\\\"UN-\\\" + tp);\\n\\n\\t\\t\\t\\tfor(Entry<String, Integer> tfTP:termsfreqsTP.entrySet()){\\n\\t\\t\\t\\t\\tif(termsscores.containsKey(tfTP.getKey())){\\n\\t\\t\\t\\t\\t\\ttermsscores.put(tfTP.getKey(), termsscores.get(tfTP.getKey()) + (float)tfTP.getValue()/tps.size());\\n\\t\\t\\t\\t\\t}else{\\n\\t\\t\\t\\t\\t\\t//\\t\\t\\t\\t\\t\\tfloat test = (float)t.getValue()/tps.size();\\n\\t\\t\\t\\t\\t\\t//\\t\\t\\t\\t\\t\\tSystem.out.println(test);\\n\\t\\t\\t\\t\\t\\ttermsscores.put(tfTP.getKey(), (float)tfTP.getValue()/tps.size());\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\t//\\t\\t\\t\\tSystem.out.println(termsscores.size() + \\\" \\\" + termsscores);\\t\\t\\t\\t\\t\\n\\t\\t\\t}\\n\\n\\t\\t\\t/*System.out.println();\\n\\t\\t\\tSystem.out.println(\\\"-----FNs----\\\");*/\\n\\t\\t\\tfor (String fp : fps) {\\n\\t\\t\\t\\t/*System.out.println(\\\"---------\\\");\\n\\t\\t\\t\\tSystem.out.println(fp);*/\\n\\t\\t\\t\\tHashMap<String, Integer> termsfreqsFP = reader.gettermfreqpairAllsecs(\\\"UN-\\\" + fp);\\n\\n\\t\\t\\t\\tfor(Entry<String, Integer> t:termsfreqsFP.entrySet()){\\n\\t\\t\\t\\t\\tif(termsscores.containsKey(t.getKey())){\\n\\t\\t\\t\\t\\t\\ttermsscores.put(t.getKey(), termsscores.get(t.getKey()) - (float)t.getValue()/fps.size());\\n\\t\\t\\t\\t\\t}else{\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\ttermsscores.put(t.getKey(), -(float)t.getValue()/fps.size());\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\t//\\t\\t\\t\\tSystem.out.println(TFreqs.size() + \\\" \\\" + TFreqs);\\n\\t\\t\\t}\\n\\t\\t\\t//\\t\\t\\tSystem.out.println(termsscores.size() + \\\" \\\" + termsscores);\\n\\t\\t\\tValueComparator bvc = new ValueComparator(termsscores);\\n\\t\\t\\ttermsscoressorted = new TreeMap<String,Float>(bvc);\\t\\t\\t\\n\\t\\t\\ttermsscoressorted.putAll(termsscores);\\n\\t\\t\\tSystem.out.println(queryid + \\\"\\\\t\\\"+ termsscoressorted.size() + \\\"\\\\t\\\" + termsscoressorted/*.keySet()*/);\\n\\t\\t\\tint overlap = 0;\\n\\t\\t\\tint i = 0;\\n\\t\\t\\tfor(Entry<String, Float> scoresorted:termsscoressorted.entrySet()){\\n\\t\\t\\t\\ti++;\\n\\t\\t\\t\\tif(i<=100){\\n\\t\\t\\t\\t\\tif(query_terms.contains(scoresorted.getKey())){\\n\\t\\t\\t\\t\\t\\toverlap++;\\n\\t\\t\\t\\t\\t}\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\t\\n\\t\\t\\tSystem.out.println(queryName + \\\"\\\\t\\\"+overlap);\\n//\\t\\t\\tps.println(queryName + \\\"\\\\t\\\"+overlap);\\n\\t\\t}\\n\\t}\",\n \"private Double getSentenceTfIdf(String sentence, Article article) {\\n Double sentenceTfIdf = 0.0;\\n PriorityQueue<Double> topFiveWords = new PriorityQueue<>(Collections.reverseOrder());\\n Set<String> alreadyConsideredWords = new HashSet<>();\\n\\n // Split the words in a sentence\\n String[] sentenceTerms = sentence.split(\\\"\\\\\\\\s+\\\");\\n\\n for (String term: sentenceTerms) {\\n // format the raw term to remove non-alphanumeric characters\\n term = term.replaceAll(\\\"[^a-zA-Z\\\\\\\\d]\\\", \\\"\\\").toLowerCase().trim();\\n\\n if (!term.isEmpty()) {\\n // lookup term in unigrams map to get its TF.IDF score\\n Unigram correspondingUnigram = article.unigrams.get(term);\\n\\n if (correspondingUnigram != null && !alreadyConsideredWords.contains(term)) {\\n topFiveWords.add(correspondingUnigram.getTf_idf());\\n alreadyConsideredWords.add(term);\\n }\\n }\\n }\\n\\n int limit = Math.min(5, topFiveWords.size());\\n for (int i = 0; i < limit; i++) {\\n sentenceTfIdf += topFiveWords.poll();\\n }\\n\\n return sentenceTfIdf;\\n }\",\n \"public void relevanceFeedback(PostingsList results, boolean[] docIsRelevant, Indexer indexer ) {\\r\\n// results contain the ranked list from the current search\\r\\n// docIsRelevant contains the users feedback on which of the 10 first hits are relevant\\r\\n\\tdouble gamma = 0.0; // används ej, de orelevanta dokumenterna. städa upp queryn. Vad innehller de orelevanta dokumenterna för termer\\r\\n// dess termer tar vi bort från den relebanta.)\\r\\n\\r\\n\\tdouble alfa = 0.8; // hur mycket litar på det gamla sökning innan feedback\\r\\n\\tdouble beta = 0.6; // hur mycket hänsyn du ska ta till nya sökningen efter feedback \\r\\n\\r\\n\\r\\n\\t/* \\r\\n\\r\\n\\tAlgorithm: \\r\\n\\tThe Rocchio algorithm is based on a method of relevance \\r\\n\\tfeedback found in information retrieval systems\\r\\n\\tThe algorithm is based on the assumption that most users \\r\\n\\thave a general conception of which documents should be denoted \\r\\n\\tas relevant or non-relevant.[1] Therefore, the user's search \\r\\n\\tquery is revised to include an arbitrary percentage of relevant \\r\\n\\tand non-relevant documents as a means of increasing the search \\r\\n\\tengine's recall, and possibly the precision as well. The number \\r\\n\\tof relevant and non-relevant documents allowed to enter a query \\r\\n\\tis dictated by the weights of the a, b.\\r\\n\\tthe associated weights (a, b) are responsible for shaping the \\r\\n\\tmodified vector in a direction closer, or farther away, from the \\r\\n\\toriginal query, related documents, and non-related documents.\\r\\n\\r\\n\\r\\n\\r\\n\\tLimitations of rocchio:\\r\\n\\t\\tTherefore the two queries of \\\"Burma\\\" and \\\"Myanmar\\\" will \\r\\n\\t\\tappear much farther apart in the vector space model, \\r\\n\\t\\tthough they both contain similar origins\\r\\n\\tWhy not use non-relevant documents:\\r\\n\\t\\tThough there are benefits to ranking documents as not-relevant, \\r\\n\\t\\ta relevant document ranking will result in more precise documents \\r\\n\\t\\tbeing made available to the user. \\r\\n\\t\\r\\n\\r\\n\\r\\n\\tRoccio algoritmen: \\r\\n\\t\\talfa = Original query weight \\r\\n\\t\\tbeta = related document weight\\r\\n\\t\\t\\r\\n\\t\\thigher alpha means that we give more focus to the original query terms\\r\\n\\t\\thigher beta means that we give more focus to the new search feedback. i.e new terms.\\r\\n\\r\\n\\t\\tTar en org query\\r\\n\\t\\tTar den gamla gånnger en viss vikt \\r\\n\\t\\tvikt är alfa + beta (entill vektor) plus att den kollar på original vektor, q0 \\r\\n\\t\\t\\thögre alfa mer fokus på original queryn \\r\\n\\t\\t\\thögra beta skiftar till mer fokus på de nya termerna. \\r\\n\\t\\tdvs utökas med ord/termer från dokument vektorerna som var relevanta. \\r\\n\\r\\n\\tVanligtvis har man väldigt häg alfa och beta lite under för att det är standard. man tycker att den \\r\\n\\tförsta queryn är väldigt bra.\\r\\n\\r\\n\\t\\r\\n\\t*/\\r\\n\\r\\n\\tPostingsList related_doc_vector = new PostingsList();\\r\\n\\tHashMap<String, Double> qm = new HashMap<String, Double>(); // spara termer och weights.\\r\\n\\t// normalize weights\\r\\n\\tfor(Double w : weights){\\r\\n\\t\\tw = w/weights.size();\\r\\n\\t}\\r\\n\\r\\n\\tIterator<PostingsEntry> it = results.iterator();\\r\\n\\tfor(int i = 0; i < docIsRelevant.length; i++){\\r\\n\\t\\tif(docIsRelevant[i] == true){\\r\\n\\t\\t\\trelated_doc_vector.list.add(results.get(i));\\r\\n\\t\\t} \\r\\n\\t}\\r\\n\\r\\n\\t// apply Rocchio algorithm.\\r\\n\\tfor(int i = 0; i < terms.size(); i++){\\r\\n\\t\\tdouble new_weigt = weights.get(i) * alfa;\\r\\n\\t\\tqm.put(terms.get(i), new_weigt);\\r\\n\\t}\\r\\n\\r\\n\\tfor(int i = 0; i < related_doc_vector.size(); i++){\\r\\n\\t\\tIterator<PostingsEntry> ite = related_doc_vector.iterator();\\r\\n\\t\\twhile(ite.hasNext()){\\r\\n\\t\\t\\tPostingsEntry postingsentry = ite.next();\\r\\n\\t\\t\\tint docID = postingsentry.docID;\\r\\n\\t\\t\\tString filename = indexer.index.docIDs.get(Integer.toString(docID)); // hämtar filnamnet\\r\\n\\t\\t\\tString path = \\\"/Users/monadadoun/Desktop/ir/lab/davisWiki/\\\" + filename; \\r\\n\\t\\t\\tFile file = new File(path);\\r\\n\\t\\t\\tHashSet<String> hs = new HashSet<>();\\r\\n\\t\\t\\t// lägger till alla ord som finns till mitt hashet\\r\\n\\t\\t\\ttry (Reader reader = new InputStreamReader( new FileInputStream(file), StandardCharsets.UTF_8 )){\\r\\n\\t\\t\\t\\tTokenizer tok = new Tokenizer( reader, true, false, true, indexer.patterns_file );\\r\\n\\t\\t\\t\\twhile (tok.hasMoreTokens()) {\\r\\n\\t\\t\\t\\t\\ths.add(tok.nextToken());\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t} catch (IOException e) {\\r\\n\\t\\t\\t\\te.printStackTrace();\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\t\\r\\n\\t\\t\\tIterator<String> iter = hs.iterator();\\r\\n\\t\\t\\twhile(iter.hasNext()){\\r\\n\\t\\t\\t\\tString s = iter.next();\\r\\n\\t\\t\\t\\tif(qm.containsKey(s)){\\r\\n\\t\\t\\t\\t\\tDouble tmp = qm.get(s);\\r\\n\\t\\t\\t\\t\\tqm.put(s, tmp + beta * postingsentry.score);\\r\\n\\t\\t\\t\\t} else {\\r\\n\\t\\t\\t\\t\\tqm.put(s, beta * postingsentry.score);\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t}\\r\\n\\t\\t}\\r\\n\\t}\\r\\n\\tLinkedList<String> term = new LinkedList<>();\\r\\n\\tLinkedList<Double> weight = new LinkedList<>();\\r\\n\\tList<Map.Entry<String,Double>> answer = new ArrayList<Map.Entry<String,Double>>(qm.entrySet());\\r\\n\\tanswer.sort((e1,e2) -> e2.getValue().compareTo(e1.getValue())); // sorterar efter värde så att orden med högst score ligger först\\r\\n\\tfor (int i = 0; i < answer.size(); i++) {\\r\\n\\t\\tterm.add(answer.get(i).getKey());\\r\\n\\t\\tweight.add(answer.get(i).getValue()/answer.size());\\r\\n\\t}\\r\\n\\r\\n\\tterms = term;\\r\\n\\tweights = weight;\\r\\n\\t}\",\n \"public TermToVertexCount[] getSubTermVertexMappings(String term)\\n {\\n /* String is not valid as-is.\\n * \\n * Replace and split words into parts.\\n */\\n term = term.replace('-', ' ');\\n String [] arr = term.split(\\\" \\\");\\n\\n /* Remove common words */\\n for(int i = 0; i < arr.length; i++)\\n {\\n if(arr[i].equals(\\\"and\\\"))\\n {\\n arr[i] = \\\"\\\";\\n }\\n else if(arr[i].equals(\\\"or\\\"))\\n {\\n arr[i] = \\\"\\\";\\n }\\n else if(arr[i].equals(\\\"to\\\"))\\n {\\n arr[i] = \\\"\\\";\\n }\\n else if(arr[i].equals(\\\"be\\\"))\\n {\\n arr[i] = \\\"\\\";\\n }\\n else if(arr[i].equals(\\\"the\\\"))\\n {\\n arr[i] = \\\"\\\";\\n }\\n else if(arr[i].equals(\\\"a\\\"))\\n {\\n arr[i] = \\\"\\\";\\n }\\n else if(arr[i].equals(\\\"of\\\"))\\n {\\n arr[i] = \\\"\\\";\\n }\\n else if(arr[i].equals(\\\"on\\\"))\\n {\\n arr[i] = \\\"\\\";\\n }\\n else if(arr[i].equals(\\\"in\\\"))\\n {\\n arr[i] = \\\"\\\";\\n }\\n else if(arr[i].equals(\\\"for\\\"))\\n {\\n arr[i] = \\\"\\\";\\n }\\n else if(arr[i].equals(\\\"with\\\"))\\n {\\n arr[i] = \\\"\\\";\\n }\\n else if(arr[i].equals(\\\"by\\\"))\\n {\\n arr[i] = \\\"\\\";\\n }\\n else if(arr[i].equals(\\\"into\\\"))\\n {\\n arr[i] = \\\"\\\";\\n }\\n else if(arr[i].equals(\\\"an\\\"))\\n {\\n arr[i] = \\\"\\\";\\n }\\n else if(arr[i].equals(\\\"is\\\"))\\n {\\n arr[i] = \\\"\\\";\\n }\\n else if(arr[i].equals(\\\"no\\\"))\\n {\\n arr[i] = \\\"\\\";\\n }\\n }//end: for(i)\\n\\n /* Create String array without common terms */\\n int size = 0;\\n for(int i = 0; i < arr.length; i++)\\n {\\n if(!arr[i].equals(\\\"\\\") && stem)\\n { // Stem if required\\n arr[i] = PorterStemmerTokenizerFactory.stem(arr[i]);\\n }\\n \\n // Check for valid term\\n if(!arr[i].equals(\\\"\\\") && getVertexMappings(arr[i]) != null)\\n {\\n size++;\\n }\\n }//end: for(i)\\n \\n if(size == 0)\\n { /* No valid terms found */\\n return null;\\n }\\n \\n /* At least one valid term was found */\\n TermToVertexCount[] words = new TermToVertexCount[size];\\n int pos = 0;\\n \\n for(int i = 0; i < arr.length; i++)\\n {\\n // Check for valid term\\n if(!arr[i].equals(\\\"\\\"))\\n {\\n // Get mappings for sub-term\\n TermToVertexCount[] temp = getVertexMappings(arr[i]);\\n \\n if(temp != null)\\n {\\n words[pos] = temp[0];\\n pos++;\\n }//end: if(temp)\\n \\n }//end: if(!arr[i])\\n }//end: for(i)\\n \\n return words; \\n }\",\n \"private static void statsForQuery(String query) {\\n\\t\\tHashMap<String,Integer> oldTerms=newTerms; // record the terms to analyze modified queries\\n\\t\\tnewTerms=new HashMap<String,Integer>();\\n\\t\\t\\t\\t\\n\\t\\tString terms[]=query.split(\\\"\\\\\\\\s\\\");\\t\\t\\t\\t\\n\\t\\tint matchingTerms=0;\\n\\t\\tint matchingTermsStopwords=0;\\n\\t\\tint matchingTermsOrder=0;\\n\\t\\tfor (int j=0;j<terms.length;j++) {\\n\\t\\t\\tif (!terms[j].equals(\\\"\\\")) {\\n\\t\\t\\t \\tif (oldTerms.containsKey(terms[j])) {\\n\\t\\t\\t \\t\\tmatchingTerms++;\\t\\t\\t\\t\\t \\n\\t\\t\\t \\t\\tif (stopwordsMap.containsKey(terms[j])) { // match if it is stopword\\n\\t\\t\\t \\t\\t\\tmatchingTermsStopwords++;\\n\\t\\t\\t \\t\\t}\\n\\t\\t\\t \\t\\tif (oldTerms.get(terms[j])==j) { // match if it has the same order\\n\\t\\t\\t \\t\\t\\tmatchingTermsOrder++;\\n\\t\\t\\t \\t\\t}\\n\\t\\t\\t \\t}\\n\\t\\t\\t \\tnewTerms.put(terms[j],j);\\n\\t\\t\\t}\\n\\t\\t}\\t\\n\\n\\t\\tif (newTerms.size()==oldTerms.size() && matchingTerms==oldTerms.size() && matchingTerms>0) { // the queries have the same terms\\n\\t\\t totalEqualTermsQueries++;\\n\\t\\t\\t\\t \\t\\t\\t\\t \\t\\t\\t\\t\\t\\t \\t\\t\\t\\t \\t\\t\\t\\t \\n\\t\\t if (matchingTermsStopwords==oldTerms.size()) {\\n\\t\\t \\ttotalEqualTermsStopwordsQueries++;\\n\\t\\t }\\n\\t\\t if (matchingTermsOrder==oldTerms.size()) {\\n\\t\\t \\ttotalEqualTermsOrderQueries++;\\n\\t\\t }\\n\\t\\t if (query.equals(oldQuery)) {\\n\\t\\t \\ttotalIdenticalQueries++;\\n\\t\\t }\\n\\t\\t if (sessionQueries.contains(query)) {\\n\\t\\t \\ttotalIdenticalSessionQueries++;\\n\\t\\t }\\n\\t\\t}\\n\\t\\telse if (matchingTerms-matchingTermsStopwords>0) { // the queries have at least one term equal and diferent from a stopword\\n\\t\\t totalModifiedQueries++;\\n\\t\\t int index=newTerms.size()-oldTerms.size()+N_MODIFIED_TERMS_RANGE/2;\\n\\t\\t if (index<0) {\\n\\t\\t \\tindex=0;\\n\\t\\t }\\n\\t\\t else if (index>N_MODIFIED_TERMS_RANGE-1) {\\n\\t\\t \\tindex=N_MODIFIED_TERMS_RANGE-1;\\n\\t\\t }\\n\\t\\t nModifiedTerms[index]++;\\n\\t\\t}\\n\\t\\toldQuery=query; \\n\\t\\t\\t\\t\\t\\t\\n\\t\\t// store session query\\n\\t\\tsessionQueries.add(query);\\n\\t}\",\n \"abstract public TermEnum terms(Term t) throws IOException;\",\n \"public int getNatureFilter();\",\n \"@Override\\n public int getDocumentFrequencyByTerm(String term) {\\n return 0;\\n }\",\n \"int getSimilarityThreshold(final int field);\",\n \"private double getTermOccurrence(String term, ClassificationClass classificationClass) {\\n int termOccurrence = 0;\\n\\n for (Document document : documents) {\\n if (document.getClassificationClasses().contains(classificationClass)) {\\n if (document.getFeatures().containsKey(term)) {\\n termOccurrence += document.getFeatures().get(term);\\n }\\n }\\n }\\n\\n return termOccurrence;\\n }\",\n \"@Override\\n\\t\\tpublic int hashCode() {\\n\\t\\t\\treturn mTerm.hashCode();\\n\\t\\t}\",\n \"private HashMap<String,HashMap<String,Integer>> computeTFForQueryWords(ArrayList<String> queryPostingLines) {\\n HashMap<String,HashMap<String,Integer>> queryWordsTF = new HashMap<>();\\n HashMap<String,HashMap<String,Integer>> queryWordsTFPerDoc = new HashMap<>();\\n String docID,term;\\n Integer tf;\\n HashSet<String> docIDs = new HashSet<>();\\n for(String postingLine : queryPostingLines){\\n HashMap<String,Integer> frequenciesInDocuments = new HashMap<>();\\n term = postingLine.substring(0,postingLine.indexOf(\\\"|\\\"));\\n postingLine = postingLine.substring(postingLine.indexOf(\\\"|\\\")+1);\\n while(!postingLine.equals(\\\"\\\")) {\\n docID = postingLine.substring(0, postingLine.indexOf(\\\":\\\"));\\n docIDs.add(docID);\\n postingLine = postingLine.substring(postingLine.indexOf(\\\"_\\\") + 1);\\n tf = Integer.valueOf(postingLine.substring(0, postingLine.indexOf(\\\"_\\\")));\\n postingLine = postingLine.substring(postingLine.indexOf(\\\"_\\\") + 1);\\n frequenciesInDocuments.put(docID,tf);\\n }\\n queryWordsTF.put(term,frequenciesInDocuments);\\n }\\n\\n ArrayList<String> allTermsInQuery = new ArrayList<>(queryWordsTF.keySet());\\n for(String doc : docIDs){\\n HashMap<String,Integer> tfsInDoc = new HashMap<>();\\n for(String termInQuery : allTermsInQuery){\\n HashMap<String,Integer> termsTFInDoc = queryWordsTF.get(termInQuery);\\n if(termsTFInDoc.containsKey(doc)){\\n tfsInDoc.put(termInQuery,termsTFInDoc.get(doc));\\n }\\n }\\n queryWordsTFPerDoc.put(doc,tfsInDoc);\\n }\\n return queryWordsTFPerDoc;\\n }\",\n \"public abstract List<LambdaTerm> containedLambdaTerms(LambdaTerm P);\",\n \"public void theDude() {\\n\\t\\ttotal_targets = 0;\\n\\t\\ttotal = 0;\\n\\t\\tint target_count = 0;\\n\\t\\tresult.clear();\\n\\t\\t\\n\\t\\tfor(int k=0; k<input.getWords().size();k++) {\\n\\t\\t\\tWord currentWordStat = input.getWordStatistics().get(k);\\n\\t\\t\\ttarget_count = 0;\\n\\t\\t\\t\\n\\t\\t\\tfor(int i=0;i<input.getWords().get(k).length();i++) {\\n\\t\\t\\t\\tif(target.contains(input.getWords().get(k).charAt(i))) {\\n\\t\\t\\t\\t\\ttarget_count++;\\n\\t\\t\\t\\t\\ttotal_targets++;\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\ttotal++;\\n\\t\\t\\t}\\n\\t\\t\\t\\n\\t\\t\\tif(result.containsKey(currentWordStat)) {\\n\\t\\t\\t\\tresult.put(currentWordStat, result.get(currentWordStat)+target_count);\\n\\t\\t\\t}\\n\\t\\t\\telse {\\n\\t\\t\\t\\tresult.put(currentWordStat, target_count);\\n\\t\\t\\t}\\n\\t\\t}\\t\\n\\t}\",\n \"public float getTFIDF(Index index, String word) {\\n long docCount = index.getDocuments().stream().filter(document -> document.hasWord(word)).count();\\n return (float) getWordOccurrence(word) * (float) Math.log((float) index.getDocuments().size() / (float) docCount);\\n }\",\n \"public int getDocFreq(Term t){\\n\\t\\tint freq = 0;\\r\\n\\t\\tfor (Map.Entry<String, IndexedDoc> set : index.entrySet()){\\r\\n\\t\\t\\tif (set.getValue().containsTerm(t)){\\r\\n\\t\\t\\t\\tfreq++;\\r\\n\\t\\t\\t}\\r\\n\\t\\t}\\r\\n\\t\\treturn freq;\\r\\n\\t}\",\n \"private Map<String,List<Invertedindex>> collecting() //\\r\\n {\\r\\n Map<String,List<Invertedindex>> maps = new TreeMap<>();\\r\\n for (Core pon:pondred){\\r\\n for(Map.Entry<String,Double> term:pon.allTerms.entrySet()){\\r\\n if (maps.containsKey(term.getKey())){\\r\\n List<Invertedindex> index = maps.get(term.getKey());\\r\\n index.add(new Invertedindex(pon.m_cle,term.getValue(),pon.getBalise(term.getKey())));\\r\\n maps.put(term.getKey(), index);\\r\\n }else {\\r\\n List<Invertedindex> index = new ArrayList<>();\\r\\n index.add(new Invertedindex(pon.m_cle,term.getValue(),pon.getBalise(term.getKey())));\\r\\n maps.put(term.getKey(), index);\\r\\n }\\r\\n if(cleFreq.containsKey(pon.m_cle))\\r\\n cleFreq.put(pon.m_cle,cleFreq.get(pon.m_cle)+term.getValue());\\r\\n else cleFreq.put(pon.m_cle,term.getValue());\\r\\n\\r\\n }\\r\\n }\\r\\n return maps;\\r\\n }\",\n \"@Override\\n protected QueryProcessor computeResult(ResultComputingContext<? extends TermsIndexingEquipment> context) {\\n final TermWeight idf = context.preliminaryResult(CalculatingInvertedTermFrequency.getInstance());\\n final TermDocumentWeight tf = context.preliminaryResult(context.equipment().termFrequencyCalculation());\\n //for obtaining set of terms in each document.\\n final EachDocumentTermsExtraction documentsTerms = context.preliminaryResult(ExtractingEachDocumentTerms.getInstance());\\n //for obtaining document length\\n final Map<Document, TermsOccurences> termsOccurences = context.preliminaryResult(CountingTermsOccurencesInEachDocument.getInstance());\\n final double averageDocLength = context.preliminaryResult(ComputingAverageDocumentLength.getInstance());\\n\\n QueryProcessor res = new QueryProcessor() {\\n @Override\\n public DocumentRanker rankForQuery(final Collection<String> query) {\\n return new DocumentRanker() {\\n @Override\\n public double score(Document document) {\\n /*\\n * BM25 score is calculated here\\n */\\n\\n //obtaining the set of terms in the document\\n Set<String> allDocTerms = documentsTerms.termsExtractedFromDocument(document).allTerms();\\n\\n //keeping only the query terms that are in the document\\n Collection<String> relevantTerms = new LinkedHashSet<>(query);\\n relevantTerms.retainAll(allDocTerms);\\n\\n //compute score using a sum formula on each query term\\n int docLength = termsOccurences.get(document).totalNumberOfOccurences();\\n double score = 0.0;\\n for (String term : relevantTerms) {\\n double termIDF = idf.weight(term);\\n double termTF = tf.weight(term, document);\\n\\n score += termIDF * (termTF * (k1 + 1)) / (termTF + k1 * (1 - b + b * (docLength / averageDocLength)));\\n }\\n\\n return score;\\n }\\n };\\n\\n }\\n };\\n\\n logger.log(Level.INFO, \\\"Just created a BM25 query processor with parameters : \\\" + \\\"k1={0}, b={1}\\\", new Object[]{k1, b});\\n\\n return res;\\n }\",\n \"String legalTerms();\",\n \"void collectLeastFrequent(FrequencyTable fq);\",\n \"public Taxonomy getInterests();\",\n \"@Override\\n protected double getTFDocument(BasicStats stats, float termFreq, float docLength) {\\n return ((k1 + 1) * termFreq / (k1 * (1 - b +\\n b * docLength / stats.getAvgFieldLength()) + termFreq));\\n }\",\n \"public abstract void addFeatures(Collection<Integer> indices,Predicate pred,Word arg,Integer offset,boolean allWords);\",\n \"@Override\\r\\n\\t\\t\\tpublic long getDocumentFrequency(String term) {\\n\\t\\t\\t\\treturn 0;\\r\\n\\t\\t\\t}\",\n \"public static HashMap<String, Double> getTFIDF(String inputStr) throws IOException{\\n\\t\\tHashMap<String, Double> result = new HashMap<String, Double>();\\n\\t\\tHashMap<String, Integer> termsMap = new HashMap<String, Integer>();\\t\\t\\n\\t\\tArrayList<String> inputTerms = getTerms(inputStr);\\n\\t\\t\\n\\t\\tfor(String s : inputTerms){\\n\\t\\t\\tif(termsMap.containsKey(s) != true){\\n\\t\\t\\t\\ttermsMap.put(s, 1);\\n\\t\\t\\t}else{\\n\\t\\t\\t\\ttermsMap.put(s, termsMap.get(s)+1);\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\t\\n\\t\\tfor(String term : termsMap.keySet()){\\n\\t\\t\\tdouble TF;\\n\\t\\t\\t//System.out.println(term + \\\" \\\" + termsMap.get(term));\\t\\t\\t\\t\\n\\t\\t\\tTF = (double)termsMap.get(term)/inputTerms.size();\\n\\t\\t\\tresult.put(term, TF*cal_IDF(term));\\n\\t\\t}\\n\\t\\t\\n\\t\\treturn result;\\n\\t}\",\n \"public static void main(String[] args) throws Exception {\\n\\t\\tint i;\\r\\n\\t\\tint [][]preci_recall = new int [5][6]; \\r\\n\\r\\n\\t\\tNGRAM ngram = new NGRAM();\\r\\n\\t\\t\\r\\n\\t\\tfor(i=0; i<5; i++) {\\r\\n\\t\\t\\t\\r\\n\\t\\t\\tSystem.out.println((i+1) + \\\" th FOLD IS A TEST SET\\\");\\r\\n\\t\\t\\t\\r\\n\\t\\t\\tdouble[][] test_ngram_features = ngram.feature(i,1);\\r\\n\\t\\t\\tdouble[][] train_ngram_features = ngram.feature(i,0);\\r\\n\\t\\t\\t\\r\\n\\t\\t\\tSystem.out.println(\\\"NGRAM FEATURES...OK\\\");\\r\\n\\t\\r\\n//\\t\\t\\t\\r\\n//\\t\\t\\tLIWC liwc = new LIWC();\\r\\n//\\t\\t\\t\\r\\n//\\t\\t\\tdouble[][] test_liwc_features = liwc.feature(i,1,test_ngram_features.length);\\r\\n//\\t\\t\\tdouble[][] train_liwc_features = liwc.feature(i,0,train_ngram_features.length);\\r\\n//\\r\\n//\\t\\t\\tSystem.out.println(\\\"LIWC FEATURES..OK\\\");\\r\\n//\\t\\t\\t\\r\\n//\\t\\t\\tCOMBINE combine = new COMBINE();\\r\\n//\\t\\t\\tdouble[][] train_features = combine.sum(train_liwc_features,train_ngram_features);\\r\\n//\\t\\t\\tdouble[][] test_features = combine.sum(test_liwc_features,test_ngram_features);\\r\\n//\\t\\t\\t\\r\\n//\\t\\t\\tSystem.out.println(\\\"COMBINE...OK\\\");\\r\\n\\t\\t\\r\\n\\t\\t\\tSVMLIGHT svmlight = new SVMLIGHT();\\r\\n\\t\\t\\tpreci_recall[i]=svmlight.calcc(train_ngram_features, test_ngram_features);\\r\\n\\r\\n\\t\\t}\\r\\n\\t\\t\\r\\n//\\t 0 : truthful TP\\r\\n//\\t 1 : truthful TP+FP\\r\\n//\\t 2 : truthful TP+FN\\r\\n//\\t 3 : deceptive TP\\r\\n//\\t 4 : deceptive TP+FP\\r\\n//\\t 5 : deceptive TP+FN\\r\\n\\t\\t\\r\\n\\t\\tint truthful_TP_sum=0,truthful_TPFP_sum=0,truthful_TPFN_sum=0;\\r\\n\\t\\tint deceptive_TP_sum=0,deceptive_TPFP_sum=0,deceptive_TPFN_sum=0;\\r\\n\\t\\t\\r\\n\\t\\tfor(i=0;i<5;i++) {\\r\\n\\t\\t\\ttruthful_TP_sum+=preci_recall[i][0];\\r\\n\\t\\t\\ttruthful_TPFP_sum+=preci_recall[i][1];\\r\\n\\t\\t\\ttruthful_TPFN_sum+=preci_recall[i][2];\\r\\n\\t\\t\\t\\r\\n\\t\\t\\tdeceptive_TP_sum+=preci_recall[i][3];\\r\\n\\t\\t\\tdeceptive_TPFP_sum+=preci_recall[i][4];\\r\\n\\t\\t\\tdeceptive_TPFN_sum+=preci_recall[i][5];\\r\\n\\t\\t}\\r\\n\\t\\t\\t\\t\\r\\n\\t\\tSystem.out.println(\\\"\\\\n\\\\nTRUTHFUL_TP_SUM : \\\" + truthful_TP_sum);\\r\\n\\t\\tSystem.out.println(\\\"TRUTHFUL_TPFP_SUM : \\\" + truthful_TPFP_sum);\\r\\n\\t\\tSystem.out.println(\\\"TRUTHFUL_TPFN_SUM : \\\" + truthful_TPFN_sum);\\r\\n\\t\\t\\r\\n\\t\\tSystem.out.println(\\\"DECEPTIVE_TP_SUM : \\\" + deceptive_TP_sum);\\r\\n\\t\\tSystem.out.println(\\\"DECEPTIVE_TPFP_SUM : \\\" + deceptive_TPFP_sum);\\r\\n\\t\\tSystem.out.println(\\\"DECEPTIVE_TPFN_SUM : \\\" + deceptive_TPFN_sum);\\r\\n\\t\\t\\r\\n\\t\\tSystem.out.println(\\\"\\\\nTRUTHFUL PRECISION : \\\" + (double)(truthful_TP_sum)/(double)(truthful_TPFP_sum));\\r\\n\\t\\tSystem.out.println(\\\"TRUTHFUL RECALL : \\\" + (double)(truthful_TP_sum)/(double)(truthful_TPFN_sum));\\r\\n\\t\\t\\r\\n\\t\\tSystem.out.println(\\\"DECEPTIVE PRECISION : \\\" + (double)(deceptive_TP_sum)/(double)(deceptive_TPFP_sum));\\r\\n\\t\\tSystem.out.println(\\\"DECEPTIVE RECALL : \\\" + (double)(deceptive_TP_sum)/(double)(deceptive_TPFN_sum));\\r\\n\\t\\t\\r\\n\\r\\n\\t}\",\n \"public int getTermTotal(){\\n\\t\\tint total = 0;\\r\\n\\t\\tfor (Map.Entry<String, IndexedDoc> set : index.entrySet()){\\r\\n\\t\\t\\ttotal += set.getValue().getTotalTerms();\\r\\n\\t\\t}\\r\\n\\t\\treturn total;\\r\\n\\t}\",\n \"private boolean classify(FeatureVector<? extends Number> wd) {\\n\\t\\tfloat sum = 0;\\n\\t\\t// Scalar Product\\n\\t\\tfor (int i = 0; i < this.getDimensionality(); ++i) {\\n\\t\\t\\t// TODO check the type of the vector\\n\\t\\t\\tsum += wd.getValue(i).doubleValue()\\n\\t\\t\\t\\t\\t* this.getValue(i).doubleValue();\\n\\t\\t}\\n\\n\\t\\t// sign binary function\\n\\t\\tif (sum <= 0) {\\n\\t\\t\\treturn false;\\n\\t\\t} else {\\n\\t\\t\\treturn true;\\n\\t\\t}\\n\\t}\",\n \"public void fillHandBuilt(Indexer index, String [] terms) {\\n\\t\\tindex.addPosition(terms[0], 3, 1); // ar Term, docID, pos\\n\\t\\tindex.addPosition(terms[1], 2, 4); // british\\n\\t\\tindex.addPosition(terms[2], 3, 3); // dog\\n\\t\\tindex.addPosition(terms[2], 4, 0); // dog\\n\\t\\tindex.addPosition(terms[2], 4, 3); // dog\\n\\t\\tindex.addPosition(terms[3], 4, 1); // enjoi\\n\\t\\tindex.addPosition(terms[4], 0, 6); // enjoy\\n\\t\\tindex.addPosition(terms[5], 1, 5); // in, potential error\\n\\t\\tindex.addPosition(terms[5], 3, 4); // in\\n\\t\\tindex.addPosition(terms[6], 1, 4); // is, potential error\\n\\t\\tindex.addPosition(terms[7], 1, 1); // known\\n\\t\\tindex.addPosition(terms[8], 3, 2); // mani\\n\\t\\tindex.addPosition(terms[9], 0, 1); // monument\\n\\t\\tindex.addPosition(terms[9], 1, 3); // monument potential error\\n\\t\\tindex.addPosition(terms[10], 0, 3); // on\\n\\t\\tindex.addPosition(terms[10], 2, 2); // on\\n\\t\\tindex.addPosition(terms[11], 0, 4); // park\\n\\t\\tindex.addPosition(terms[11], 4, 4); // park\\n\\t\\tindex.addPosition(terms[12], 0, 2); // raid\\n\\t\\tindex.addPosition(terms[12], 2, 1); // raid\\n\\t\\tindex.addPosition(terms[13], 3, 5); // seattl\\n\\t\\tindex.addPosition(terms[14], 0, 0); // the\\n\\t\\tindex.addPosition(terms[14], 1, 0); // the\\n\\t\\tindex.addPosition(terms[14], 2, 3); // the\\n\\t\\tindex.addPosition(terms[14], 4, 2); // the\\n\\t\\tindex.addPosition(terms[15], 3, 0); // there\\n\\t\\tindex.addPosition(terms[16], 0, 5); // wa\\n\\t\\tindex.addPosition(terms[17], 1, 2); // washington potential error\\n\\t\\tindex.addPosition(terms[17], 2, 6); // washington potential error\\n\\t\\tindex.addPosition(terms[17], 2, 0); // washington\\n\\t\\tindex.addPosition(terms[17], 3, 6); // washington\\n\\t\\tindex.addPosition(terms[18], 1, 1); // well potential error\\n\\t\\tindex.addPosition(terms[18], 2, 6); // well \\n\\t\\tindex.addPosition(terms[19], 1, 1); // wellknown\\n\\t\\tindex.addPosition(terms[20], 2, 6); // went\\n\\t}\",\n \"int indexOfFeature(Feature feature);\",\n \"private static void banFeature(ArrayList t) {\\n\\t\\tSet setKeys = Utility.vocabHM.keySet();\\n\\t\\tIterator i = setKeys.iterator();\\n\\t\\tSystem.out.print(\\\"Word cut : [\\\");\\n\\t\\tint idx = 0;\\n\\t\\twhile (i.hasNext()) {\\n\\t\\t\\tString s = (String) i.next();\\n\\t\\t\\tInteger df = (Integer) Utility.vocabHM.get(s);\\n\\n\\t\\t\\tif (t.contains(s)){\\n\\t\\t\\t\\tSystem.out.print(s+\\\", \\\");\\n\\t\\t\\t\\ti.remove();\\n\\t\\t\\t\\tidx++;\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\tSystem.out.println(\\\"]\\\\n ::banned::\\\"+idx+\\\" feature.\\\");\\n\\t}\",\n \"public void translate() {\\n\\t\\tif(!init)\\r\\n\\t\\t\\treturn; \\r\\n\\t\\ttermPhraseTranslation.clear();\\r\\n\\t\\t// document threshold: number of terms / / 8\\r\\n//\\t\\tdocThreshold = (int) (wordKeyList.size() / computeAvgTermNum(documentTermRelation) / 8.0);\\r\\n\\t\\t//\\t\\tuseDocFrequency = true;\\r\\n\\t\\tint minFrequency=1;\\r\\n\\t\\temBkgCoefficient=0.5;\\r\\n\\t\\tprobThreshold=0.001;//\\r\\n\\t\\titerationNum = 20;\\r\\n\\t\\tArrayList<Token> tokenList;\\r\\n\\t\\tToken curToken;\\r\\n\\t\\tint j,k;\\r\\n\\t\\t//p(w|C)\\r\\n\\r\\n\\t\\tint[] termValues = termIndexList.values;\\r\\n\\t\\tboolean[] termActive = termIndexList.allocated;\\r\\n\\t\\ttotalCollectionCount = 0;\\r\\n\\t\\tfor(k=0;k<termActive.length;k++){\\r\\n\\t\\t\\tif(!termActive[k])\\r\\n\\t\\t\\t\\tcontinue;\\r\\n\\t\\t\\ttotalCollectionCount +=termValues[k];\\r\\n\\t\\t}\\r\\n\\t\\t\\r\\n\\t\\t// for each phrase\\r\\n\\t\\tint[] phraseFreqKeys = phraseFrequencyIndex.keys;\\r\\n\\t\\tint[] phraseFreqValues = phraseFrequencyIndex.values;\\r\\n\\t\\tboolean[] states = phraseFrequencyIndex.allocated;\\r\\n\\t\\tfor (int phraseEntry = 0;phraseEntry<states.length;phraseEntry++){\\r\\n\\t\\t\\tif(!states[phraseEntry]){\\r\\n\\t\\t\\t\\tcontinue;\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\tif (phraseFreqValues[phraseEntry] < minFrequency)\\r\\n\\t\\t\\t\\tcontinue;\\r\\n\\t\\t\\ttokenList=genSignatureTranslation(phraseFreqKeys[phraseEntry]); // i is phrase number\\r\\n\\t\\t\\tfor (j = 0; j <tokenList.size(); j++) {\\r\\n\\t\\t\\t\\tcurToken=(Token)tokenList.get(j);\\r\\n\\t\\t\\t\\tif(termPhraseTranslation.containsKey(curToken.getIndex())){\\r\\n\\t\\t\\t\\t\\tIntFloatOpenHashMap old = termPhraseTranslation.get(curToken.getIndex());\\r\\n\\t\\t\\t\\t\\tif(old.containsKey(phraseFreqKeys[phraseEntry])){\\r\\n\\t\\t\\t\\t\\t\\tSystem.out.println(\\\"aha need correction\\\");\\r\\n\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\told.put(phraseFreqKeys[phraseEntry], (float) curToken.getWeight()); //phrase, weight\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\telse {\\r\\n\\t\\t\\t\\t\\tIntFloatOpenHashMap newPhrase = new IntFloatOpenHashMap();\\r\\n\\t\\t\\t\\t\\tnewPhrase.put(phraseFreqKeys[phraseEntry], (float) curToken.getWeight());\\r\\n\\t\\t\\t\\t\\ttermPhraseTranslation.put(curToken.getIndex(), newPhrase);\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t//\\t\\t\\t\\toutputTransMatrix.add(i,curToken.getIndex(),curToken.getWeight());\\r\\n\\t\\t\\t\\t//\\t\\t\\t\\toutputTransTMatrix.add(curToken.getIndex(), i, curToken.getWeight());\\r\\n\\t\\t\\t\\t//TODO termPhrase exists, create PhraseTerm\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\ttokenList.clear();\\r\\n\\t\\t}\\r\\n\\r\\n\\t}\",\n \"private void calculateIDF2Values() throws IOException {\\n\\t\\tfor (int i = 0; i < getTfMapArrayIDF().size(); i++) {\\n\\t\\t\\tList<Map<String, List<Double>>> gestureDocument = getTfMapArrayIDF()\\n\\t\\t\\t\\t\\t.get(i);\\n\\t\\t\\tMap<String, Double> idf2PerDocument = getTfMapArrayIDF2().get(i);\\n\\n\\t\\t\\tfor (int j = 0; j < gestureDocument.size(); j++) {\\n\\t\\t\\t\\tMap<String, List<Double>> tempMap = gestureDocument.get(j);\\n\\t\\t\\t\\tIterator<Entry<String, List<Double>>> it = tempMap.entrySet()\\n\\t\\t\\t\\t\\t\\t.iterator();\\n\\t\\t\\t\\twhile (it.hasNext()) {\\n\\t\\t\\t\\t\\tMap.Entry<String, List<Double>> pairs = (Map.Entry) it\\n\\t\\t\\t\\t\\t\\t\\t.next();\\n\\t\\t\\t\\t\\tDouble inverse = (new Double(getTfMapArrayIDF().get(0)\\n\\t\\t\\t\\t\\t\\t\\t.size()) / idf2PerDocument.get(pairs.getKey())); // already\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t// inversse\\n\\t\\t\\t\\t\\tList<Double> tf = pairs.getValue();\\n\\t\\t\\t\\t\\ttf.set(2,Math.log(inverse));\\n\\t\\t\\t\\t\\ttf.set(3,tf.get(0) * tf.get(1)); //tf-idf\\n\\t\\t\\t\\t\\tidfValues.add(tf.get(1));\\n\\t\\t\\t\\t\\ttf.set(4,tf.get(0) * tf.get(2)); //tf-idf2\\n\\t\\t\\t\\t\\tidf2Values.add(tf.get(2));\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t}\\n\\t}\",\n \"private void evaluationLogic() {\\n // setup for logic:\\n // if distToClosestEstimate[i][0] is smaller than threshold, we have a Tp\\n // if distToClosestEstimate[i][0] is larger than threshold, we have a Fn\\n // all estimatedFeatures that are not assigned Tp are therefore Fp\\n for (int i = 0; i < groundTruthInstant.size(); ++i) {\\n if (distToClosestEstimate[i][0] < truePositiveThreshold) {\\n ++truePositiveCount;\\n int assignedEstimatedFeature = (int) distToClosestEstimate[i][1];\\n assignedEstimatedFeatures[assignedEstimatedFeature] = true;\\n } else\\n ++falseNegativeCount;\\n }\\n for (int i = 0; i < estimatedInstant.size(); ++i)\\n if (!assignedEstimatedFeatures[i])\\n ++falsePositiveCount;\\n }\",\n \"static double binarySearchForBuckets (double[] splits, double feature, boolean keepInvalid) { throw new RuntimeException(); }\",\n \"abstract public TermEnum terms() throws IOException;\",\n \"public abstract double score(double tf, double docLength, double precomp);\",\n \"boolean isIndexed();\",\n \"boolean isIndexed();\",\n \"@Override\\n public double classify(String[] words) {\\n if (words == null || words.length == 0) {\\n throw new IllegalArgumentException(\\\"words must not be null or empty\\\");\\n }\\n return Activation.SIGMOID.apply(bias + dotProduct(words));\\n }\",\n \"public Map<Integer, Boolean> testCategorization(String topic, String[] features) {\\n\\n\\t\\tint n = trainingSet.size(); // Count docs.\\n\\n\\t\\t// Count docs in class.\\n\\t\\tint nc = 0;\\n\\t\\tfor (Integer id : trainingSet) {\\n\\t\\t\\tboolean inClass = this.getDocument(id).getTopics().contains(topic);\\n\\t\\t\\tif (inClass)\\n\\t\\t\\t\\tnc++;\\n\\t\\t}\\n\\n\\t\\tdouble prior_c = nc / (double) n;\\n\\t\\tdouble prior_cbar = (n - nc) / (double) n;\\n\\n\\t\\tMap<String, Double> condProb_c = new HashMap<String, Double>();\\n\\t\\tMap<String, Double> condProb_cbar = new HashMap<String, Double>();\\n\\n\\t\\t// Count docs in class containing term.\\n\\t\\tfor (String term : features) {\\n\\t\\t\\tSet<Integer> postings = terms.get(term).getPostings().keySet();\\n\\t\\t\\tint nct_c = 0, nct_cbar = 0;\\n\\t\\t\\tfor (Integer id : trainingSet) {\\n\\t\\t\\t\\tboolean inClass = this.getDocument(id).getTopics().contains(topic);\\n\\t\\t\\t\\tif (postings.contains(id)) { // document contains the term\\n\\t\\t\\t\\t\\tif (inClass)\\n\\t\\t\\t\\t\\t\\tnct_c++;\\n\\t\\t\\t\\t\\telse\\n\\t\\t\\t\\t\\t\\tnct_cbar++;\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t\\t// And calculate conditional probabilities.\\n\\t\\t\\tcondProb_c.put(term, (nct_c + 1) / (double) (nc + 2));\\n\\t\\t\\tcondProb_cbar.put(term, (nct_cbar + 1) / (double) ((n - nc) + 2));\\n\\t\\t}\\n\\n\\t\\t// ---APPLY BERNOULLI----\\n\\n\\t\\tMap<Integer, Boolean> marked = new HashMap<Integer, Boolean>();\\n\\t\\tfor (Integer id : testSet) {\\n\\t\\t\\tdouble score_c = Math.log(prior_c);\\n\\t\\t\\tdouble score_cbar = Math.log(prior_cbar);\\n\\t\\t\\tfor (String term : features) {\\n\\t\\t\\t\\tSet<Integer> postings = terms.get(term).getPostings().keySet();\\n\\t\\t\\t\\tif (postings.contains(id)) {\\n\\t\\t\\t\\t\\tscore_c += Math.log(condProb_c.get(term));\\n\\t\\t\\t\\t\\tscore_cbar += Math.log(condProb_cbar.get(term));\\n\\t\\t\\t\\t} else {\\n\\t\\t\\t\\t\\tscore_c += Math.log(1 - condProb_c.get(term));\\n\\t\\t\\t\\t\\tscore_cbar += Math.log(1 - condProb_cbar.get(term));\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t\\tif (score_c > score_cbar)\\n\\t\\t\\t\\tmarked.put(id, true);\\n\\t\\t\\telse\\n\\t\\t\\t\\tmarked.put(id, false);\\n\\t\\t}\\n\\t\\treturn marked;\\n\\t}\",\n \"public Object eval(Individual ind)\\r\\n {\\r\\n BinaryIndividual bi = (BinaryIndividual)ind;\\r\\n int partialFitness = 0;\\r\\n int distance = 0;\\r\\n double fitness = 0.0;\\r\\n\\r\\n\\t for (int i=0; i<100; i++){\\r\\n\\r\\n\\t distance = 0;\\r\\n\\r\\n\\t for (int j=0; j<100; j++){\\r\\n\\t if (!((BinaryIndividual)target[i]).getBooleanAllele(j)^bi.getBooleanAllele(j)) { \\r\\n\\t\\t distance++;\\r\\n\\t }\\r\\n \\r\\n\\t if (distance > partialFitness) {\\r\\n\\t partialFitness = distance;\\r\\n\\t }\\r\\n\\t }\\r\\n }\\r\\n\\r\\n fitness = (double)partialFitness/100.0;\\r\\n return new Double(fitness);\\r\\n \\r\\n\\r\\n }\",\n \"private static List<SearchData> booleanSearchFrequency(Query query, Indexer si) {\\n Tokenizer tkn = new SimpleTokenizer();\\n tkn.tokenize(query.getStr(), \\\"[a-zA-Z]{3,}\\\", true, true);\\n List<SearchData> searchList = new ArrayList<>();\\n LinkedList<Token> wordsList = tkn.getTokens();\\n Iterator<Token> wordsIt = wordsList.iterator();\\n HashMap<String, LinkedList<Posting>> indexer = si.getIndexer();\\n int idx;\\n SearchData searched_doc;\\n\\n while (wordsIt.hasNext()) {\\n String word = wordsIt.next().getSequence();\\n if (indexer.containsKey(word)) {\\n\\n LinkedList<Posting> posting = indexer.get(word);\\n\\n for (Posting pst : posting) {\\n\\n SearchData sd = new SearchData(query, pst.getDocId());\\n\\n if (!searchList.contains(sd)) {\\n sd.setScore(pst.getTermFreq());\\n searchList.add(sd);\\n } else {\\n idx = searchList.indexOf(sd);\\n searched_doc = searchList.get(idx);\\n searched_doc.setScore(searched_doc.getScore() + pst.getTermFreq());\\n }\\n }\\n }\\n }\\n\\n Collections.sort(searchList);\\n\\n return searchList;\\n }\",\n \"public int getIDFScore(String term) { \\r\\n\\t\\tif (map.containsKey(term) == false)\\r\\n\\t\\t\\treturn 0;\\r\\n\\t\\treturn map.get(term).size();\\r\\n\\t}\",\n \"public interface Term {\\n\\t\\n\\t/**\\n\\t * Get the coefficient of a term\\n\\t * @return the coefficient \\n\\t */\\n\\tpublic double getCoefficient();\\n\\t\\n\\t/**\\n\\t * Get the exponent of a term\\n\\t * @return the exponent\\n\\t */\\n\\tpublic int getExponent();\\n\\t\\n\\t/**\\n\\t * Evaluate a term by a given value. c = constant, a(c)^n \\n\\t * @param x The value to be evaluated \\n\\t * @return The result of the evaluated term \\n\\t */\\n\\tpublic double evaluate(double x);\\n\\t\\n}\",\n \"public void setTerm(java.lang.Integer value) {\\n this.term = value;\\n }\",\n \"public double idfCalculator(String targetWord, List<List<String>> tokenizedDescriptionCollection) {\\n // indicator if the List<String> uniqueWordCollection contains the String targetWord\\n // indicator can only be 1 or 0\\n // 1: indicates List<String> uniqueWordCollection contains the target word\\n // 0: indicates List<String> uniqueWordCollection does not contain the target word\\n double totalCount = 0.0;\\n for (List<String> uniqueWordCollection : tokenizedDescriptionCollection) {\\n double indicator = 0.0;\\n for (String word : uniqueWordCollection) {\\n if (word.equals(targetWord)) {\\n indicator++;\\n break; // break statement is needed since indicator is either 0 or 1\\n }\\n }\\n totalCount += indicator;\\n }\\n return Math.log10( (1 + tokenizedDescriptionCollection.size()) / (1 + totalCount) ) + 1;\\n }\",\n \"public static void main(String[] args) throws Exception \\n\\t{\\n\\t\\tList<String> stopWords = new ArrayList<String>();\\n\\t\\tstopWords = stopWordsCreation();\\n\\n\\n\\t\\t\\n\\t\\tHashMap<Integer, String> hmap = new HashMap<Integer, String>();\\t//Used in tittle, all terms are unique, and any dups become \\\" \\\"\\n\\t\\n\\t\\t\\n\\t\\tList<String> uniqueTerms = new ArrayList<String>();\\n\\t\\tList<String> allTerms = new ArrayList<String>();\\n\\t\\t\\t\\t\\n\\t\\t\\n\\t\\tHashMap<Integer, String> hmap2 = new HashMap<Integer, String>();\\n\\t\\tHashMap<Integer, String> allValues = new HashMap<Integer, String>();\\n\\t\\tHashMap<Integer, Double> docNorms = new HashMap<Integer, Double>();\\n\\t\\t\\n\\t\\t\\n\\t\\t\\n\\t\\t\\n\\t\\tMap<Integer, List<String>> postingsFileListAllWords = new HashMap<>();\\t\\t\\n\\t\\tMap<Integer, List<String>> postingsFileList = new HashMap<>();\\n\\t\\t\\n\\t\\tMap<Integer, List<StringBuilder>> docAndTitles = new HashMap<>();\\n\\t\\tMap<Integer, List<StringBuilder>> docAndAbstract = new HashMap<>();\\n\\t\\tMap<Integer, List<StringBuilder>> docAndAuthors = new HashMap<>();\\n\\t\\t\\n\\t\\t\\n\\t\\tMap<Integer, List<Double>> termWeights = new HashMap<>();\\n\\t\\t\\n\\t\\tList<Integer> docTermCountList = new ArrayList<Integer>();\\n\\t\\t\\n\\t\\tBufferedReader br = null;\\n\\t\\tFileReader fr = null;\\n\\t\\tString sCurrentLine;\\n\\n\\t\\tint documentCount = 0;\\n\\t\\tint documentFound = 0;\\n\\t\\tint articleNew = 0;\\n\\t\\tint docTermCount = 0;\\n\\t\\t\\n\\t\\t\\n\\t\\tboolean abstractReached = false;\\n\\n\\t\\ttry {\\n\\t\\t\\tfr = new FileReader(FILENAME);\\n\\t\\t\\tbr = new BufferedReader(fr);\\n\\n\\t\\t\\t// Continues to get 1 line from document until it reaches the end of EVERY doc\\n\\t\\t\\twhile ((sCurrentLine = br.readLine()) != null) \\n\\t\\t\\t{\\n\\t\\t\\t\\t// sCurrentLine now contains the 1 line from the document\\n\\n\\t\\t\\t\\t// Take line and split each word and place them into array\\n\\t\\t\\t\\tString[] arr = sCurrentLine.split(\\\" \\\");\\n\\n\\n\\t\\t\\t\\t//Go through the entire array\\n\\t\\t\\t\\tfor (String ss : arr) \\n\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t/*\\n\\t\\t\\t\\t\\t * This section takes the array and checks to see if it has reached a new\\n\\t\\t\\t\\t\\t * document or not. If the current line begins with an .I, then it knows that a\\n\\t\\t\\t\\t\\t * document has just started. If it incounters another .I, then it knows that a\\n\\t\\t\\t\\t\\t * new document has started.\\n\\t\\t\\t\\t\\t */\\n\\t\\t\\t\\t\\t//System.out.println(\\\"Before anything: \\\"+sCurrentLine);\\n\\t\\t\\t\\t\\tif (arr[0].equals(\\\".I\\\")) \\n\\t\\t\\t\\t\\t{\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\tif (articleNew == 0) \\n\\t\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\t\\tarticleNew = 1;\\n\\t\\t\\t\\t\\t\\t\\tdocumentFound = Integer.parseInt(arr[1]);\\n\\t\\t\\t\\t\\t\\t} \\n\\t\\t\\t\\t\\t\\telse if (articleNew == 1) \\n\\t\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\t\\tarticleNew = 0;\\n\\t\\t\\t\\t\\t\\t\\tdocumentFound = Integer.parseInt(arr[1]);\\n\\t\\t\\t\\t\\t\\t}\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t//System.out.println(documentFound);\\n\\t\\t\\t\\t\\t\\t//count++;\\n\\t\\t\\t\\t\\t\\tbreak;\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t/* This section detects that after a document has entered,\\n\\t\\t\\t\\t\\t * it has to gather all the words contained in the title \\n\\t\\t\\t\\t\\t * section.\\n\\t\\t\\t\\t\\t */\\n\\t\\t\\t\\t\\tif (arr[0].equals(\\\".T\\\") ) \\n\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t// Go to line UNDER .T since that is where tittle is located\\n\\t\\t\\t\\t\\t\\t//sCurrentLine = br.readLine();\\n\\t\\t\\t\\t\\t\\tdocAndTitles.put(documentFound, new ArrayList<StringBuilder>());\\n\\t\\t\\t\\t\\t\\t//System.out.println(\\\"docAndTitles.get(documentCount+1): \\\" +docAndTitles.get(documentFound));\\n\\t\\t\\t\\t\\t\\t//System.out.println(\\\"Docs and titles: \\\"+docAndTitles);\\n\\t\\t\\t\\t\\t\\tStringBuilder title = new StringBuilder();\\n\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\twhile ( !(sCurrentLine = br.readLine()).matches(\\\".B|.A|.N|.X|.K|.C\\\") )\\n\\t\\t\\t\\t\\t\\t{\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t/* In this section, there are 2 lists being made. One list\\n\\t\\t\\t\\t\\t\\t\\t * is for all the unique words in every title in the document (hmap).\\n\\t\\t\\t\\t\\t\\t\\t * Hmap contains all unique words, and anytime a duplicate word is \\n\\t\\t\\t\\t\\t\\t\\t * found, it is replaced with an empty space in the map.\\n\\t\\t\\t\\t\\t\\t\\t * All Values \\n\\t\\t\\t\\t\\t\\t\\t * \\n\\t\\t\\t\\t\\t\\t\\t */\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t//postingsFileList.put(documentFound - 1, new ArrayList<String>());\\n\\t\\t\\t\\t\\t\\t\\t//postingsFileList.get(documentFound - 1).add(term2);\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t//System.out.println(\\\"current line: \\\"+sCurrentLine);\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\tString[] tittle = sCurrentLine.split(\\\" \\\");\\n\\t\\t\\t\\t\\t\\t\\tif (tittle[0].equals(\\\".W\\\") )\\n\\t\\t\\t\\t\\t\\t\\t{\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\tabstractReached = true;\\n\\t\\t\\t\\t\\t\\t\\t\\tbreak;\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\ttitle.append(sCurrentLine);\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\tfor (String tittleWords : tittle)\\n\\t\\t\\t\\t\\t\\t\\t{\\t\\n\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\ttittleWords = tittleWords.toLowerCase();\\n\\t\\t\\t\\t\\t\\t\\t\\ttittleWords = tittleWords.replaceAll(\\\"[-&^%'{}*|$+\\\\\\\\/\\\\\\\\?!<>=.,;_:()\\\\\\\\[\\\\\\\\]\\\\\\\"\\\\\\\\d]\\\", \\\"\\\");\\n\\t\\t\\t\\t\\t\\t\\t\\ttittleWords = tittleWords.replaceAll(\\\"[-&^%'*{}|$+\\\\\\\\/\\\\\\\\?!<>=.,;_:()\\\\\\\\[\\\\\\\\]\\\\\\\"\\\\\\\\d]\\\", \\\"\\\");\\n\\t\\t\\t\\t\\t\\t\\t\\ttittleWords = tittleWords.replaceAll(\\\"[-&^%'{}*|$+\\\\\\\\/\\\\\\\\?!<>=.,;_:()\\\\\\\\[\\\\\\\\]\\\\\\\"\\\\\\\\d]\\\", \\\"\\\");\\n\\t\\t\\t\\t\\t\\t\\t\\t//System.out.println(tittleWords);\\n\\t\\t\\t\\t\\t\\t\\t\\tif (hmap.containsValue(tittleWords)) \\n\\t\\t\\t\\t\\t\\t\\t\\t{\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\t\\thmap.put(documentCount, \\\" \\\");\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tallValues.put(documentCount, tittleWords);\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tallTerms.add(tittleWords);\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tdocumentCount++;\\n\\t\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\t\\telse \\n\\t\\t\\t\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tallTerms.add(tittleWords);\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tallValues.put(documentCount, tittleWords);\\n\\t\\t\\t\\t\\t\\t\\t\\t\\thmap.put(documentCount, tittleWords);\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tif (!(uniqueTerms.contains(tittleWords)))\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tif ((stopWordsSetting && !(stopWords.contains(tittleWords))))\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tuniqueTerms.add(tittleWords);\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tdocumentCount++;\\n\\t\\t\\t\\t\\t\\t\\t\\t}\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\t//docAndTitles.get(documentCount).add(\\\" \\\");\\n\\t\\t\\t\\t\\t\\t\\ttitle.append(\\\"\\\\n\\\");\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t//System.out.println(\\\"Title: \\\"+title);\\n\\t\\t\\t\\t\\t\\t//System.out.println(\\\"docAndTitles.get(documentCount+1): \\\" +docAndTitles.get(documentFound));\\n\\t\\t\\t\\t\\t\\tdocAndTitles.get(documentFound).add(title);\\n\\t\\t\\t\\t\\t\\t//System.out.println(\\\"Done!: \\\"+ docAndTitles);\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\tif (arr[0].equals(\\\".A\\\") ) \\n\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t// Go to line UNDER .T since that is where tittle is located\\n\\t\\t\\t\\t\\t\\t//sCurrentLine = br.readLine();\\n\\t\\t\\t\\t\\t\\tdocAndAuthors.put(documentFound, new ArrayList<StringBuilder>());\\n\\t\\t\\t\\t\\t\\t//System.out.println(\\\"docAndTitles.get(documentCount+1): \\\" +docAndTitles.get(documentFound));\\n\\t\\t\\t\\t\\t\\t//System.out.println(\\\"Docs and titles: \\\"+docAndTitles);\\n\\t\\t\\t\\t\\t\\tStringBuilder author = new StringBuilder();\\n\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\twhile ( !(sCurrentLine = br.readLine()).matches(\\\".N|.X|.K|.C\\\") )\\n\\t\\t\\t\\t\\t\\t{\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t/* In this section, there are 2 lists being made. One list\\n\\t\\t\\t\\t\\t\\t\\t * is for all the unique words in every title in the document (hmap).\\n\\t\\t\\t\\t\\t\\t\\t * Hmap contains all unique words, and anytime a duplicate word is \\n\\t\\t\\t\\t\\t\\t\\t * found, it is replaced with an empty space in the map.\\n\\t\\t\\t\\t\\t\\t\\t * All Values \\n\\t\\t\\t\\t\\t\\t\\t * \\n\\t\\t\\t\\t\\t\\t\\t */\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t//postingsFileList.put(documentFound - 1, new ArrayList<String>());\\n\\t\\t\\t\\t\\t\\t\\t//postingsFileList.get(documentFound - 1).add(term2);\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t//System.out.println(\\\"current line: \\\"+sCurrentLine);\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\tString[] tittle = sCurrentLine.split(\\\" \\\");\\n\\t\\t\\t\\t\\t\\t\\tif (tittle[0].equals(\\\".W\\\") )\\n\\t\\t\\t\\t\\t\\t\\t{\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\tabstractReached = true;\\n\\t\\t\\t\\t\\t\\t\\t\\tbreak;\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\tauthor.append(sCurrentLine);\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t//docAndTitles.get(documentCount).add(\\\" \\\");\\n\\t\\t\\t\\t\\t\\t\\tauthor.append(\\\"\\\\n\\\");\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t//System.out.println(\\\"Title: \\\"+title);\\n\\t\\t\\t\\t\\t\\t//System.out.println(\\\"docAndTitles.get(documentCount+1): \\\" +docAndTitles.get(documentFound));\\n\\t\\t\\t\\t\\t\\tdocAndAuthors.get(documentFound).add(author);\\n\\t\\t\\t\\t\\t\\t//System.out.println(\\\"Done!: \\\"+ docAndTitles);\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t/* Since there may or may not be an asbtract after\\n\\t\\t\\t\\t\\t * the title, we need to check what the next section\\n\\t\\t\\t\\t\\t * is. We know that every doc has a publication date,\\n\\t\\t\\t\\t\\t * so it can end there, but if there is no abstract,\\n\\t\\t\\t\\t\\t * then it will keep scanning until it reaches the publication\\n\\t\\t\\t\\t\\t * date. If abstract is empty (in tests), it will also finish instantly\\n\\t\\t\\t\\t\\t * since it's blank and goes straight to .B (the publishing date).\\n\\t\\t\\t\\t\\t * Works EXACTLY like Title \\t\\t \\n\\t\\t\\t\\t\\t */\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\tif (abstractReached) \\n\\t\\t\\t\\t\\t{\\t\\n\\t\\t\\t\\t\\t\\t//System.out.println(\\\"\\\\n\\\");\\n\\t\\t\\t\\t\\t\\t//System.out.println(\\\"REACHED ABSTRACT and current line is: \\\" +sCurrentLine);\\n\\t\\t\\t\\t\\t\\tdocAndAbstract.put(documentFound, new ArrayList<StringBuilder>());\\n\\t\\t\\t\\t\\t\\tStringBuilder totalAbstract = new StringBuilder();\\n\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\twhile ( !(sCurrentLine = br.readLine()).matches(\\\".T|.I|.A|.N|.X|.K|.C\\\") )\\n\\t\\t\\t\\t\\t\\t{\\t\\n\\t\\t\\t\\t\\t\\t\\tString[] abstaract = sCurrentLine.split(\\\" \\\");\\n\\t\\t\\t\\t\\t\\t\\tif (abstaract[0].equals(\\\".B\\\") )\\n\\t\\t\\t\\t\\t\\t\\t{\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\tabstractReached = false;\\n\\t\\t\\t\\t\\t\\t\\t\\tbreak;\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\ttotalAbstract.append(sCurrentLine);\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\tString[] misc = sCurrentLine.split(\\\" \\\");\\n\\t\\t\\t\\t\\t\\t\\tfor (String miscWords : misc) \\n\\t\\t\\t\\t\\t\\t\\t{\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\tmiscWords = miscWords.toLowerCase(); \\n\\t\\t\\t\\t\\t\\t\\t\\tmiscWords = miscWords.replaceAll(\\\"[-&^%'*$+|{}?!\\\\\\\\/<\\\\\\\\>=.,;_:()\\\\\\\\[\\\\\\\\]\\\\\\\"\\\\\\\\d]\\\", \\\"\\\");\\n\\t\\t\\t\\t\\t\\t\\t\\tmiscWords = miscWords.replaceAll(\\\"[-&^%'*$+|?{}!\\\\\\\\/<\\\\\\\\>=.,;_:()\\\\\\\\[\\\\\\\\]\\\\\\\"\\\\\\\\d]\\\", \\\"\\\");\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\tmiscWords = miscWords.replaceAll(\\\"[-&^%'*$+|{}?!\\\\\\\\/<\\\\\\\\>=.,;_:()\\\\\\\\[\\\\\\\\]\\\\\\\"\\\\\\\\d]\\\", \\\"\\\");\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\t//System.out.println(miscWords);\\n\\t\\t\\t\\t\\t\\t\\t\\tif (hmap.containsValue(miscWords)) \\n\\t\\t\\t\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\t\\t\\t\\thmap.put(documentCount, \\\" \\\");\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tallValues.put(documentCount, miscWords);\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tallTerms.add(miscWords);\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tdocumentCount++;\\n\\t\\n\\t\\t\\t\\t\\t\\t\\t\\t} \\n\\t\\t\\t\\t\\t\\t\\t\\telse \\n\\t\\t\\t\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tallTerms.add(miscWords);\\n\\t\\t\\t\\t\\t\\t\\t\\t\\thmap.put(documentCount, miscWords);\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tallValues.put(documentCount, miscWords);\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tif (!(uniqueTerms.contains(miscWords)))\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tif ((stopWordsSetting && !(stopWords.contains(miscWords))))\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tuniqueTerms.add(miscWords);\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tdocumentCount++;\\n\\t\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\t}\\t\\n\\t\\t\\t\\t\\t\\t\\ttotalAbstract.append(\\\"\\\\n\\\");\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\tdocAndAbstract.get(documentFound).add(totalAbstract);\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t}\\t\\n\\t\\t\\t\\t\\n\\t\\t\\t\\t//Once article is found, we enter all of of it's title and abstract terms \\n\\t\\t\\t\\tif (articleNew == 0) \\n\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\tdocumentFound = documentFound - 1;\\n\\t\\t\\t\\t\\t//System.out.println(\\\"Words found in Doc: \\\" + documentFound);\\n\\t\\t\\t\\t\\t//System.out.println(\\\"Map is\\\" +allValues);\\n\\t\\t\\t\\t\\tSet set = hmap.entrySet();\\n\\t\\t\\t\\t\\tIterator iterator = set.iterator();\\n\\n\\t\\t\\t\\t\\tSet set2 = allValues.entrySet();\\n\\t\\t\\t\\t\\tIterator iterator2 = set2.iterator();\\n\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\tpostingsFileList.put(documentFound - 1, new ArrayList<String>());\\n\\t\\t\\t\\t\\tpostingsFileListAllWords.put(documentFound - 1, new ArrayList<String>());\\n\\t\\t\\t\\t\\twhile (iterator.hasNext()) {\\n\\t\\t\\t\\t\\t\\tMap.Entry mentry = (Map.Entry) iterator.next();\\n\\t\\t\\t\\t\\t\\t// (\\\"key is: \\\"+ mentry.getKey() + \\\" & Value is: \\\" + mentry.getValue());\\n\\t\\t\\t\\t\\t\\t// (\\\"Value is: \\\" + mentry.getValue());\\n\\t\\t\\t\\t\\t\\t// );\\n\\t\\t\\t\\t\\t\\tString term = mentry.getValue().toString();\\n\\t\\t\\t\\t\\t\\t// //\\\"This is going to be put in doc3: \\\"+ (documentFound-1));\\n\\t\\t\\t\\t\\t\\tpostingsFileList.get(documentFound - 1).add(term);\\n\\t\\t\\t\\t\\t\\t// if ( !((mentry.getValue()).equals(\\\" \\\")) )\\n\\t\\t\\t\\t\\t\\tdocTermCount++;\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t// \\\"BEFORE its put in, this is what it looks like\\\" + hmap);\\n\\t\\t\\t\\t\\thmap2.putAll(hmap);\\n\\t\\t\\t\\t\\thmap.clear();\\n\\t\\t\\t\\t\\tarticleNew = 1;\\n\\n\\t\\t\\t\\t\\tdocTermCountList.add(docTermCount);\\n\\t\\t\\t\\t\\tdocTermCount = 0;\\n\\n\\t\\t\\t\\t\\twhile (iterator2.hasNext()) {\\n\\t\\t\\t\\t\\t\\tMap.Entry mentry2 = (Map.Entry) iterator2.next();\\n\\t\\t\\t\\t\\t\\t// (\\\"key is: \\\"+ mentry.getKey() + \\\" & Value is: \\\" + mentry.getValue());\\n\\t\\t\\t\\t\\t\\t// (\\\"Value2 is: \\\" + mentry2.getValue());\\n\\t\\t\\t\\t\\t\\t// );\\n\\t\\t\\t\\t\\t\\tString term = mentry2.getValue().toString();\\n\\t\\t\\t\\t\\t\\t// //\\\"This is going to be put in doc3: \\\"+ (documentFound-1));\\n\\t\\t\\t\\t\\t\\tpostingsFileListAllWords.get(documentFound - 1).add(term);\\n\\t\\t\\t\\t\\t\\t// if ( !((mentry.getValue()).equals(\\\" \\\")) )\\n\\t\\t\\t\\t\\t\\t// docTermCount++;\\n\\t\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\t\\tallValues.clear();\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\tdocumentFound = Integer.parseInt(arr[1]);\\n\\n\\t\\t\\t\\t\\t// \\\"MEANWHILE THESE ARE ALL VALUES\\\" + postingsFileListAllWords);\\n\\n\\t\\t\\t\\t}\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t}\\n\\t\\t\\t\\n\\t\\t\\t\\n\\t\\t\\t\\n\\t\\t\\t//System.out.println(\\\"Looking at final doc!\\\");\\n\\t\\t\\t//Final loop for last sets\\n\\t\\t\\tSet set = hmap.entrySet();\\n\\t\\t\\tIterator iterator = set.iterator();\\n\\n\\t\\t\\tSet setA = allValues.entrySet();\\n\\t\\t\\tIterator iteratorA = setA.iterator();\\n\\t\\t\\tpostingsFileList.put(documentFound - 1, new ArrayList<String>());\\n\\t\\t\\tpostingsFileListAllWords.put(documentFound - 1, new ArrayList<String>());\\n\\t\\t\\twhile (iterator.hasNext()) {\\n\\t\\t\\t\\tMap.Entry mentry = (Map.Entry) iterator.next();\\n\\t\\t\\t\\t// (\\\"key is: \\\"+ mentry.getKey() + \\\" & Value is: \\\" + mentry.getValue());\\n\\t\\t\\t\\t// (\\\"Value is: \\\" + mentry.getValue());\\n\\t\\t\\t\\t// //);\\n\\t\\t\\t\\t// if ( !((mentry.getValue()).equals(\\\" \\\")) )\\n\\t\\t\\t\\tString term2 = mentry.getValue().toString();\\n\\t\\t\\t\\tpostingsFileList.get(documentFound - 1).add(term2);\\n\\n\\t\\t\\t\\tdocTermCount++;\\n\\t\\t\\t}\\n\\t\\t\\t//System.out.println(\\\"Done looking at final doc!\\\");\\n\\t\\t\\t\\n\\t\\t\\t\\n\\t\\t\\t//System.out.println(\\\"Sorting time!\\\");\\n\\t\\t\\twhile (iteratorA.hasNext()) {\\n\\t\\t\\t\\tMap.Entry mentry2 = (Map.Entry) iteratorA.next();\\n\\t\\t\\t\\t// (\\\"key is: \\\"+ mentry.getKey() + \\\" & Value is: \\\" + mentry.getValue());\\n\\t\\t\\t\\t// (\\\"Value2 is: \\\" + mentry2.getValue());\\n\\t\\t\\t\\t// //);\\n\\t\\t\\t\\tString term = mentry2.getValue().toString();\\n\\t\\t\\t\\t// //\\\"This is going to be put in doc3: \\\"+ (documentFound-1));\\n\\t\\t\\t\\tpostingsFileListAllWords.get(documentFound - 1).add(term);\\n\\t\\t\\t\\t// if ( !((mentry.getValue()).equals(\\\" \\\")) )\\n\\t\\t\\t\\t// docTermCount++;\\n\\t\\t\\t}\\n\\n\\t\\t\\thmap2.putAll(hmap);\\n\\t\\t\\thmap.clear();\\n\\t\\t\\tdocTermCountList.add(docTermCount);\\n\\t\\t\\tdocTermCount = 0;\\n\\n\\n\\t\\t\\t\\n\\t\\t\\n\\t\\t\\t// END OF LOOKING AT ALL DOCS\\n\\t\\t\\t\\n\\t\\t\\t//System.out.println(\\\"Docs and titles: \\\"+docAndTitles);\\n\\t\\t\\t\\n\\t\\t\\t//System.out.println(\\\"All terms\\\" +allTerms);\\n\\t\\t\\tString[] sortedArray = allTerms.toArray(new String[0]);\\n\\t\\t\\tString[] sortedArrayUnique = uniqueTerms.toArray(new String[0]);\\n\\t\\t\\t//System.out.println(Arrays.toString(sortedArray));\\n\\t\\t\\t\\n\\t\\t\\tArrays.sort(sortedArray);\\n\\t\\t\\tArrays.sort(sortedArrayUnique);\\n\\t\\t\\t\\n\\t\\t\\t\\n\\t\\t\\t\\n\\t\\t\\t//Sortings \\n\\t\\t\\tSet set3 = hmap2.entrySet();\\n\\t\\t\\tIterator iterator3 = set3.iterator();\\n\\n\\t\\t\\t// Sorting the map\\n\\t\\t\\t//System.out.println(\\\"Before sorting \\\" +hmap2);\\t\\t\\t\\n\\t\\t\\tMap<Integer, String> map = sortByValues(hmap2);\\n\\t\\t\\t//System.out.println(\\\"after sorting \\\" +map);\\n\\t\\t\\t// //\\\"After Sorting:\\\");\\n\\t\\t\\tSet set2 = map.entrySet();\\n\\t\\t\\tIterator iterator2 = set2.iterator();\\n\\t\\t\\tint docCount = 1;\\n\\t\\t\\twhile (iterator2.hasNext()) {\\n\\t\\t\\t\\tMap.Entry me2 = (Map.Entry) iterator2.next();\\n\\t\\t\\t\\t// (me2.getKey() + \\\": \\\");\\n\\t\\t\\t\\t// //me2.getValue());\\n\\t\\t\\t}\\n\\t\\t\\t\\n\\t\\t\\t//System.out.println(\\\"Done sorting!\\\");\\n\\t\\t\\n\\t\\t\\t\\n\\t\\t\\t\\n\\t\\t\\t\\n\\t\\t\\t//System.out.println(\\\"Posting starts \\\");\\n\\t\\t\\t//\\\"THIS IS START OF DICTIONARTY\\\" \\n\\t\\t\\tBufferedWriter bw = null;\\n\\t\\t\\tFileWriter fw = null;\\n\\t\\t\\t\\n\\t\\t\\t\\n\\t\\t\\t//System.out.println(\\\"Start making an array thats big as every doc total \\\");\\n\\t\\t\\tfor (int z = 1; z < documentFound+1; z++)\\n\\t\\t\\t{\\n\\t\\t\\t\\ttermWeights.put(z, new ArrayList<Double>());\\n\\t\\t\\t}\\n\\t\\t\\t//System.out.println(\\\"Done making that large array Doc \\\");\\n\\t\\t\\t\\n\\t\\t\\t//System.out.println(\\\"Current Weights: \\\"+termWeights);\\n\\t\\t\\t\\n\\t\\t\\t//System.out.println(\\\"All terms\\\" +allTerms)\\n\\t\\t\\t//System.out.println(Arrays.toString(sortedArray));\\n\\t\\t\\t//System.out.println(Arrays.toString(sortedArrayUnique));\\n\\t\\t\\t//System.out.println(uniqueTerms);\\n\\t\\t\\t\\n\\t\\t\\t\\n\\t\\t\\t\\n\\t\\t\\t//\\tSystem.out.println(\\\"Posting starts \\\");\\n\\t\\t\\t// \\tPOSTING FILE STARTS \\n\\t\\t\\ttry {\\n\\t\\t\\t\\t// Posting File\\n\\t\\t\\t\\t//System.out.println(\\\"postingsFileListAllWords: \\\"+postingsFileListAllWords); //Contains every word including Dups, seperated per doc\\n\\t\\t\\t\\t//System.out.println(\\\"postingsFileList: \\\"+postingsFileList); \\t\\t //Contains unique words, dups are \\\" \\\", seperated per doc\\n\\t\\t\\t\\t//System.out.println(\\\"postingsFileListAllWords.size(): \\\" +postingsFileListAllWords.size()); //Total # of docs \\n\\t\\t\\t\\t//System.out.println(\\\"Array size: \\\"+sortedArrayUnique.length);\\n\\n\\t\\t\\t\\tfw = new FileWriter(POSTING);\\n\\t\\t\\t\\tbw = new BufferedWriter(fw);\\n\\t\\t\\t\\tString temp = \\\" \\\";\\n\\t\\t\\t\\tDouble termFreq = 0.0;\\n\\t\\t\\t\\t// //postingsFileListAllWords);\\n\\t\\t\\t\\tList<String> finalTermList = new ArrayList<String>();\\n\\t\\t\\t\\t\\n\\t\\t\\t\\t\\n\\t\\t\\t\\n\\t\\t\\t\\t\\t// //postingsFileList.get(i).size());\\n\\t\\t\\t\\t\\tfor (int j = 0; j < sortedArrayUnique.length; ++j)\\t\\t\\t\\t\\t // go thru each word, CURRENT TERM\\n\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\t//System.out.println(\\\"Term is: \\\" + sortedArrayUnique[j]);\\n\\t\\t\\t\\t\\t\\ttemp = sortedArrayUnique[j];\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\tif ((stopWordsSetting && stopWords.contains(temp))) \\n\\t\\t\\t\\t\\t\\t{\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\tcontinue;\\n\\t\\t\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\t\\t\\tif (!(finalTermList.contains(temp))) \\n\\t\\t\\t\\t\\t\\t{\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t//PART TO FIND DOCUMENT FREQ\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\tint docCountIDF = 0;\\n\\t\\t\\t\\t\\t\\t\\t//Start here for dictionary \\n\\t\\t\\t\\t\\t\\t\\tfor (int totalWords = 0; totalWords < sortedArray.length; totalWords++) \\t\\t\\n\\t\\t\\t\\t\\t\\t\\t{\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\tif (temp.compareTo(\\\" \\\") == 0 || (stopWordsSetting && stopWords.contains(temp))) \\n\\t\\t\\t\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t//EITHER BLANK OR STOPWORD \\n\\t\\t\\t\\t\\t\\t\\t\\t\\t//System.out.println(\\\"fOUND STOP WORD\\\");\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tcontinue;\\n\\t\\t\\t\\t\\t\\t\\t\\t}\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tString temp2 = sortedArray[totalWords];\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t//System.out.println(\\\"Compare: \\\"+temp+ \\\" with \\\" +temp2);\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tif (temp.compareTo(temp2) == 0) {\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t// (temp2+\\\" \\\");\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tdocCountIDF++;\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\t//System.out.println(\\\"Total Number: \\\" +docCountIDF);\\n\\t\\t\\t\\t\\t\\t\\t//System.out.println(\\\"documentFound: \\\" +documentFound);\\n\\t\\t\\t\\t\\t\\t\\t//System.out.println(\\\"So its \\\" + documentFound + \\\" dividied by \\\" +docCountIDF);\\n\\t\\t\\t\\t\\t\\t\\t//docCountIDF = 1;\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\tdouble idf = (Math.log10(((double)documentFound/(double)docCountIDF)));\\n\\t\\t\\t\\t\\t\\t\\t//System.out.println(\\\"Calculated IDF: \\\"+idf);\\n\\t\\t\\t\\t\\t\\t\\tif (idf < 0.0)\\n\\t\\t\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\t\\t\\tidf = 0.0;\\n\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\t//System.out.println(\\\"IDF is: \\\" +idf);\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t//System.out.println(\\\"Size of doc words: \\\" + postingsFileListAllWords.size());\\n\\t\\t\\t\\t\\t\\t\\tfor (int k = 0; k < postingsFileListAllWords.size(); k++) \\t\\t//Go thru each doc. Since only looking at 1 term, it does it once per doc\\n\\t\\t\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\t\\t\\t//System.out.println(\\\"Current Doc: \\\" +(k+1));\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\t\\ttermFreq = 1 + (Math.log10(Collections.frequency(postingsFileListAllWords.get(k), temp)));\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t//System.out.println(\\\"Freq is: \\\" +Collections.frequency(postingsFileListAllWords.get(k), temp));\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t//System.out.println(termFreq + \\\": \\\" + termFreq.isInfinite());\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tif (termFreq.isInfinite() || termFreq <= 0)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\ttermFreq = 0.0;\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t}\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t//System.out.println(\\\"termFreq :\\\" +termFreq); \\n\\t\\t\\t\\t\\t\\t\\t\\t\\t//System.out.println(\\\"idf: \\\" +idf);\\n\\t\\t\\t\\t\\t\\t\\t\\t\\ttermWeights.get(k+1).add( (idf*termFreq) );\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t//System.out.println(\\\"\\\");\\n\\t\\t\\t\\t\\t\\t\\tfinalTermList.add(temp);\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t}\\t\\n\\t\\t\\t\\t\\t\\t//System.out.println(\\\"Current Weights: \\\"+termWeights);\\n\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t//FINALCOUNTER\\n\\t\\t\\t\\t\\t\\t//System.out.println(\\\"Done looking at word: \\\" +j);\\n\\t\\t\\t\\t\\t\\t//System.out.println(\\\"\\\");\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t//System.out.println(\\\"Current Weights: \\\"+termWeights);\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\twhile (true)\\n\\t\\t\\t\\t {\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\tSystem.out.println(\\\"Enter a query: \\\");\\n\\t\\t\\t\\t\\t\\n\\t \\tScanner scanner = new Scanner(System.in);\\n\\t \\tString enterQuery = scanner.nextLine();\\n\\t \\t\\n\\t \\t\\n\\t\\t\\t\\t\\tList<Double> queryWeights = new ArrayList<Double>();\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t// Query turn\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\tenterQuery = enterQuery.toLowerCase();\\t\\t\\n\\t\\t\\t\\t\\tenterQuery = enterQuery.replaceAll(\\\"[-&^%'*$+|{}?!\\\\\\\\/<\\\\\\\\>=.,;_:()\\\\\\\\[\\\\\\\\]\\\\\\\"]\\\", \\\"\\\");\\n\\t\\t\\t\\t\\t//System.out.println(\\\"Query is: \\\" + enterQuery);\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\tif (enterQuery.equals(\\\"exit\\\"))\\n\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\tbreak;\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\tString[] queryArray = enterQuery.split(\\\" \\\");\\n\\t\\t\\t\\t\\tArrays.sort(queryArray);\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t//Find the query weights for each term in vocab\\n\\t\\t\\t\\t\\tfor (int j = 0; j < sortedArrayUnique.length; ++j)\\t\\t\\t\\t\\t // go thru each word, CURRENT TERM\\n\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\t//System.out.println(\\\"Term is: \\\" + sortedArrayUnique[j]);\\n\\t\\t\\t\\t\\t\\ttemp = sortedArrayUnique[j];\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\tif ((stopWordsSetting && stopWords.contains(temp))) \\n\\t\\t\\t\\t\\t\\t{\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\tcontinue;\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\tint docCountDF = 0;\\n\\t\\t\\t\\t\\t\\t//Start here for dictionary \\n\\t\\t\\t\\t\\t\\tfor (int totalWords = 0; totalWords < queryArray.length; totalWords++) \\t\\t\\n\\t\\t\\t\\t\\t\\t{\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\tif (temp.compareTo(\\\" \\\") == 0 || (stopWordsSetting && stopWords.contains(temp))) \\n\\t\\t\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\t\\t\\t//EITHER BLANK OR STOPWORD\\n\\t\\t\\t\\t\\t\\t\\t\\tcontinue;\\n\\t\\t\\t\\t\\t\\t\\t}\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\tString temp2 = queryArray[totalWords];\\n\\t\\t\\t\\t\\t\\t\\t\\t//System.out.println(\\\"Compare: \\\"+temp+ \\\" with \\\" +temp2);\\n\\t\\t\\t\\t\\t\\t\\t\\tif (temp.compareTo(temp2) == 0) {\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t// (temp2+\\\" \\\");\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tdocCountDF++;\\n\\t\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\tDouble queryWeight = 1 + (Math.log10(docCountDF));\\n\\t\\t\\t\\t\\t\\tif (queryWeight.isInfinite())\\n\\t\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\t\\tqueryWeight = 0.0;\\n\\t\\t\\t\\t\\t\\t}\\t\\t\\n\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\tqueryWeights.add(queryWeight);\\n\\t\\t\\t\\t\\t}\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t//System.out.println(\\\"Query WEights is: \\\"+queryWeights);\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t// Finding the norms for DOCS\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\tfor (int norms = 1; norms < documentFound+1; norms++)\\n\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\tdouble currentTotal = 0.0;\\n\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\tfor (int weightsPerDoc = 0; weightsPerDoc < termWeights.get(norms).size(); weightsPerDoc++)\\n\\t\\t\\t\\t\\t\\t{\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\tdouble square = Math.pow(termWeights.get(norms).get(weightsPerDoc), 2);\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t//System.out.println(\\\"Current square: \\\" + termWeights.get(norms).get(weightsPerDoc));\\n\\t\\t\\t\\t\\t\\t\\tcurrentTotal = currentTotal + square;\\n\\t\\t\\t\\t\\t\\t\\t//System.out.println(\\\"Current total: \\\" + currentTotal);\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t//System.out.println(\\\"About to square root this: \\\" +currentTotal);\\n\\t\\t\\t\\t\\t\\tdouble root = Math.sqrt(currentTotal);\\n\\t\\t\\t\\t\\t\\tdocNorms.put(norms, root);\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t//System.out.println(\\\"All of the docs norms: \\\"+docNorms);\\n\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t//Finding the norm for the query\\n\\t\\t\\t\\t\\tdouble currentTotal = 0.0;\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\tfor (int weightsPerDoc = 0; weightsPerDoc < queryWeights.size(); weightsPerDoc++)\\n\\t\\t\\t\\t\\t{\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\tdouble square = Math.pow(queryWeights.get(weightsPerDoc), 2);\\n\\t\\t\\t\\t\\t\\tcurrentTotal = currentTotal + square;\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\tdouble root = Math.sqrt(currentTotal);\\n\\t\\t\\t\\t\\tdouble queryNorm = root; \\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t//System.out.println(\\\"Query norm \\\" + queryNorm);\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t//Finding the cosine sim\\n\\t\\t\\t\\t\\t//System.out.println(\\\"Term Weights \\\" + termWeights);\\n\\t\\t\\t\\t\\tHashMap<Integer, Double> cosineScore = new HashMap<Integer, Double>();\\n\\t\\t\\t\\t\\tfor (int cosineSim = 1; cosineSim < documentFound+1; cosineSim++)\\n\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\tdouble total = 0.0;\\n\\t\\t\\t\\t\\t\\tfor (int docTerms = 0; docTerms < termWeights.get(cosineSim).size(); docTerms++)\\n\\t\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\tdouble docTermWeight = termWeights.get(cosineSim).get(docTerms);\\n\\t\\t\\t\\t\\t\\t\\tdouble queryTermWeight = queryWeights.get(docTerms);\\n\\t\\t\\t\\t\\t\\t\\t//System.out.println(\\\"queryTermWeight \\\" + queryTermWeight);\\n\\t\\t\\t\\t\\t\\t\\t//System.out.println(\\\"docTermWeight \\\" + docTermWeight);\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\ttotal = total + (docTermWeight*queryTermWeight);\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\tdouble cosineSimScore = 0.0;\\n\\t\\t\\t\\t\\t\\tif (!(total == 0.0 || (docNorms.get(cosineSim) * queryNorm) == 0))\\n\\t\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\t\\tcosineSimScore = total / (docNorms.get(cosineSim) * queryNorm);\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\telse\\n\\t\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\t\\tcosineSimScore = 0.0;\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\tcosineScore.put(cosineSim, cosineSimScore);\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\tcosineScore = sortByValues2(cosineScore);\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t//System.out.println(\\\"This is the cosineScores: \\\" +cosineScore);\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t//System.out.println(\\\"docAndTitles: \\\"+ docAndTitles);\\n\\t\\t\\t\\t\\tint topK = 0;\\n\\t\\t\\t\\t\\tint noValue = 0;\\n\\t\\t\\t\\t\\tfor (Integer name: cosineScore.keySet())\\n\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\tif (topK < 50)\\n\\t\\t\\t\\t\\t\\t{\\t\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t String key =name.toString();\\n\\t\\t\\t\\t //String value = cosineScore.get(name).toString(); \\n\\t\\t\\t\\t if (!(cosineScore.get(name) <= 0))\\n\\t\\t\\t\\t {\\n\\t\\t\\t\\t \\tSystem.out.println(\\\"Doc: \\\"+key);\\t\\t\\t\\t \\t\\t\\t\\t\\t \\t\\t\\t\\t\\t \\t\\n\\t\\t\\t\\t \\t\\n\\t\\t\\t\\t \\tStringBuilder builder = new StringBuilder();\\n\\t\\t\\t\\t \\tfor (StringBuilder value : docAndTitles.get(name)) {\\n\\t\\t\\t\\t \\t builder.append(value);\\n\\t\\t\\t\\t \\t}\\n\\t\\t\\t\\t \\tString text = builder.toString();\\t\\t\\t\\t \\t\\n\\t\\t\\t\\t \\t//System.out.println(\\\"Title:\\\\n\\\" +docAndTitles.get(name));\\n\\t\\t\\t\\t \\tSystem.out.println(\\\"Title: \\\" +text);\\n\\t\\t\\t\\t \\t\\n\\t\\t\\t\\t \\t\\n\\t\\t\\t\\t \\t\\n\\t\\t\\t\\t \\t\\n\\t\\t\\t\\t \\t\\n\\t\\t\\t\\t \\t//System.out.println(\\\"Authors:\\\\n\\\" +docAndAuthors.get(name));\\n\\t\\t\\t\\t \\t\\n\\t\\t\\t\\t \\tif (docAndAuthors.get(name) == null || docAndAuthors.get(name).toString().equals(\\\"\\\"))\\n\\t\\t\\t\\t \\t{\\n\\t\\t\\t\\t \\t\\tSystem.out.println(\\\"Authors: N\\\\\\\\A\\\\n\\\");\\n\\t\\t\\t\\t \\t}\\n\\t\\t\\t\\t \\telse \\n\\t\\t\\t\\t \\t{\\t\\t\\t\\t \\t\\t\\t\\t\\t\\t \\t\\n\\t\\t\\t\\t\\t \\tStringBuilder builder2 = new StringBuilder();\\n\\t\\t\\t\\t\\t \\tfor (StringBuilder value : docAndAuthors.get(name)) {\\n\\t\\t\\t\\t\\t \\t builder2.append(value);\\n\\t\\t\\t\\t\\t \\t}\\n\\t\\t\\t\\t\\t \\tString text2 = builder2.toString();\\t\\t\\t\\t \\t\\n\\t\\t\\t\\t\\t \\t\\n\\t\\t\\t\\t\\t \\tSystem.out.println(\\\"Authors found: \\\" +text2);\\n\\t\\t\\t\\t \\t}\\t\\n\\t\\t\\t\\t \\t\\n\\t\\t\\t\\t \\t\\n\\t\\t\\t\\t \\t/* ABSTRACT \\n\\t\\t\\t\\t \\tif (docAndAbstract.get(name) == null)\\n\\t\\t\\t\\t \\t{\\n\\t\\t\\t\\t \\t\\tSystem.out.println(\\\"Abstract: N\\\\\\\\A\\\\n\\\");\\n\\t\\t\\t\\t \\t}\\n\\t\\t\\t\\t \\telse \\n\\t\\t\\t\\t \\t{\\t\\t\\t\\t \\t\\t\\t\\t\\t\\t \\t\\n\\t\\t\\t\\t\\t \\tStringBuilder builder2 = new StringBuilder();\\n\\t\\t\\t\\t\\t \\tfor (StringBuilder value : docAndAbstract.get(name)) {\\n\\t\\t\\t\\t\\t \\t builder2.append(value);\\n\\t\\t\\t\\t\\t \\t}\\n\\t\\t\\t\\t\\t \\tString text2 = builder2.toString();\\t\\t\\t\\t \\t\\n\\t\\t\\t\\t\\t \\t\\n\\t\\t\\t\\t\\t \\tSystem.out.println(\\\"Abstract: \\\" +text2);\\n\\t\\t\\t\\t \\t}\\t\\n\\t\\t\\t\\t \\t*/\\n\\t\\t\\t\\t \\t\\n\\t\\t\\t\\t \\tSystem.out.println(\\\"\\\");\\n\\t\\t\\t\\t }\\n\\t\\t\\t\\t else {\\n\\t\\t\\t\\t \\tnoValue++;\\n\\t\\t\\t\\t }\\n\\t\\t\\t\\t topK++;\\n\\t\\t\\t\\t \\n\\t\\t\\t\\t\\t\\t}\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\tif (noValue == documentFound)\\n\\t\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\t\\tSystem.out.println(\\\"No documents contain query!\\\");\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t} \\n\\t\\t\\t\\t\\ttopK=0;\\n\\t\\t\\t\\t\\tnoValue = 0;\\n\\t\\t\\t\\t }\\n\\t\\t\\t\\t\\n\\t\\t\\t} finally {\\n\\t\\t\\t\\ttry {\\n\\t\\t\\t\\t\\tif (bw != null)\\n\\t\\t\\t\\t\\t\\tbw.close();\\n\\n\\t\\t\\t\\t\\tif (fw != null)\\n\\t\\t\\t\\t\\t\\tfw.close();\\n\\n\\t\\t\\t\\t} catch (IOException ex) {\\n\\n\\t\\t\\t\\t\\tex.printStackTrace();\\n\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t}\\n\\t\\t\\t\\n\\n\\t\\t} catch (IOException e) {\\n\\t\\t\\te.printStackTrace();\\n\\t\\t} finally {\\n\\t\\t\\ttry {\\n\\t\\t\\t\\tif (br != null)\\n\\t\\t\\t\\t\\tbr.close();\\n\\n\\t\\t\\t\\tif (fr != null)\\n\\t\\t\\t\\t\\tfr.close();\\n\\n\\t\\t\\t} catch (IOException ex) {\\n\\n\\t\\t\\t\\tex.printStackTrace();\\n\\n\\t\\t\\t}\\n\\n\\t\\t}\\n\\t\\t\\t\\n\\t\\t\\t\\n\\t\\t\\t\\n\\t\\t\\t\\n\\t\\t\\t\\n\\n\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\tint itemCount = uniqueTerms.size();\\n\\t\\t\\t//System.out.println(allValues);\\n\\t\\t\\tSystem.out.println(\\\"Total Terms BEFORE STEMING: \\\" +itemCount);\\n\\t\\t\\tSystem.out.println(\\\"Total Documents \\\" + documentFound);\\n\\t\\t\\t\\t\\t\\t\\n\\t\\t \\n\\t\\t\\t \\n\\t\\t\\t \\n\\t\\t\\t//END OF MAIN\\n\\t\\t}\",\n \"private int disjunctMatch( int ix0, int ix1 )\\n {\\n \\tint n = 0;\\n if( ix0 == ix1 ){\\n // TODO: complain, this should never happen.\\n return 0;\\n }\\n \\n if( ix0>ix1 ){\\n int h = ix0;\\n ix0 = ix1;\\n ix1 = h;\\n }\\n \\twhile( (ix0+n)<ix1 && (text[ix0+n] == text[ix1+n]) && (text[ix0+n] != STOP) ){\\n \\t n++;\\n \\t}\\n \\treturn n;\\n }\",\n \"private void countOnePseudoDoc(int docIdx) {\\n\\t\\tFeatureSequence fs = (FeatureSequence)documents.get(docIdx).getData();\\n\\t\\tint[] tokens = fs.getFeatures();\\n\\t\\tdouble[] tmpCounts = new double[numOfTerms];\\n\\t\\tArrays.fill(tmpCounts, 0);\\n\\t\\tfor(int i=0; i<tokens.length; i++) {\\n\\t\\t\\tint term = tokens[i];\\n\\t\\t\\ttmpCounts[term] += alpha * 1;\\n\\t\\t}\\n\\t\\t\\n\\t\\tPairedInfo pairedDocs = pairs.links.get(docIdx);\\n\\t\\tif(!pairedDocs.isEmpty()) {\\n//\\t\\t\\tSystem.out.println(docIdx + \\\":\\\" + Arrays.toString(tokens));\\n\\t\\t\\tint[] pIds = pairedDocs.getPairedIdsArray();\\n//\\t\\t\\tSystem.out.println(docIdx + \\\": \\\" + pairedDocs.getLength() + \\\":\\\" + Arrays.toString(pIds));\\n\\t\\t\\tdouble[] sims = pairedDocs.getPairedSimArray();\\n\\t\\t\\tsims = Util.reWeightVector(sims);\\n\\t\\t\\tfor(int p=0; p<pIds.length; p++) {\\n\\t\\t\\t\\tfs = (FeatureSequence)documents.get(p).getData();\\n\\t\\t\\t\\tint[] pTokens = fs.getFeatures();\\n\\t\\t\\t\\tfor(int i=0; i<pTokens.length; i++) {\\n\\t\\t\\t\\t\\tint term = pTokens[i];\\n\\t\\t\\t\\t\\ttmpCounts[term] += (1-alpha) * sims[p];\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\ttokens = ArrayUtils.append(tokens, fs.getFeatures());\\n\\t\\t\\t}\\n//\\t\\t\\tSystem.out.println(docIdx + \\\":\\\" + Arrays.toString(tokens));\\n\\t\\t}\\n\\t\\t\\n\\t\\tint termNum = MalletTfidf.distinctNumbers(tokens);\\n\\t\\tpseudoTermIndex[docIdx]= new int[termNum];\\n\\t\\tpseudoTf[docIdx] = new double[termNum];\\n\\t\\tint[] tmpTf = new int[termNum];\\n\\t\\tMalletTfidf.countTf(tokens, pseudoTermIndex[docIdx], tmpTf); // count the tf frequency\\n\\t\\tfor(int i=0; i<pseudoTermIndex[docIdx].length; i++) {\\n\\t\\t\\tint term = pseudoTermIndex[docIdx][i];\\n\\t\\t\\tpseudoTf[docIdx][i] = tmpCounts[term];\\n\\t\\t}\\n\\t\\tpseudoTermWeight[docIdx] = Util.reWeightVector(pseudoTf[docIdx]);\\n\\t}\",\n \"int countTypedFeatures();\",\n \"public java.lang.Integer getTerm() {\\n return term;\\n }\",\n \"public abstract double score(double tf, double docLength);\",\n \"boolean hasFixedHotwordGain();\",\n \"public static float[] getVector(\\n Map<String, Map<String, List<Integer>>> index,\\n List<String> allTerms,\\n Map<String, List<Integer>> docTerms,\\n int docCount) {\\n\\n float[] vector = new float[allTerms.size()];\\n\\n for (int i = 0; i < allTerms.size(); i++) {\\n String term = allTerms.get(i);\\n\\n // the number of documents in which the term appears\\n int termDocCount = 0;\\n if (index.containsKey(term)) {\\n termDocCount = index.get(term).size();\\n }\\n\\n if (docTerms.containsKey(term)) {\\n vector[i] =\\n (float)\\n (Math.sqrt(docTerms.get(term).size())\\n * Math.log10((double) docCount / termDocCount));\\n }\\n }\\n\\n return vector;\\n }\",\n \"@Override\\n public void postInserts() \\n {\\n for(IndexObject i: myIndex.values())\\n {\\n i.tfidf(documentData);\\n }\\n }\",\n \"@Override\\n public double makePrediction(ParsedText text) {\\n double pr = 0.0;\\n\\n /* FILL IN HERE */\\n double productSpam = 0;\\n double productNoSpam = 0;\\n \\n int i, tempSpam,tempNoSpam;\\n int minSpam, minNoSpam ;\\n \\n \\n for (String ng: text.ngrams) {\\n \\tminSpam = Integer.MAX_VALUE;\\n \\tminNoSpam = Integer.MAX_VALUE;\\n \\n\\n \\tfor (int h = 0;h < nbOfHashes; h++) {\\n \\t\\ti = hash(ng,h);\\n\\n \\t\\ttempSpam = counts[1][h][i];\\n \\t\\ttempNoSpam = counts[0][h][i];\\n \\t\\t\\n \\t\\t//System.out.print(tempSpam + \\\" \\\");\\n\\n \\t\\tminSpam = minSpam<tempSpam?minSpam:tempSpam; \\n \\t\\tminNoSpam = minNoSpam<tempNoSpam?minNoSpam:tempNoSpam; \\n \\t\\t\\n \\t}\\n\\n \\t//System.out.println(minSpam + \\\"\\\\n\\\");\\n \\tproductSpam += Math.log(minSpam);\\n \\tproductNoSpam += Math.log(minNoSpam);\\n }\\n \\n // size of set minus 1\\n int lm1 = text.ngrams.size() - 1;\\n \\n //System.out.println((productNoSpam - productSpam ));\\n //System.out.println((lm1*Math.log(this.classCounts[1]) - lm1*Math.log(this.classCounts[0])));\\n\\n //\\n pr = 1 + Math.exp(productNoSpam - productSpam + lm1*(Math.log(classCounts[1]) - Math.log(classCounts[0])));\\n // System.out.print(1.0/pr + \\\"\\\\n\\\");\\n \\n return 1.0 / pr;\\n\\n }\",\n \"int countFeatures();\",\n \"int countFeatures();\",\n \"private IDictionary<URI, IDictionary<String, Double>> computeAllDocumentTfIdfVectors(ISet<Webpage> pages) {\\n // Hint: this method should use the idfScores field and\\n // call the computeTfScores(...) method.\\n\\t\\tdocumentTfIdfVectors = new ChainedHashDictionary<URI, IDictionary<String, Double>>();\\n\\t\\t\\n\\t\\t// Iterates through the given set of webpages\\n\\t\\tfor (Webpage page: pages) {\\n\\t\\t\\tIDictionary<String, Double> tfIdfScores = new ChainedHashDictionary<String, Double>();\\n\\t\\t\\tIDictionary<String, Double> tfScores = computeTfScores(page.getWords());\\n\\t\\t\\t\\n\\t\\t\\t// Computes TfIdf scores\\n\\t\\t\\tfor (KVPair<String, Double> pair: tfScores) {\\n\\t\\t\\t\\tDouble tfIdfScore = pair.getValue() * idfScores.get(pair.getKey());\\n\\t\\t\\t\\ttfIdfScores.put(pair.getKey(), tfIdfScore);\\n\\t\\t\\t}\\n\\t\\t\\tdocumentTfIdfVectors.put(page.getUri(), tfIdfScores);\\n\\t\\t}\\n\\t\\treturn documentTfIdfVectors;\\n }\",\n \"static boolean checkTerm() {\\r\\n // Checks if this is a complete term\\r\\n boolean complete = false;\\r\\n\\r\\n // simple_term (base case)\\r\\n if (token.equals(\\\"IDENTIFIER\\\") || token.equals(\\\"SIGNED_INTEGER\\\") || token.equals(\\\"UNSIGNED_INTEGER\\\")) {\\r\\n complete = true;\\r\\n lex();\\r\\n\\r\\n // simple_term op\\r\\n if (token.equals(\\\"PLUS\\\") || token.equals(\\\"MINUS\\\") || token.equals(\\\"STAR\\\") || token.equals(\\\"DIVOP\\\") || token.equals(\\\"MOD\\\")) {\\r\\n complete = false;\\r\\n lex();\\r\\n\\r\\n // simple_term op term\\r\\n if(checkTerm()) {\\r\\n complete = true;\\r\\n }\\r\\n }\\r\\n }\\r\\n\\r\\n // (\\r\\n else if (token.equals(\\\"LEFT_PAREN\\\")) {\\r\\n lex();\\r\\n\\r\\n // ( term\\r\\n if(checkTerm()) {\\r\\n\\r\\n // ( term )\\r\\n if (token.equals(\\\"RIGHT_PAREN\\\")) {\\r\\n complete = true;\\r\\n lex();\\r\\n\\r\\n // ( term ) op\\r\\n if (token.equals(\\\"PLUS\\\") || token.equals(\\\"MINUS\\\") || token.equals(\\\"STAR\\\") || token.equals(\\\"DIVOP\\\") || token.equals(\\\"MOD\\\")) {\\r\\n complete = false;\\r\\n lex();\\r\\n\\r\\n // ( term ) op term\\r\\n if (checkTerm()) {\\r\\n complete = true;\\r\\n }\\r\\n }\\r\\n }\\r\\n\\r\\n // ( term op\\r\\n else if (token.equals(\\\"PLUS\\\") || token.equals(\\\"MINUS\\\") || token.equals(\\\"STAR\\\") || token.equals(\\\"DIVOP\\\") || token.equals(\\\"MOD\\\")) {\\r\\n complete = false;\\r\\n lex();\\r\\n\\r\\n // ( term op term\\r\\n if(checkTerm()) {\\r\\n\\r\\n // ( term op term )\\r\\n if (token.equals(\\\"RIGHT_PAREN\\\")) {\\r\\n complete = true;\\r\\n lex();\\r\\n\\r\\n // ( term op term ) op\\r\\n if (token.equals(\\\"PLUS\\\") || token.equals(\\\"MINUS\\\") || token.equals(\\\"STAR\\\") || token.equals(\\\"DIVOP\\\") || token.equals(\\\"MOD\\\")) {\\r\\n complete = false;\\r\\n lex();\\r\\n\\r\\n // ( term op term ) op term\\r\\n if (checkTerm()) {\\r\\n complete = true;\\r\\n }\\r\\n }\\r\\n }\\r\\n }\\r\\n }\\r\\n }\\r\\n }\\r\\n return complete;\\r\\n }\",\n \"public abstract double score(\\n\\t\\tdouble tf,\\n\\t\\tdouble docLength,\\n\\t\\tdouble n_t,\\n\\t\\tdouble F_t,\\n\\t\\tdouble keyFrequency);\",\n \"public double computeIDF(HashMap<String, Integer> termPostings, int documents) {\\n // Document frequency is the number of postings\\n int df = termPostings.size();\\n\\n return Math.log(((double) documents) / (df + 1));\\n }\",\n \"public Set<String> calculateDistance() throws IOException {\\n booleanSearch();\\n\\n Set<String> words = invertedIndexForQuerryWords.keySet();\\n Map<String, Double> tfidfQuerry = new TreeMap<>();\\n\\n //load idf\\n char c='a';\\n char prC = 'v';\\n for (String word : words){\\n c = word.charAt(0);\\n if(c != prC) {\\n String path = Constants.PATH_TO_IDF + c + \\\"IDF.idf\\\";\\n prC = c;\\n idfMap.putAll(objectMapper.readValue(new File(path), new TypeReference<TreeMap<String, Double>>(){}));\\n }\\n }\\n\\n Map<String, Double> distanceMap = new HashMap<>();\\n double sum = 0.0;\\n //calculez norma interogarii\\n for(String word:words){\\n double idf, tf;\\n if(idfMap.containsKey(word)) {\\n idf = idfMap.get(word);\\n tf = 1.0 / words.size();\\n tfidfQuerry.put(word, tf * idf);\\n\\n sum += (tf * idf) * (tf * idf);\\n } else {\\n sum += 0.0;\\n }\\n }\\n\\n double normQuerry = Math.sqrt(sum);\\n\\n //iau toate documentele rezultate din boolean search\\n Set<String> docs = new TreeSet<>();\\n for(List<MyPair> list : invertedIndexForQuerryWords.values()) {\\n if (list != null) {\\n docs.addAll(list.stream().map(p -> p.getKey()).collect(Collectors.toSet()));\\n }\\n }\\n\\n List<File> documents = FileLoader.getFilesForInternalPath(\\\"Norms\\\", \\\".norm\\\");\\n\\n Map<String, Double> norms = new HashMap<>();\\n for(File file : documents) {\\n norms.putAll(objectMapper.readValue(file, new TypeReference<TreeMap<String, Double>>(){}));\\n }\\n\\n //pentru fiecare document din boolean search calculez distanta cosinus\\n for(String doc : docs) {\\n\\n String fileName = Paths.get(doc).getFileName().toString();\\n\\n String filePath = Constants.PATH_TO_TF + fileName.replaceFirst(\\\"[.][^.]+$\\\", \\\".tf\\\");\\n\\n Map<String, Double> tf = objectMapper.readValue(new File(filePath), new TypeReference<TreeMap<String, Double>>(){});\\n double wordTF, wordIDF;\\n double vectorialProduct = 0.0;\\n double tfidfForQueryWord;\\n\\n for(String word : words) {\\n if (tf.containsKey(word)) {\\n wordTF = tf.get(word);\\n wordIDF = idfMap.get(word);\\n tfidfForQueryWord = tfidfQuerry.get(word);\\n\\n vectorialProduct += tfidfForQueryWord * wordIDF * wordTF;\\n }\\n }\\n\\n double normProduct = normQuerry * norms.get(Paths.get(doc).getFileName().toString());\\n\\n distanceMap.put(doc, vectorialProduct / normProduct);\\n }\\n\\n //sortare distance map\\n distanceMap = distanceMap.entrySet().stream()\\n .sorted(Map.Entry.comparingByValue(Collections.reverseOrder()))\\n .collect(Collectors.toMap(\\n Map.Entry::getKey,\\n Map.Entry::getValue,\\n (e1, e2) -> e1,\\n LinkedHashMap::new));\\n\\n// System.out.println(\\\"Cos distance:\\\");\\n// for(Map.Entry entry : distanceMap.entrySet()){\\n// System.out.println(entry);\\n// }\\n\\n return distanceMap.keySet();\\n }\",\n \"public void countTerm() throws IOException {\\n\\n long countBody = reader.getSumDocFreq(\\\"body\\\");\\n long countTitle = reader.getSumDocFreq(\\\"title\\\");\\n\\n System.out.println(\\\"Body: \\\" + countBody);\\n System.out.println(\\\"Title: \\\" + countTitle);\\n System.out.println(\\\"Total count Terms: \\\" + (countTitle + countBody));\\n\\n }\",\n \"public void computeTermTable(IndexReader reader) throws IOException {\\n\\t\\t//MultiFields.getFields(reader).terms(field)\\n\\t\\tint numDocs = reader.numDocs();\\n\\t\\tfor (int docID =0 ; docID < numDocs; docID++) {\\n\\t\\t\\tTerms termVector = reader.getTermVector(docID, FieldName.METHOD_DESC.getName());\\n\\t\\t\\tif(termVector == null)\\n\\t\\t\\t\\tcontinue;\\n\\t\\t\\tTermsEnum iterator = termVector.iterator(null);\\n\\t\\t\\tBytesRef next = iterator.next();\\n\\t\\t\\twhile (next != null) {\\n\\t\\t\\t\\tint docFreq = reader.docFreq(FieldName.METHOD_DESC.getName(), next);\\n\\t\\t\\t\\t\\n\\t\\t\\t\\ttermTable.put(next.utf8ToString(), docFreq);\\n\\t\\t\\t\\tnext = iterator.next();\\n\\t\\t\\t}\\n\\t\\t\\t\\n\\t\\t}\\n\\t\\t\\n\\t\\tcomputeStatProperties(reader,termTable);\\n\\t}\",\n \"public abstract Object[] getSimilarityFactors();\",\n \"public static void InvertedDocFrequency() throws FileNotFoundException {\\n //int totalDoc = totaldocument;\\n int i = 0;\\n for(Entry<String, List<Integer>> entry: dictionary.entrySet()) {\\n List<Integer> docFrequency = new ArrayList<>();\\n //\\tList<Double> idfValue = new ArrayList<>();\\n docFrequency = entry.getValue(); //again taking the list of word terms from the same dictionary hashmap\\n int df = docFrequency.get(totaldocument+1); // it will save the idf of every word term at the 57th index\\n double ans = Math.log10(df);\\n ans /= totaldocument;\\n\\n idfFinal.add(i,ans); //updatin\\n i++;\\n }\\n saveidf();\\n }\",\n \"default List<String> interestingConcepts(int topK, UnitLocation located,\\n Set<Location> irrelevantSet){\\n // collect frequent words outside the blacklist of locations\\n final TokenIterator extractor = new TokenIterator(irrelevantSet);\\n located.getUnitNode().accept(extractor);\\n\\n final WordCounter wordCounter = new WordCounter(extractor.getItems());\\n\\n return wordCounter.mostFrequent(topK);\\n }\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.60107577","0.5797017","0.5660234","0.5633843","0.5564556","0.5551654","0.554559","0.5543597","0.5539202","0.55127895","0.54864407","0.54860085","0.54856205","0.54337925","0.5350816","0.5343665","0.5324684","0.53126794","0.5291859","0.5283408","0.52833915","0.52810985","0.5260584","0.52293646","0.522235","0.52118814","0.5193171","0.51519144","0.51427376","0.5131274","0.5105942","0.50823694","0.50749946","0.5070671","0.5065016","0.5063753","0.5063058","0.50403696","0.5039093","0.50314504","0.50302464","0.50160533","0.5011331","0.5007651","0.50058025","0.50027436","0.5000992","0.49926874","0.4987358","0.49833938","0.49646062","0.49582765","0.4934672","0.49273926","0.4921564","0.49116609","0.4903203","0.48812383","0.48807624","0.4877343","0.48594695","0.48582518","0.48558256","0.48537046","0.4849764","0.4843289","0.48429158","0.48374242","0.48346326","0.48346326","0.48248807","0.48203266","0.4818896","0.48164356","0.48157892","0.48115194","0.4808889","0.48057535","0.4804191","0.48023957","0.48015392","0.4785952","0.47762436","0.47581244","0.4757003","0.47550023","0.47509572","0.47498724","0.47487736","0.47487736","0.47469592","0.47441903","0.47415993","0.4738378","0.4735741","0.4734797","0.47299358","0.47286695","0.47264475","0.47118115"],"string":"[\n \"0.60107577\",\n \"0.5797017\",\n \"0.5660234\",\n \"0.5633843\",\n \"0.5564556\",\n \"0.5551654\",\n \"0.554559\",\n \"0.5543597\",\n \"0.5539202\",\n \"0.55127895\",\n \"0.54864407\",\n \"0.54860085\",\n \"0.54856205\",\n \"0.54337925\",\n \"0.5350816\",\n \"0.5343665\",\n \"0.5324684\",\n \"0.53126794\",\n \"0.5291859\",\n \"0.5283408\",\n \"0.52833915\",\n \"0.52810985\",\n \"0.5260584\",\n \"0.52293646\",\n \"0.522235\",\n \"0.52118814\",\n \"0.5193171\",\n \"0.51519144\",\n \"0.51427376\",\n \"0.5131274\",\n \"0.5105942\",\n \"0.50823694\",\n \"0.50749946\",\n \"0.5070671\",\n \"0.5065016\",\n \"0.5063753\",\n \"0.5063058\",\n \"0.50403696\",\n \"0.5039093\",\n \"0.50314504\",\n \"0.50302464\",\n \"0.50160533\",\n \"0.5011331\",\n \"0.5007651\",\n \"0.50058025\",\n \"0.50027436\",\n \"0.5000992\",\n \"0.49926874\",\n \"0.4987358\",\n \"0.49833938\",\n \"0.49646062\",\n \"0.49582765\",\n \"0.4934672\",\n \"0.49273926\",\n \"0.4921564\",\n \"0.49116609\",\n \"0.4903203\",\n \"0.48812383\",\n \"0.48807624\",\n \"0.4877343\",\n \"0.48594695\",\n \"0.48582518\",\n \"0.48558256\",\n \"0.48537046\",\n \"0.4849764\",\n \"0.4843289\",\n \"0.48429158\",\n \"0.48374242\",\n \"0.48346326\",\n \"0.48346326\",\n \"0.48248807\",\n \"0.48203266\",\n \"0.4818896\",\n \"0.48164356\",\n \"0.48157892\",\n \"0.48115194\",\n \"0.4808889\",\n \"0.48057535\",\n \"0.4804191\",\n \"0.48023957\",\n \"0.48015392\",\n \"0.4785952\",\n \"0.47762436\",\n \"0.47581244\",\n \"0.4757003\",\n \"0.47550023\",\n \"0.47509572\",\n \"0.47498724\",\n \"0.47487736\",\n \"0.47487736\",\n \"0.47469592\",\n \"0.47441903\",\n \"0.47415993\",\n \"0.4738378\",\n \"0.4735741\",\n \"0.4734797\",\n \"0.47299358\",\n \"0.47286695\",\n \"0.47264475\",\n \"0.47118115\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.6349889"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":13890,"cells":{"query":{"kind":"string","value":"[NEW] Finds documents containing the query as a phrase TODO: Skip pointer"},"document":{"kind":"string","value":"public PostingsList phrase_query(Query query){\n\n LinkedList<PostingsList> listQueriedPostings = new LinkedList<PostingsList>();\n // List with postings corresponding to the queries\n for (int i = 0; i<query.size(); i++){\n // If any query has zero matches, return 0 results\n //if(!(new File(\"postings/t\"+hash(query.terms.get(i))+\".json\")).exists()){\n if (!this.index.containsKey(query.terms.get(i))){\n return null;\n }\n // Otherwise store postings in the list\n listQueriedPostings.add(this.getPostings(query.terms.get(i)));\n }\n\n PostingsList result = new PostingsList();\n result = listQueriedPostings.get(0);\n\n // In case only one word is queried\n if (listQueriedPostings.size() == 1){\n return result;\n }\n\n // Apply algorithm as many times as words in the query\n for(int i = 1; i < listQueriedPostings.size(); i++){\n result = phrase_query(result, listQueriedPostings.get(i));\n if (result.isEmpty()){\n return null;\n }\n }\n return result;\n }"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["@Test\n public void testPhrase() {\n assertQ(req(\"q\",\"text:now-cow\", \"indent\",\"true\")\n ,\"//*[@numFound='1']\"\n );\n // should generate a query of (now OR cow) and match both docs\n assertQ(req(\"q\",\"text_np:now-cow\", \"indent\",\"true\")\n ,\"//*[@numFound='2']\"\n );\n }","private static String handlePhrases(String PubmedQuery) {\r\n //Find phrases \"between double quotes\"\r\n String[] phrases = PubmedQuery.split(\"\\\"\");\r\n for(int i = 0 ; i < phrases.length ; i++){\r\n phrases[i] = phrases[i].trim();\r\n if(!phrases[i].equals(\"\")){ // String not Empty\r\n if(i%2 != 0){ // String surrounded by quotes, i.e. a phrase\r\n phrases[i] = \"\\\"\" + phrases[i] + \"\\\"\";\r\n } else { // not a phrase, i.e. a bag of terms, operator or [field of index] (inside brackets)\r\n if(phrases[i].startsWith(\"[\")){ //index field of previus component contained (i.e. case: \"...\"[...])\r\n boolean perviusPhraseFound = false; // True if index field was added to previus phrase element\r\n // Get index field of previus component and handle proprietly\r\n String [] tokens = phrases[i].split(\"]\");\r\n String indexField = tokens[0].replace(\"[\", \"\");\r\n String luceneField = supportedIndexFields.get(indexField);\r\n if(luceneField != null){ \r\n //add \"indexField:\" as a prefix in previus (not empty) phrase\r\n int tmp = i-1;\r\n while(!perviusPhraseFound & tmp >= 0){\r\n if(!phrases[tmp].equals(\"\")){\r\n perviusPhraseFound = true;\r\n //TO DO : handle wrong syntax (e.g. ... AND [ArticleTitle])\r\n phrases[tmp] = luceneField + \":\" + phrases[tmp] + \"\";\r\n } else {\r\n tmp--;\r\n }\r\n }\r\n } // else : Lucene counterpart not found, unsupported field - do nothing\r\n // Remove from current phrase this index field (prefix)\r\n phrases[i] = phrases[i].substring(indexField.length()+2 );\r\n } \r\n // Further handling...\r\n phrases[i] = handleNonPhraseToken(phrases[i]);\r\n }\r\n } //else { /* Empty token, do nothing with this */ System.out.println(\"\\t\\t\\t empty\"); }\r\n }\r\n \r\n String luceneQuery = \"\";\r\n boolean fisrtPhrase = true;\r\n for(int i = 0 ; i < phrases.length ; i ++){\r\n if(phrases[i].length() > 0){\r\n if(!phrases[i].startsWith(\" OR \") & !phrases[i].startsWith(\" -\") & !phrases[i].startsWith(\" +\") ){\r\n if(fisrtPhrase){\r\n luceneQuery += \" +\";\r\n fisrtPhrase = false;\r\n } else {\r\n if(!phrases[i-1].endsWith(\" OR \") & !phrases[i-1].endsWith(\" -\") & !phrases[i-1].endsWith(\" +\")){\r\n luceneQuery += \" +\";\r\n }\r\n } \r\n } // add default operator + when required (no OR or - is present for that term)\r\n luceneQuery += phrases[i];\r\n }// else empty phrase : skip\r\n }\r\n return luceneQuery;\r\n }","private static List<SearchData> booleanSearchWord(Query query, Indexer si) {\n Tokenizer tkn = new SimpleTokenizer();\n tkn.tokenize(query.getStr(), \"[a-zA-Z]{3,}\", true, true);\n List<SearchData> searchList = new ArrayList<>();\n LinkedList<Token> wordsList = tkn.getTokens();\n Iterator<Token> wordsIt = wordsList.iterator();\n HashMap<String, LinkedList<Posting>> indexer = si.getIndexer();\n int idx;\n SearchData searched_doc;\n\n while (wordsIt.hasNext()) {\n String word = wordsIt.next().getSequence();\n if (indexer.containsKey(word)) {\n\n LinkedList<Posting> posting = indexer.get(word);\n\n for (Posting pst : posting) {\n\n SearchData sd = new SearchData(query, pst.getDocId());\n\n if (!searchList.contains(sd)) {\n sd.setScore(1);\n searchList.add(sd);\n } else {\n idx = searchList.indexOf(sd);\n searched_doc = searchList.get(idx);\n searched_doc.setScore(searched_doc.getScore() + 1);\n }\n }\n\n }\n\n\n }\n\n Collections.sort(searchList);\n\n return searchList;\n }","@Override\r\n\t\t\tpublic List<ScoredDocument> search(Query query) {\n\t\t\t\treturn null;\r\n\t\t\t}","public Map<String, String> directQuoteSearch (String q, String contentOrTitle) throws IOException, ParseException{\n\n\t\t\n\t\tif (contentOrTitle.equals(\"content\")){\n\t\t\tcontentOrTitle=field;\n\t\t} else if (contentOrTitle.equals(\"title\")){\n\t\t\tcontentOrTitle=title;\n\t\t}\n\t\t\n\t\tIndexReader reader = DirectoryReader.open(FSDirectory.open(Paths.get(index)));\n\t\tIndexSearcher searcher = new IndexSearcher(reader);\n\t\tboolean raw = false;\n\t\tint repeat = 0;\n\n\t\tfinal List<String> stopWords = Arrays.asList();\n\t\tfinal CharArraySet stopSet = new CharArraySet(stopWords, true);\n\n\t\tAnalyzer analyzer = new StandardAnalyzer(stopSet);\n\t\tAnalyzingQueryParser parser = new AnalyzingQueryParser(contentOrTitle, analyzer);\n\t\t\n\n\t\t\n\t\tString[] items = q.split(\" \");\n\t\tList<String> itemList = Arrays.asList(items);\n\t\tQuery query=null;\n\t\t\n\t\t\n\t\tif (q.equals(\"\")){\n\t\t\tSystem.out.println(\"no input\");\n\t\t\t\n\t\t} else {\n\t\t\tquery = parser.parse(q);\n\n\t\t}\n\n\t\t\n\t\t\n\t\tBufferedReader in = null;\n\t\tin = new BufferedReader(new InputStreamReader(System.in, StandardCharsets.UTF_8));\n\n\t\tif (repeat > 0) { // repeat & time as benchmark\n\t\t\tDate start = new Date();\n\t\t\tfor (int i = 0; i < repeat; i++) {\n\t\t\t\tsearcher.search(query, 100);\n\t\t\t}\n\t\t\tDate end = new Date();\n\t\t\tSystem.out.println(\"Time: \"+(end.getTime()-start.getTime())+\"ms\");\n\t\t}\n\n\t\treturn doPagingSearch(in, searcher, query, hitsPerPage, raw, true);\n\t}","@In String search();","public byte filter(Manager m, SearchRequest q, ResultSet rs, int DocAtNumber, int DocNo)\n\t{\t\t\n\t\tString originalQuery = q.getOriginalQuery();\n\t\t//highlight query terms only for the queries, \n\t\t//which are not about finding related documents\n\t\t//this check may be removed, because the preparation of the \n\t\t//query terms for highlighting takes into account\n\t\t//the related: operator\n\t\tboolean highlightQueryTerms = true;\n\t\tif (originalQuery.matches(\"\\\\brelated:\\\\d+\\\\b\") || //check if the query uses the related: operator \n\t\t\t!enableQueryTermsHighlight || //check if the highlighting of terms is enabled\n\t\t\thighlight.pattern().equals(\"(\\\\b)()(\\\\b)\")) //check if there are no query terms to highlight\n\t\t\thighlightQueryTerms = false;\n\t\t\n\t\tString[] qTerms = q.getOriginalQuery().replaceAll(\" \\\\w+\\\\p{Punct}\\\\w+ \",\" \").toLowerCase().split(\" \");\n\t\t\n\t\tString[] metadata = null;\n\t\tint tmpSentence;\n\t\tdouble tmpScore;\n\t\tsynchronized(metaCache) {\n\t\t\ttry {\n\t\t\t\tInteger DocNoObject = new Integer(DocNo);\n\t\t\t\tif (metaCache.containsKey(DocNoObject))\n\t\t\t\t\t\tmetadata = (String[]) metaCache.get(DocNoObject);\n\t\t\t\telse {\n\t\t\t\t\tmetadata = metaIndex.getItems(keys, DocNo);\n\t\t\t\t\tmetaCache.put(DocNoObject,metadata);\n\t\t\t\t}\n\t\t\t} catch(IOException ioe) {} \n\t\t}\n\t\n\t\tif (show_snippet)\n\t\t{\n\t\t\tString extract = metadata[1];\n\t\t\tString[] sentences = sentencePattern.split(extract, 50); //use 50 sentences at most\n\t\t\tdouble[] sentenceScores = new double[sentences.length]; \n\t\t\tint frsSentence = -1;\n\t\t\tint sndSentence = -1;\n\t\t\tint top1Sentence = 0;\n\t\t\tint top2Sentence = 0;\n\t\t\tdouble max1Score = -1;\n\t\t\tdouble max2Score = 0;\n\t\t\tfinal int qTermsLength = qTerms.length;\n\t\t\tfor (int i=0; i<qTermsLength; i++) {\n\t\t\t\tqTerms[i] = removeEndings.matcher(qTerms[i]).replaceAll(\"\");\n\t\t\t}\n\t\t\tString lowerCaseSentence;\n\t\t\tint sentenceLength;\n\t\t\tfinal int sentencesLength = sentences.length;\n\n\t\t\tfor (int i=0; i<sentencesLength; i++) {\n\t\t\t\t\n\t\t\t\tlowerCaseSentence = sentences[i].toLowerCase();\n\t\t\t\tsentenceLength=sentences[i].length();\n\t\t\t\tif (sentenceLength < 20 || sentenceLength > 250) {\n\t\t\t\t\tfor (int j=0; j<qTermsLength; j++) {\n\t\t\t\t\t\tif (lowerCaseSentence.indexOf(qTerms[j])>=0) {\n\t\t\t\t\t\t\tsentenceScores[i]+=1.0d + sentenceLength / (20.0d + sentenceLength);\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\n\t\t\t\t\t\n\t\t\t\t} else {\n\t\t\t\t\tfor (int j=0; j<qTermsLength; j++) {\n\t\t\t\t\t\tif (lowerCaseSentence.indexOf(qTerms[j])>=0) {\n\t\t\t\t\t\t\tsentenceScores[i]+=qTerms[j].length() + sentenceLength / (1.0d + sentenceLength);\n\t\t\t\t\t\t}\n\t\t\t\t\t}\t\t\t\t\t\n\t\t\t\t}\n\t\t\t\t\t\t\t\t\n\t\t\t\t//do your best to get at least a second sentence for the snippet, \n\t\t\t\t//after having found the first one\n\t\t\t\tif (frsSentence > -1 && sndSentence == -1 && sentenceLength > 5) {\n\t\t\t\t\tsndSentence = i;\n\t\t\t\t}\n\n\t\t\t\t//do your best to get at least one sentence for the snippet\n\t\t\t\tif (frsSentence == -1 && sentenceLength > 5) { \n\t\t\t\t\tfrsSentence = i;\n\t\t\t\t}\n\n\t\t\t\tif (max2Score < sentenceScores[i]) {\n\t\t\t\t\tmax2Score = sentenceScores[i];\n\t\t\t\t\ttop2Sentence = i;\n\t\t\t\t\t//logger.debug(\"top 2 sentence is \" + i);\n\t\t\t\t\tif (max2Score > max1Score) {\n\t\t\t\t\t\ttmpScore = max1Score; max1Score = max2Score; max2Score = tmpScore;\n\t\t\t\t\t\ttmpSentence = top1Sentence; top1Sentence = top2Sentence; top2Sentence = tmpSentence;\n\t\t\t\t\t}\n\t\t\t\t}\n\n\t\t\t}\n\t\t\tint lastIndexOfSpace = -1;\n\t\t\tString sentence=\"\";\n\t\t\tString secondSentence=\"\";\n\t\t\tString snippet = \"\";\n\t\t\tif (max1Score == -1) {\n\t\t\t\tif (frsSentence>=0) {\n\t\t\t\t\tsentence = sentences[frsSentence];\n\t\t\t\t\tif (sentence.length() > 100) {\n\t\t\t\t\t\tlastIndexOfSpace = sentence.substring(0, 100).lastIndexOf(\" \");\n\t\t\t\t\t\tsentence = sentence.substring(0, lastIndexOfSpace > 0 ? lastIndexOfSpace : 100);\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t\t\n\t\t\t\tif (sndSentence>=0) {\n\t\t\t\t\tsecondSentence = sentences[sndSentence];\n\t\t\t\t\tif (secondSentence.length() > 100) {\n\t\t\t\t\t\tlastIndexOfSpace = secondSentence.substring(0, 100).lastIndexOf(\" \");\n\t\t\t\t\t\tsecondSentence = secondSentence.substring(0, lastIndexOfSpace>0 ? lastIndexOfSpace : 100);\n\t\t\t\t\t}\t\t\t\t\t\n\t\t\t\t}\n\t\t\t\t\n\t\t\t\tif (frsSentence >=0 && sndSentence >= 0) \n\t\t\t\t\tsnippet = sentence.trim() + \"...\" + secondSentence.trim();\n\t\t\t\telse if (frsSentence >= 0 && sndSentence<0) \n\t\t\t\t\tsnippet = sentence.trim();\n\t\t\t\t\n\t\t\t} else if (sentences[top1Sentence].length()<100 && top1Sentence!=top2Sentence) {\n\t\t\t\tsentence = sentences[top1Sentence];\n\t\t\t\tif (sentence.length() > 100) {\n\t\t\t\t\tlastIndexOfSpace = sentence.substring(0, 100).lastIndexOf(\" \");\n\t\t\t\t\tsentence = sentence.substring(0, lastIndexOfSpace > 0 ? lastIndexOfSpace : 100);\n\t\t\t\t}\n\t\t\t\t\t\t\t\t\n\t\t\t\tsecondSentence = sentences[top2Sentence];\n\t\t\t\tif (secondSentence.length() > 100) {\n\t\t\t\t\tlastIndexOfSpace = secondSentence.substring(0, 100).lastIndexOf(\" \");\n\t\t\t\t\tsecondSentence = secondSentence.substring(0, lastIndexOfSpace>0 ? lastIndexOfSpace : 100);\n\t\t\t\t}\n\t\t\t\tsnippet = sentence.trim() + \"...\" + secondSentence.trim();\n\t\t\t} else {\n\t\t\t\tsentence = sentences[top1Sentence];\n\t\t\t\tif (sentence.length()>200) {\n\t\t\t\t\tlastIndexOfSpace = sentence.substring(0, 200).lastIndexOf(\" \");\n\t\t\t\t\tsentence = sentence.substring(0, lastIndexOfSpace > 0 ? lastIndexOfSpace : 200);\n\t\t\t\t}\n\t\t\t\tsnippet = sentence.trim();\n\t\t\t}\n\t\t\t\n\t\t\t//checking and removing any control characters\n\t\t\tcontrolNonVisibleCharactersMatcher.reset(snippet);\n\t\t\tsnippet = controlNonVisibleCharactersMatcher.replaceAll(\"\");\n\t\t\t\n\t\t\t//String escapedSnippet = StringEscapeUtils.escapeHtml(snippet);\n\t\t\t//if (highlightQueryTerms)\n\t\t\t//\tescapedSnippet = highlight.matcher(escapedSnippet).replaceAll(\"$1<b>$2</b>$3\");\n\t\t\tif (highlightQueryTerms)\n\t\t\t\tsnippet = highlight.matcher(snippet).replaceAll(\"$1<b>$2</b>$3\");\n\t\t\t//else \n\t\t\t//\tsnippet = StringEscapeUtils.escapeHtml(snippet);\n\t\t\t\n\t\t\t//change by Vassilis, 20/09/2006\n\t\t\t//disabling the xml escaping in order to move the data into ![CDATA[ ]]\n\t\t\t//the code was:\n\t\t\t//rs.addMetaItem(\"snippet\", DocAtNumber, StringEscapeUtils.escapeXml(snippet));\n\t\t\t//and now it is:\n\t\t\t//snippet.replaceAll(\"[^\\\\u0009\\\\u000A\\\\u000D\\\\u0020-\\\\uD7FF\\\\uE000-\\\\uFFFD\\\\u10000-\\\\u10FFFF]\",\"\");\n\t\t\trs.addMetaItem(\"snippet\", DocAtNumber, snippet);\n\t\t\t\n\t\t}\n\t\tif (show_title)\n\t\t{\n\t\t\tString title = metadata[2];\n\t\t\t\n\t\t\t//checking and removing any control characters\n\t\t\tcontrolNonVisibleCharactersMatcher.reset(title);\n\t\t\ttitle = controlNonVisibleCharactersMatcher.replaceAll(\"\");\n\t\t\ttitle = (highlightQueryTerms)\n\t\t\t\t ? highlight.matcher(metadata[2]).replaceAll(\"$1<b>$2</b>$3\") \n\t\t\t\t : metadata[2];\n\t\t\t\n\t\t\t\n\t\t\t//String escapedTitle = StringEscapeUtils.escapeHtml(metadata[2]);\n\t\t\t//String title = (highlightQueryTerms)\n\t\t\t//\t\t\t ? highlight.matcher(escapedTitle).replaceAll(\"$1<b>$2</b>$3\") \n\t\t\t//\t\t\t : escapedTitle;\n\t\t\t//String title = (highlightQueryTerms) \n\t\t\t//\t\t? highlight.matcher(metadata[2]).replaceAll(\"$1<b>$2</b>$3\") \n\t\t\t//\t\t: metadata[2];\n\n\t\t\t//change by Vassilis, 20/09/2006\n\t\t\t//disabling the xml escaping in order to move the data into ![CDATA[ ]]\n\t\t\t//the code was:\n\t\t\t//rs.addMetaItem(\"title\", DocAtNumber, StringEscapeUtils.escapeXml(title));\n\t\t\t//and now is:\n\t\t\t//title.replaceAll(\"[^\\\\u0009\\\\u000A\\\\u000D\\\\u0020-\\\\uD7FF\\\\uE000-\\\\uFFFD\\\\u10000-\\\\u10FFFF]\",\"\");\n\t\t\trs.addMetaItem(\"title\", DocAtNumber, title);\n\t\t\t\n\t\t}\n\t\tif (!show_docid_early && show_docid)\n\t\t{\n\t\t\trs.addMetaItem(\"docid\", DocAtNumber, docIndex.getDocumentNumber(DocNo));\n\t\t}\n\t\tif (!show_url_early && show_url)\n\t\t{\n\n\t\t\trs.addMetaItem(\"url\", DocAtNumber, StringEscapeUtils.escapeXml(metadata[0]));\n\t\t}\n\t\t\n\t\treturn FILTER_OK;\n\t}","@Test\n\tpublic void phraseGrepTest1() throws Exception {\n\t\t// phrase is \"I am forced\"\n\t\tHashSet<String> grepFound = loadGrepResults(\"i+am+forced\");\n\t\tCollection<Page> index = queryTest.query(\"\\\"I am Forced\\\"\");\n\t\tHashSet<String> indexFound = new HashSet<String>();\n\n\t\tfor (Page p : index)\n\t\t\tindexFound.add(p.getURL().getPath().toLowerCase());\n\t\t\n\t\t// tests set equality \n\t\tassertEquals(indexFound, grepFound);\n\t}","private ArrayList<WordDocument> executeRegularQuery(){\n String[] splitedQuery = this.query.split(\" \");\n ArrayList<WordDocument> listOfWordDocuments = new ArrayList<WordDocument>();\n String word = \"\";\n\n for(int i = 0; i < splitedQuery.length; i++){\n if(!isOrderByCommand(splitedQuery[i]) && i == 0) {\n word = splitedQuery[i];\n\n if(cache.isCached(word))\n addWithoutDuplicate(listOfWordDocuments, cache.getCachedResult(word));\n else\n addWithoutDuplicate(listOfWordDocuments, getDocumentsWhereWordExists(word));\n\n }else if(i >= 1 && isOrderByCommand(splitedQuery[i])) {\n subQueries.add(word);\n listOfWordDocuments = orderBy(listOfWordDocuments, splitedQuery[++i], splitedQuery[++i]);\n break;\n }\n else\n throw new IllegalArgumentException();\n }\n\n return listOfWordDocuments;\n }","public void search(Indexer indexer, CityIndexer cityIndexer, Ranker ranker, String query, boolean withSemantic, ArrayList<String> chosenCities, ObservableList<String> citiesByTag, boolean withStemming, String saveInPath, String queryId, String queryDescription) {\n String[] originalQueryTerms = query.split(\" \");\n String originQuery = query;\n docsResults = new HashMap<>();\n parser = new Parse(withStemming, saveInPath, saveInPath);\n HashSet<String> docsOfChosenCities = new HashSet<>();\n query = \"\" + query + queryDescription;\n HashMap<String, Integer> queryTerms = parser.parseQuery(query);\n HashMap<String, ArrayList<Integer>> dictionary = indexer.getDictionary();\n if (!withStemming){\n setDocsInfo(saveInPath + \"\\\\docsInformation.txt\");\n }\n else{\n setDocsInfo(saveInPath + \"\\\\docsInformation_stemming.txt\");\n }\n\n\n //add semantic words of each term in query to 'queryTerms'\n if(withSemantic) {\n HashMap<String,ArrayList<String>> semanticWords = ws.connectToApi(originQuery);\n }\n\n //give an ID to query if it's a regular query (not queries file)\n if(queryId.equals(\"\")){\n queryId = \"\" + Searcher.queryID;\n Searcher.queryID++;\n }\n\n String postingDir;\n if (!withStemming) {\n postingDir = \"\\\\indexResults\\\\postingFiles\";\n } else {\n postingDir = \"\\\\indexResults\\\\postingFiles_Stemming\";\n }\n int pointer = 0;\n\n //find docs that contain the terms in the query in their text\n HashMap<String, Integer> queryTermsIgnoreCase = new HashMap<>();\n for (String term : queryTerms.keySet()) {\n String originTerm = term;\n if (!dictionary.containsKey(term.toUpperCase()) && !dictionary.containsKey(term.toLowerCase())) {\n continue;\n }\n if(dictionary.containsKey(term.toLowerCase())){\n term = term.toLowerCase();\n }\n else {\n term = term.toUpperCase();\n }\n queryTermsIgnoreCase.put(term,queryTerms.get(originTerm));\n pointer = dictionary.get(term).get(2);\n String chunk = (\"\" + term.charAt(0)).toUpperCase();\n\n //get the relevant line from posting file\n BufferedReader br = null;\n try {\n br = new BufferedReader(new FileReader(new File(saveInPath + postingDir + \"\\\\posting_\" + chunk + \".txt\")));\n String line = \"\";\n int i = 1;\n while ((line = (br.readLine())) != null) {\n if (i == pointer) {\n break;\n }\n i++;\n }\n br.close();\n\n //get docs from posting line and add them to the data structure 'docsResults'\n if(line != null) {\n findDocsFromLine(line, term);\n }\n\n } catch (IOException e) {\n e.printStackTrace();\n }\n }\n\n //find docs that contain the chosen cities in their text\n for (String cityTerm : chosenCities) {\n if (!dictionary.containsKey(cityTerm) && !dictionary.containsKey(cityTerm.toLowerCase())) {\n continue;\n }\n if(dictionary.containsKey(cityTerm.toLowerCase())){\n cityTerm = cityTerm.toLowerCase();\n }\n pointer = dictionary.get(cityTerm).get(2);\n // char chunk = indexer.classifyToPosting(term).charAt(0);\n String chunk = (\"\" + cityTerm.charAt(0)).toUpperCase();\n\n //get the relevant line from posting file\n BufferedReader br = null;\n try {\n br = new BufferedReader(new FileReader(new File(saveInPath + postingDir + \"\\\\posting_\" + chunk + \".txt\")));\n String line = \"\";\n int i = 1;\n while ((line = (br.readLine())) != null) {\n if (i == pointer) {\n break;\n }\n i++;\n }\n br.close();\n\n //get docs from posting line and add them to the data structure 'docsOfChosenCities'\n String docs = line.substring(0, line.indexOf(\"[\") - 1); //get 'docsListStr'\n String[] docsArr = docs.split(\";\");\n for (String docInfo : docsArr) {\n String doc = docInfo.substring(0, docInfo.indexOf(\": \"));\n while(doc.charAt(0) == ' '){\n doc = doc.substring(1);\n }\n docsOfChosenCities.add(doc);\n }\n } catch (IOException e) {\n e.printStackTrace();\n }\n }\n\n //find docs that contain the chosen cities in their city tag\n if(!chosenCities.isEmpty()){\n for (String cityDicRec: chosenCities) {\n //get pointer to posting from cityDictionary\n try {\n pointer = cityIndexer.getCitiesDictionary().get(cityDicRec);\n } catch (NumberFormatException e) {\n e.printStackTrace();\n }\n //get the relevant line from posting file\n BufferedReader br = null;\n try {\n br = new BufferedReader(new FileReader(new File(saveInPath + \"\\\\cityIndexResults\" + \"\\\\posting_city\" + \".txt\")));\n String line = \"\";\n int i = 1;\n while ((line = (br.readLine())) != null) {\n if (i == pointer) {\n break;\n }\n i++;\n }\n br.close();\n\n //get docs from posting line and add them to the data structure 'docsOfChosenCities'\n String docs = line.substring(line.indexOf(\"[\") + 1, line.indexOf(\"]\")); //get 'docsListStr'\n String[] docsArr = docs.split(\"; \");\n for (String doc : docsArr) {\n docsOfChosenCities.add(doc);\n }\n } catch (IOException e) {\n e.printStackTrace();\n }\n }\n }\n\n\n ranker.rank(docsResults, docsOfChosenCities, queryTermsIgnoreCase, dictionary, docsInfo,entities, queryId);\n }","public DocumentListFeed fullTextQuery(String text) throws MalformedURLException, IOException, ServiceException;","private static Query computeBooleanQueryNP(String textQuery){\n\t\tBooleanQuery query = new BooleanQuery();\n\n\t\tHmmDecoder mPosTagger = null;\n\t\tTokenizerFactory mTokenizerFactory = null;\n\t\tPhraseChunker pChunker = new PhraseChunker(mPosTagger,mTokenizerFactory);\n\t\tArrayList<String> pchuncker = new ArrayList<String>();\n\n\t\tpchuncker = pChunker.getCHunkNounPhrases(textQuery.toLowerCase());\n\n\t\tfor (int k = 0; k<= pchuncker.size()-1;k++ ){\n\t\t\tString wordInList = ((String) pchuncker.get(k));\n\t\t\twordInList = wordInList.toLowerCase().replaceAll(\"-\",\" \");\n\t\t\tString [] wordInListSplit = wordInList.split(\" \");\n\t\t\tfor (String word: wordInListSplit){\n\n\t\t\t\tquery.add(new TermQuery(new Term(\"content\", word)), Occur.SHOULD );\n\t\t\t}\n\n\t\t}\n\n\t\t/* String[] tQuery = textQuery.split(\" \");\n\t\t for(String s: tQuery )\n\t\t\t query.add(new TermQuery(new Term(\"text\", s)), Occur.SHOULD);*/\n\n\t\treturn query;\n\t}","private static String getPhraseInput() {\n\t\treturn getQuery(\"Query Phrase\");\n\t}","public SearchResult search(String text, String subText);","List<String> getDocumentTitles(String query) throws SearcherException;","public List<Document> SearchField(String queryStr ,String fieldName)\r\n\t{\r\n\t\treturn null;\r\n\t}","String phraseQuery(String field, String val, int from, int size,\n\t\t\tboolean isSubdoc, DomeoPermissions permissions3) {\n\t\tString query = buildPhraseQuery(field, val, from, size, permissions3);\n\t\tString searchUrl = isSubdoc ? esSearchSubdocUrl : esSearchUrl;\n\t\t@SuppressWarnings(\"unused\")\n\t\tint resCode = doHttpOperation(searchUrl, HTTP_POST, query);\n\t\treturn decodeNS(lastResponse);\n\t}","SpellResponse spellQuery(SearchRequest request, Map<SearchParam, String> params);","@Test\n\tpublic void singleWordGrepTest4() throws Exception {\n\t\t// word is 'undocumented'\n\t\tHashSet<String> grepFound = loadGrepResults(\"undocumented\");\n\t\tCollection<Page> index = queryTest.query(\"undocumented\");\n\t\tHashSet<String> indexFound = new HashSet<String>();\n\n\t\tfor (Page p : index)\n\t\t\tindexFound.add(p.getURL().getPath().toLowerCase());\n\t\t\n\t\t// tests set equality \n\t\tassertEquals(indexFound, grepFound);\n\t}","@Test\n\tpublic void notPhraseGrepTest() throws Exception {\n\t\t// phrase is \"I am forced\"\n\t\tHashSet<String> grepFound = loadGrepResults(\"!i+am+forced\");\n\t\tCollection<Page> index = queryTest.query(\"! \\\"I am Forced\\\"\");\n\t\tHashSet<String> indexFound = new HashSet<String>();\n\n\t\tfor (Page p : index)\n\t\t\tindexFound.add(p.getURL().getPath().toLowerCase());\n\t\tassertEquals(grepFound, indexFound);\n\t}","public static ArrayList<Result> findMatches(Query query, DataManager myVocab){\n\n\t\t//Uncomment this for logging in this class\t\n//\t\tmyLogger.setLevel(Level.INFO); \n\n\t\t// get the term we're going to search for and\n\t\t// take out any leading or trailing whitespaces\n\t\tString querystr = query.getQuery();\n\t\tquerystr = querystr.trim();\n\t\tString uncleaned = querystr;\n\t\t\n\t\t// This is in case of numeric entries. Google Refine doesn't seem\n\t\t// to have int cell types, instead it adds an invisible .0 to all\n\t\t// numbers. This fixes that issue, as it sometimes causes false negatives.\n\t\tif (querystr.endsWith(\".0\")){\n\t\t Pattern p = Pattern.compile(\"[^0-9\\\\.]+\");\n\t\t Matcher m = p.matcher(querystr);\n\t\t boolean result = m.find();\n\t\t if (!result){\n\t\t \t querystr = querystr.substring(0, querystr.length()-2);\n\t\t }\n\t\t}\n\t\t// see if it's in the synonyms map, if it is\n\t\t// replace it with the appropriate term, if it's\n\t\t// not, don't do anything. \n\n\t\tif (myVocab.subMap.get(querystr)!=null){\n\t\t\tquerystr = myVocab.subMap.get(querystr);\n\t\t\tquery.setQuery(querystr);\n\t\t}\n\t\t\n\t\t// Clean up the query string if it isn't case/punctuation sensitive\n\t\tif (!myVocab.capsSensitive()){\t\t\n\t\t\tquerystr = querystr.toLowerCase();\n\t\t}\n\t\tif (! myVocab.punctSensitive()){\t\t\n\t\t\tquerystr = querystr.replaceAll(\"[\\\\W_]\", \"\");\n\t\t}\n\t\t\n\t\t// see if it's in the synonyms map, if it is\n\t\t// replace it with the appropriate term, if it's\n\t\t// not, don't do anything. \n\t\tif(myVocab.subMap.get(querystr)!=null){\n\t\t\tquerystr = myVocab.subMap.get(querystr);\n\t\t\tquery.setQuery(querystr);\n\t\t}\n\n\t\tString type = query.getType();\n\n\t\t// This ArrayList is the results that are going to be returned. \n\t\tArrayList<Result> results = getDirectMatches(myVocab, querystr, uncleaned, type);\n\t\t\n\t\t// If there's a perfect match return it.\n\t\tif (results.size() == 1 && results.get(0).match){\n\t\t\treturn results;\n\t\t}else{\n\t\t\t// Otherwise, add the initial ones and try matching\n\t\t\t// based on distance to vocabulary terms.\n\t\t\tresults.addAll(distanceMatching(query, myVocab));\n\t\t\t\n\t\t\t// Split the original query term by space and non-alphanumeric characters \n\t\t\t// to find how many words there are.\n\t\t\t//querystr = query.getQuery().replaceAll(\"[\\\\W_]\", \" \");\n\t\t\tString [] termList = querystr.split(\" \");\n\t\t\t\n\t\t\t// if there's more than one, run bagOfWords\n\t\t\t// which tries to find a match for each of the words.\n\t\t\tif (termList.length > 1){\n\t\t\t\tresults.addAll(bagOfWords(query, myVocab));\n\t\t\t}\n\t\t}\n\t\t\n\t\t// Clean the results: no duplicates\n\t\t// no extra results to return, and sorted\n\t\t// them by score before returning them\n\t\tresults = removeDuplicates(results);\n\t\t\n\t\t// They do not need to be reduced in \n\t\t// number if there are fewer than \n\t\t// the max results.\n\t\t// The pruneResults sorts them\n\t\t// by score already.\n\t\tif(query.getLimit()!=null){\n\t\t\tresults = pruneResults(results,Integer.parseInt(query.getLimit()));\n\t\t}else{\n\t\t\tresults = pruneResults(results,MAX_RESULTS);\n\t\t}\n\t\t\t\n\t\tresults = sortByScore(results);\n\t\tfor (int i = 0; i< results.size(); i++){\n//\t\t\tmyLogger.log(Level.SEVERE,results.get(i).getScore()+ \" is bigger than 100?\");\n\t\t\tif(results.get(i).getScore() > (double)100){\n\t\t\t\tresults.get(i).setScore((double)100 - (results.get(i).getScore()-(double)100));\n//\t\t\t\tmyLogger.log(Level.SEVERE,results.get(i).getScore()+\" is bigger than 100! and was set to \"+\n//\t\t\t\t\t\t((double)100 - (results.get(i).getScore()-(double)100)));\n\t\t\t}\n\t\t}\n\t\treturn results;\n\t}","private String keywordFound(){\r\n\t\tString rtn = \"\";\r\n\t\tString tmp = \"\";\r\n\t\tint carr_pos = getCaretPosition();\r\n\t\t//estract part of text for keyword search\r\n\t\ttry { \r\n\t\tif(carr_pos>50)\r\n\t\t\ttmp = doc.getText(carr_pos-50,50);\r\n\t\telse\r\n\t\t\ttmp = doc.getText(0,carr_pos);\r\n\t\t}catch(BadLocationException a){\r\n\t\t\tSystem.out.println(\"exception\");\r\n\t\t\treturn rtn;\r\n\t\t};\r\n\t\t//Start check\r\n\t\tint i = 0;\r\n\t\tif(tmp.length() >= 2)i = tmp.length()-2;\t\r\n\t\twhile(checkOperator(tmp.charAt(i)) && i > 0){\r\n\t\t\trtn += tmp.charAt(i);\r\n\t\t\ti--;\r\n\t\t}\r\n\t\tif(i == 0)rtn += tmp.charAt(i);\t\t\r\n\t\treturn mirrorString(rtn);\r\n\t}","@Override\n public List<Document> search(String string)\n { \n ArrayList<ArrayList> data = new ArrayList<ArrayList>();\n data.add(new ArrayList<Document>()); //documents\n data.add(new ArrayList<Double>()); //relevance\n data.add(new ArrayList<Integer>()); //occurrence\n data.add(new ArrayList<Integer>()); //popularity\n \n ParseTree tree = new ParseTree(this);\n \n String inputarray[]= StringUtils.split(string); //Splits the query on \" \" \n if(inputarray.length == 0)\n {\n errorMsg();\n return null;\n }\n \n for(int i = 0; i<inputarray.length; i++) //Inserts the operators/operands in the parsetree.\n {\n tree.insert(inputarray[i]);\n }\n data = tree.execute(); //executes the parsetree (the difference operations\n //are executed and data is returned.\n this.infix = tree.getInfix(); //gets the infix-notation.\n\n if(data != null)\n {\n return data.get(0);\n }\n return null;\n }","@Override\r\n\tpublic SearchableTeletextPage[] getPagesWithText(String query) {\n\t\treturn null;\r\n\t}","private void termQuerySearch(String[] terms) {\n for (String term : terms) {\n LinkedList<TermPositions> postingLists = indexMap.get(analyzeTerm(term));\n if (postingLists != null) {\n for (TermPositions matches : postingLists) {\n double score = (double) 1 + Math.log((double) matches.getPositionList().size()) *\n Math.log((double) N / (double) postingLists.size());\n resultsCollector.add(new DocCollector(matches.getDocId(), score));\n }\n }\n }\n }","@Override\n\tpublic List<ScoredTextDocument> search(String query) {\n\t\tList<ScoredTextDocument> scored = new ArrayList<>();\n\t\tDirectory dir = null;\n\n\t\tStandardAnalyzer analyzer = new StandardAnalyzer(Version.LUCENE_35);\n\n\t\tQuery q;\n\t\ttry {\n\t\t\tq = new QueryParser(Version.LUCENE_35, Utils.STR_CONTENT, analyzer).parse(query);\n\t\t} catch (ParseException ex) {\n\t\t\tLogger.getLogger(LuceneSearcher.class.getName()).log(Level.SEVERE, null, ex);\n\t\t\tSystem.out.println(\"Error en LuceneSearcher\");\n\t\t\treturn null;\n\t\t}\n\t\tTopDocs top;\n\t\ttry {\n\t\t\t//Finds the top n hits for query.\n\t\t\ttop = this.indexSearcher.search(q, null, this.indexSearcher.maxDoc());\n\t\t} catch (IOException ex) {\n\t\t\tLogger.getLogger(LuceneSearcher.class.getName()).log(Level.SEVERE, null, ex);\n\t\t\tSystem.out.println(\"Error en LuceneSearcher\");\n\t\t\treturn null;\n\t\t}\n\n\t\tfor (ScoreDoc d : top.scoreDocs) {\n\t\t\tDocument aux = null;\n\t\t\ttry {\n\t\t\t\t//aux=reader.document(top.scoreDocs[j].doc);\n\t\t\t\taux = this.indexSearcher.doc(d.doc);\n\t\t\t} catch (IOException ex) {\n\t\t\t\tLogger.getLogger(LuceneSearcher.class.getName()).log(Level.SEVERE, null, ex);\n\t\t\t}\n\t\t\tif (aux == null) {\n\t\t\t\tcontinue;\n\t\t\t}\n\t\t\tString docPath = aux.getFieldable(Utils.DOC_STR_NAME).stringValue();\n\t\t\tScoredTextDocument textdoc = new ScoredTextDocument(docPath, d.score);\n\t\t\tscored.add(textdoc);\n\t\t}\n\t\tCollections.sort(scored);\n\n\t\treturn scored;\n\t}","public void SearchPhrase(Object_Ord temp) {\n\tif (!Doneloading) {\r\n\t return;\r\n\t}\r\n\tif (temp == null) {\r\n\t return;\r\n\t} else if (temp.Ordet.equals(\"\")) {\r\n\t return;\r\n\t}\r\n\ttemp.Set_Searched();\r\n\t//PrintAction( this.getClass().toString() + \" Searching for phrase \" + temp.Ordet );\r\n\tThread thread = new Thread_PhraseSearcher(this, temp);\r\n\tThreadsRunning++;\r\n\tThreadsStarted++;\r\n }","List<DataTerm> search(String searchTerm);","protected Query analyzePhrase(String field, TokenStream stream, int slop) throws IOException {\n PhraseQuery.Builder builder = new PhraseQuery.Builder();\n builder.setSlop(slop);\n\n TermToBytesRefAttribute termAtt = stream.getAttribute(TermToBytesRefAttribute.class);\n BoostAttribute boostAtt = stream.addAttribute(BoostAttribute.class);\n PositionIncrementAttribute posIncrAtt = stream.getAttribute(PositionIncrementAttribute.class);\n int position = -1;\n float phraseBoost = DEFAULT_BOOST;\n stream.reset();\n while (stream.incrementToken()) {\n if (enablePositionIncrements) {\n position += posIncrAtt.getPositionIncrement();\n } else {\n position += 1;\n }\n builder.add(new Term(field, termAtt.getBytesRef()), position);\n phraseBoost *= boostAtt.getBoost();\n }\n PhraseQuery query = builder.build();\n if (phraseBoost == DEFAULT_BOOST) {\n return query;\n }\n return new BoostQuery(query, phraseBoost);\n }","private ScoreDoc[] searchExec (Query query) {\n\n ScoreDoc[] hits = null;\n\n try {\n IndexReader reader = DirectoryReader.open(indexDir);\n IndexSearcher searcher = new IndexSearcher(reader);\n TopDocs docs = searcher.search(query, hitsPerPage, new Sort(SortField.FIELD_SCORE)); //search(query, docs);\n hits = docs.scoreDocs;\n } catch (IOException e) {\n e.printStackTrace();\n }\n\n return hits;\n }","public void search() {\n try {\n for(int i = 0; i < this.queries.size(); i++){\n search(i);\n // in case of error stop\n if(!this.searchOK(i)){\n System.out.println(\"\\t\" + new Date().toString() + \" \" + db + \" Search for rest queries cancelled, because failed for query \" + i + \" : \" + this.queries.get(i));\n break;\n }\n }\n } catch (UnsupportedEncodingException ex) {\n Logger.getLogger(EntrezSearcher.class.getName()).log(Level.SEVERE, null, ex);\n }\n }","private ArrayList<WordDocument> executeAdvancedQuery(){\n ArrayList<WordDocument> documents = customDijkstrasTwoStack(this.query.split(\" \"));\n ArrayList<WordDocument> result = new ArrayList<WordDocument>();\n\n try{\n String[] orderByPart = query.substring(query.indexOf(\"ORDERBY\")).trim().toLowerCase().split(\" \");\n if(isOrderByCommand(orderByPart[0]))\n result = orderBy(documents, orderByPart[1], orderByPart[2]);\n }catch (StringIndexOutOfBoundsException ex){\n result = documents;\n }\n\n return result;\n }","public interface DocumentRelatedTermsSearcher {\n List<ScoredTerm> getDocumentRelatedTerms(int docId, String term) throws SearchException;\n}","@Test\n public void testCase3 () throws IOException {\n //\t\tlog.trace(\"Testcase3\");\n sq = new SpanSegmentQuery(new SpanTermQuery(new Term(\"base\", \"s:d\")),\n new SpanTermQuery(new Term(\"base\", \"s:b\")));\n\n kr = ki.search(sq, (short) 10);\n ki.close();\n\n assertEquals(\"totalResults\", kr.getTotalResults(), 1);\n assertEquals(\"doc-number\", 2, kr.getMatch(0).getLocalDocID());\n assertEquals(\"StartPos (0)\", 1, kr.getMatch(0).startPos);\n assertEquals(\"EndPos (0)\", 2, kr.getMatch(0).endPos);\n }","public void search() {\n String q = this.query.getText();\n String cat = this.category.getValue();\n if(cat.equals(\"Book\")) {\n searchBook(q);\n } else {\n searchCharacter(q);\n }\n }","CampusSearchQuery generateQuery();","@Override\n\tprotected void executeSearch(String term) {\n\t\t\n\t}","@Override\n public List<SearchResult> search(String queryString, int k) {\n // TODO: YOUR CODE HERE\n\n // Tokenize the query and put it into a Set\n HashSet<String> tokenSet = new HashSet<>(Searcher.tokenize(queryString));\n\n /*\n * Section 1: FETCHING termId, termFreq and relevant docId from the Query\n */\n\n // Init a set to store Relevant Document Id\n HashSet<Integer> relevantDocIdSet = new HashSet<>();\n for (String token : tokenSet) { // Iterates thru all query tokens\n int termId;\n try {\n termId = indexer.getTermDict().get(token);\n } catch (NullPointerException e) { // In case current token is not in the termDict\n continue; // Skip this one\n }\n // Get the Posting associate to the termId\n HashSet<Integer> posting = indexer.getPostingLists().get(termId);\n relevantDocIdSet.addAll(posting); // Add them all to the Relevant Document Id set\n }\n\n /*\n * Section 2: Calculate Jaccard Coefficient between the Query and all POTENTIAL DOCUMENTS\n */\n\n // ArrayList for the Final Result\n ArrayList<SearchResult> searchResults = new ArrayList<>();\n for (Document doc : documents) { // Iterates thru all documents\n if (!relevantDocIdSet.contains(doc.getId())) { // If the document is relevant\n searchResults.add(new SearchResult(doc, 0)); // Add the document as a SearchResult with zero score\n } else {\n HashSet<String> termIdSet = new HashSet<>(doc.getTokens()); // Get the token set from the document\n\n // Calculate Jaccard Coefficient of the document\n double jaccardScore = JaccardMathHelper.calculateJaccardSimilarity(tokenSet, termIdSet);\n\n // Add the SearchResult with the computed Jaccard Score\n searchResults.add(new SearchResult(doc, jaccardScore));\n }\n }\n\n return TFIDFSearcher.finalizeSearchResult(searchResults, k);\n }","public String[] searchIndex(Directory ramdir, Query query) \n\t\t\tthrows Exception {\n\t\tSortedMap<Float,String> sentenceMap = \n\t\t\t\tnew TreeMap<Float,String>();\n\t\tIndexReader indexReader = DirectoryReader.open(ramdir);\n\t\tIndexSearcher indexSearcher = new IndexSearcher(indexReader);\n\t\tBM25Similarity similarity = new BM25Similarity(1.2f, 100f);\n\n\t\tindexSearcher.setSimilarity(similarity);\n\t\tTopDocs topDocs = indexSearcher.search(query, this.numSentences);\n\n\t\tfor (ScoreDoc scoreDoc : topDocs.scoreDocs) {\n\n\t\t\t// System.out.println(scoreDoc.score)\n\t\t\tint docId = scoreDoc.doc;\n\t\t\t//System.out.println(searcher.explain(query, docId));\n\t\t\tDocument doc = indexSearcher.doc(docId);\n\t\t\t// System.out.println(sentences.get(docId));\n\t\t\tSystem.out.println(doc.get(\"content\"));\n\n\t\t\t// System.out.println(doc.get(\"text\"));\n\n\t\t\t// if(scoreDoc.score>=0.1F){\n\n\t\t\tsentenceMap.put((float) scoreDoc.doc, \">> \"+StringUtils.chomp(doc.get(\"content\")));\n\t\t\t//sentenceMap.put(1/scoreDoc.score,sentences.get(docId));\n\t\t\t// System.out.println(scoreDoc);\n\t\t\t// System.out.println(StringUtils.chomp(doc.get(\"text\")));\n\t\t\t// }\n\t\t}\n\n\t\treturn sentenceMap.values().toArray(new String[0]);\n\n\t}","public List<Document> SearchField(String queryStr ,List<String> fieldName)\r\n\t{\r\n\t\treturn null;\r\n\t}","@Override\r\n\t\t\tpublic List<ScoredDocument> search(Query query, long maxNumberOfDocuments) {\n\t\t\t\treturn null;\r\n\t\t\t}","public static void doPagingSearch(BufferedReader in, IndexSearcher searcher, Query query,\n int hitsPerPage, boolean raw, boolean interactive) throws IOException {\n TopDocs results = searcher.search(query, 5 * hitsPerPage);\n ScoreDoc[] hits = results.scoreDocs;\n\n int numTotalHits = results.totalHits;\n System.out.println(numTotalHits + \" total matching documents\");\n\n int start = 0;\n int end = Math.min(numTotalHits, hitsPerPage);\n\n while (true) {\n if (end > hits.length) {\n //System.out.println(\"Only results 1 - \" + hits.length + \" of \" + numTotalHits + \" total matching documents collected.\");\n //System.out.println(\"Collect more (y/n) ?\");\n String line = in.readLine();\n if (line.length() == 0 || line.charAt(0) == 'n') {\n break;\n }\n hits = searcher.search(query, numTotalHits).scoreDocs;\n }\n\n end = Math.min(hits.length, start + hitsPerPage);\n\n for (int i = start; i < end; i++) {\n if (raw) {\n System.out.println(\"doc=\" + hits[i].doc + \" score= \" + hits[i].score);\n continue;\n }\n\n Document doc = searcher.doc(hits[i].doc);\n String path = doc.get(\"path\");\n if (path != null) {\n System.out.println((i + 1) + \". \" + path);\n String title = doc.get(\"title\");\n if (title != null) {\n System.out.println(\" Title: \" + doc.get(\"title\"));\n }\n } else {\n System.out.println((i + 1) + \". \" + \"No path for this document\");\n }\n }\n\n if (!interactive || end == 0) {\n break;\n }\n\n if (numTotalHits >= end) {\n boolean quit = false;\n while (true) {\n System.out.print(\"Press \");\n if (start - hitsPerPage >= 0) {\n System.out.print(\"(p)revious page, \");\n }\n if (start + hitsPerPage < numTotalHits) {\n System.out.print(\"(n)ext page, \");\n }\n System.out.println(\"(q)uit or enter number to jump to a page.\");\n\n String line = in.readLine();\n if (line.length() == 0 || line.charAt(0) == 'q') {\n quit = true;\n break;\n }\n if (line.charAt(0) == 'p') {\n start = Math.max(0, start - hitsPerPage);\n break;\n } else if (line.charAt(0) == 'n') {\n if (start + hitsPerPage < numTotalHits) {\n start += hitsPerPage;\n }\n break;\n } else {\n int page = Integer.parseInt(line);\n if ((page - 1) * hitsPerPage < numTotalHits) {\n start = (page - 1) * hitsPerPage;\n break;\n } else {\n System.out.println(\"No such page\");\n }\n }\n }\n if (quit) break;\n end = Math.min(numTotalHits, start + hitsPerPage);\n }\n }\n }","public List<String> findPhrases() {\n\t\t\n\t\tTrie root = new Trie();\n\t\tList<String> result = new ArrayList<>();\n\t\tQueue<TrieNode> queue = new LinkedList<>();\n\n\t\tfor (String phrase : phrases) {\n\t\t\t// build the trie\n\t\t\t\n\t\t\troot.insert(phrase);\n\t\t}\n\t\t\n\t\t// initialize the queue\n\t\tqueue.offer(root.getRootNode());\n\t\t\t\t\n\t\tfor (String word : stream) {\n\t\t\t\n\t\t\t// Search one word at a time and store TrieNodes that match this word.\n\t\t\t// If the current word extends a previous TrieNode, it may be a matching phrase\n\t\t\t\n\t\t\t// buffer to store current matches\n\t\t\tQueue<TrieNode> buffer = new LinkedList<>();\n\t\t\t\n\t\t\twhile(!queue.isEmpty()) {\n\t\t\t\t// iterate through previous matches\n\t\t\t\t\n\t\t\t\tTrieNode next = queue.poll().find(word);\n\t\t\t\t\n\t\t\t\tif (next != null) {\n\t\t\t\t\t\n\t\t\t\t\t// if this word extends the previous word, add it to the buffer\n\t\t\t\t\t// in case the next word can also extend it\n\t\t\t\t\t\n\t\t\t\t\tbuffer.offer(next);\n\t\t\t\t\t\n\t\t\t\t\tif (next.isPhrase()) {\n\t\t\t\t\t\t// if we found a valid phrase node, add it to the result\t\n\t\t\t\t\t\t\n\t\t\t\t\t\tresult.add(next.getPhrase());\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t\t\n\t\t\t}\n\t\t\t\n\t\t\tqueue = buffer;\n\t\t\tqueue.offer(root.getRootNode());\n\t\t}\n\t\t\n\t\treturn result;\n\t}","protected final void searchForText() {\n Logger.debug(\" - search for text\");\n final String searchText = theSearchEdit.getText().toString();\n\n MultiDaoSearchTask task = new MultiDaoSearchTask() {\n @Override\n protected void onSearchCompleted(List<Object> results) {\n adapter.setData(results);\n }\n\n @Override\n protected int getMinSearchTextLength() {\n return 0;\n }\n };\n task.readDaos.add(crDao);\n task.readDaos.add(monsterDao);\n task.readDaos.add(customMonsterDao);\n task.execute(searchText.toUpperCase());\n }","List<SearchResult> search(SearchQuery searchQuery);","public PostingsList phrase_query(PostingsList l1, PostingsList l2){\n\n PostingsList phrase = new PostingsList();\n\n // Counters to iterate docIDs\n int count1 = 0;\n int count2 = 0;\n // Counters to iterate positional indices\n int subcount1 = 0;\n int subcount2 = 0;\n\n // First posting\n PostingsEntry p1 = l1.get(0);\n PostingsEntry p2 = l2.get(0);\n\n // List of positional indices (changes at each iteration)\n LinkedList<Integer> ll1;\n LinkedList<Integer> ll2;\n\n // Used to store positional index\n int pp1;\n int pp2;\n\n while(true){\n // docID match (1/2) //\n if (p1.docID == p2.docID){\n // Obtain list of positional indices\n ll1 = p1.positions;\n ll2 = p2.positions;\n // First positional indices\n pp1 = ll1.get(0);\n pp2 = ll2.get(0);\n // Initialize counter\n subcount1 = 0;\n subcount2 = 0;\n\n // Search if the phrase exists\n while(true){\n // Match, consecutive words (2/2) - EUREKA! //\n if (pp1+1 == pp2){\n // Save found match (docID and positional index of last\n // word)\n phrase.insert(p1.docID, pp2);\n // Increase counters and pos indices if list is not finished\n subcount1++;\n subcount2++;\n if (subcount1<ll1.size() && subcount2<ll2.size()){\n pp1 = ll1.get(subcount1);\n pp2 = ll2.get(subcount2);\n }\n // If list finished, break\n else\n break;\n }\n // Not match\n else if (pp1+1 < pp2){\n subcount1++;\n if (subcount1<ll1.size())\n pp1 = ll1.get(subcount1);\n // If list finished, break\n else\n break;\n }\n // Not match\n else{\n subcount2++;\n if (subcount2<ll2.size())\n pp2 = ll2.get(subcount2);\n else\n break;\n }\n }\n\n // Once we finished looking at the list of positional indices of one\n // posting, increase counters and go to next postings (if there are)\n count1++;\n count2++;\n if (count1<l1.size() && count2<l2.size()){\n p1 = l1.get(count1);\n p2 = l2.get(count2);\n }\n else{\n break;\n }\n }\n // docID not match, increase lowest counter\n else if (p1.docID < p2.docID){\n count1++;\n if (count1<l1.size()){\n p1 = l1.get(count1);\n }\n else{\n break;\n }\n }\n // docID not match, increase lowest counter\n else{\n count2++;\n if (count2<l2.size()){\n p2 = l2.get(count2);\n }\n else{\n break;\n }\n }\n }\n\n return phrase;\n }","Page<NoteDTO> search(String query, Pageable pageable);","public List<SearchResultDocument> getSearchResults(String query) throws IOException, ParseException {\n return luceneIndexer.getSearchResults(query);\n }","public abstract Search defaultSearch(StringBuilder sb);","@Override\n\tpublic NodeIterator search(String queryString) throws Exception {\n\t\treturn null;\n\t}","@Query(\"name = ?\")\n List<PersonDocument> findByName(String name);","public HashMap<String, Double> search(String query) {\n // ===================================================\n // 1. Fetch all inverted lists corresponding to terms\n // in the query.\n // ===================================================\n String[] terms = query.split(\" \");\n HashMap<String, Integer> qf = new HashMap<String, Integer>();\n // Calculate term frequencies in the query\n for (String term : terms) {\n if (qf.containsKey(term))\n qf.put(term, qf.get(term) + 1);\n else\n qf.put(term, 1);\n }\n HashMap<String, Double> docScore = new HashMap<String, Double>();\n for (Entry<String, Integer> termEntry : qf.entrySet()) {\n String term = termEntry.getKey();\n int qfi = termEntry.getValue();\n\n // ===================================================\n // 2. Compute BM25 scores for documents in the lists.\n // Make a score list for documents in the inverted\n // lists. Assume that no relevance information is \n // available. For parameters, use k1=1.2, b=0.75, \n // k2=100.\n // ===================================================\n double k1 = 1.2;\n double b = 0.75;\n double k2 = 100;\n int ni = invIndex.get(term).size();\n\n\n for (Entry<String, IndexEntry> invListEntry : invIndex.get(term).entrySet()) {\n String docID = invListEntry.getKey();\n double bm25Score;\n if (docScore.containsKey(docID))\n bm25Score = docScore.get(docID);\n else\n bm25Score = 0;\n\n // length of the document\n int dl = docStat.get(docID);\n // frequency of the term in the document\n int fi = invListEntry.getValue().getTf();\n double K = k1 * ((1 - b) + b * ((double) dl / avdl));\n\n // ===================================================\n // 3. Accumulate scores for each term in a query\n // on the score list.\n // ===================================================\n bm25Score += Math.log((N - ni + 0.5) / (ni + 0.5))\n * (((k1 + 1) * fi * (k2 + 1) * qfi) / ((K + fi) * (k2 + qfi)));\n docScore.put(docID, bm25Score);\n }\n }\n\n return docScore;\n }","abstract public void search();","MongoCursor<Document> findByPersonName(String personName);","private ArrayList<WordDocument> getDocumentsWhereWordExists(String word){\n try{\n return dictionary.get(word).getDocumentWhereWordExistsIn();\n }catch (NullPointerException ex){\n return new ArrayList<WordDocument>();\n }\n }","@Override\n public List<DefinitionDTO> findWordsByWord(String query) {\n List<Word> words = wordRepository.findBySearchString(query);\n return DTOMapper.mapWordListToDefinitionDTOList(words);\n }","List<Corretor> search(String query);","public void doSearch(BufferedReader in, IndexSearcher searcher, Query query, \n int hitsPerPage, boolean raw, boolean interactive) throws IOException {\n TopDocs results = searcher.search(query, 5 * hitsPerPage);\n ScoreDoc[] hits = results.scoreDocs;\n \n int numTotalHits = results.totalHits;\n System.out.println(numTotalHits + \" total matching documents\");\n\n int start = 0;\n int end = Math.min(numTotalHits, hitsPerPage);\n \n for (int i = start; i < end; i++) \n {\n Document doc = searcher.doc(hits[i].doc);\n String id = doc.get(\"id\");\n String author=doc.get(\"author\");\n String price=doc.get(\"price\");\n String category=doc.get(\"category\");\n String bookname=doc.get(\"bookname\");\n System.out.println(id+author+price+category+bookname);\n }\n }","static void allDocumentAnalyzer() throws IOException {\n\t\tFile allFiles = new File(\".\"); // current directory\n\t\tFile[] files = allFiles.listFiles(); // file array\n\n\t\t// recurse through all documents\n\t\tfor (File doc : files) {\n\t\t\t// other files we don't need\n\t\t\tif (doc.getName().contains(\".java\") || doc.getName().contains(\"words\") || doc.getName().contains(\"names\")\n\t\t\t\t\t|| doc.getName().contains(\"phrases\") || doc.getName().contains(\".class\")\n\t\t\t\t\t|| doc.getName().contains(\"Data\") || doc.getName().contains(\".sh\") || doc.isDirectory()\n\t\t\t\t\t|| !doc.getName().contains(\".txt\")) {\n\t\t\t\tcontinue;\n\t\t\t}\n\n\t\t\tString name = doc.getName();\n\t\t\tSystem.out.println(name);\n\t\t\tname = name.substring(0, name.length() - 11);\n\t\t\tSystem.out.println(name);\n\n\t\t\tif (!names.contains(name)) {\n\t\t\t\tcontinue;\n\t\t\t}\n\n\t\t\t// make readers\n\t\t\tFileReader fr = new FileReader(doc);\n\t\t\tBufferedReader br = new BufferedReader(fr);\n\n\t\t\t// phrase list\n\t\t\tArrayList<String> words = new ArrayList<String>();\n\n\t\t\t// retrieve all text, trim, refine and add to phrase list\n\t\t\tString nextLine = br.readLine();\n\t\t\twhile (nextLine != null) {\n\t\t\t\tnextLine = nextLine.replace(\"\\n\", \" \");\n\t\t\t\tnextLine = nextLine.trim();\n\n\t\t\t\tif (nextLine.contains(\"no experience listed\")) {\n\t\t\t\t\tbreak;\n\t\t\t\t}\n\n\t\t\t\tString[] lineArray = nextLine.split(\"\\\\s+\");\n\n\t\t\t\t// recurse through every word to find phrases\n\t\t\t\tfor (int i = 0; i < lineArray.length - 1; i++) {\n\t\t\t\t\t// get the current word and refine\n\t\t\t\t\tString currentWord = lineArray[i];\n\n\t\t\t\t\tcurrentWord = currentWord.trim();\n\t\t\t\t\tcurrentWord = refineWord(currentWord);\n\n\t\t\t\t\tif (currentWord.equals(\"\") || currentWord.isEmpty()) {\n\t\t\t\t\t\tcontinue;\n\t\t\t\t\t}\n\n\t\t\t\t\twords.add(currentWord);\n\t\t\t\t}\n\t\t\t\tnextLine = br.readLine();\n\t\t\t}\n\n\t\t\tbr.close();\n\n\t\t\t// continue if empty\n\t\t\tif (words.size() == 0) {\n\t\t\t\tcontinue;\n\t\t\t}\n\n\t\t\t// otherwise, increment number of files in corpus\n\t\t\tsize++;\n\n\t\t\t// updating the phrase count map for tf\n\t\t\tString fileName = doc.getName();\n\t\t\tphraseCountMap.put(fileName, words.size());\n\n\t\t\t// recurse through every word\n\t\t\tfor (String word : words) {\n\t\t\t\t// get map from string to freq\n\t\t\t\tHashMap<String, Integer> textFreqMap = wordFreqMap.get(fileName);\n\n\t\t\t\t// if it's null, make one\n\t\t\t\tif (textFreqMap == null) {\n\t\t\t\t\ttextFreqMap = new HashMap<String, Integer>();\n\t\t\t\t\t// make freq as 1\n\t\t\t\t\ttextFreqMap.put(word, 1);\n\t\t\t\t\t// put that in wordFreq\n\t\t\t\t\twordFreqMap.put(fileName, textFreqMap);\n\t\t\t\t} else {\n\t\t\t\t\t// otherwise, get the current num\n\t\t\t\t\tInteger currentFreq = textFreqMap.get(word);\n\n\t\t\t\t\t// if it's null,\n\t\t\t\t\tif (currentFreq == null) {\n\t\t\t\t\t\t// the frequency is just 0\n\t\t\t\t\t\tcurrentFreq = 0;\n\t\t\t\t\t}\n\n\t\t\t\t\t// increment the frequency\n\t\t\t\t\tcurrentFreq++;\n\n\t\t\t\t\t// put it in the textFreqMap\n\t\t\t\t\ttextFreqMap.put(word, currentFreq);\n\n\t\t\t\t\t// put that in the wordFreqMap\n\t\t\t\t\twordFreqMap.put(fileName, textFreqMap);\n\t\t\t\t}\n\n\t\t\t\t// add this to record (map from phrases to docs with that\n\t\t\t\t// phrase)\n\t\t\t\tinvertedMap.addValue(word, doc);\n\t\t\t}\n\t\t}\n\t}","public void search() {\r\n \t\r\n }","private void searchWord()\n {\n String inputWord = searchField.getText();\n \n if(inputWord.isEmpty())\n queryResult = null;\n \n else\n {\n char firstLetter = inputWord.toUpperCase().charAt(0);\n \n for(int i = 0 ; i < lexiNodeTrees.size() ; i++)\n {\n if(lexiNodeTrees.get(i).getCurrentCharacter() == firstLetter)\n {\n queryResult = lexiNodeTrees.get(i).searchWord(inputWord, false);\n i = lexiNodeTrees.size(); // escape the loop\n }\n }\n }\n \n // update the list on the GUI\n if(queryResult != null)\n {\n ArrayList<String> words = new ArrayList<>();\n for(WordDefinition word : queryResult)\n {\n words.add(word.getWord());\n }\n \n // sort the list of words alphabetically \n Collections.sort(words);\n \n // display the list of wordsin the UI\n DefaultListModel model = new DefaultListModel();\n for(String word : words)\n {\n model.addElement(word);\n }\n\n this.getSearchSuggestionList().setModel(model);\n }\n \n else\n this.getSearchSuggestionList().setModel( new DefaultListModel() );\n }","private List<FindResult> findOnPage(int page) {\n\t\t\tif (this.text == null) throw new IllegalStateException(\"text cannot be null\");\n\t\t\treturn this.parent.pdf.find(this.text, page);\n\t\t}","public void searchIndex(Directory index) throws Exception{\n\t\tString searchString = getSearchString();\n\t\t\n\t\tSystem.out.println(\"Searching for '\" + searchString + \"'\");\n\n\t\tIndexReader indexReader = DirectoryReader.open(index);\n\t\tIndexSearcher indexSearcher = new IndexSearcher(indexReader);\n\n\t\tAnalyzer analyzer = new StandardAnalyzer();\n\t\t\n\t\tString query_string = \"title:\" + searchString + \" OR content:\" + searchString + \"OR important:\" + searchString + \"OR h1:\" + searchString +\n\t\t\t\t\"OR h2:\" + searchString + \"OR h3:\" + searchString + \"OR h4:\" + searchString + \"OR h5:\" + searchString + \"OR h6:\" + searchString;\n\t\tQueryParser queryParser = new QueryParser(\"title\", analyzer);\n\t\t\n\t\tTopDocs docs = indexSearcher.search(queryParser.parse(query_string), 10);\n\t\t\n\t\t\n//\t\tString[] fields = {\"content\", \"title\", \"important\", \"h1\", \"h2\", \"h3\", \"h4\", \"h5\", \"h6\"};\n//\t\tBooleanClause.Occur[] flags = \n//\t\t{\n//\t\t\tBooleanClause.Occur.SHOULD,\n//\t\t\tBooleanClause.Occur.SHOULD,\n//\t\t\tBooleanClause.Occur.SHOULD,\n//\t\t\tBooleanClause.Occur.SHOULD,\n//\t\t\tBooleanClause.Occur.SHOULD,\n//\t\t\tBooleanClause.Occur.SHOULD,\n//\t\t\tBooleanClause.Occur.SHOULD,\n//\t\t\tBooleanClause.Occur.SHOULD,\n//\t\t\tBooleanClause.Occur.SHOULD,\n// };\n//\t\t\n//\t\tTopDocs docs = indexSearcher.search(MultiFieldQueryParser.parse(searchString, fields, flags, analyzer), 10);\n\n\t\tScoreDoc[] hits = docs.scoreDocs;\n\n\t System.out.println(\"Found \" + hits.length + \" hits.\");\n\t for(int i=0;i<hits.length;++i) {\n\t \tint docId = hits[i].doc;\n\t Document d = indexSearcher.doc(docId);\n\t System.out.println((i + 1) + \". \" + d.get(\"title\") + \"\\t\" + d.get(\"url\") + \"\\t\" + hits[i].score);\n\t }\n\t}","@Test\n\tpublic void testKeywordQuery(){\n\t\t//manager.getResponse(\"american football \"); //match multiple keywords\n//\t\tmanager.getResponse(\"list of Bond 007 movies\");\n//\tmanager.getResponse(\"Disney movies\");\n\t\t//manager.keywordQuery(\"Paul Brown Stadium location\");\n\t\t//manager.keywordQuery(\"0Francesco\");\n System.out.println(\"******* keyword query *******\");\n\t\t//manager.keywordQuery(\"sportspeople in tennis\");\n\t\t//manager.keywordSearch(\"list of movies starring Sean Connery\",ElasticIndex.analyzed,100 );\n//\t\tmanager.keywordSearch(\"movies starring Sean Connery\",ElasticIndex.notStemmed,100 );\n// manager.keywordSearch(\"musical movies tony award\",ElasticIndex.analyzed,100 );\n// manager.keywordSearch(\"movies directed by Woody Allen\",ElasticIndex.analyzed,100 );\n// manager.keywordSearch(\"United states professional sports teams\",ElasticIndex.analyzed,100 );\n// manager.keywordSearch(\"computer games developed by Ubisoft\",ElasticIndex.analyzed,100 );\n// manager.keywordSearch(\"computer games developed by Ubisoft\",ElasticIndex.notStemmed,100 );\n// manager.keywordSearch(\"movies academy award nominations\",ElasticIndex.notStemmed,100 );\n System.out.println(SearchResultUtil.toSummary(manager.keywordSearch(\"movies directed by Woody Allen\",ElasticIndex.notLowercased,20 )));\n //manager.keywordSearch(\"grammy best album in 2012\",ElasticIndex.notAnalyzed,100 );\n //(better than analyzed) manager.keywordSearch(\"grammy best album in 2012\",ElasticIndex.notStemmed,100 );\n System.out.println(\"*****************************\");\n\n\t\t//manager.keywordQuery(\"Disney movies\");\n\t}","List<PilotContainer> Search(String cas, String word);","@Test\n public void findsByKeyword() throws Exception {\n final Base base = new DyBase(\n this.dynamo.region(), new MkSttc().counters().get(\"ttt\")\n );\n final Book book = base.books().add(\n \"@book{best2014, author=\\\"Walter\\\"}\"\n );\n final Quotes quotes = base.quotes();\n quotes.add(\n book, \"never give up and never think about bad things, Bobby\",\n \"99-101, 256-257, 315\"\n );\n MatcherAssert.assertThat(\n quotes.refine(\"bobby\").iterate(),\n Matchers.<Quote>iterableWithSize(1)\n );\n MatcherAssert.assertThat(\n quotes.refine(\"another-something\").iterate(),\n Matchers.<Quote>iterableWithSize(0)\n );\n }","@Override\n\tpublic List<Document> findDocumentsByQuestion(String question) {\n\t\t\n\t\tString [] keyWords = question.split(\" \");\n\t\tList<Document> documents = new ArrayList<>();\n\t\t\n\t\tList<Filters> filters = filtersRepository.findByCommonsWordsWordIn(keyWords);\n\t\tfor(Filters f : filters){\n\t\t\tdocuments.addAll(f.getDocuments());\n\t\t}\n\t\t\n\t\treturn documents;\n\t}","List<Cemetery> search(String query);","public List<Document> retrieveQuery( Query aQuery, int TopN ) throws IOException {\n\t\t// NT: you will find our IndexingLucene.Myindexreader provides method: docLength()\n\t\t// implement your retrieval model here, and for each input query, return the topN retrieved documents\n\t\t// sort the documents based on their relevance score, from high to low\n\n\t\tHashMap<Integer, HashMap<String,Integer>> idTokenDocFrequencyMap = new HashMap<>();\t//docid - (token - document frequency) map\n\t\tHashMap<String, Long> tokenColFrequencyMap = new HashMap<>();\t// token - collection frequency map\n\t\tString content = aQuery.GetQueryContent();\n\t\tString[] tokens = content.split(\" \");\n\n\t\tfor(String token : tokens){\n\t\t\ttokenColFrequencyMap.put(token, indexReader.CollectionFreq(token)); \t// update the second map\n\t\t\tint [][]postingList = indexReader.getPostingList(token);\n\t\t\tif(postingList == null) continue;\n\t\t\tfor(int i = 0; i < postingList.length; i++){\n\t\t\t\tint docid = postingList[i][0];\n\t\t\t\tint freq = postingList[i][1];\n\t\t\t\tif(idTokenDocFrequencyMap.containsKey(docid)){\t\t// update the first map\n\t\t\t\t\tidTokenDocFrequencyMap.get(docid).put(token,freq);\n\t\t\t\t}else {\n\t\t\t\t\tHashMap<String,Integer> tokenFrequencyMap = new HashMap<>();\n\t\t\t\t\ttokenFrequencyMap.put(token,freq);\n\t\t\t\t\tidTokenDocFrequencyMap.put(docid,tokenFrequencyMap);\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t\tdouble U = 2000.0;\n\t\tList<Document> documentList = new ArrayList<>();\n\t\t// if use a docidList, it will have some duplicates.\n\t\tfor(Map.Entry<Integer, HashMap<String,Integer>> entry : idTokenDocFrequencyMap.entrySet()){\n\t\t\tdouble score = 1.0;\t\t\t// each document have one score\n\t\t\tint docid = entry.getKey();\n\t\t\tint docLen = indexReader.docLength(docid);\t// get document length\n\t\t\tHashMap<String,Integer> tokenDocFrequencyMap = idTokenDocFrequencyMap.get(docid);\n\t\t\tfor(String token : tokens){\t\t// for each token, not the token just exist in the document\n\t\t\t\tlong colFreq = tokenColFrequencyMap.getOrDefault(token,0l);\t// get collection frequency\n\t\t\t\tif(colFreq != 0){\n\t\t\t\t\tint docFreq = 0;\t// if this document don't have token, just set document frequency as 0\n\t\t\t\t\tif(tokenDocFrequencyMap.containsKey(token)){\n\t\t\t\t\t\tdocFreq = tokenDocFrequencyMap.get(token);\n\t\t\t\t\t}\n\t\t\t\t\tscore = score * (docFreq + U * ((double)colFreq / colLen)) / (docLen + U);\t//equation\n\t\t\t\t}\n\t\t\t}\n\t\t\tDocument document = new Document(docid+\"\", indexReader.getDocno(docid),score);\n\t\t\tdocumentList.add(document);\n\t\t}\n\n\t\tCollections.sort(documentList, new Comparator<Document>() {\n\t\t\t@Override\n\t\t\tpublic int compare(Document o1, Document o2) {\n\t\t\t\treturn Double.compare(o2.score(),o1.score());\n\t\t\t}\n\t\t});\n\t\tList<Document> res = new ArrayList<>();\n\t\tfor(int i = 0 ; i < TopN; i++){\n\t\t\tres.add(documentList.get(i));\n\t\t}\n\t\treturn res;\n\t}","public static SearchQuery buildAutocompleteKnowledgeQuery(String searchWord) {\n\n BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery();\n boolQueryBuilder.should(QueryBuilders.matchQuery(\"nameNgram\", searchWord))\n .must(QueryBuilders.matchQuery(\"nameSimple\", searchWord));\n// boolQueryBuilder.must(QueryBuilders.matchQuery(\"nameNgram\", searchWord)).must(QueryBuilders.matchQuery(\"nameSimple\", searchWord));\n// boolQueryBuilder.should(QueryBuilders.matchQuery(\"nameNgram\", searchWord));\n\n return buildNativeQuery(boolQueryBuilder, 0, 20);\n }","private DocFile[] search (String[] queries, String[] filters, BooleanClause.Occur filterOccur) throws ParseException {\n // create a master query builder\n BooleanQuery.Builder masterQueryBuilder = new BooleanQuery.Builder();\n // loop through all queries\n for (String query : queries) {\n if (query.equals(\"\")) continue;\n // create a boolean query for the each query\n BooleanQuery.Builder queryBuilder = new BooleanQuery.Builder();\n // loop through all filters\n for (String filter : filters) {\n if (filter.equals(\"\")) continue;\n QueryParser parser = new QueryParser(filter, analyzer);\n parser.setAllowLeadingWildcard(true);\n if (!filter.equals(Constants.INDEX_KEY_OWNER)) {\n Query parsedQ = parser.parse(query);\n queryBuilder.add(parsedQ, filterOccur);\n }\n else {\n queryBuilder.add(new PhraseQuery(filter, queries), filterOccur);\n }\n }\n masterQueryBuilder.add(queryBuilder.build(), BooleanClause.Occur.SHOULD);\n }\n\n // build the masterQuery\n BooleanQuery masterQuery = masterQueryBuilder.build();\n\n return searchResponse(searchExec(masterQuery), masterQuery);\n }","Set<Document> findDocuments(Map<String, String> fields, int offset, int numberOfResults);","@Override\n public String search(String word) {\n return search(word, root);\n }","@Override\n public boolean onQueryTextSubmit(String query) {\n prepareBooks(engine.search(query.toLowerCase(),filter));\n return false;\n }","@Test\n public void testCase2 () throws IOException {\n //\t\tlog.trace(\"Testcase2\");\n sq = new SpanSegmentQuery(new SpanTermQuery(new Term(\"base\", \"s:a\")),\n new SpanTermQuery(new Term(\"base\", \"s:b\")));\n\n kr = ki.search(sq, (short) 10);\n ki.close();\n\n assertEquals(\"totalResults\", kr.getTotalResults(), 3);\n // Match #0\n assertEquals(\"doc-number\", 1, kr.getMatch(0).getLocalDocID());\n assertEquals(\"StartPos\", 1, kr.getMatch(0).startPos);\n assertEquals(\"EndPos\", 2, kr.getMatch(0).endPos);\n // Match #2\n assertEquals(\"doc-number\", 2, kr.getMatch(2).getLocalDocID());\n assertEquals(\"StartPos\", 2, kr.getMatch(2).startPos);\n assertEquals(\"EndPos\", 3, kr.getMatch(2).endPos);\n }","public abstract int search(String[] words, String wordToFind) throws ItemNotFoundException;","public void parseQueryStringAndSearch(String searchString) {\n char[] chars = searchString.toCharArray();\n for (int i = 0; i < chars.length; i++) {\n Queue<Character> queue;\n int k;\n if (Character.isDigit(chars[i])) {\n k = Integer.parseInt(String.valueOf(chars[i]));\n i++;\n queue = new LinkedList<>();\n while (i < chars.length && chars[i] != ')') {\n queue.add(chars[i]);\n i++;\n }\n i++;\n String query = queryToString(queue);\n String[] terms = query.split(\" \");\n //System.out.println(query + \" and k: \" + k);\n positionIntersects(indexMap.get(analyzeTerm(terms[0])), indexMap.get(analyzeTerm(terms[1])), k);\n } else {\n queue = new LinkedList<>();\n while (i < chars.length && !Character.isDigit(chars[i])) {\n queue.add(chars[i]);\n i++;\n }\n i--;\n String query = queryToString(queue);\n String[] terms = query.trim().split(\" \");\n termQuerySearch(terms);\n }\n\n }\n\n }","@Override\n public SearchDocument nextDocument(SearchQuery query, int docId) {\n return null;\n }","public void doSearch(String query)\n \t{\n \t\tlistener.onQueryTextSubmit(query);\n \t}","public void search() {\n }","private static String lookForSentenceWhichContains(String[] words, String documentPath) throws IOException {\r\n\r\n File document = new File(documentPath);\r\n\r\n if (!document.exists()) throw new FileNotFoundException(\"File located at \"+documentPath+\" doesn't exist.\\n\");\r\n\r\n FileReader r = new FileReader(document);\r\n BufferedReader br = new BufferedReader(r);\r\n\r\n String line;\r\n String documentText = \"\";\r\n while ( (line=br.readLine()) != null) {\r\n documentText += line;\r\n }\r\n\r\n documentText = Jsoup.parse(documentText).text();\r\n\r\n String[] listOfSentences = documentText.split(\"\\\\.\");\r\n HashMap<String,String> originalToNormalized = new HashMap<>();\r\n String original;\r\n\r\n for (String sentence: listOfSentences){\r\n\r\n original = sentence;\r\n\r\n sentence = sentence.toLowerCase();\r\n sentence = StringUtils.stripAccents(sentence);\r\n sentence = sentence.replaceAll(\"[^a-z0-9-._\\\\n]\", \" \");\r\n\r\n originalToNormalized.put(original,sentence);\r\n }\r\n\r\n int matches, maxMatches = 0;\r\n String output = \"\";\r\n\r\n for (Map.Entry<String,String> sentence: originalToNormalized.entrySet()){\r\n\r\n matches = 0;\r\n\r\n for (String word: words){\r\n if (sentence.getValue().contains(word)) matches++;\r\n }\r\n\r\n if (matches == words.length) return sentence.getKey();\r\n if (matches > maxMatches){\r\n maxMatches = matches;\r\n output = sentence.getKey();\r\n }\r\n }\r\n\r\n return output;\r\n\r\n }","@Override\r\n\tpublic List<Post> searchInfResult(String word) {\n\t\tpostDao=new PostDaoImpl(TransactionManager.connection);\r\n\t\treturn postDao.selectPosts(word);\r\n\t}","Page<T> search(Pageable pageable, String query);","@Test\n public void testCase1 () throws IOException {\n sq = new SpanSegmentQuery(new SpanTermQuery(new Term(\"base\", \"s:b\")),\n new SpanTermQuery(new Term(\"base\", \"s:c\")));\n\n kr = ki.search(sq, (short) 10);\n ki.close();\n\n assertEquals(\"totalResults\", kr.getTotalResults(), 3);\n assertEquals(\"StartPos (0)\", 1, kr.getMatch(0).startPos);\n assertEquals(\"EndPos (0)\", 2, kr.getMatch(0).endPos);\n assertEquals(\"StartPos (1)\", 4, kr.getMatch(1).startPos);\n assertEquals(\"EndPos (1)\", 5, kr.getMatch(1).endPos);\n }","void search();","void search();","@Override\n public List<Document> findInDocuments(String collectionName, Bson query) {\n return null;\n }","private boolean isTermAppearInQuery(String term) {\n boolean isTermAppear = false;\n query thisQuery = listDocumentRetrievedForThisQuery.getQuery();\n StringTokenizer token = new StringTokenizer(thisQuery.getQueryContent(), \" %&\\\"*#@$^_<>|`+=-1234567890'(){}[]/.:;?!,\\n\");\n while (token.hasMoreTokens()) {\n String keyTerm = token.nextToken();\n if (invertedFile.isStemmingApplied()) {\n keyTerm = StemmingPorter.stripAffixes(keyTerm);\n }\n if (term.equals(keyTerm.toLowerCase())) {\n isTermAppear = true;\n break;\n }\n }\n return isTermAppear;\n }","Page<T> search(Pageable pageable, QueryBuilder query);","public MagicSearch createMagicSearch();","@Test\n public void testCase4 () throws IOException {\n //\t\tlog.trace(\"Testcase4\");\n\n ki = new KrillIndex();\n ki.addDoc(createFieldDoc0());\n ki.commit();\n ki.addDoc(createFieldDoc1());\n ki.addDoc(createFieldDoc2());\n ki.commit();\n\n sq = new SpanSegmentQuery(new SpanElementQuery(\"base\", \"e\"),\n new SpanNextQuery(new SpanTermQuery(new Term(\"base\", \"s:a\")),\n new SpanTermQuery(new Term(\"base\", \"s:b\"))));\n\n kr = ki.search(sq, (short) 10);\n ki.close();\n\n assertEquals(\"totalResults\", kr.getTotalResults(), 2);\n // Match #0\n assertEquals(\"doc-number\", 0, kr.getMatch(0).getLocalDocID());\n assertEquals(\"StartPos\", 3, kr.getMatch(0).startPos);\n assertEquals(\"EndPos\", 5, kr.getMatch(0).endPos);\n // Match #1\n assertEquals(\"doc-number\", 0, kr.getMatch(1).getLocalDocID());\n assertEquals(\"StartPos\", 1, kr.getMatch(1).startPos);\n assertEquals(\"EndPos\", 3, kr.getMatch(1).endPos);\n }","public DocFile[] searchResponse(ScoreDoc[] results, Query query) {\n\n DocFile[] result = new DocFile[results.length];\n FastVectorHighlighter highlighter = new FastVectorHighlighter(true,true);\n FieldQuery highlightQuery = highlighter.getFieldQuery(query); \n\n try {\n IndexReader reader = DirectoryReader.open(indexDir);\n IndexSearcher searcher = new IndexSearcher(reader);\n\n for (int i = 0; i < results.length; i++) {\n int docId = results[i].doc;\n Document document = searcher.doc(docId);\n \n //Highlight the best Content context from each Doc\n String contextString = highlighter.getBestFragment(highlightQuery, \n searcher.getIndexReader(), results[i].doc,Constants.INDEX_KEY_CONTENT,140);\n \n DocFile toAdd = new DocFile(\n document.get(Constants.INDEX_KEY_FILENAME),\n document.get(Constants.INDEX_KEY_TITLE),\n document.get(Constants.INDEX_KEY_OWNER),\n document.get(Constants.INDEX_KEY_PATH),\n document.get(Constants.INDEX_KEY_STATUS).equalsIgnoreCase(\"true\"));\n \n if (contextString != null) {\n toAdd.setContextString(contextString);\n }\n \n toAdd.setId(document.get(Constants.INDEX_KEY_ID));\n toAdd.setPermissions(Integer.parseInt(document.get(Constants.INDEX_KEY_PERMISSION)));\n toAdd.setCourseCode(document.get(Constants.INDEX_KEY_COURSE));\n result[i] = toAdd;\n\n }\n } catch (Exception e) {\n e.printStackTrace();\n }\n\n return result;\n }","private List<SearchWord> getSearchWords(Long lastUpdateTime) {\n return new ArrayList<>();\n }","@SuppressWarnings(\"unchecked\")\n\tpublic JSONArray findMatches(String query){\n\t\t\n\t\t// Increment the search tasks counter\n\t\t++numOfSearchTasks;\n\t\t\n\t\t// Start the timer for this task\n\t\tTimer.start();\n\t\t\n\t\t// Number of needed matches\n\t\tresultsToBeFound = 10;\n\t\t\n\t\t// Clear the matches list\n\t\tsetForTypeahead.clear();\n\t\t\n\t\t// The returned JSON array\n\t\tJSONArray arrayObj = new JSONArray();\n\t\t\n\t\t// Search in all predicates\n\t\tfor(int i = 0; i < predicatesList.size(); ++i){\n\t\t\tif(predicatesList.get(i).toLowerCase().contains(query.toLowerCase())){\n\t\t\t\tarrayObj.add(predicatesList.get(i));\n\t\t\t}\n\t\t\tArrayList<String> semanticRelations = semanticRelationsMap.get(query.toLowerCase());\n\t\t\tif(semanticRelations != null) {\n\t\t\t\tfor(String s : semanticRelations) {\n\t\t\t\t\tif(predicatesList.get(i).toLowerCase().contains(s.toLowerCase())){\n\t\t\t\t\t\tarrayObj.add(predicatesList.get(i));\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t\t\n\t\t// Start the timer for this task\n\t\tTimer.start();\n\t\t\n\t\t// Search in index first\n\t\tCollection<Integer> list = in.search(query.toLowerCase());\n\t\tHashSet<Integer> output = null;\n\t\tif(list.size() > 0) {\n\t\t\toutput = (HashSet<Integer>) list;\n\t\t}\n\t\telse {\n\t\t\toutput = new HashSet<Integer>();\n\t\t}\n\n\t\t// If found a match, that's a hit\n\t\tif(output.size() > 0) {\n\t\t\t++numOfIndexHits;\n\t\t}\n\t\t\n\t\tfor(Integer index : output) {\n\t\t\tarrayObj.add(frequentLiteralsList.get(index));\n \t\t--resultsToBeFound;\n \t}\n\t\tdouble tempStopTime;\n\t\t// If all results were found in suffix tree\n\t\tif(resultsToBeFound < 0) {\n\t\t\tTimer.stop();\n\t\t\tsuffixTreeTime += Timer.getTimeInSeconds();\n\t\t\ttotalTime += Timer.getTimeInSeconds();\n\t\t\twriteStatsToFile();\n\t\t\treturn arrayObj;\n\t\t}\n\t\t\n\t\tTimer.stop();\n\t\tsuffixTreeTime += Timer.getTimeInSeconds();\n\t\ttempStopTime = Timer.getTimeInSeconds();\n\t\tTimer.start();\n\t\t// In length bins\n\t\t// Search in bins with a minimum length of the query\n\t\t// and a maximum of the query length + 10\n\t\tint minLength = query.length()-1;\n\t\tint maxLength = query.length() + 9;\n\t\t\n\t\tint minIndex = Integer.MAX_VALUE;\n\t\tint maxIndex = -1;\n\t\t\n\t\t// Determine which indices of the literals array\n\t\t// to search within\n\t\tfor(int i = 0; i < lengths.size(); ++i){\n\t\t\tif(lengths.get(i) > maxLength) {\n\t\t\t\tmaxIndex = indexes.get(i);\n\t\t\t\tbreak;\n\t\t\t}\n\t\t\tif(minLength >= lengths.get(i)) {\n\t\t\t\tminIndex = indexes.get(i);\n\t\t\t}\n\t\t}\n\t\t\n\t\tpruningPercentage += 1 - (1.0 * (maxIndex - minIndex) / literalsList.size());\n\t\ttry{\n\t\tSystem.out.println(\"Searching for \" + query + \" between indeces: \" + minIndex + \n\t\t\t\t\" corresponding to length \" + (literalsList.get(minIndex).length()-5) +\n\t\t\t\t\" and \" + maxIndex + \" corresponding to length \" + \n\t\t\t\t(literalsList.get(maxIndex).length()-5));\n\t\t}\n\t\tcatch(IndexOutOfBoundsException e) {\n\t\t\tSystem.out.println(\"query = \" + query);\n\t\t\tSystem.out.println(\"minIndex = \" + minIndex);\n\t\t\tSystem.out.println(\"maxIndex = \" + maxIndex);\n\t\t}\n\t\t\n\t\t// Assign threads to search tasks\n\t\tint indexesPerThread = (maxIndex - minIndex) / (numOfCores);\n\t\t\n\t\t// Arraylist to keep track of threads\n\t\tArrayList<Thread> threads = new ArrayList<Thread>();\n\t\t\n\t\tfor(int i = minIndex; i < maxIndex; i += indexesPerThread) {\n\t\t\tthreads.add(new Thread(new SearchTask(i, i + indexesPerThread, query)));\n\t\t}\n\t\t\n\t\t// Start threads\n\t\tfor(int i = 0; i < threads.size(); ++i) {\n\t\t\tthreads.get(i).start();\n\t\t}\n\t\t\n\t\t// Join threads before continue\n\t\tfor(int i = 0; i < threads.size(); ++i) {\n\t\t\ttry {\n\t\t\t\tthreads.get(i).join();\n\t\t\t} catch (InterruptedException e) {\n\t\t\t\te.printStackTrace();\n\t\t\t}\n\t\t}\n\t\t\n\t\t// Stop timer\n\t\tTimer.stop();\n\t\ttotalTime += tempStopTime + Timer.getTimeInSeconds();\n\t\t\n\t\t// Sort by length\n\t\tArrayList<String> tempList = new ArrayList<String>();\n\t\tfor(String string : setForTypeahead) {\n\t\t\tif(!arrayObj.contains(string))\n\t\t\t\ttempList.add(string);\n\t\t}\n\t\tjava.util.Collections.sort(tempList, new LengthComparator());\n\t\t\n\t\t// Fill the array\n\t\tfor(int i = 0; i < tempList.size() && resultsToBeFound > 0; ++i, --resultsToBeFound) {\n\t\t\tarrayObj.add(tempList.get(i));\n\t\t}\n\t\t\n\t\t\n\t\t\n\t\t// Update the stats file with number of tasks and hits\n\t\twriteStatsToFile();\n\t\t\n\t\treturn arrayObj;\n\t}","void findAllWords() {\n\t\tScanner in = new Scanner(textEditor.getText());\n\t\tint head = 0;\n\t\twhile (in.hasNext()) {\n\t\t\tString value = in.next();\n\t\t\tif (value.equals(findWord)) {\n\t\t\t\tint tail = value.length();\n\t\t\t\tfinder.add(new WordPosition(head, tail + head +1));\n\t\t\t}\n\t\t\thead += (value.length()+1);\n\t\t}\n\t\tin.close();\n\t}","private void performSearch() {\n String text = txtSearch.getText();\n String haystack = field.getText();\n \n // Is this case sensitive?\n if (!chkMatchCase.isSelected()) {\n text = text.toLowerCase();\n haystack = haystack.toLowerCase();\n }\n \n // Check if it is a new string that the user is searching for.\n if (!text.equals(needle)) {\n needle = text;\n curr_index = 0;\n }\n \n // Grab the list of places where we found it.\n populateFoundList(haystack);\n \n // Nothing was found.\n if (found.isEmpty()) {\n Debug.println(\"FINDING\", \"No occurrences of \" + needle + \" found.\");\n JOptionPane.showMessageDialog(null, \"No occurrences of \" + needle + \" found.\",\n \"Nothing found\", JOptionPane.INFORMATION_MESSAGE);\n \n return;\n }\n \n // Loop back the indexes if we have reached the end.\n if (curr_index == found.size()) {\n curr_index = 0;\n }\n \n // Go through the findings one at a time.\n int indexes[] = found.get(curr_index);\n field.select(indexes[0], indexes[1]);\n curr_index++;\n }","public static void textQueries(List<String> sentences, List<String> queries) {\n // Write your code here\n for(String q: queries){\n boolean a = false;\n int i=0;\n for(String s: sentences){\n if(Arrays.asList(s.split(\" \")).containsAll(Arrays.asList(q.split(\" \")))){\n System.out.print(i+\" \");\n a = true;\n }\n i++;\n }\n if(!a)\n System.out.println(-1);\n else\n System.out.println(\"\");\n }\n \n }","public void searchIndexWithTermQueryByBody(final String toSearch) throws IOException, ParseException {\n searchIndexWithTermQuery(toSearch, \"body\", DEFAULT_LIMIT);\n }","Search getSearch();","private static Boolean specialQueries(String query) throws ClassNotFoundException, InstantiationException, IllegalAccessException {\n clickList = false;\n //newCorpus = true;\n\n if (query.equals(\"q\")) {\n\n System.exit(0);\n return true;\n }\n\n String[] subqueries = query.split(\"\\\\s+\"); //split around white space\n\n if (subqueries[0].equals(\"stem\")) //first term in subqueries tells computer what to do \n {\n GUI.JListModel.clear();\n GUI.ResultsLabel.setText(\"\");\n TokenProcessor processor = new NewTokenProcessor();\n if (subqueries.length > 1) //user meant to stem the token not to search stem\n {\n List<String> stems = processor.processToken(subqueries[1]);\n\n //clears list and repopulates it \n String stem = \"Stem of query '\" + subqueries[1] + \"' is '\" + stems.get(0) + \"'\";\n\n GUI.ResultsLabel.setText(stem);\n\n return true;\n }\n\n } else if (subqueries[0].equals(\"vocab\")) {\n List<String> vocabList = Disk_posIndex.getVocabulary();\n GUI.JListModel.clear();\n GUI.ResultsLabel.setText(\"\");\n\n int vocabCount = 0;\n for (String v : vocabList) {\n if (vocabCount < 1000) {\n vocabCount++;\n GUI.JListModel.addElement(v);\n }\n }\n GUI.ResultsLabel.setText(\"Total size of vocabulary: \" + vocabCount);\n return true;\n }\n\n return false;\n }"],"string":"[\n \"@Test\\n public void testPhrase() {\\n assertQ(req(\\\"q\\\",\\\"text:now-cow\\\", \\\"indent\\\",\\\"true\\\")\\n ,\\\"//*[@numFound='1']\\\"\\n );\\n // should generate a query of (now OR cow) and match both docs\\n assertQ(req(\\\"q\\\",\\\"text_np:now-cow\\\", \\\"indent\\\",\\\"true\\\")\\n ,\\\"//*[@numFound='2']\\\"\\n );\\n }\",\n \"private static String handlePhrases(String PubmedQuery) {\\r\\n //Find phrases \\\"between double quotes\\\"\\r\\n String[] phrases = PubmedQuery.split(\\\"\\\\\\\"\\\");\\r\\n for(int i = 0 ; i < phrases.length ; i++){\\r\\n phrases[i] = phrases[i].trim();\\r\\n if(!phrases[i].equals(\\\"\\\")){ // String not Empty\\r\\n if(i%2 != 0){ // String surrounded by quotes, i.e. a phrase\\r\\n phrases[i] = \\\"\\\\\\\"\\\" + phrases[i] + \\\"\\\\\\\"\\\";\\r\\n } else { // not a phrase, i.e. a bag of terms, operator or [field of index] (inside brackets)\\r\\n if(phrases[i].startsWith(\\\"[\\\")){ //index field of previus component contained (i.e. case: \\\"...\\\"[...])\\r\\n boolean perviusPhraseFound = false; // True if index field was added to previus phrase element\\r\\n // Get index field of previus component and handle proprietly\\r\\n String [] tokens = phrases[i].split(\\\"]\\\");\\r\\n String indexField = tokens[0].replace(\\\"[\\\", \\\"\\\");\\r\\n String luceneField = supportedIndexFields.get(indexField);\\r\\n if(luceneField != null){ \\r\\n //add \\\"indexField:\\\" as a prefix in previus (not empty) phrase\\r\\n int tmp = i-1;\\r\\n while(!perviusPhraseFound & tmp >= 0){\\r\\n if(!phrases[tmp].equals(\\\"\\\")){\\r\\n perviusPhraseFound = true;\\r\\n //TO DO : handle wrong syntax (e.g. ... AND [ArticleTitle])\\r\\n phrases[tmp] = luceneField + \\\":\\\" + phrases[tmp] + \\\"\\\";\\r\\n } else {\\r\\n tmp--;\\r\\n }\\r\\n }\\r\\n } // else : Lucene counterpart not found, unsupported field - do nothing\\r\\n // Remove from current phrase this index field (prefix)\\r\\n phrases[i] = phrases[i].substring(indexField.length()+2 );\\r\\n } \\r\\n // Further handling...\\r\\n phrases[i] = handleNonPhraseToken(phrases[i]);\\r\\n }\\r\\n } //else { /* Empty token, do nothing with this */ System.out.println(\\\"\\\\t\\\\t\\\\t empty\\\"); }\\r\\n }\\r\\n \\r\\n String luceneQuery = \\\"\\\";\\r\\n boolean fisrtPhrase = true;\\r\\n for(int i = 0 ; i < phrases.length ; i ++){\\r\\n if(phrases[i].length() > 0){\\r\\n if(!phrases[i].startsWith(\\\" OR \\\") & !phrases[i].startsWith(\\\" -\\\") & !phrases[i].startsWith(\\\" +\\\") ){\\r\\n if(fisrtPhrase){\\r\\n luceneQuery += \\\" +\\\";\\r\\n fisrtPhrase = false;\\r\\n } else {\\r\\n if(!phrases[i-1].endsWith(\\\" OR \\\") & !phrases[i-1].endsWith(\\\" -\\\") & !phrases[i-1].endsWith(\\\" +\\\")){\\r\\n luceneQuery += \\\" +\\\";\\r\\n }\\r\\n } \\r\\n } // add default operator + when required (no OR or - is present for that term)\\r\\n luceneQuery += phrases[i];\\r\\n }// else empty phrase : skip\\r\\n }\\r\\n return luceneQuery;\\r\\n }\",\n \"private static List<SearchData> booleanSearchWord(Query query, Indexer si) {\\n Tokenizer tkn = new SimpleTokenizer();\\n tkn.tokenize(query.getStr(), \\\"[a-zA-Z]{3,}\\\", true, true);\\n List<SearchData> searchList = new ArrayList<>();\\n LinkedList<Token> wordsList = tkn.getTokens();\\n Iterator<Token> wordsIt = wordsList.iterator();\\n HashMap<String, LinkedList<Posting>> indexer = si.getIndexer();\\n int idx;\\n SearchData searched_doc;\\n\\n while (wordsIt.hasNext()) {\\n String word = wordsIt.next().getSequence();\\n if (indexer.containsKey(word)) {\\n\\n LinkedList<Posting> posting = indexer.get(word);\\n\\n for (Posting pst : posting) {\\n\\n SearchData sd = new SearchData(query, pst.getDocId());\\n\\n if (!searchList.contains(sd)) {\\n sd.setScore(1);\\n searchList.add(sd);\\n } else {\\n idx = searchList.indexOf(sd);\\n searched_doc = searchList.get(idx);\\n searched_doc.setScore(searched_doc.getScore() + 1);\\n }\\n }\\n\\n }\\n\\n\\n }\\n\\n Collections.sort(searchList);\\n\\n return searchList;\\n }\",\n \"@Override\\r\\n\\t\\t\\tpublic List<ScoredDocument> search(Query query) {\\n\\t\\t\\t\\treturn null;\\r\\n\\t\\t\\t}\",\n \"public Map<String, String> directQuoteSearch (String q, String contentOrTitle) throws IOException, ParseException{\\n\\n\\t\\t\\n\\t\\tif (contentOrTitle.equals(\\\"content\\\")){\\n\\t\\t\\tcontentOrTitle=field;\\n\\t\\t} else if (contentOrTitle.equals(\\\"title\\\")){\\n\\t\\t\\tcontentOrTitle=title;\\n\\t\\t}\\n\\t\\t\\n\\t\\tIndexReader reader = DirectoryReader.open(FSDirectory.open(Paths.get(index)));\\n\\t\\tIndexSearcher searcher = new IndexSearcher(reader);\\n\\t\\tboolean raw = false;\\n\\t\\tint repeat = 0;\\n\\n\\t\\tfinal List<String> stopWords = Arrays.asList();\\n\\t\\tfinal CharArraySet stopSet = new CharArraySet(stopWords, true);\\n\\n\\t\\tAnalyzer analyzer = new StandardAnalyzer(stopSet);\\n\\t\\tAnalyzingQueryParser parser = new AnalyzingQueryParser(contentOrTitle, analyzer);\\n\\t\\t\\n\\n\\t\\t\\n\\t\\tString[] items = q.split(\\\" \\\");\\n\\t\\tList<String> itemList = Arrays.asList(items);\\n\\t\\tQuery query=null;\\n\\t\\t\\n\\t\\t\\n\\t\\tif (q.equals(\\\"\\\")){\\n\\t\\t\\tSystem.out.println(\\\"no input\\\");\\n\\t\\t\\t\\n\\t\\t} else {\\n\\t\\t\\tquery = parser.parse(q);\\n\\n\\t\\t}\\n\\n\\t\\t\\n\\t\\t\\n\\t\\tBufferedReader in = null;\\n\\t\\tin = new BufferedReader(new InputStreamReader(System.in, StandardCharsets.UTF_8));\\n\\n\\t\\tif (repeat > 0) { // repeat & time as benchmark\\n\\t\\t\\tDate start = new Date();\\n\\t\\t\\tfor (int i = 0; i < repeat; i++) {\\n\\t\\t\\t\\tsearcher.search(query, 100);\\n\\t\\t\\t}\\n\\t\\t\\tDate end = new Date();\\n\\t\\t\\tSystem.out.println(\\\"Time: \\\"+(end.getTime()-start.getTime())+\\\"ms\\\");\\n\\t\\t}\\n\\n\\t\\treturn doPagingSearch(in, searcher, query, hitsPerPage, raw, true);\\n\\t}\",\n \"@In String search();\",\n \"public byte filter(Manager m, SearchRequest q, ResultSet rs, int DocAtNumber, int DocNo)\\n\\t{\\t\\t\\n\\t\\tString originalQuery = q.getOriginalQuery();\\n\\t\\t//highlight query terms only for the queries, \\n\\t\\t//which are not about finding related documents\\n\\t\\t//this check may be removed, because the preparation of the \\n\\t\\t//query terms for highlighting takes into account\\n\\t\\t//the related: operator\\n\\t\\tboolean highlightQueryTerms = true;\\n\\t\\tif (originalQuery.matches(\\\"\\\\\\\\brelated:\\\\\\\\d+\\\\\\\\b\\\") || //check if the query uses the related: operator \\n\\t\\t\\t!enableQueryTermsHighlight || //check if the highlighting of terms is enabled\\n\\t\\t\\thighlight.pattern().equals(\\\"(\\\\\\\\b)()(\\\\\\\\b)\\\")) //check if there are no query terms to highlight\\n\\t\\t\\thighlightQueryTerms = false;\\n\\t\\t\\n\\t\\tString[] qTerms = q.getOriginalQuery().replaceAll(\\\" \\\\\\\\w+\\\\\\\\p{Punct}\\\\\\\\w+ \\\",\\\" \\\").toLowerCase().split(\\\" \\\");\\n\\t\\t\\n\\t\\tString[] metadata = null;\\n\\t\\tint tmpSentence;\\n\\t\\tdouble tmpScore;\\n\\t\\tsynchronized(metaCache) {\\n\\t\\t\\ttry {\\n\\t\\t\\t\\tInteger DocNoObject = new Integer(DocNo);\\n\\t\\t\\t\\tif (metaCache.containsKey(DocNoObject))\\n\\t\\t\\t\\t\\t\\tmetadata = (String[]) metaCache.get(DocNoObject);\\n\\t\\t\\t\\telse {\\n\\t\\t\\t\\t\\tmetadata = metaIndex.getItems(keys, DocNo);\\n\\t\\t\\t\\t\\tmetaCache.put(DocNoObject,metadata);\\n\\t\\t\\t\\t}\\n\\t\\t\\t} catch(IOException ioe) {} \\n\\t\\t}\\n\\t\\n\\t\\tif (show_snippet)\\n\\t\\t{\\n\\t\\t\\tString extract = metadata[1];\\n\\t\\t\\tString[] sentences = sentencePattern.split(extract, 50); //use 50 sentences at most\\n\\t\\t\\tdouble[] sentenceScores = new double[sentences.length]; \\n\\t\\t\\tint frsSentence = -1;\\n\\t\\t\\tint sndSentence = -1;\\n\\t\\t\\tint top1Sentence = 0;\\n\\t\\t\\tint top2Sentence = 0;\\n\\t\\t\\tdouble max1Score = -1;\\n\\t\\t\\tdouble max2Score = 0;\\n\\t\\t\\tfinal int qTermsLength = qTerms.length;\\n\\t\\t\\tfor (int i=0; i<qTermsLength; i++) {\\n\\t\\t\\t\\tqTerms[i] = removeEndings.matcher(qTerms[i]).replaceAll(\\\"\\\");\\n\\t\\t\\t}\\n\\t\\t\\tString lowerCaseSentence;\\n\\t\\t\\tint sentenceLength;\\n\\t\\t\\tfinal int sentencesLength = sentences.length;\\n\\n\\t\\t\\tfor (int i=0; i<sentencesLength; i++) {\\n\\t\\t\\t\\t\\n\\t\\t\\t\\tlowerCaseSentence = sentences[i].toLowerCase();\\n\\t\\t\\t\\tsentenceLength=sentences[i].length();\\n\\t\\t\\t\\tif (sentenceLength < 20 || sentenceLength > 250) {\\n\\t\\t\\t\\t\\tfor (int j=0; j<qTermsLength; j++) {\\n\\t\\t\\t\\t\\t\\tif (lowerCaseSentence.indexOf(qTerms[j])>=0) {\\n\\t\\t\\t\\t\\t\\t\\tsentenceScores[i]+=1.0d + sentenceLength / (20.0d + sentenceLength);\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t} else {\\n\\t\\t\\t\\t\\tfor (int j=0; j<qTermsLength; j++) {\\n\\t\\t\\t\\t\\t\\tif (lowerCaseSentence.indexOf(qTerms[j])>=0) {\\n\\t\\t\\t\\t\\t\\t\\tsentenceScores[i]+=qTerms[j].length() + sentenceLength / (1.0d + sentenceLength);\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t}\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t//do your best to get at least a second sentence for the snippet, \\n\\t\\t\\t\\t//after having found the first one\\n\\t\\t\\t\\tif (frsSentence > -1 && sndSentence == -1 && sentenceLength > 5) {\\n\\t\\t\\t\\t\\tsndSentence = i;\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\t//do your best to get at least one sentence for the snippet\\n\\t\\t\\t\\tif (frsSentence == -1 && sentenceLength > 5) { \\n\\t\\t\\t\\t\\tfrsSentence = i;\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\tif (max2Score < sentenceScores[i]) {\\n\\t\\t\\t\\t\\tmax2Score = sentenceScores[i];\\n\\t\\t\\t\\t\\ttop2Sentence = i;\\n\\t\\t\\t\\t\\t//logger.debug(\\\"top 2 sentence is \\\" + i);\\n\\t\\t\\t\\t\\tif (max2Score > max1Score) {\\n\\t\\t\\t\\t\\t\\ttmpScore = max1Score; max1Score = max2Score; max2Score = tmpScore;\\n\\t\\t\\t\\t\\t\\ttmpSentence = top1Sentence; top1Sentence = top2Sentence; top2Sentence = tmpSentence;\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t}\\n\\t\\t\\tint lastIndexOfSpace = -1;\\n\\t\\t\\tString sentence=\\\"\\\";\\n\\t\\t\\tString secondSentence=\\\"\\\";\\n\\t\\t\\tString snippet = \\\"\\\";\\n\\t\\t\\tif (max1Score == -1) {\\n\\t\\t\\t\\tif (frsSentence>=0) {\\n\\t\\t\\t\\t\\tsentence = sentences[frsSentence];\\n\\t\\t\\t\\t\\tif (sentence.length() > 100) {\\n\\t\\t\\t\\t\\t\\tlastIndexOfSpace = sentence.substring(0, 100).lastIndexOf(\\\" \\\");\\n\\t\\t\\t\\t\\t\\tsentence = sentence.substring(0, lastIndexOfSpace > 0 ? lastIndexOfSpace : 100);\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\n\\t\\t\\t\\tif (sndSentence>=0) {\\n\\t\\t\\t\\t\\tsecondSentence = sentences[sndSentence];\\n\\t\\t\\t\\t\\tif (secondSentence.length() > 100) {\\n\\t\\t\\t\\t\\t\\tlastIndexOfSpace = secondSentence.substring(0, 100).lastIndexOf(\\\" \\\");\\n\\t\\t\\t\\t\\t\\tsecondSentence = secondSentence.substring(0, lastIndexOfSpace>0 ? lastIndexOfSpace : 100);\\n\\t\\t\\t\\t\\t}\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\n\\t\\t\\t\\tif (frsSentence >=0 && sndSentence >= 0) \\n\\t\\t\\t\\t\\tsnippet = sentence.trim() + \\\"...\\\" + secondSentence.trim();\\n\\t\\t\\t\\telse if (frsSentence >= 0 && sndSentence<0) \\n\\t\\t\\t\\t\\tsnippet = sentence.trim();\\n\\t\\t\\t\\t\\n\\t\\t\\t} else if (sentences[top1Sentence].length()<100 && top1Sentence!=top2Sentence) {\\n\\t\\t\\t\\tsentence = sentences[top1Sentence];\\n\\t\\t\\t\\tif (sentence.length() > 100) {\\n\\t\\t\\t\\t\\tlastIndexOfSpace = sentence.substring(0, 100).lastIndexOf(\\\" \\\");\\n\\t\\t\\t\\t\\tsentence = sentence.substring(0, lastIndexOfSpace > 0 ? lastIndexOfSpace : 100);\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\tsecondSentence = sentences[top2Sentence];\\n\\t\\t\\t\\tif (secondSentence.length() > 100) {\\n\\t\\t\\t\\t\\tlastIndexOfSpace = secondSentence.substring(0, 100).lastIndexOf(\\\" \\\");\\n\\t\\t\\t\\t\\tsecondSentence = secondSentence.substring(0, lastIndexOfSpace>0 ? lastIndexOfSpace : 100);\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\tsnippet = sentence.trim() + \\\"...\\\" + secondSentence.trim();\\n\\t\\t\\t} else {\\n\\t\\t\\t\\tsentence = sentences[top1Sentence];\\n\\t\\t\\t\\tif (sentence.length()>200) {\\n\\t\\t\\t\\t\\tlastIndexOfSpace = sentence.substring(0, 200).lastIndexOf(\\\" \\\");\\n\\t\\t\\t\\t\\tsentence = sentence.substring(0, lastIndexOfSpace > 0 ? lastIndexOfSpace : 200);\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\tsnippet = sentence.trim();\\n\\t\\t\\t}\\n\\t\\t\\t\\n\\t\\t\\t//checking and removing any control characters\\n\\t\\t\\tcontrolNonVisibleCharactersMatcher.reset(snippet);\\n\\t\\t\\tsnippet = controlNonVisibleCharactersMatcher.replaceAll(\\\"\\\");\\n\\t\\t\\t\\n\\t\\t\\t//String escapedSnippet = StringEscapeUtils.escapeHtml(snippet);\\n\\t\\t\\t//if (highlightQueryTerms)\\n\\t\\t\\t//\\tescapedSnippet = highlight.matcher(escapedSnippet).replaceAll(\\\"$1<b>$2</b>$3\\\");\\n\\t\\t\\tif (highlightQueryTerms)\\n\\t\\t\\t\\tsnippet = highlight.matcher(snippet).replaceAll(\\\"$1<b>$2</b>$3\\\");\\n\\t\\t\\t//else \\n\\t\\t\\t//\\tsnippet = StringEscapeUtils.escapeHtml(snippet);\\n\\t\\t\\t\\n\\t\\t\\t//change by Vassilis, 20/09/2006\\n\\t\\t\\t//disabling the xml escaping in order to move the data into ![CDATA[ ]]\\n\\t\\t\\t//the code was:\\n\\t\\t\\t//rs.addMetaItem(\\\"snippet\\\", DocAtNumber, StringEscapeUtils.escapeXml(snippet));\\n\\t\\t\\t//and now it is:\\n\\t\\t\\t//snippet.replaceAll(\\\"[^\\\\\\\\u0009\\\\\\\\u000A\\\\\\\\u000D\\\\\\\\u0020-\\\\\\\\uD7FF\\\\\\\\uE000-\\\\\\\\uFFFD\\\\\\\\u10000-\\\\\\\\u10FFFF]\\\",\\\"\\\");\\n\\t\\t\\trs.addMetaItem(\\\"snippet\\\", DocAtNumber, snippet);\\n\\t\\t\\t\\n\\t\\t}\\n\\t\\tif (show_title)\\n\\t\\t{\\n\\t\\t\\tString title = metadata[2];\\n\\t\\t\\t\\n\\t\\t\\t//checking and removing any control characters\\n\\t\\t\\tcontrolNonVisibleCharactersMatcher.reset(title);\\n\\t\\t\\ttitle = controlNonVisibleCharactersMatcher.replaceAll(\\\"\\\");\\n\\t\\t\\ttitle = (highlightQueryTerms)\\n\\t\\t\\t\\t ? highlight.matcher(metadata[2]).replaceAll(\\\"$1<b>$2</b>$3\\\") \\n\\t\\t\\t\\t : metadata[2];\\n\\t\\t\\t\\n\\t\\t\\t\\n\\t\\t\\t//String escapedTitle = StringEscapeUtils.escapeHtml(metadata[2]);\\n\\t\\t\\t//String title = (highlightQueryTerms)\\n\\t\\t\\t//\\t\\t\\t ? highlight.matcher(escapedTitle).replaceAll(\\\"$1<b>$2</b>$3\\\") \\n\\t\\t\\t//\\t\\t\\t : escapedTitle;\\n\\t\\t\\t//String title = (highlightQueryTerms) \\n\\t\\t\\t//\\t\\t? highlight.matcher(metadata[2]).replaceAll(\\\"$1<b>$2</b>$3\\\") \\n\\t\\t\\t//\\t\\t: metadata[2];\\n\\n\\t\\t\\t//change by Vassilis, 20/09/2006\\n\\t\\t\\t//disabling the xml escaping in order to move the data into ![CDATA[ ]]\\n\\t\\t\\t//the code was:\\n\\t\\t\\t//rs.addMetaItem(\\\"title\\\", DocAtNumber, StringEscapeUtils.escapeXml(title));\\n\\t\\t\\t//and now is:\\n\\t\\t\\t//title.replaceAll(\\\"[^\\\\\\\\u0009\\\\\\\\u000A\\\\\\\\u000D\\\\\\\\u0020-\\\\\\\\uD7FF\\\\\\\\uE000-\\\\\\\\uFFFD\\\\\\\\u10000-\\\\\\\\u10FFFF]\\\",\\\"\\\");\\n\\t\\t\\trs.addMetaItem(\\\"title\\\", DocAtNumber, title);\\n\\t\\t\\t\\n\\t\\t}\\n\\t\\tif (!show_docid_early && show_docid)\\n\\t\\t{\\n\\t\\t\\trs.addMetaItem(\\\"docid\\\", DocAtNumber, docIndex.getDocumentNumber(DocNo));\\n\\t\\t}\\n\\t\\tif (!show_url_early && show_url)\\n\\t\\t{\\n\\n\\t\\t\\trs.addMetaItem(\\\"url\\\", DocAtNumber, StringEscapeUtils.escapeXml(metadata[0]));\\n\\t\\t}\\n\\t\\t\\n\\t\\treturn FILTER_OK;\\n\\t}\",\n \"@Test\\n\\tpublic void phraseGrepTest1() throws Exception {\\n\\t\\t// phrase is \\\"I am forced\\\"\\n\\t\\tHashSet<String> grepFound = loadGrepResults(\\\"i+am+forced\\\");\\n\\t\\tCollection<Page> index = queryTest.query(\\\"\\\\\\\"I am Forced\\\\\\\"\\\");\\n\\t\\tHashSet<String> indexFound = new HashSet<String>();\\n\\n\\t\\tfor (Page p : index)\\n\\t\\t\\tindexFound.add(p.getURL().getPath().toLowerCase());\\n\\t\\t\\n\\t\\t// tests set equality \\n\\t\\tassertEquals(indexFound, grepFound);\\n\\t}\",\n \"private ArrayList<WordDocument> executeRegularQuery(){\\n String[] splitedQuery = this.query.split(\\\" \\\");\\n ArrayList<WordDocument> listOfWordDocuments = new ArrayList<WordDocument>();\\n String word = \\\"\\\";\\n\\n for(int i = 0; i < splitedQuery.length; i++){\\n if(!isOrderByCommand(splitedQuery[i]) && i == 0) {\\n word = splitedQuery[i];\\n\\n if(cache.isCached(word))\\n addWithoutDuplicate(listOfWordDocuments, cache.getCachedResult(word));\\n else\\n addWithoutDuplicate(listOfWordDocuments, getDocumentsWhereWordExists(word));\\n\\n }else if(i >= 1 && isOrderByCommand(splitedQuery[i])) {\\n subQueries.add(word);\\n listOfWordDocuments = orderBy(listOfWordDocuments, splitedQuery[++i], splitedQuery[++i]);\\n break;\\n }\\n else\\n throw new IllegalArgumentException();\\n }\\n\\n return listOfWordDocuments;\\n }\",\n \"public void search(Indexer indexer, CityIndexer cityIndexer, Ranker ranker, String query, boolean withSemantic, ArrayList<String> chosenCities, ObservableList<String> citiesByTag, boolean withStemming, String saveInPath, String queryId, String queryDescription) {\\n String[] originalQueryTerms = query.split(\\\" \\\");\\n String originQuery = query;\\n docsResults = new HashMap<>();\\n parser = new Parse(withStemming, saveInPath, saveInPath);\\n HashSet<String> docsOfChosenCities = new HashSet<>();\\n query = \\\"\\\" + query + queryDescription;\\n HashMap<String, Integer> queryTerms = parser.parseQuery(query);\\n HashMap<String, ArrayList<Integer>> dictionary = indexer.getDictionary();\\n if (!withStemming){\\n setDocsInfo(saveInPath + \\\"\\\\\\\\docsInformation.txt\\\");\\n }\\n else{\\n setDocsInfo(saveInPath + \\\"\\\\\\\\docsInformation_stemming.txt\\\");\\n }\\n\\n\\n //add semantic words of each term in query to 'queryTerms'\\n if(withSemantic) {\\n HashMap<String,ArrayList<String>> semanticWords = ws.connectToApi(originQuery);\\n }\\n\\n //give an ID to query if it's a regular query (not queries file)\\n if(queryId.equals(\\\"\\\")){\\n queryId = \\\"\\\" + Searcher.queryID;\\n Searcher.queryID++;\\n }\\n\\n String postingDir;\\n if (!withStemming) {\\n postingDir = \\\"\\\\\\\\indexResults\\\\\\\\postingFiles\\\";\\n } else {\\n postingDir = \\\"\\\\\\\\indexResults\\\\\\\\postingFiles_Stemming\\\";\\n }\\n int pointer = 0;\\n\\n //find docs that contain the terms in the query in their text\\n HashMap<String, Integer> queryTermsIgnoreCase = new HashMap<>();\\n for (String term : queryTerms.keySet()) {\\n String originTerm = term;\\n if (!dictionary.containsKey(term.toUpperCase()) && !dictionary.containsKey(term.toLowerCase())) {\\n continue;\\n }\\n if(dictionary.containsKey(term.toLowerCase())){\\n term = term.toLowerCase();\\n }\\n else {\\n term = term.toUpperCase();\\n }\\n queryTermsIgnoreCase.put(term,queryTerms.get(originTerm));\\n pointer = dictionary.get(term).get(2);\\n String chunk = (\\\"\\\" + term.charAt(0)).toUpperCase();\\n\\n //get the relevant line from posting file\\n BufferedReader br = null;\\n try {\\n br = new BufferedReader(new FileReader(new File(saveInPath + postingDir + \\\"\\\\\\\\posting_\\\" + chunk + \\\".txt\\\")));\\n String line = \\\"\\\";\\n int i = 1;\\n while ((line = (br.readLine())) != null) {\\n if (i == pointer) {\\n break;\\n }\\n i++;\\n }\\n br.close();\\n\\n //get docs from posting line and add them to the data structure 'docsResults'\\n if(line != null) {\\n findDocsFromLine(line, term);\\n }\\n\\n } catch (IOException e) {\\n e.printStackTrace();\\n }\\n }\\n\\n //find docs that contain the chosen cities in their text\\n for (String cityTerm : chosenCities) {\\n if (!dictionary.containsKey(cityTerm) && !dictionary.containsKey(cityTerm.toLowerCase())) {\\n continue;\\n }\\n if(dictionary.containsKey(cityTerm.toLowerCase())){\\n cityTerm = cityTerm.toLowerCase();\\n }\\n pointer = dictionary.get(cityTerm).get(2);\\n // char chunk = indexer.classifyToPosting(term).charAt(0);\\n String chunk = (\\\"\\\" + cityTerm.charAt(0)).toUpperCase();\\n\\n //get the relevant line from posting file\\n BufferedReader br = null;\\n try {\\n br = new BufferedReader(new FileReader(new File(saveInPath + postingDir + \\\"\\\\\\\\posting_\\\" + chunk + \\\".txt\\\")));\\n String line = \\\"\\\";\\n int i = 1;\\n while ((line = (br.readLine())) != null) {\\n if (i == pointer) {\\n break;\\n }\\n i++;\\n }\\n br.close();\\n\\n //get docs from posting line and add them to the data structure 'docsOfChosenCities'\\n String docs = line.substring(0, line.indexOf(\\\"[\\\") - 1); //get 'docsListStr'\\n String[] docsArr = docs.split(\\\";\\\");\\n for (String docInfo : docsArr) {\\n String doc = docInfo.substring(0, docInfo.indexOf(\\\": \\\"));\\n while(doc.charAt(0) == ' '){\\n doc = doc.substring(1);\\n }\\n docsOfChosenCities.add(doc);\\n }\\n } catch (IOException e) {\\n e.printStackTrace();\\n }\\n }\\n\\n //find docs that contain the chosen cities in their city tag\\n if(!chosenCities.isEmpty()){\\n for (String cityDicRec: chosenCities) {\\n //get pointer to posting from cityDictionary\\n try {\\n pointer = cityIndexer.getCitiesDictionary().get(cityDicRec);\\n } catch (NumberFormatException e) {\\n e.printStackTrace();\\n }\\n //get the relevant line from posting file\\n BufferedReader br = null;\\n try {\\n br = new BufferedReader(new FileReader(new File(saveInPath + \\\"\\\\\\\\cityIndexResults\\\" + \\\"\\\\\\\\posting_city\\\" + \\\".txt\\\")));\\n String line = \\\"\\\";\\n int i = 1;\\n while ((line = (br.readLine())) != null) {\\n if (i == pointer) {\\n break;\\n }\\n i++;\\n }\\n br.close();\\n\\n //get docs from posting line and add them to the data structure 'docsOfChosenCities'\\n String docs = line.substring(line.indexOf(\\\"[\\\") + 1, line.indexOf(\\\"]\\\")); //get 'docsListStr'\\n String[] docsArr = docs.split(\\\"; \\\");\\n for (String doc : docsArr) {\\n docsOfChosenCities.add(doc);\\n }\\n } catch (IOException e) {\\n e.printStackTrace();\\n }\\n }\\n }\\n\\n\\n ranker.rank(docsResults, docsOfChosenCities, queryTermsIgnoreCase, dictionary, docsInfo,entities, queryId);\\n }\",\n \"public DocumentListFeed fullTextQuery(String text) throws MalformedURLException, IOException, ServiceException;\",\n \"private static Query computeBooleanQueryNP(String textQuery){\\n\\t\\tBooleanQuery query = new BooleanQuery();\\n\\n\\t\\tHmmDecoder mPosTagger = null;\\n\\t\\tTokenizerFactory mTokenizerFactory = null;\\n\\t\\tPhraseChunker pChunker = new PhraseChunker(mPosTagger,mTokenizerFactory);\\n\\t\\tArrayList<String> pchuncker = new ArrayList<String>();\\n\\n\\t\\tpchuncker = pChunker.getCHunkNounPhrases(textQuery.toLowerCase());\\n\\n\\t\\tfor (int k = 0; k<= pchuncker.size()-1;k++ ){\\n\\t\\t\\tString wordInList = ((String) pchuncker.get(k));\\n\\t\\t\\twordInList = wordInList.toLowerCase().replaceAll(\\\"-\\\",\\\" \\\");\\n\\t\\t\\tString [] wordInListSplit = wordInList.split(\\\" \\\");\\n\\t\\t\\tfor (String word: wordInListSplit){\\n\\n\\t\\t\\t\\tquery.add(new TermQuery(new Term(\\\"content\\\", word)), Occur.SHOULD );\\n\\t\\t\\t}\\n\\n\\t\\t}\\n\\n\\t\\t/* String[] tQuery = textQuery.split(\\\" \\\");\\n\\t\\t for(String s: tQuery )\\n\\t\\t\\t query.add(new TermQuery(new Term(\\\"text\\\", s)), Occur.SHOULD);*/\\n\\n\\t\\treturn query;\\n\\t}\",\n \"private static String getPhraseInput() {\\n\\t\\treturn getQuery(\\\"Query Phrase\\\");\\n\\t}\",\n \"public SearchResult search(String text, String subText);\",\n \"List<String> getDocumentTitles(String query) throws SearcherException;\",\n \"public List<Document> SearchField(String queryStr ,String fieldName)\\r\\n\\t{\\r\\n\\t\\treturn null;\\r\\n\\t}\",\n \"String phraseQuery(String field, String val, int from, int size,\\n\\t\\t\\tboolean isSubdoc, DomeoPermissions permissions3) {\\n\\t\\tString query = buildPhraseQuery(field, val, from, size, permissions3);\\n\\t\\tString searchUrl = isSubdoc ? esSearchSubdocUrl : esSearchUrl;\\n\\t\\t@SuppressWarnings(\\\"unused\\\")\\n\\t\\tint resCode = doHttpOperation(searchUrl, HTTP_POST, query);\\n\\t\\treturn decodeNS(lastResponse);\\n\\t}\",\n \"SpellResponse spellQuery(SearchRequest request, Map<SearchParam, String> params);\",\n \"@Test\\n\\tpublic void singleWordGrepTest4() throws Exception {\\n\\t\\t// word is 'undocumented'\\n\\t\\tHashSet<String> grepFound = loadGrepResults(\\\"undocumented\\\");\\n\\t\\tCollection<Page> index = queryTest.query(\\\"undocumented\\\");\\n\\t\\tHashSet<String> indexFound = new HashSet<String>();\\n\\n\\t\\tfor (Page p : index)\\n\\t\\t\\tindexFound.add(p.getURL().getPath().toLowerCase());\\n\\t\\t\\n\\t\\t// tests set equality \\n\\t\\tassertEquals(indexFound, grepFound);\\n\\t}\",\n \"@Test\\n\\tpublic void notPhraseGrepTest() throws Exception {\\n\\t\\t// phrase is \\\"I am forced\\\"\\n\\t\\tHashSet<String> grepFound = loadGrepResults(\\\"!i+am+forced\\\");\\n\\t\\tCollection<Page> index = queryTest.query(\\\"! \\\\\\\"I am Forced\\\\\\\"\\\");\\n\\t\\tHashSet<String> indexFound = new HashSet<String>();\\n\\n\\t\\tfor (Page p : index)\\n\\t\\t\\tindexFound.add(p.getURL().getPath().toLowerCase());\\n\\t\\tassertEquals(grepFound, indexFound);\\n\\t}\",\n \"public static ArrayList<Result> findMatches(Query query, DataManager myVocab){\\n\\n\\t\\t//Uncomment this for logging in this class\\t\\n//\\t\\tmyLogger.setLevel(Level.INFO); \\n\\n\\t\\t// get the term we're going to search for and\\n\\t\\t// take out any leading or trailing whitespaces\\n\\t\\tString querystr = query.getQuery();\\n\\t\\tquerystr = querystr.trim();\\n\\t\\tString uncleaned = querystr;\\n\\t\\t\\n\\t\\t// This is in case of numeric entries. Google Refine doesn't seem\\n\\t\\t// to have int cell types, instead it adds an invisible .0 to all\\n\\t\\t// numbers. This fixes that issue, as it sometimes causes false negatives.\\n\\t\\tif (querystr.endsWith(\\\".0\\\")){\\n\\t\\t Pattern p = Pattern.compile(\\\"[^0-9\\\\\\\\.]+\\\");\\n\\t\\t Matcher m = p.matcher(querystr);\\n\\t\\t boolean result = m.find();\\n\\t\\t if (!result){\\n\\t\\t \\t querystr = querystr.substring(0, querystr.length()-2);\\n\\t\\t }\\n\\t\\t}\\n\\t\\t// see if it's in the synonyms map, if it is\\n\\t\\t// replace it with the appropriate term, if it's\\n\\t\\t// not, don't do anything. \\n\\n\\t\\tif (myVocab.subMap.get(querystr)!=null){\\n\\t\\t\\tquerystr = myVocab.subMap.get(querystr);\\n\\t\\t\\tquery.setQuery(querystr);\\n\\t\\t}\\n\\t\\t\\n\\t\\t// Clean up the query string if it isn't case/punctuation sensitive\\n\\t\\tif (!myVocab.capsSensitive()){\\t\\t\\n\\t\\t\\tquerystr = querystr.toLowerCase();\\n\\t\\t}\\n\\t\\tif (! myVocab.punctSensitive()){\\t\\t\\n\\t\\t\\tquerystr = querystr.replaceAll(\\\"[\\\\\\\\W_]\\\", \\\"\\\");\\n\\t\\t}\\n\\t\\t\\n\\t\\t// see if it's in the synonyms map, if it is\\n\\t\\t// replace it with the appropriate term, if it's\\n\\t\\t// not, don't do anything. \\n\\t\\tif(myVocab.subMap.get(querystr)!=null){\\n\\t\\t\\tquerystr = myVocab.subMap.get(querystr);\\n\\t\\t\\tquery.setQuery(querystr);\\n\\t\\t}\\n\\n\\t\\tString type = query.getType();\\n\\n\\t\\t// This ArrayList is the results that are going to be returned. \\n\\t\\tArrayList<Result> results = getDirectMatches(myVocab, querystr, uncleaned, type);\\n\\t\\t\\n\\t\\t// If there's a perfect match return it.\\n\\t\\tif (results.size() == 1 && results.get(0).match){\\n\\t\\t\\treturn results;\\n\\t\\t}else{\\n\\t\\t\\t// Otherwise, add the initial ones and try matching\\n\\t\\t\\t// based on distance to vocabulary terms.\\n\\t\\t\\tresults.addAll(distanceMatching(query, myVocab));\\n\\t\\t\\t\\n\\t\\t\\t// Split the original query term by space and non-alphanumeric characters \\n\\t\\t\\t// to find how many words there are.\\n\\t\\t\\t//querystr = query.getQuery().replaceAll(\\\"[\\\\\\\\W_]\\\", \\\" \\\");\\n\\t\\t\\tString [] termList = querystr.split(\\\" \\\");\\n\\t\\t\\t\\n\\t\\t\\t// if there's more than one, run bagOfWords\\n\\t\\t\\t// which tries to find a match for each of the words.\\n\\t\\t\\tif (termList.length > 1){\\n\\t\\t\\t\\tresults.addAll(bagOfWords(query, myVocab));\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\t\\n\\t\\t// Clean the results: no duplicates\\n\\t\\t// no extra results to return, and sorted\\n\\t\\t// them by score before returning them\\n\\t\\tresults = removeDuplicates(results);\\n\\t\\t\\n\\t\\t// They do not need to be reduced in \\n\\t\\t// number if there are fewer than \\n\\t\\t// the max results.\\n\\t\\t// The pruneResults sorts them\\n\\t\\t// by score already.\\n\\t\\tif(query.getLimit()!=null){\\n\\t\\t\\tresults = pruneResults(results,Integer.parseInt(query.getLimit()));\\n\\t\\t}else{\\n\\t\\t\\tresults = pruneResults(results,MAX_RESULTS);\\n\\t\\t}\\n\\t\\t\\t\\n\\t\\tresults = sortByScore(results);\\n\\t\\tfor (int i = 0; i< results.size(); i++){\\n//\\t\\t\\tmyLogger.log(Level.SEVERE,results.get(i).getScore()+ \\\" is bigger than 100?\\\");\\n\\t\\t\\tif(results.get(i).getScore() > (double)100){\\n\\t\\t\\t\\tresults.get(i).setScore((double)100 - (results.get(i).getScore()-(double)100));\\n//\\t\\t\\t\\tmyLogger.log(Level.SEVERE,results.get(i).getScore()+\\\" is bigger than 100! and was set to \\\"+\\n//\\t\\t\\t\\t\\t\\t((double)100 - (results.get(i).getScore()-(double)100)));\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\treturn results;\\n\\t}\",\n \"private String keywordFound(){\\r\\n\\t\\tString rtn = \\\"\\\";\\r\\n\\t\\tString tmp = \\\"\\\";\\r\\n\\t\\tint carr_pos = getCaretPosition();\\r\\n\\t\\t//estract part of text for keyword search\\r\\n\\t\\ttry { \\r\\n\\t\\tif(carr_pos>50)\\r\\n\\t\\t\\ttmp = doc.getText(carr_pos-50,50);\\r\\n\\t\\telse\\r\\n\\t\\t\\ttmp = doc.getText(0,carr_pos);\\r\\n\\t\\t}catch(BadLocationException a){\\r\\n\\t\\t\\tSystem.out.println(\\\"exception\\\");\\r\\n\\t\\t\\treturn rtn;\\r\\n\\t\\t};\\r\\n\\t\\t//Start check\\r\\n\\t\\tint i = 0;\\r\\n\\t\\tif(tmp.length() >= 2)i = tmp.length()-2;\\t\\r\\n\\t\\twhile(checkOperator(tmp.charAt(i)) && i > 0){\\r\\n\\t\\t\\trtn += tmp.charAt(i);\\r\\n\\t\\t\\ti--;\\r\\n\\t\\t}\\r\\n\\t\\tif(i == 0)rtn += tmp.charAt(i);\\t\\t\\r\\n\\t\\treturn mirrorString(rtn);\\r\\n\\t}\",\n \"@Override\\n public List<Document> search(String string)\\n { \\n ArrayList<ArrayList> data = new ArrayList<ArrayList>();\\n data.add(new ArrayList<Document>()); //documents\\n data.add(new ArrayList<Double>()); //relevance\\n data.add(new ArrayList<Integer>()); //occurrence\\n data.add(new ArrayList<Integer>()); //popularity\\n \\n ParseTree tree = new ParseTree(this);\\n \\n String inputarray[]= StringUtils.split(string); //Splits the query on \\\" \\\" \\n if(inputarray.length == 0)\\n {\\n errorMsg();\\n return null;\\n }\\n \\n for(int i = 0; i<inputarray.length; i++) //Inserts the operators/operands in the parsetree.\\n {\\n tree.insert(inputarray[i]);\\n }\\n data = tree.execute(); //executes the parsetree (the difference operations\\n //are executed and data is returned.\\n this.infix = tree.getInfix(); //gets the infix-notation.\\n\\n if(data != null)\\n {\\n return data.get(0);\\n }\\n return null;\\n }\",\n \"@Override\\r\\n\\tpublic SearchableTeletextPage[] getPagesWithText(String query) {\\n\\t\\treturn null;\\r\\n\\t}\",\n \"private void termQuerySearch(String[] terms) {\\n for (String term : terms) {\\n LinkedList<TermPositions> postingLists = indexMap.get(analyzeTerm(term));\\n if (postingLists != null) {\\n for (TermPositions matches : postingLists) {\\n double score = (double) 1 + Math.log((double) matches.getPositionList().size()) *\\n Math.log((double) N / (double) postingLists.size());\\n resultsCollector.add(new DocCollector(matches.getDocId(), score));\\n }\\n }\\n }\\n }\",\n \"@Override\\n\\tpublic List<ScoredTextDocument> search(String query) {\\n\\t\\tList<ScoredTextDocument> scored = new ArrayList<>();\\n\\t\\tDirectory dir = null;\\n\\n\\t\\tStandardAnalyzer analyzer = new StandardAnalyzer(Version.LUCENE_35);\\n\\n\\t\\tQuery q;\\n\\t\\ttry {\\n\\t\\t\\tq = new QueryParser(Version.LUCENE_35, Utils.STR_CONTENT, analyzer).parse(query);\\n\\t\\t} catch (ParseException ex) {\\n\\t\\t\\tLogger.getLogger(LuceneSearcher.class.getName()).log(Level.SEVERE, null, ex);\\n\\t\\t\\tSystem.out.println(\\\"Error en LuceneSearcher\\\");\\n\\t\\t\\treturn null;\\n\\t\\t}\\n\\t\\tTopDocs top;\\n\\t\\ttry {\\n\\t\\t\\t//Finds the top n hits for query.\\n\\t\\t\\ttop = this.indexSearcher.search(q, null, this.indexSearcher.maxDoc());\\n\\t\\t} catch (IOException ex) {\\n\\t\\t\\tLogger.getLogger(LuceneSearcher.class.getName()).log(Level.SEVERE, null, ex);\\n\\t\\t\\tSystem.out.println(\\\"Error en LuceneSearcher\\\");\\n\\t\\t\\treturn null;\\n\\t\\t}\\n\\n\\t\\tfor (ScoreDoc d : top.scoreDocs) {\\n\\t\\t\\tDocument aux = null;\\n\\t\\t\\ttry {\\n\\t\\t\\t\\t//aux=reader.document(top.scoreDocs[j].doc);\\n\\t\\t\\t\\taux = this.indexSearcher.doc(d.doc);\\n\\t\\t\\t} catch (IOException ex) {\\n\\t\\t\\t\\tLogger.getLogger(LuceneSearcher.class.getName()).log(Level.SEVERE, null, ex);\\n\\t\\t\\t}\\n\\t\\t\\tif (aux == null) {\\n\\t\\t\\t\\tcontinue;\\n\\t\\t\\t}\\n\\t\\t\\tString docPath = aux.getFieldable(Utils.DOC_STR_NAME).stringValue();\\n\\t\\t\\tScoredTextDocument textdoc = new ScoredTextDocument(docPath, d.score);\\n\\t\\t\\tscored.add(textdoc);\\n\\t\\t}\\n\\t\\tCollections.sort(scored);\\n\\n\\t\\treturn scored;\\n\\t}\",\n \"public void SearchPhrase(Object_Ord temp) {\\n\\tif (!Doneloading) {\\r\\n\\t return;\\r\\n\\t}\\r\\n\\tif (temp == null) {\\r\\n\\t return;\\r\\n\\t} else if (temp.Ordet.equals(\\\"\\\")) {\\r\\n\\t return;\\r\\n\\t}\\r\\n\\ttemp.Set_Searched();\\r\\n\\t//PrintAction( this.getClass().toString() + \\\" Searching for phrase \\\" + temp.Ordet );\\r\\n\\tThread thread = new Thread_PhraseSearcher(this, temp);\\r\\n\\tThreadsRunning++;\\r\\n\\tThreadsStarted++;\\r\\n }\",\n \"List<DataTerm> search(String searchTerm);\",\n \"protected Query analyzePhrase(String field, TokenStream stream, int slop) throws IOException {\\n PhraseQuery.Builder builder = new PhraseQuery.Builder();\\n builder.setSlop(slop);\\n\\n TermToBytesRefAttribute termAtt = stream.getAttribute(TermToBytesRefAttribute.class);\\n BoostAttribute boostAtt = stream.addAttribute(BoostAttribute.class);\\n PositionIncrementAttribute posIncrAtt = stream.getAttribute(PositionIncrementAttribute.class);\\n int position = -1;\\n float phraseBoost = DEFAULT_BOOST;\\n stream.reset();\\n while (stream.incrementToken()) {\\n if (enablePositionIncrements) {\\n position += posIncrAtt.getPositionIncrement();\\n } else {\\n position += 1;\\n }\\n builder.add(new Term(field, termAtt.getBytesRef()), position);\\n phraseBoost *= boostAtt.getBoost();\\n }\\n PhraseQuery query = builder.build();\\n if (phraseBoost == DEFAULT_BOOST) {\\n return query;\\n }\\n return new BoostQuery(query, phraseBoost);\\n }\",\n \"private ScoreDoc[] searchExec (Query query) {\\n\\n ScoreDoc[] hits = null;\\n\\n try {\\n IndexReader reader = DirectoryReader.open(indexDir);\\n IndexSearcher searcher = new IndexSearcher(reader);\\n TopDocs docs = searcher.search(query, hitsPerPage, new Sort(SortField.FIELD_SCORE)); //search(query, docs);\\n hits = docs.scoreDocs;\\n } catch (IOException e) {\\n e.printStackTrace();\\n }\\n\\n return hits;\\n }\",\n \"public void search() {\\n try {\\n for(int i = 0; i < this.queries.size(); i++){\\n search(i);\\n // in case of error stop\\n if(!this.searchOK(i)){\\n System.out.println(\\\"\\\\t\\\" + new Date().toString() + \\\" \\\" + db + \\\" Search for rest queries cancelled, because failed for query \\\" + i + \\\" : \\\" + this.queries.get(i));\\n break;\\n }\\n }\\n } catch (UnsupportedEncodingException ex) {\\n Logger.getLogger(EntrezSearcher.class.getName()).log(Level.SEVERE, null, ex);\\n }\\n }\",\n \"private ArrayList<WordDocument> executeAdvancedQuery(){\\n ArrayList<WordDocument> documents = customDijkstrasTwoStack(this.query.split(\\\" \\\"));\\n ArrayList<WordDocument> result = new ArrayList<WordDocument>();\\n\\n try{\\n String[] orderByPart = query.substring(query.indexOf(\\\"ORDERBY\\\")).trim().toLowerCase().split(\\\" \\\");\\n if(isOrderByCommand(orderByPart[0]))\\n result = orderBy(documents, orderByPart[1], orderByPart[2]);\\n }catch (StringIndexOutOfBoundsException ex){\\n result = documents;\\n }\\n\\n return result;\\n }\",\n \"public interface DocumentRelatedTermsSearcher {\\n List<ScoredTerm> getDocumentRelatedTerms(int docId, String term) throws SearchException;\\n}\",\n \"@Test\\n public void testCase3 () throws IOException {\\n //\\t\\tlog.trace(\\\"Testcase3\\\");\\n sq = new SpanSegmentQuery(new SpanTermQuery(new Term(\\\"base\\\", \\\"s:d\\\")),\\n new SpanTermQuery(new Term(\\\"base\\\", \\\"s:b\\\")));\\n\\n kr = ki.search(sq, (short) 10);\\n ki.close();\\n\\n assertEquals(\\\"totalResults\\\", kr.getTotalResults(), 1);\\n assertEquals(\\\"doc-number\\\", 2, kr.getMatch(0).getLocalDocID());\\n assertEquals(\\\"StartPos (0)\\\", 1, kr.getMatch(0).startPos);\\n assertEquals(\\\"EndPos (0)\\\", 2, kr.getMatch(0).endPos);\\n }\",\n \"public void search() {\\n String q = this.query.getText();\\n String cat = this.category.getValue();\\n if(cat.equals(\\\"Book\\\")) {\\n searchBook(q);\\n } else {\\n searchCharacter(q);\\n }\\n }\",\n \"CampusSearchQuery generateQuery();\",\n \"@Override\\n\\tprotected void executeSearch(String term) {\\n\\t\\t\\n\\t}\",\n \"@Override\\n public List<SearchResult> search(String queryString, int k) {\\n // TODO: YOUR CODE HERE\\n\\n // Tokenize the query and put it into a Set\\n HashSet<String> tokenSet = new HashSet<>(Searcher.tokenize(queryString));\\n\\n /*\\n * Section 1: FETCHING termId, termFreq and relevant docId from the Query\\n */\\n\\n // Init a set to store Relevant Document Id\\n HashSet<Integer> relevantDocIdSet = new HashSet<>();\\n for (String token : tokenSet) { // Iterates thru all query tokens\\n int termId;\\n try {\\n termId = indexer.getTermDict().get(token);\\n } catch (NullPointerException e) { // In case current token is not in the termDict\\n continue; // Skip this one\\n }\\n // Get the Posting associate to the termId\\n HashSet<Integer> posting = indexer.getPostingLists().get(termId);\\n relevantDocIdSet.addAll(posting); // Add them all to the Relevant Document Id set\\n }\\n\\n /*\\n * Section 2: Calculate Jaccard Coefficient between the Query and all POTENTIAL DOCUMENTS\\n */\\n\\n // ArrayList for the Final Result\\n ArrayList<SearchResult> searchResults = new ArrayList<>();\\n for (Document doc : documents) { // Iterates thru all documents\\n if (!relevantDocIdSet.contains(doc.getId())) { // If the document is relevant\\n searchResults.add(new SearchResult(doc, 0)); // Add the document as a SearchResult with zero score\\n } else {\\n HashSet<String> termIdSet = new HashSet<>(doc.getTokens()); // Get the token set from the document\\n\\n // Calculate Jaccard Coefficient of the document\\n double jaccardScore = JaccardMathHelper.calculateJaccardSimilarity(tokenSet, termIdSet);\\n\\n // Add the SearchResult with the computed Jaccard Score\\n searchResults.add(new SearchResult(doc, jaccardScore));\\n }\\n }\\n\\n return TFIDFSearcher.finalizeSearchResult(searchResults, k);\\n }\",\n \"public String[] searchIndex(Directory ramdir, Query query) \\n\\t\\t\\tthrows Exception {\\n\\t\\tSortedMap<Float,String> sentenceMap = \\n\\t\\t\\t\\tnew TreeMap<Float,String>();\\n\\t\\tIndexReader indexReader = DirectoryReader.open(ramdir);\\n\\t\\tIndexSearcher indexSearcher = new IndexSearcher(indexReader);\\n\\t\\tBM25Similarity similarity = new BM25Similarity(1.2f, 100f);\\n\\n\\t\\tindexSearcher.setSimilarity(similarity);\\n\\t\\tTopDocs topDocs = indexSearcher.search(query, this.numSentences);\\n\\n\\t\\tfor (ScoreDoc scoreDoc : topDocs.scoreDocs) {\\n\\n\\t\\t\\t// System.out.println(scoreDoc.score)\\n\\t\\t\\tint docId = scoreDoc.doc;\\n\\t\\t\\t//System.out.println(searcher.explain(query, docId));\\n\\t\\t\\tDocument doc = indexSearcher.doc(docId);\\n\\t\\t\\t// System.out.println(sentences.get(docId));\\n\\t\\t\\tSystem.out.println(doc.get(\\\"content\\\"));\\n\\n\\t\\t\\t// System.out.println(doc.get(\\\"text\\\"));\\n\\n\\t\\t\\t// if(scoreDoc.score>=0.1F){\\n\\n\\t\\t\\tsentenceMap.put((float) scoreDoc.doc, \\\">> \\\"+StringUtils.chomp(doc.get(\\\"content\\\")));\\n\\t\\t\\t//sentenceMap.put(1/scoreDoc.score,sentences.get(docId));\\n\\t\\t\\t// System.out.println(scoreDoc);\\n\\t\\t\\t// System.out.println(StringUtils.chomp(doc.get(\\\"text\\\")));\\n\\t\\t\\t// }\\n\\t\\t}\\n\\n\\t\\treturn sentenceMap.values().toArray(new String[0]);\\n\\n\\t}\",\n \"public List<Document> SearchField(String queryStr ,List<String> fieldName)\\r\\n\\t{\\r\\n\\t\\treturn null;\\r\\n\\t}\",\n \"@Override\\r\\n\\t\\t\\tpublic List<ScoredDocument> search(Query query, long maxNumberOfDocuments) {\\n\\t\\t\\t\\treturn null;\\r\\n\\t\\t\\t}\",\n \"public static void doPagingSearch(BufferedReader in, IndexSearcher searcher, Query query,\\n int hitsPerPage, boolean raw, boolean interactive) throws IOException {\\n TopDocs results = searcher.search(query, 5 * hitsPerPage);\\n ScoreDoc[] hits = results.scoreDocs;\\n\\n int numTotalHits = results.totalHits;\\n System.out.println(numTotalHits + \\\" total matching documents\\\");\\n\\n int start = 0;\\n int end = Math.min(numTotalHits, hitsPerPage);\\n\\n while (true) {\\n if (end > hits.length) {\\n //System.out.println(\\\"Only results 1 - \\\" + hits.length + \\\" of \\\" + numTotalHits + \\\" total matching documents collected.\\\");\\n //System.out.println(\\\"Collect more (y/n) ?\\\");\\n String line = in.readLine();\\n if (line.length() == 0 || line.charAt(0) == 'n') {\\n break;\\n }\\n hits = searcher.search(query, numTotalHits).scoreDocs;\\n }\\n\\n end = Math.min(hits.length, start + hitsPerPage);\\n\\n for (int i = start; i < end; i++) {\\n if (raw) {\\n System.out.println(\\\"doc=\\\" + hits[i].doc + \\\" score= \\\" + hits[i].score);\\n continue;\\n }\\n\\n Document doc = searcher.doc(hits[i].doc);\\n String path = doc.get(\\\"path\\\");\\n if (path != null) {\\n System.out.println((i + 1) + \\\". \\\" + path);\\n String title = doc.get(\\\"title\\\");\\n if (title != null) {\\n System.out.println(\\\" Title: \\\" + doc.get(\\\"title\\\"));\\n }\\n } else {\\n System.out.println((i + 1) + \\\". \\\" + \\\"No path for this document\\\");\\n }\\n }\\n\\n if (!interactive || end == 0) {\\n break;\\n }\\n\\n if (numTotalHits >= end) {\\n boolean quit = false;\\n while (true) {\\n System.out.print(\\\"Press \\\");\\n if (start - hitsPerPage >= 0) {\\n System.out.print(\\\"(p)revious page, \\\");\\n }\\n if (start + hitsPerPage < numTotalHits) {\\n System.out.print(\\\"(n)ext page, \\\");\\n }\\n System.out.println(\\\"(q)uit or enter number to jump to a page.\\\");\\n\\n String line = in.readLine();\\n if (line.length() == 0 || line.charAt(0) == 'q') {\\n quit = true;\\n break;\\n }\\n if (line.charAt(0) == 'p') {\\n start = Math.max(0, start - hitsPerPage);\\n break;\\n } else if (line.charAt(0) == 'n') {\\n if (start + hitsPerPage < numTotalHits) {\\n start += hitsPerPage;\\n }\\n break;\\n } else {\\n int page = Integer.parseInt(line);\\n if ((page - 1) * hitsPerPage < numTotalHits) {\\n start = (page - 1) * hitsPerPage;\\n break;\\n } else {\\n System.out.println(\\\"No such page\\\");\\n }\\n }\\n }\\n if (quit) break;\\n end = Math.min(numTotalHits, start + hitsPerPage);\\n }\\n }\\n }\",\n \"public List<String> findPhrases() {\\n\\t\\t\\n\\t\\tTrie root = new Trie();\\n\\t\\tList<String> result = new ArrayList<>();\\n\\t\\tQueue<TrieNode> queue = new LinkedList<>();\\n\\n\\t\\tfor (String phrase : phrases) {\\n\\t\\t\\t// build the trie\\n\\t\\t\\t\\n\\t\\t\\troot.insert(phrase);\\n\\t\\t}\\n\\t\\t\\n\\t\\t// initialize the queue\\n\\t\\tqueue.offer(root.getRootNode());\\n\\t\\t\\t\\t\\n\\t\\tfor (String word : stream) {\\n\\t\\t\\t\\n\\t\\t\\t// Search one word at a time and store TrieNodes that match this word.\\n\\t\\t\\t// If the current word extends a previous TrieNode, it may be a matching phrase\\n\\t\\t\\t\\n\\t\\t\\t// buffer to store current matches\\n\\t\\t\\tQueue<TrieNode> buffer = new LinkedList<>();\\n\\t\\t\\t\\n\\t\\t\\twhile(!queue.isEmpty()) {\\n\\t\\t\\t\\t// iterate through previous matches\\n\\t\\t\\t\\t\\n\\t\\t\\t\\tTrieNode next = queue.poll().find(word);\\n\\t\\t\\t\\t\\n\\t\\t\\t\\tif (next != null) {\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t// if this word extends the previous word, add it to the buffer\\n\\t\\t\\t\\t\\t// in case the next word can also extend it\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\tbuffer.offer(next);\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\tif (next.isPhrase()) {\\n\\t\\t\\t\\t\\t\\t// if we found a valid phrase node, add it to the result\\t\\n\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\tresult.add(next.getPhrase());\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\n\\t\\t\\t}\\n\\t\\t\\t\\n\\t\\t\\tqueue = buffer;\\n\\t\\t\\tqueue.offer(root.getRootNode());\\n\\t\\t}\\n\\t\\t\\n\\t\\treturn result;\\n\\t}\",\n \"protected final void searchForText() {\\n Logger.debug(\\\" - search for text\\\");\\n final String searchText = theSearchEdit.getText().toString();\\n\\n MultiDaoSearchTask task = new MultiDaoSearchTask() {\\n @Override\\n protected void onSearchCompleted(List<Object> results) {\\n adapter.setData(results);\\n }\\n\\n @Override\\n protected int getMinSearchTextLength() {\\n return 0;\\n }\\n };\\n task.readDaos.add(crDao);\\n task.readDaos.add(monsterDao);\\n task.readDaos.add(customMonsterDao);\\n task.execute(searchText.toUpperCase());\\n }\",\n \"List<SearchResult> search(SearchQuery searchQuery);\",\n \"public PostingsList phrase_query(PostingsList l1, PostingsList l2){\\n\\n PostingsList phrase = new PostingsList();\\n\\n // Counters to iterate docIDs\\n int count1 = 0;\\n int count2 = 0;\\n // Counters to iterate positional indices\\n int subcount1 = 0;\\n int subcount2 = 0;\\n\\n // First posting\\n PostingsEntry p1 = l1.get(0);\\n PostingsEntry p2 = l2.get(0);\\n\\n // List of positional indices (changes at each iteration)\\n LinkedList<Integer> ll1;\\n LinkedList<Integer> ll2;\\n\\n // Used to store positional index\\n int pp1;\\n int pp2;\\n\\n while(true){\\n // docID match (1/2) //\\n if (p1.docID == p2.docID){\\n // Obtain list of positional indices\\n ll1 = p1.positions;\\n ll2 = p2.positions;\\n // First positional indices\\n pp1 = ll1.get(0);\\n pp2 = ll2.get(0);\\n // Initialize counter\\n subcount1 = 0;\\n subcount2 = 0;\\n\\n // Search if the phrase exists\\n while(true){\\n // Match, consecutive words (2/2) - EUREKA! //\\n if (pp1+1 == pp2){\\n // Save found match (docID and positional index of last\\n // word)\\n phrase.insert(p1.docID, pp2);\\n // Increase counters and pos indices if list is not finished\\n subcount1++;\\n subcount2++;\\n if (subcount1<ll1.size() && subcount2<ll2.size()){\\n pp1 = ll1.get(subcount1);\\n pp2 = ll2.get(subcount2);\\n }\\n // If list finished, break\\n else\\n break;\\n }\\n // Not match\\n else if (pp1+1 < pp2){\\n subcount1++;\\n if (subcount1<ll1.size())\\n pp1 = ll1.get(subcount1);\\n // If list finished, break\\n else\\n break;\\n }\\n // Not match\\n else{\\n subcount2++;\\n if (subcount2<ll2.size())\\n pp2 = ll2.get(subcount2);\\n else\\n break;\\n }\\n }\\n\\n // Once we finished looking at the list of positional indices of one\\n // posting, increase counters and go to next postings (if there are)\\n count1++;\\n count2++;\\n if (count1<l1.size() && count2<l2.size()){\\n p1 = l1.get(count1);\\n p2 = l2.get(count2);\\n }\\n else{\\n break;\\n }\\n }\\n // docID not match, increase lowest counter\\n else if (p1.docID < p2.docID){\\n count1++;\\n if (count1<l1.size()){\\n p1 = l1.get(count1);\\n }\\n else{\\n break;\\n }\\n }\\n // docID not match, increase lowest counter\\n else{\\n count2++;\\n if (count2<l2.size()){\\n p2 = l2.get(count2);\\n }\\n else{\\n break;\\n }\\n }\\n }\\n\\n return phrase;\\n }\",\n \"Page<NoteDTO> search(String query, Pageable pageable);\",\n \"public List<SearchResultDocument> getSearchResults(String query) throws IOException, ParseException {\\n return luceneIndexer.getSearchResults(query);\\n }\",\n \"public abstract Search defaultSearch(StringBuilder sb);\",\n \"@Override\\n\\tpublic NodeIterator search(String queryString) throws Exception {\\n\\t\\treturn null;\\n\\t}\",\n \"@Query(\\\"name = ?\\\")\\n List<PersonDocument> findByName(String name);\",\n \"public HashMap<String, Double> search(String query) {\\n // ===================================================\\n // 1. Fetch all inverted lists corresponding to terms\\n // in the query.\\n // ===================================================\\n String[] terms = query.split(\\\" \\\");\\n HashMap<String, Integer> qf = new HashMap<String, Integer>();\\n // Calculate term frequencies in the query\\n for (String term : terms) {\\n if (qf.containsKey(term))\\n qf.put(term, qf.get(term) + 1);\\n else\\n qf.put(term, 1);\\n }\\n HashMap<String, Double> docScore = new HashMap<String, Double>();\\n for (Entry<String, Integer> termEntry : qf.entrySet()) {\\n String term = termEntry.getKey();\\n int qfi = termEntry.getValue();\\n\\n // ===================================================\\n // 2. Compute BM25 scores for documents in the lists.\\n // Make a score list for documents in the inverted\\n // lists. Assume that no relevance information is \\n // available. For parameters, use k1=1.2, b=0.75, \\n // k2=100.\\n // ===================================================\\n double k1 = 1.2;\\n double b = 0.75;\\n double k2 = 100;\\n int ni = invIndex.get(term).size();\\n\\n\\n for (Entry<String, IndexEntry> invListEntry : invIndex.get(term).entrySet()) {\\n String docID = invListEntry.getKey();\\n double bm25Score;\\n if (docScore.containsKey(docID))\\n bm25Score = docScore.get(docID);\\n else\\n bm25Score = 0;\\n\\n // length of the document\\n int dl = docStat.get(docID);\\n // frequency of the term in the document\\n int fi = invListEntry.getValue().getTf();\\n double K = k1 * ((1 - b) + b * ((double) dl / avdl));\\n\\n // ===================================================\\n // 3. Accumulate scores for each term in a query\\n // on the score list.\\n // ===================================================\\n bm25Score += Math.log((N - ni + 0.5) / (ni + 0.5))\\n * (((k1 + 1) * fi * (k2 + 1) * qfi) / ((K + fi) * (k2 + qfi)));\\n docScore.put(docID, bm25Score);\\n }\\n }\\n\\n return docScore;\\n }\",\n \"abstract public void search();\",\n \"MongoCursor<Document> findByPersonName(String personName);\",\n \"private ArrayList<WordDocument> getDocumentsWhereWordExists(String word){\\n try{\\n return dictionary.get(word).getDocumentWhereWordExistsIn();\\n }catch (NullPointerException ex){\\n return new ArrayList<WordDocument>();\\n }\\n }\",\n \"@Override\\n public List<DefinitionDTO> findWordsByWord(String query) {\\n List<Word> words = wordRepository.findBySearchString(query);\\n return DTOMapper.mapWordListToDefinitionDTOList(words);\\n }\",\n \"List<Corretor> search(String query);\",\n \"public void doSearch(BufferedReader in, IndexSearcher searcher, Query query, \\n int hitsPerPage, boolean raw, boolean interactive) throws IOException {\\n TopDocs results = searcher.search(query, 5 * hitsPerPage);\\n ScoreDoc[] hits = results.scoreDocs;\\n \\n int numTotalHits = results.totalHits;\\n System.out.println(numTotalHits + \\\" total matching documents\\\");\\n\\n int start = 0;\\n int end = Math.min(numTotalHits, hitsPerPage);\\n \\n for (int i = start; i < end; i++) \\n {\\n Document doc = searcher.doc(hits[i].doc);\\n String id = doc.get(\\\"id\\\");\\n String author=doc.get(\\\"author\\\");\\n String price=doc.get(\\\"price\\\");\\n String category=doc.get(\\\"category\\\");\\n String bookname=doc.get(\\\"bookname\\\");\\n System.out.println(id+author+price+category+bookname);\\n }\\n }\",\n \"static void allDocumentAnalyzer() throws IOException {\\n\\t\\tFile allFiles = new File(\\\".\\\"); // current directory\\n\\t\\tFile[] files = allFiles.listFiles(); // file array\\n\\n\\t\\t// recurse through all documents\\n\\t\\tfor (File doc : files) {\\n\\t\\t\\t// other files we don't need\\n\\t\\t\\tif (doc.getName().contains(\\\".java\\\") || doc.getName().contains(\\\"words\\\") || doc.getName().contains(\\\"names\\\")\\n\\t\\t\\t\\t\\t|| doc.getName().contains(\\\"phrases\\\") || doc.getName().contains(\\\".class\\\")\\n\\t\\t\\t\\t\\t|| doc.getName().contains(\\\"Data\\\") || doc.getName().contains(\\\".sh\\\") || doc.isDirectory()\\n\\t\\t\\t\\t\\t|| !doc.getName().contains(\\\".txt\\\")) {\\n\\t\\t\\t\\tcontinue;\\n\\t\\t\\t}\\n\\n\\t\\t\\tString name = doc.getName();\\n\\t\\t\\tSystem.out.println(name);\\n\\t\\t\\tname = name.substring(0, name.length() - 11);\\n\\t\\t\\tSystem.out.println(name);\\n\\n\\t\\t\\tif (!names.contains(name)) {\\n\\t\\t\\t\\tcontinue;\\n\\t\\t\\t}\\n\\n\\t\\t\\t// make readers\\n\\t\\t\\tFileReader fr = new FileReader(doc);\\n\\t\\t\\tBufferedReader br = new BufferedReader(fr);\\n\\n\\t\\t\\t// phrase list\\n\\t\\t\\tArrayList<String> words = new ArrayList<String>();\\n\\n\\t\\t\\t// retrieve all text, trim, refine and add to phrase list\\n\\t\\t\\tString nextLine = br.readLine();\\n\\t\\t\\twhile (nextLine != null) {\\n\\t\\t\\t\\tnextLine = nextLine.replace(\\\"\\\\n\\\", \\\" \\\");\\n\\t\\t\\t\\tnextLine = nextLine.trim();\\n\\n\\t\\t\\t\\tif (nextLine.contains(\\\"no experience listed\\\")) {\\n\\t\\t\\t\\t\\tbreak;\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\tString[] lineArray = nextLine.split(\\\"\\\\\\\\s+\\\");\\n\\n\\t\\t\\t\\t// recurse through every word to find phrases\\n\\t\\t\\t\\tfor (int i = 0; i < lineArray.length - 1; i++) {\\n\\t\\t\\t\\t\\t// get the current word and refine\\n\\t\\t\\t\\t\\tString currentWord = lineArray[i];\\n\\n\\t\\t\\t\\t\\tcurrentWord = currentWord.trim();\\n\\t\\t\\t\\t\\tcurrentWord = refineWord(currentWord);\\n\\n\\t\\t\\t\\t\\tif (currentWord.equals(\\\"\\\") || currentWord.isEmpty()) {\\n\\t\\t\\t\\t\\t\\tcontinue;\\n\\t\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\t\\twords.add(currentWord);\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\tnextLine = br.readLine();\\n\\t\\t\\t}\\n\\n\\t\\t\\tbr.close();\\n\\n\\t\\t\\t// continue if empty\\n\\t\\t\\tif (words.size() == 0) {\\n\\t\\t\\t\\tcontinue;\\n\\t\\t\\t}\\n\\n\\t\\t\\t// otherwise, increment number of files in corpus\\n\\t\\t\\tsize++;\\n\\n\\t\\t\\t// updating the phrase count map for tf\\n\\t\\t\\tString fileName = doc.getName();\\n\\t\\t\\tphraseCountMap.put(fileName, words.size());\\n\\n\\t\\t\\t// recurse through every word\\n\\t\\t\\tfor (String word : words) {\\n\\t\\t\\t\\t// get map from string to freq\\n\\t\\t\\t\\tHashMap<String, Integer> textFreqMap = wordFreqMap.get(fileName);\\n\\n\\t\\t\\t\\t// if it's null, make one\\n\\t\\t\\t\\tif (textFreqMap == null) {\\n\\t\\t\\t\\t\\ttextFreqMap = new HashMap<String, Integer>();\\n\\t\\t\\t\\t\\t// make freq as 1\\n\\t\\t\\t\\t\\ttextFreqMap.put(word, 1);\\n\\t\\t\\t\\t\\t// put that in wordFreq\\n\\t\\t\\t\\t\\twordFreqMap.put(fileName, textFreqMap);\\n\\t\\t\\t\\t} else {\\n\\t\\t\\t\\t\\t// otherwise, get the current num\\n\\t\\t\\t\\t\\tInteger currentFreq = textFreqMap.get(word);\\n\\n\\t\\t\\t\\t\\t// if it's null,\\n\\t\\t\\t\\t\\tif (currentFreq == null) {\\n\\t\\t\\t\\t\\t\\t// the frequency is just 0\\n\\t\\t\\t\\t\\t\\tcurrentFreq = 0;\\n\\t\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\t\\t// increment the frequency\\n\\t\\t\\t\\t\\tcurrentFreq++;\\n\\n\\t\\t\\t\\t\\t// put it in the textFreqMap\\n\\t\\t\\t\\t\\ttextFreqMap.put(word, currentFreq);\\n\\n\\t\\t\\t\\t\\t// put that in the wordFreqMap\\n\\t\\t\\t\\t\\twordFreqMap.put(fileName, textFreqMap);\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\t// add this to record (map from phrases to docs with that\\n\\t\\t\\t\\t// phrase)\\n\\t\\t\\t\\tinvertedMap.addValue(word, doc);\\n\\t\\t\\t}\\n\\t\\t}\\n\\t}\",\n \"public void search() {\\r\\n \\t\\r\\n }\",\n \"private void searchWord()\\n {\\n String inputWord = searchField.getText();\\n \\n if(inputWord.isEmpty())\\n queryResult = null;\\n \\n else\\n {\\n char firstLetter = inputWord.toUpperCase().charAt(0);\\n \\n for(int i = 0 ; i < lexiNodeTrees.size() ; i++)\\n {\\n if(lexiNodeTrees.get(i).getCurrentCharacter() == firstLetter)\\n {\\n queryResult = lexiNodeTrees.get(i).searchWord(inputWord, false);\\n i = lexiNodeTrees.size(); // escape the loop\\n }\\n }\\n }\\n \\n // update the list on the GUI\\n if(queryResult != null)\\n {\\n ArrayList<String> words = new ArrayList<>();\\n for(WordDefinition word : queryResult)\\n {\\n words.add(word.getWord());\\n }\\n \\n // sort the list of words alphabetically \\n Collections.sort(words);\\n \\n // display the list of wordsin the UI\\n DefaultListModel model = new DefaultListModel();\\n for(String word : words)\\n {\\n model.addElement(word);\\n }\\n\\n this.getSearchSuggestionList().setModel(model);\\n }\\n \\n else\\n this.getSearchSuggestionList().setModel( new DefaultListModel() );\\n }\",\n \"private List<FindResult> findOnPage(int page) {\\n\\t\\t\\tif (this.text == null) throw new IllegalStateException(\\\"text cannot be null\\\");\\n\\t\\t\\treturn this.parent.pdf.find(this.text, page);\\n\\t\\t}\",\n \"public void searchIndex(Directory index) throws Exception{\\n\\t\\tString searchString = getSearchString();\\n\\t\\t\\n\\t\\tSystem.out.println(\\\"Searching for '\\\" + searchString + \\\"'\\\");\\n\\n\\t\\tIndexReader indexReader = DirectoryReader.open(index);\\n\\t\\tIndexSearcher indexSearcher = new IndexSearcher(indexReader);\\n\\n\\t\\tAnalyzer analyzer = new StandardAnalyzer();\\n\\t\\t\\n\\t\\tString query_string = \\\"title:\\\" + searchString + \\\" OR content:\\\" + searchString + \\\"OR important:\\\" + searchString + \\\"OR h1:\\\" + searchString +\\n\\t\\t\\t\\t\\\"OR h2:\\\" + searchString + \\\"OR h3:\\\" + searchString + \\\"OR h4:\\\" + searchString + \\\"OR h5:\\\" + searchString + \\\"OR h6:\\\" + searchString;\\n\\t\\tQueryParser queryParser = new QueryParser(\\\"title\\\", analyzer);\\n\\t\\t\\n\\t\\tTopDocs docs = indexSearcher.search(queryParser.parse(query_string), 10);\\n\\t\\t\\n\\t\\t\\n//\\t\\tString[] fields = {\\\"content\\\", \\\"title\\\", \\\"important\\\", \\\"h1\\\", \\\"h2\\\", \\\"h3\\\", \\\"h4\\\", \\\"h5\\\", \\\"h6\\\"};\\n//\\t\\tBooleanClause.Occur[] flags = \\n//\\t\\t{\\n//\\t\\t\\tBooleanClause.Occur.SHOULD,\\n//\\t\\t\\tBooleanClause.Occur.SHOULD,\\n//\\t\\t\\tBooleanClause.Occur.SHOULD,\\n//\\t\\t\\tBooleanClause.Occur.SHOULD,\\n//\\t\\t\\tBooleanClause.Occur.SHOULD,\\n//\\t\\t\\tBooleanClause.Occur.SHOULD,\\n//\\t\\t\\tBooleanClause.Occur.SHOULD,\\n//\\t\\t\\tBooleanClause.Occur.SHOULD,\\n//\\t\\t\\tBooleanClause.Occur.SHOULD,\\n// };\\n//\\t\\t\\n//\\t\\tTopDocs docs = indexSearcher.search(MultiFieldQueryParser.parse(searchString, fields, flags, analyzer), 10);\\n\\n\\t\\tScoreDoc[] hits = docs.scoreDocs;\\n\\n\\t System.out.println(\\\"Found \\\" + hits.length + \\\" hits.\\\");\\n\\t for(int i=0;i<hits.length;++i) {\\n\\t \\tint docId = hits[i].doc;\\n\\t Document d = indexSearcher.doc(docId);\\n\\t System.out.println((i + 1) + \\\". \\\" + d.get(\\\"title\\\") + \\\"\\\\t\\\" + d.get(\\\"url\\\") + \\\"\\\\t\\\" + hits[i].score);\\n\\t }\\n\\t}\",\n \"@Test\\n\\tpublic void testKeywordQuery(){\\n\\t\\t//manager.getResponse(\\\"american football \\\"); //match multiple keywords\\n//\\t\\tmanager.getResponse(\\\"list of Bond 007 movies\\\");\\n//\\tmanager.getResponse(\\\"Disney movies\\\");\\n\\t\\t//manager.keywordQuery(\\\"Paul Brown Stadium location\\\");\\n\\t\\t//manager.keywordQuery(\\\"0Francesco\\\");\\n System.out.println(\\\"******* keyword query *******\\\");\\n\\t\\t//manager.keywordQuery(\\\"sportspeople in tennis\\\");\\n\\t\\t//manager.keywordSearch(\\\"list of movies starring Sean Connery\\\",ElasticIndex.analyzed,100 );\\n//\\t\\tmanager.keywordSearch(\\\"movies starring Sean Connery\\\",ElasticIndex.notStemmed,100 );\\n// manager.keywordSearch(\\\"musical movies tony award\\\",ElasticIndex.analyzed,100 );\\n// manager.keywordSearch(\\\"movies directed by Woody Allen\\\",ElasticIndex.analyzed,100 );\\n// manager.keywordSearch(\\\"United states professional sports teams\\\",ElasticIndex.analyzed,100 );\\n// manager.keywordSearch(\\\"computer games developed by Ubisoft\\\",ElasticIndex.analyzed,100 );\\n// manager.keywordSearch(\\\"computer games developed by Ubisoft\\\",ElasticIndex.notStemmed,100 );\\n// manager.keywordSearch(\\\"movies academy award nominations\\\",ElasticIndex.notStemmed,100 );\\n System.out.println(SearchResultUtil.toSummary(manager.keywordSearch(\\\"movies directed by Woody Allen\\\",ElasticIndex.notLowercased,20 )));\\n //manager.keywordSearch(\\\"grammy best album in 2012\\\",ElasticIndex.notAnalyzed,100 );\\n //(better than analyzed) manager.keywordSearch(\\\"grammy best album in 2012\\\",ElasticIndex.notStemmed,100 );\\n System.out.println(\\\"*****************************\\\");\\n\\n\\t\\t//manager.keywordQuery(\\\"Disney movies\\\");\\n\\t}\",\n \"List<PilotContainer> Search(String cas, String word);\",\n \"@Test\\n public void findsByKeyword() throws Exception {\\n final Base base = new DyBase(\\n this.dynamo.region(), new MkSttc().counters().get(\\\"ttt\\\")\\n );\\n final Book book = base.books().add(\\n \\\"@book{best2014, author=\\\\\\\"Walter\\\\\\\"}\\\"\\n );\\n final Quotes quotes = base.quotes();\\n quotes.add(\\n book, \\\"never give up and never think about bad things, Bobby\\\",\\n \\\"99-101, 256-257, 315\\\"\\n );\\n MatcherAssert.assertThat(\\n quotes.refine(\\\"bobby\\\").iterate(),\\n Matchers.<Quote>iterableWithSize(1)\\n );\\n MatcherAssert.assertThat(\\n quotes.refine(\\\"another-something\\\").iterate(),\\n Matchers.<Quote>iterableWithSize(0)\\n );\\n }\",\n \"@Override\\n\\tpublic List<Document> findDocumentsByQuestion(String question) {\\n\\t\\t\\n\\t\\tString [] keyWords = question.split(\\\" \\\");\\n\\t\\tList<Document> documents = new ArrayList<>();\\n\\t\\t\\n\\t\\tList<Filters> filters = filtersRepository.findByCommonsWordsWordIn(keyWords);\\n\\t\\tfor(Filters f : filters){\\n\\t\\t\\tdocuments.addAll(f.getDocuments());\\n\\t\\t}\\n\\t\\t\\n\\t\\treturn documents;\\n\\t}\",\n \"List<Cemetery> search(String query);\",\n \"public List<Document> retrieveQuery( Query aQuery, int TopN ) throws IOException {\\n\\t\\t// NT: you will find our IndexingLucene.Myindexreader provides method: docLength()\\n\\t\\t// implement your retrieval model here, and for each input query, return the topN retrieved documents\\n\\t\\t// sort the documents based on their relevance score, from high to low\\n\\n\\t\\tHashMap<Integer, HashMap<String,Integer>> idTokenDocFrequencyMap = new HashMap<>();\\t//docid - (token - document frequency) map\\n\\t\\tHashMap<String, Long> tokenColFrequencyMap = new HashMap<>();\\t// token - collection frequency map\\n\\t\\tString content = aQuery.GetQueryContent();\\n\\t\\tString[] tokens = content.split(\\\" \\\");\\n\\n\\t\\tfor(String token : tokens){\\n\\t\\t\\ttokenColFrequencyMap.put(token, indexReader.CollectionFreq(token)); \\t// update the second map\\n\\t\\t\\tint [][]postingList = indexReader.getPostingList(token);\\n\\t\\t\\tif(postingList == null) continue;\\n\\t\\t\\tfor(int i = 0; i < postingList.length; i++){\\n\\t\\t\\t\\tint docid = postingList[i][0];\\n\\t\\t\\t\\tint freq = postingList[i][1];\\n\\t\\t\\t\\tif(idTokenDocFrequencyMap.containsKey(docid)){\\t\\t// update the first map\\n\\t\\t\\t\\t\\tidTokenDocFrequencyMap.get(docid).put(token,freq);\\n\\t\\t\\t\\t}else {\\n\\t\\t\\t\\t\\tHashMap<String,Integer> tokenFrequencyMap = new HashMap<>();\\n\\t\\t\\t\\t\\ttokenFrequencyMap.put(token,freq);\\n\\t\\t\\t\\t\\tidTokenDocFrequencyMap.put(docid,tokenFrequencyMap);\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\tdouble U = 2000.0;\\n\\t\\tList<Document> documentList = new ArrayList<>();\\n\\t\\t// if use a docidList, it will have some duplicates.\\n\\t\\tfor(Map.Entry<Integer, HashMap<String,Integer>> entry : idTokenDocFrequencyMap.entrySet()){\\n\\t\\t\\tdouble score = 1.0;\\t\\t\\t// each document have one score\\n\\t\\t\\tint docid = entry.getKey();\\n\\t\\t\\tint docLen = indexReader.docLength(docid);\\t// get document length\\n\\t\\t\\tHashMap<String,Integer> tokenDocFrequencyMap = idTokenDocFrequencyMap.get(docid);\\n\\t\\t\\tfor(String token : tokens){\\t\\t// for each token, not the token just exist in the document\\n\\t\\t\\t\\tlong colFreq = tokenColFrequencyMap.getOrDefault(token,0l);\\t// get collection frequency\\n\\t\\t\\t\\tif(colFreq != 0){\\n\\t\\t\\t\\t\\tint docFreq = 0;\\t// if this document don't have token, just set document frequency as 0\\n\\t\\t\\t\\t\\tif(tokenDocFrequencyMap.containsKey(token)){\\n\\t\\t\\t\\t\\t\\tdocFreq = tokenDocFrequencyMap.get(token);\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\tscore = score * (docFreq + U * ((double)colFreq / colLen)) / (docLen + U);\\t//equation\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t\\tDocument document = new Document(docid+\\\"\\\", indexReader.getDocno(docid),score);\\n\\t\\t\\tdocumentList.add(document);\\n\\t\\t}\\n\\n\\t\\tCollections.sort(documentList, new Comparator<Document>() {\\n\\t\\t\\t@Override\\n\\t\\t\\tpublic int compare(Document o1, Document o2) {\\n\\t\\t\\t\\treturn Double.compare(o2.score(),o1.score());\\n\\t\\t\\t}\\n\\t\\t});\\n\\t\\tList<Document> res = new ArrayList<>();\\n\\t\\tfor(int i = 0 ; i < TopN; i++){\\n\\t\\t\\tres.add(documentList.get(i));\\n\\t\\t}\\n\\t\\treturn res;\\n\\t}\",\n \"public static SearchQuery buildAutocompleteKnowledgeQuery(String searchWord) {\\n\\n BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery();\\n boolQueryBuilder.should(QueryBuilders.matchQuery(\\\"nameNgram\\\", searchWord))\\n .must(QueryBuilders.matchQuery(\\\"nameSimple\\\", searchWord));\\n// boolQueryBuilder.must(QueryBuilders.matchQuery(\\\"nameNgram\\\", searchWord)).must(QueryBuilders.matchQuery(\\\"nameSimple\\\", searchWord));\\n// boolQueryBuilder.should(QueryBuilders.matchQuery(\\\"nameNgram\\\", searchWord));\\n\\n return buildNativeQuery(boolQueryBuilder, 0, 20);\\n }\",\n \"private DocFile[] search (String[] queries, String[] filters, BooleanClause.Occur filterOccur) throws ParseException {\\n // create a master query builder\\n BooleanQuery.Builder masterQueryBuilder = new BooleanQuery.Builder();\\n // loop through all queries\\n for (String query : queries) {\\n if (query.equals(\\\"\\\")) continue;\\n // create a boolean query for the each query\\n BooleanQuery.Builder queryBuilder = new BooleanQuery.Builder();\\n // loop through all filters\\n for (String filter : filters) {\\n if (filter.equals(\\\"\\\")) continue;\\n QueryParser parser = new QueryParser(filter, analyzer);\\n parser.setAllowLeadingWildcard(true);\\n if (!filter.equals(Constants.INDEX_KEY_OWNER)) {\\n Query parsedQ = parser.parse(query);\\n queryBuilder.add(parsedQ, filterOccur);\\n }\\n else {\\n queryBuilder.add(new PhraseQuery(filter, queries), filterOccur);\\n }\\n }\\n masterQueryBuilder.add(queryBuilder.build(), BooleanClause.Occur.SHOULD);\\n }\\n\\n // build the masterQuery\\n BooleanQuery masterQuery = masterQueryBuilder.build();\\n\\n return searchResponse(searchExec(masterQuery), masterQuery);\\n }\",\n \"Set<Document> findDocuments(Map<String, String> fields, int offset, int numberOfResults);\",\n \"@Override\\n public String search(String word) {\\n return search(word, root);\\n }\",\n \"@Override\\n public boolean onQueryTextSubmit(String query) {\\n prepareBooks(engine.search(query.toLowerCase(),filter));\\n return false;\\n }\",\n \"@Test\\n public void testCase2 () throws IOException {\\n //\\t\\tlog.trace(\\\"Testcase2\\\");\\n sq = new SpanSegmentQuery(new SpanTermQuery(new Term(\\\"base\\\", \\\"s:a\\\")),\\n new SpanTermQuery(new Term(\\\"base\\\", \\\"s:b\\\")));\\n\\n kr = ki.search(sq, (short) 10);\\n ki.close();\\n\\n assertEquals(\\\"totalResults\\\", kr.getTotalResults(), 3);\\n // Match #0\\n assertEquals(\\\"doc-number\\\", 1, kr.getMatch(0).getLocalDocID());\\n assertEquals(\\\"StartPos\\\", 1, kr.getMatch(0).startPos);\\n assertEquals(\\\"EndPos\\\", 2, kr.getMatch(0).endPos);\\n // Match #2\\n assertEquals(\\\"doc-number\\\", 2, kr.getMatch(2).getLocalDocID());\\n assertEquals(\\\"StartPos\\\", 2, kr.getMatch(2).startPos);\\n assertEquals(\\\"EndPos\\\", 3, kr.getMatch(2).endPos);\\n }\",\n \"public abstract int search(String[] words, String wordToFind) throws ItemNotFoundException;\",\n \"public void parseQueryStringAndSearch(String searchString) {\\n char[] chars = searchString.toCharArray();\\n for (int i = 0; i < chars.length; i++) {\\n Queue<Character> queue;\\n int k;\\n if (Character.isDigit(chars[i])) {\\n k = Integer.parseInt(String.valueOf(chars[i]));\\n i++;\\n queue = new LinkedList<>();\\n while (i < chars.length && chars[i] != ')') {\\n queue.add(chars[i]);\\n i++;\\n }\\n i++;\\n String query = queryToString(queue);\\n String[] terms = query.split(\\\" \\\");\\n //System.out.println(query + \\\" and k: \\\" + k);\\n positionIntersects(indexMap.get(analyzeTerm(terms[0])), indexMap.get(analyzeTerm(terms[1])), k);\\n } else {\\n queue = new LinkedList<>();\\n while (i < chars.length && !Character.isDigit(chars[i])) {\\n queue.add(chars[i]);\\n i++;\\n }\\n i--;\\n String query = queryToString(queue);\\n String[] terms = query.trim().split(\\\" \\\");\\n termQuerySearch(terms);\\n }\\n\\n }\\n\\n }\",\n \"@Override\\n public SearchDocument nextDocument(SearchQuery query, int docId) {\\n return null;\\n }\",\n \"public void doSearch(String query)\\n \\t{\\n \\t\\tlistener.onQueryTextSubmit(query);\\n \\t}\",\n \"public void search() {\\n }\",\n \"private static String lookForSentenceWhichContains(String[] words, String documentPath) throws IOException {\\r\\n\\r\\n File document = new File(documentPath);\\r\\n\\r\\n if (!document.exists()) throw new FileNotFoundException(\\\"File located at \\\"+documentPath+\\\" doesn't exist.\\\\n\\\");\\r\\n\\r\\n FileReader r = new FileReader(document);\\r\\n BufferedReader br = new BufferedReader(r);\\r\\n\\r\\n String line;\\r\\n String documentText = \\\"\\\";\\r\\n while ( (line=br.readLine()) != null) {\\r\\n documentText += line;\\r\\n }\\r\\n\\r\\n documentText = Jsoup.parse(documentText).text();\\r\\n\\r\\n String[] listOfSentences = documentText.split(\\\"\\\\\\\\.\\\");\\r\\n HashMap<String,String> originalToNormalized = new HashMap<>();\\r\\n String original;\\r\\n\\r\\n for (String sentence: listOfSentences){\\r\\n\\r\\n original = sentence;\\r\\n\\r\\n sentence = sentence.toLowerCase();\\r\\n sentence = StringUtils.stripAccents(sentence);\\r\\n sentence = sentence.replaceAll(\\\"[^a-z0-9-._\\\\\\\\n]\\\", \\\" \\\");\\r\\n\\r\\n originalToNormalized.put(original,sentence);\\r\\n }\\r\\n\\r\\n int matches, maxMatches = 0;\\r\\n String output = \\\"\\\";\\r\\n\\r\\n for (Map.Entry<String,String> sentence: originalToNormalized.entrySet()){\\r\\n\\r\\n matches = 0;\\r\\n\\r\\n for (String word: words){\\r\\n if (sentence.getValue().contains(word)) matches++;\\r\\n }\\r\\n\\r\\n if (matches == words.length) return sentence.getKey();\\r\\n if (matches > maxMatches){\\r\\n maxMatches = matches;\\r\\n output = sentence.getKey();\\r\\n }\\r\\n }\\r\\n\\r\\n return output;\\r\\n\\r\\n }\",\n \"@Override\\r\\n\\tpublic List<Post> searchInfResult(String word) {\\n\\t\\tpostDao=new PostDaoImpl(TransactionManager.connection);\\r\\n\\t\\treturn postDao.selectPosts(word);\\r\\n\\t}\",\n \"Page<T> search(Pageable pageable, String query);\",\n \"@Test\\n public void testCase1 () throws IOException {\\n sq = new SpanSegmentQuery(new SpanTermQuery(new Term(\\\"base\\\", \\\"s:b\\\")),\\n new SpanTermQuery(new Term(\\\"base\\\", \\\"s:c\\\")));\\n\\n kr = ki.search(sq, (short) 10);\\n ki.close();\\n\\n assertEquals(\\\"totalResults\\\", kr.getTotalResults(), 3);\\n assertEquals(\\\"StartPos (0)\\\", 1, kr.getMatch(0).startPos);\\n assertEquals(\\\"EndPos (0)\\\", 2, kr.getMatch(0).endPos);\\n assertEquals(\\\"StartPos (1)\\\", 4, kr.getMatch(1).startPos);\\n assertEquals(\\\"EndPos (1)\\\", 5, kr.getMatch(1).endPos);\\n }\",\n \"void search();\",\n \"void search();\",\n \"@Override\\n public List<Document> findInDocuments(String collectionName, Bson query) {\\n return null;\\n }\",\n \"private boolean isTermAppearInQuery(String term) {\\n boolean isTermAppear = false;\\n query thisQuery = listDocumentRetrievedForThisQuery.getQuery();\\n StringTokenizer token = new StringTokenizer(thisQuery.getQueryContent(), \\\" %&\\\\\\\"*#@$^_<>|`+=-1234567890'(){}[]/.:;?!,\\\\n\\\");\\n while (token.hasMoreTokens()) {\\n String keyTerm = token.nextToken();\\n if (invertedFile.isStemmingApplied()) {\\n keyTerm = StemmingPorter.stripAffixes(keyTerm);\\n }\\n if (term.equals(keyTerm.toLowerCase())) {\\n isTermAppear = true;\\n break;\\n }\\n }\\n return isTermAppear;\\n }\",\n \"Page<T> search(Pageable pageable, QueryBuilder query);\",\n \"public MagicSearch createMagicSearch();\",\n \"@Test\\n public void testCase4 () throws IOException {\\n //\\t\\tlog.trace(\\\"Testcase4\\\");\\n\\n ki = new KrillIndex();\\n ki.addDoc(createFieldDoc0());\\n ki.commit();\\n ki.addDoc(createFieldDoc1());\\n ki.addDoc(createFieldDoc2());\\n ki.commit();\\n\\n sq = new SpanSegmentQuery(new SpanElementQuery(\\\"base\\\", \\\"e\\\"),\\n new SpanNextQuery(new SpanTermQuery(new Term(\\\"base\\\", \\\"s:a\\\")),\\n new SpanTermQuery(new Term(\\\"base\\\", \\\"s:b\\\"))));\\n\\n kr = ki.search(sq, (short) 10);\\n ki.close();\\n\\n assertEquals(\\\"totalResults\\\", kr.getTotalResults(), 2);\\n // Match #0\\n assertEquals(\\\"doc-number\\\", 0, kr.getMatch(0).getLocalDocID());\\n assertEquals(\\\"StartPos\\\", 3, kr.getMatch(0).startPos);\\n assertEquals(\\\"EndPos\\\", 5, kr.getMatch(0).endPos);\\n // Match #1\\n assertEquals(\\\"doc-number\\\", 0, kr.getMatch(1).getLocalDocID());\\n assertEquals(\\\"StartPos\\\", 1, kr.getMatch(1).startPos);\\n assertEquals(\\\"EndPos\\\", 3, kr.getMatch(1).endPos);\\n }\",\n \"public DocFile[] searchResponse(ScoreDoc[] results, Query query) {\\n\\n DocFile[] result = new DocFile[results.length];\\n FastVectorHighlighter highlighter = new FastVectorHighlighter(true,true);\\n FieldQuery highlightQuery = highlighter.getFieldQuery(query); \\n\\n try {\\n IndexReader reader = DirectoryReader.open(indexDir);\\n IndexSearcher searcher = new IndexSearcher(reader);\\n\\n for (int i = 0; i < results.length; i++) {\\n int docId = results[i].doc;\\n Document document = searcher.doc(docId);\\n \\n //Highlight the best Content context from each Doc\\n String contextString = highlighter.getBestFragment(highlightQuery, \\n searcher.getIndexReader(), results[i].doc,Constants.INDEX_KEY_CONTENT,140);\\n \\n DocFile toAdd = new DocFile(\\n document.get(Constants.INDEX_KEY_FILENAME),\\n document.get(Constants.INDEX_KEY_TITLE),\\n document.get(Constants.INDEX_KEY_OWNER),\\n document.get(Constants.INDEX_KEY_PATH),\\n document.get(Constants.INDEX_KEY_STATUS).equalsIgnoreCase(\\\"true\\\"));\\n \\n if (contextString != null) {\\n toAdd.setContextString(contextString);\\n }\\n \\n toAdd.setId(document.get(Constants.INDEX_KEY_ID));\\n toAdd.setPermissions(Integer.parseInt(document.get(Constants.INDEX_KEY_PERMISSION)));\\n toAdd.setCourseCode(document.get(Constants.INDEX_KEY_COURSE));\\n result[i] = toAdd;\\n\\n }\\n } catch (Exception e) {\\n e.printStackTrace();\\n }\\n\\n return result;\\n }\",\n \"private List<SearchWord> getSearchWords(Long lastUpdateTime) {\\n return new ArrayList<>();\\n }\",\n \"@SuppressWarnings(\\\"unchecked\\\")\\n\\tpublic JSONArray findMatches(String query){\\n\\t\\t\\n\\t\\t// Increment the search tasks counter\\n\\t\\t++numOfSearchTasks;\\n\\t\\t\\n\\t\\t// Start the timer for this task\\n\\t\\tTimer.start();\\n\\t\\t\\n\\t\\t// Number of needed matches\\n\\t\\tresultsToBeFound = 10;\\n\\t\\t\\n\\t\\t// Clear the matches list\\n\\t\\tsetForTypeahead.clear();\\n\\t\\t\\n\\t\\t// The returned JSON array\\n\\t\\tJSONArray arrayObj = new JSONArray();\\n\\t\\t\\n\\t\\t// Search in all predicates\\n\\t\\tfor(int i = 0; i < predicatesList.size(); ++i){\\n\\t\\t\\tif(predicatesList.get(i).toLowerCase().contains(query.toLowerCase())){\\n\\t\\t\\t\\tarrayObj.add(predicatesList.get(i));\\n\\t\\t\\t}\\n\\t\\t\\tArrayList<String> semanticRelations = semanticRelationsMap.get(query.toLowerCase());\\n\\t\\t\\tif(semanticRelations != null) {\\n\\t\\t\\t\\tfor(String s : semanticRelations) {\\n\\t\\t\\t\\t\\tif(predicatesList.get(i).toLowerCase().contains(s.toLowerCase())){\\n\\t\\t\\t\\t\\t\\tarrayObj.add(predicatesList.get(i));\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\t\\n\\t\\t// Start the timer for this task\\n\\t\\tTimer.start();\\n\\t\\t\\n\\t\\t// Search in index first\\n\\t\\tCollection<Integer> list = in.search(query.toLowerCase());\\n\\t\\tHashSet<Integer> output = null;\\n\\t\\tif(list.size() > 0) {\\n\\t\\t\\toutput = (HashSet<Integer>) list;\\n\\t\\t}\\n\\t\\telse {\\n\\t\\t\\toutput = new HashSet<Integer>();\\n\\t\\t}\\n\\n\\t\\t// If found a match, that's a hit\\n\\t\\tif(output.size() > 0) {\\n\\t\\t\\t++numOfIndexHits;\\n\\t\\t}\\n\\t\\t\\n\\t\\tfor(Integer index : output) {\\n\\t\\t\\tarrayObj.add(frequentLiteralsList.get(index));\\n \\t\\t--resultsToBeFound;\\n \\t}\\n\\t\\tdouble tempStopTime;\\n\\t\\t// If all results were found in suffix tree\\n\\t\\tif(resultsToBeFound < 0) {\\n\\t\\t\\tTimer.stop();\\n\\t\\t\\tsuffixTreeTime += Timer.getTimeInSeconds();\\n\\t\\t\\ttotalTime += Timer.getTimeInSeconds();\\n\\t\\t\\twriteStatsToFile();\\n\\t\\t\\treturn arrayObj;\\n\\t\\t}\\n\\t\\t\\n\\t\\tTimer.stop();\\n\\t\\tsuffixTreeTime += Timer.getTimeInSeconds();\\n\\t\\ttempStopTime = Timer.getTimeInSeconds();\\n\\t\\tTimer.start();\\n\\t\\t// In length bins\\n\\t\\t// Search in bins with a minimum length of the query\\n\\t\\t// and a maximum of the query length + 10\\n\\t\\tint minLength = query.length()-1;\\n\\t\\tint maxLength = query.length() + 9;\\n\\t\\t\\n\\t\\tint minIndex = Integer.MAX_VALUE;\\n\\t\\tint maxIndex = -1;\\n\\t\\t\\n\\t\\t// Determine which indices of the literals array\\n\\t\\t// to search within\\n\\t\\tfor(int i = 0; i < lengths.size(); ++i){\\n\\t\\t\\tif(lengths.get(i) > maxLength) {\\n\\t\\t\\t\\tmaxIndex = indexes.get(i);\\n\\t\\t\\t\\tbreak;\\n\\t\\t\\t}\\n\\t\\t\\tif(minLength >= lengths.get(i)) {\\n\\t\\t\\t\\tminIndex = indexes.get(i);\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\t\\n\\t\\tpruningPercentage += 1 - (1.0 * (maxIndex - minIndex) / literalsList.size());\\n\\t\\ttry{\\n\\t\\tSystem.out.println(\\\"Searching for \\\" + query + \\\" between indeces: \\\" + minIndex + \\n\\t\\t\\t\\t\\\" corresponding to length \\\" + (literalsList.get(minIndex).length()-5) +\\n\\t\\t\\t\\t\\\" and \\\" + maxIndex + \\\" corresponding to length \\\" + \\n\\t\\t\\t\\t(literalsList.get(maxIndex).length()-5));\\n\\t\\t}\\n\\t\\tcatch(IndexOutOfBoundsException e) {\\n\\t\\t\\tSystem.out.println(\\\"query = \\\" + query);\\n\\t\\t\\tSystem.out.println(\\\"minIndex = \\\" + minIndex);\\n\\t\\t\\tSystem.out.println(\\\"maxIndex = \\\" + maxIndex);\\n\\t\\t}\\n\\t\\t\\n\\t\\t// Assign threads to search tasks\\n\\t\\tint indexesPerThread = (maxIndex - minIndex) / (numOfCores);\\n\\t\\t\\n\\t\\t// Arraylist to keep track of threads\\n\\t\\tArrayList<Thread> threads = new ArrayList<Thread>();\\n\\t\\t\\n\\t\\tfor(int i = minIndex; i < maxIndex; i += indexesPerThread) {\\n\\t\\t\\tthreads.add(new Thread(new SearchTask(i, i + indexesPerThread, query)));\\n\\t\\t}\\n\\t\\t\\n\\t\\t// Start threads\\n\\t\\tfor(int i = 0; i < threads.size(); ++i) {\\n\\t\\t\\tthreads.get(i).start();\\n\\t\\t}\\n\\t\\t\\n\\t\\t// Join threads before continue\\n\\t\\tfor(int i = 0; i < threads.size(); ++i) {\\n\\t\\t\\ttry {\\n\\t\\t\\t\\tthreads.get(i).join();\\n\\t\\t\\t} catch (InterruptedException e) {\\n\\t\\t\\t\\te.printStackTrace();\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\t\\n\\t\\t// Stop timer\\n\\t\\tTimer.stop();\\n\\t\\ttotalTime += tempStopTime + Timer.getTimeInSeconds();\\n\\t\\t\\n\\t\\t// Sort by length\\n\\t\\tArrayList<String> tempList = new ArrayList<String>();\\n\\t\\tfor(String string : setForTypeahead) {\\n\\t\\t\\tif(!arrayObj.contains(string))\\n\\t\\t\\t\\ttempList.add(string);\\n\\t\\t}\\n\\t\\tjava.util.Collections.sort(tempList, new LengthComparator());\\n\\t\\t\\n\\t\\t// Fill the array\\n\\t\\tfor(int i = 0; i < tempList.size() && resultsToBeFound > 0; ++i, --resultsToBeFound) {\\n\\t\\t\\tarrayObj.add(tempList.get(i));\\n\\t\\t}\\n\\t\\t\\n\\t\\t\\n\\t\\t\\n\\t\\t// Update the stats file with number of tasks and hits\\n\\t\\twriteStatsToFile();\\n\\t\\t\\n\\t\\treturn arrayObj;\\n\\t}\",\n \"void findAllWords() {\\n\\t\\tScanner in = new Scanner(textEditor.getText());\\n\\t\\tint head = 0;\\n\\t\\twhile (in.hasNext()) {\\n\\t\\t\\tString value = in.next();\\n\\t\\t\\tif (value.equals(findWord)) {\\n\\t\\t\\t\\tint tail = value.length();\\n\\t\\t\\t\\tfinder.add(new WordPosition(head, tail + head +1));\\n\\t\\t\\t}\\n\\t\\t\\thead += (value.length()+1);\\n\\t\\t}\\n\\t\\tin.close();\\n\\t}\",\n \"private void performSearch() {\\n String text = txtSearch.getText();\\n String haystack = field.getText();\\n \\n // Is this case sensitive?\\n if (!chkMatchCase.isSelected()) {\\n text = text.toLowerCase();\\n haystack = haystack.toLowerCase();\\n }\\n \\n // Check if it is a new string that the user is searching for.\\n if (!text.equals(needle)) {\\n needle = text;\\n curr_index = 0;\\n }\\n \\n // Grab the list of places where we found it.\\n populateFoundList(haystack);\\n \\n // Nothing was found.\\n if (found.isEmpty()) {\\n Debug.println(\\\"FINDING\\\", \\\"No occurrences of \\\" + needle + \\\" found.\\\");\\n JOptionPane.showMessageDialog(null, \\\"No occurrences of \\\" + needle + \\\" found.\\\",\\n \\\"Nothing found\\\", JOptionPane.INFORMATION_MESSAGE);\\n \\n return;\\n }\\n \\n // Loop back the indexes if we have reached the end.\\n if (curr_index == found.size()) {\\n curr_index = 0;\\n }\\n \\n // Go through the findings one at a time.\\n int indexes[] = found.get(curr_index);\\n field.select(indexes[0], indexes[1]);\\n curr_index++;\\n }\",\n \"public static void textQueries(List<String> sentences, List<String> queries) {\\n // Write your code here\\n for(String q: queries){\\n boolean a = false;\\n int i=0;\\n for(String s: sentences){\\n if(Arrays.asList(s.split(\\\" \\\")).containsAll(Arrays.asList(q.split(\\\" \\\")))){\\n System.out.print(i+\\\" \\\");\\n a = true;\\n }\\n i++;\\n }\\n if(!a)\\n System.out.println(-1);\\n else\\n System.out.println(\\\"\\\");\\n }\\n \\n }\",\n \"public void searchIndexWithTermQueryByBody(final String toSearch) throws IOException, ParseException {\\n searchIndexWithTermQuery(toSearch, \\\"body\\\", DEFAULT_LIMIT);\\n }\",\n \"Search getSearch();\",\n \"private static Boolean specialQueries(String query) throws ClassNotFoundException, InstantiationException, IllegalAccessException {\\n clickList = false;\\n //newCorpus = true;\\n\\n if (query.equals(\\\"q\\\")) {\\n\\n System.exit(0);\\n return true;\\n }\\n\\n String[] subqueries = query.split(\\\"\\\\\\\\s+\\\"); //split around white space\\n\\n if (subqueries[0].equals(\\\"stem\\\")) //first term in subqueries tells computer what to do \\n {\\n GUI.JListModel.clear();\\n GUI.ResultsLabel.setText(\\\"\\\");\\n TokenProcessor processor = new NewTokenProcessor();\\n if (subqueries.length > 1) //user meant to stem the token not to search stem\\n {\\n List<String> stems = processor.processToken(subqueries[1]);\\n\\n //clears list and repopulates it \\n String stem = \\\"Stem of query '\\\" + subqueries[1] + \\\"' is '\\\" + stems.get(0) + \\\"'\\\";\\n\\n GUI.ResultsLabel.setText(stem);\\n\\n return true;\\n }\\n\\n } else if (subqueries[0].equals(\\\"vocab\\\")) {\\n List<String> vocabList = Disk_posIndex.getVocabulary();\\n GUI.JListModel.clear();\\n GUI.ResultsLabel.setText(\\\"\\\");\\n\\n int vocabCount = 0;\\n for (String v : vocabList) {\\n if (vocabCount < 1000) {\\n vocabCount++;\\n GUI.JListModel.addElement(v);\\n }\\n }\\n GUI.ResultsLabel.setText(\\\"Total size of vocabulary: \\\" + vocabCount);\\n return true;\\n }\\n\\n return false;\\n }\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7247035","0.6326672","0.61507344","0.614432","0.6127424","0.61083686","0.60629725","0.60173154","0.5970413","0.59642434","0.595486","0.59493905","0.5948072","0.5947946","0.5944434","0.5918083","0.59072393","0.5887826","0.58828676","0.58804107","0.5874601","0.58453447","0.58405197","0.58261496","0.58032167","0.58024776","0.57938033","0.5765702","0.5764247","0.5741455","0.5736575","0.5722735","0.57102543","0.56955045","0.5693578","0.56882","0.56584895","0.5657661","0.5642594","0.5636657","0.5628783","0.56138533","0.56103","0.56093293","0.56061774","0.5588893","0.5581583","0.5576428","0.55657125","0.5539316","0.5535463","0.55315137","0.553116","0.55238885","0.5523665","0.5521453","0.55085516","0.5501453","0.54891545","0.5488139","0.54749084","0.546393","0.5462747","0.5462017","0.54545933","0.54507387","0.5447161","0.54422414","0.5441447","0.5440184","0.544018","0.5438049","0.54374784","0.5434466","0.54322106","0.5424088","0.54239994","0.5418512","0.54134786","0.5410486","0.54064715","0.54029024","0.5401156","0.54010284","0.5391461","0.5391461","0.5384889","0.5382696","0.5373321","0.5367916","0.5365786","0.53656626","0.5365409","0.5362767","0.5354548","0.53532493","0.5344425","0.5344344","0.53431","0.53379005"],"string":"[\n \"0.7247035\",\n \"0.6326672\",\n \"0.61507344\",\n \"0.614432\",\n \"0.6127424\",\n \"0.61083686\",\n \"0.60629725\",\n \"0.60173154\",\n \"0.5970413\",\n \"0.59642434\",\n \"0.595486\",\n \"0.59493905\",\n \"0.5948072\",\n \"0.5947946\",\n \"0.5944434\",\n \"0.5918083\",\n \"0.59072393\",\n \"0.5887826\",\n \"0.58828676\",\n \"0.58804107\",\n \"0.5874601\",\n \"0.58453447\",\n \"0.58405197\",\n \"0.58261496\",\n \"0.58032167\",\n \"0.58024776\",\n \"0.57938033\",\n \"0.5765702\",\n \"0.5764247\",\n \"0.5741455\",\n \"0.5736575\",\n \"0.5722735\",\n \"0.57102543\",\n \"0.56955045\",\n \"0.5693578\",\n \"0.56882\",\n \"0.56584895\",\n \"0.5657661\",\n \"0.5642594\",\n \"0.5636657\",\n \"0.5628783\",\n \"0.56138533\",\n \"0.56103\",\n \"0.56093293\",\n \"0.56061774\",\n \"0.5588893\",\n \"0.5581583\",\n \"0.5576428\",\n \"0.55657125\",\n \"0.5539316\",\n \"0.5535463\",\n \"0.55315137\",\n \"0.553116\",\n \"0.55238885\",\n \"0.5523665\",\n \"0.5521453\",\n \"0.55085516\",\n \"0.5501453\",\n \"0.54891545\",\n \"0.5488139\",\n \"0.54749084\",\n \"0.546393\",\n \"0.5462747\",\n \"0.5462017\",\n \"0.54545933\",\n \"0.54507387\",\n \"0.5447161\",\n \"0.54422414\",\n \"0.5441447\",\n \"0.5440184\",\n \"0.544018\",\n \"0.5438049\",\n \"0.54374784\",\n \"0.5434466\",\n \"0.54322106\",\n \"0.5424088\",\n \"0.54239994\",\n \"0.5418512\",\n \"0.54134786\",\n \"0.5410486\",\n \"0.54064715\",\n \"0.54029024\",\n \"0.5401156\",\n \"0.54010284\",\n \"0.5391461\",\n \"0.5391461\",\n \"0.5384889\",\n \"0.5382696\",\n \"0.5373321\",\n \"0.5367916\",\n \"0.5365786\",\n \"0.53656626\",\n \"0.5365409\",\n \"0.5362767\",\n \"0.5354548\",\n \"0.53532493\",\n \"0.5344425\",\n \"0.5344344\",\n \"0.53431\",\n \"0.53379005\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.60083085"},"document_rank":{"kind":"string","value":"8"}}},{"rowIdx":13891,"cells":{"query":{"kind":"string","value":"[NEW] Finds documents containing a twowords phrase"},"document":{"kind":"string","value":"public PostingsList phrase_query(PostingsList l1, PostingsList l2){\n\n PostingsList phrase = new PostingsList();\n\n // Counters to iterate docIDs\n int count1 = 0;\n int count2 = 0;\n // Counters to iterate positional indices\n int subcount1 = 0;\n int subcount2 = 0;\n\n // First posting\n PostingsEntry p1 = l1.get(0);\n PostingsEntry p2 = l2.get(0);\n\n // List of positional indices (changes at each iteration)\n LinkedList<Integer> ll1;\n LinkedList<Integer> ll2;\n\n // Used to store positional index\n int pp1;\n int pp2;\n\n while(true){\n // docID match (1/2) //\n if (p1.docID == p2.docID){\n // Obtain list of positional indices\n ll1 = p1.positions;\n ll2 = p2.positions;\n // First positional indices\n pp1 = ll1.get(0);\n pp2 = ll2.get(0);\n // Initialize counter\n subcount1 = 0;\n subcount2 = 0;\n\n // Search if the phrase exists\n while(true){\n // Match, consecutive words (2/2) - EUREKA! //\n if (pp1+1 == pp2){\n // Save found match (docID and positional index of last\n // word)\n phrase.insert(p1.docID, pp2);\n // Increase counters and pos indices if list is not finished\n subcount1++;\n subcount2++;\n if (subcount1<ll1.size() && subcount2<ll2.size()){\n pp1 = ll1.get(subcount1);\n pp2 = ll2.get(subcount2);\n }\n // If list finished, break\n else\n break;\n }\n // Not match\n else if (pp1+1 < pp2){\n subcount1++;\n if (subcount1<ll1.size())\n pp1 = ll1.get(subcount1);\n // If list finished, break\n else\n break;\n }\n // Not match\n else{\n subcount2++;\n if (subcount2<ll2.size())\n pp2 = ll2.get(subcount2);\n else\n break;\n }\n }\n\n // Once we finished looking at the list of positional indices of one\n // posting, increase counters and go to next postings (if there are)\n count1++;\n count2++;\n if (count1<l1.size() && count2<l2.size()){\n p1 = l1.get(count1);\n p2 = l2.get(count2);\n }\n else{\n break;\n }\n }\n // docID not match, increase lowest counter\n else if (p1.docID < p2.docID){\n count1++;\n if (count1<l1.size()){\n p1 = l1.get(count1);\n }\n else{\n break;\n }\n }\n // docID not match, increase lowest counter\n else{\n count2++;\n if (count2<l2.size()){\n p2 = l2.get(count2);\n }\n else{\n break;\n }\n }\n }\n\n return phrase;\n }"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["@Test\n public void testPhrase() {\n assertQ(req(\"q\",\"text:now-cow\", \"indent\",\"true\")\n ,\"//*[@numFound='1']\"\n );\n // should generate a query of (now OR cow) and match both docs\n assertQ(req(\"q\",\"text_np:now-cow\", \"indent\",\"true\")\n ,\"//*[@numFound='2']\"\n );\n }","private static String lookForSentenceWhichContains(String[] words, String documentPath) throws IOException {\r\n\r\n File document = new File(documentPath);\r\n\r\n if (!document.exists()) throw new FileNotFoundException(\"File located at \"+documentPath+\" doesn't exist.\\n\");\r\n\r\n FileReader r = new FileReader(document);\r\n BufferedReader br = new BufferedReader(r);\r\n\r\n String line;\r\n String documentText = \"\";\r\n while ( (line=br.readLine()) != null) {\r\n documentText += line;\r\n }\r\n\r\n documentText = Jsoup.parse(documentText).text();\r\n\r\n String[] listOfSentences = documentText.split(\"\\\\.\");\r\n HashMap<String,String> originalToNormalized = new HashMap<>();\r\n String original;\r\n\r\n for (String sentence: listOfSentences){\r\n\r\n original = sentence;\r\n\r\n sentence = sentence.toLowerCase();\r\n sentence = StringUtils.stripAccents(sentence);\r\n sentence = sentence.replaceAll(\"[^a-z0-9-._\\\\n]\", \" \");\r\n\r\n originalToNormalized.put(original,sentence);\r\n }\r\n\r\n int matches, maxMatches = 0;\r\n String output = \"\";\r\n\r\n for (Map.Entry<String,String> sentence: originalToNormalized.entrySet()){\r\n\r\n matches = 0;\r\n\r\n for (String word: words){\r\n if (sentence.getValue().contains(word)) matches++;\r\n }\r\n\r\n if (matches == words.length) return sentence.getKey();\r\n if (matches > maxMatches){\r\n maxMatches = matches;\r\n output = sentence.getKey();\r\n }\r\n }\r\n\r\n return output;\r\n\r\n }","private ArrayList<WordDocument> getDocumentsWhereWordExists(String word){\n try{\n return dictionary.get(word).getDocumentWhereWordExistsIn();\n }catch (NullPointerException ex){\n return new ArrayList<WordDocument>();\n }\n }","public List<String> findPhrases() {\n\t\t\n\t\tTrie root = new Trie();\n\t\tList<String> result = new ArrayList<>();\n\t\tQueue<TrieNode> queue = new LinkedList<>();\n\n\t\tfor (String phrase : phrases) {\n\t\t\t// build the trie\n\t\t\t\n\t\t\troot.insert(phrase);\n\t\t}\n\t\t\n\t\t// initialize the queue\n\t\tqueue.offer(root.getRootNode());\n\t\t\t\t\n\t\tfor (String word : stream) {\n\t\t\t\n\t\t\t// Search one word at a time and store TrieNodes that match this word.\n\t\t\t// If the current word extends a previous TrieNode, it may be a matching phrase\n\t\t\t\n\t\t\t// buffer to store current matches\n\t\t\tQueue<TrieNode> buffer = new LinkedList<>();\n\t\t\t\n\t\t\twhile(!queue.isEmpty()) {\n\t\t\t\t// iterate through previous matches\n\t\t\t\t\n\t\t\t\tTrieNode next = queue.poll().find(word);\n\t\t\t\t\n\t\t\t\tif (next != null) {\n\t\t\t\t\t\n\t\t\t\t\t// if this word extends the previous word, add it to the buffer\n\t\t\t\t\t// in case the next word can also extend it\n\t\t\t\t\t\n\t\t\t\t\tbuffer.offer(next);\n\t\t\t\t\t\n\t\t\t\t\tif (next.isPhrase()) {\n\t\t\t\t\t\t// if we found a valid phrase node, add it to the result\t\n\t\t\t\t\t\t\n\t\t\t\t\t\tresult.add(next.getPhrase());\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t\t\n\t\t\t}\n\t\t\t\n\t\t\tqueue = buffer;\n\t\t\tqueue.offer(root.getRootNode());\n\t\t}\n\t\t\n\t\treturn result;\n\t}","public boolean find(T word);","private static String handlePhrases(String PubmedQuery) {\r\n //Find phrases \"between double quotes\"\r\n String[] phrases = PubmedQuery.split(\"\\\"\");\r\n for(int i = 0 ; i < phrases.length ; i++){\r\n phrases[i] = phrases[i].trim();\r\n if(!phrases[i].equals(\"\")){ // String not Empty\r\n if(i%2 != 0){ // String surrounded by quotes, i.e. a phrase\r\n phrases[i] = \"\\\"\" + phrases[i] + \"\\\"\";\r\n } else { // not a phrase, i.e. a bag of terms, operator or [field of index] (inside brackets)\r\n if(phrases[i].startsWith(\"[\")){ //index field of previus component contained (i.e. case: \"...\"[...])\r\n boolean perviusPhraseFound = false; // True if index field was added to previus phrase element\r\n // Get index field of previus component and handle proprietly\r\n String [] tokens = phrases[i].split(\"]\");\r\n String indexField = tokens[0].replace(\"[\", \"\");\r\n String luceneField = supportedIndexFields.get(indexField);\r\n if(luceneField != null){ \r\n //add \"indexField:\" as a prefix in previus (not empty) phrase\r\n int tmp = i-1;\r\n while(!perviusPhraseFound & tmp >= 0){\r\n if(!phrases[tmp].equals(\"\")){\r\n perviusPhraseFound = true;\r\n //TO DO : handle wrong syntax (e.g. ... AND [ArticleTitle])\r\n phrases[tmp] = luceneField + \":\" + phrases[tmp] + \"\";\r\n } else {\r\n tmp--;\r\n }\r\n }\r\n } // else : Lucene counterpart not found, unsupported field - do nothing\r\n // Remove from current phrase this index field (prefix)\r\n phrases[i] = phrases[i].substring(indexField.length()+2 );\r\n } \r\n // Further handling...\r\n phrases[i] = handleNonPhraseToken(phrases[i]);\r\n }\r\n } //else { /* Empty token, do nothing with this */ System.out.println(\"\\t\\t\\t empty\"); }\r\n }\r\n \r\n String luceneQuery = \"\";\r\n boolean fisrtPhrase = true;\r\n for(int i = 0 ; i < phrases.length ; i ++){\r\n if(phrases[i].length() > 0){\r\n if(!phrases[i].startsWith(\" OR \") & !phrases[i].startsWith(\" -\") & !phrases[i].startsWith(\" +\") ){\r\n if(fisrtPhrase){\r\n luceneQuery += \" +\";\r\n fisrtPhrase = false;\r\n } else {\r\n if(!phrases[i-1].endsWith(\" OR \") & !phrases[i-1].endsWith(\" -\") & !phrases[i-1].endsWith(\" +\")){\r\n luceneQuery += \" +\";\r\n }\r\n } \r\n } // add default operator + when required (no OR or - is present for that term)\r\n luceneQuery += phrases[i];\r\n }// else empty phrase : skip\r\n }\r\n return luceneQuery;\r\n }","@Override\r\n\t\t\tpublic boolean containsTerm(Document document, String term) {\n\t\t\t\treturn false;\r\n\t\t\t}","private static List<SearchData> booleanSearchWord(Query query, Indexer si) {\n Tokenizer tkn = new SimpleTokenizer();\n tkn.tokenize(query.getStr(), \"[a-zA-Z]{3,}\", true, true);\n List<SearchData> searchList = new ArrayList<>();\n LinkedList<Token> wordsList = tkn.getTokens();\n Iterator<Token> wordsIt = wordsList.iterator();\n HashMap<String, LinkedList<Posting>> indexer = si.getIndexer();\n int idx;\n SearchData searched_doc;\n\n while (wordsIt.hasNext()) {\n String word = wordsIt.next().getSequence();\n if (indexer.containsKey(word)) {\n\n LinkedList<Posting> posting = indexer.get(word);\n\n for (Posting pst : posting) {\n\n SearchData sd = new SearchData(query, pst.getDocId());\n\n if (!searchList.contains(sd)) {\n sd.setScore(1);\n searchList.add(sd);\n } else {\n idx = searchList.indexOf(sd);\n searched_doc = searchList.get(idx);\n searched_doc.setScore(searched_doc.getScore() + 1);\n }\n }\n\n }\n\n\n }\n\n Collections.sort(searchList);\n\n return searchList;\n }","List<String> searchTweets(String keywords) throws TwitterException;","public List<String> getRelatedWords(String word) throws IOException {\n List<String> result = new ArrayList<String>();\n IDictionary dict = new Dictionary(new File(WORDNET_LOCATION));\n try {\n dict.open();\n IStemmer stemmer = new WordnetStemmer(dict);\n for (POS pos : EnumSet.of(POS.ADJECTIVE, POS.ADVERB, POS.NOUN, POS.VERB)) {\n List<String> resultForPos = new ArrayList<String>();\n List<String> stems = new ArrayList<String>();\n stems.add(word);\n for (String stem : stemmer.findStems(word, pos)) {\n if (!stems.contains(stem))\n stems.add(stem);\n }\n for (String stem : stems) {\n if (!resultForPos.contains(stem)) {\n resultForPos.add(stem);\n IIndexWord idxWord = dict.getIndexWord(stem, pos);\n if (idxWord == null) continue;\n List<IWordID> wordIDs = idxWord.getWordIDs();\n if (wordIDs == null) continue;\n IWordID wordID = wordIDs.get(0);\n IWord iword = dict.getWord(wordID);\n \n ISynset synonyms = iword.getSynset();\n List<IWord> iRelatedWords = synonyms.getWords();\n if (iRelatedWords != null) {\n for (IWord iRelatedWord : iRelatedWords) {\n String relatedWord = iRelatedWord.getLemma();\n if (!resultForPos.contains(relatedWord))\n resultForPos.add(relatedWord);\n }\n }\n \n List<ISynsetID> hypernymIDs = synonyms.getRelatedSynsets();\n if (hypernymIDs != null) {\n for (ISynsetID relatedSynsetID : hypernymIDs) {\n ISynset relatedSynset = dict.getSynset(relatedSynsetID);\n if (relatedSynset != null) {\n iRelatedWords = relatedSynset.getWords();\n if (iRelatedWords != null) {\n for (IWord iRelatedWord : iRelatedWords) {\n String relatedWord = iRelatedWord.getLemma();\n if (!resultForPos.contains(relatedWord))\n resultForPos.add(relatedWord);\n }\n }\n }\n }\n }\n }\n }\n for (String relatedWord : resultForPos) {\n if (relatedWord.length() > 3\n && !relatedWord.contains(\"-\")\n && !result.contains(relatedWord)) {\n // TODO: Hack alert!\n // The - check is to prevent lucene from interpreting hyphenated words as negative search terms\n // Fix!\n result.add(relatedWord);\n }\n }\n }\n } finally {\n dict.close();\n }\n return result;\n }","public SearchResult search(String text, String subText);","@Test\n\tpublic void singleWordGrepTest4() throws Exception {\n\t\t// word is 'undocumented'\n\t\tHashSet<String> grepFound = loadGrepResults(\"undocumented\");\n\t\tCollection<Page> index = queryTest.query(\"undocumented\");\n\t\tHashSet<String> indexFound = new HashSet<String>();\n\n\t\tfor (Page p : index)\n\t\t\tindexFound.add(p.getURL().getPath().toLowerCase());\n\t\t\n\t\t// tests set equality \n\t\tassertEquals(indexFound, grepFound);\n\t}","public abstract int search(String[] words, String wordToFind) throws ItemNotFoundException;","public Double[] SentiwordsMatch(String tweets) throws IOException\r\n {\r\n String[] ar=new String[100];\r\n \r\n ar=tweets.split(\" \");\r\n \r\n /* for(String splited_text:ar)\r\n System.out.println(splited_text);*/\r\n \r\n Double price[]=PriceCalculator(ar);\r\n \r\n \r\n return price;\r\n \r\n }","PsiFile[] findFilesWithPlainTextWords( String word);","ArrayList<String> searchWordTweet(String word) throws SQLException {\r\n //Query che seleziona il mittente e il corpo data una parola\r\n String query=\"SELECT DISTINCT mittente,corpo FROM tweet WHERE corpo LIKE '%\"+word+\"%'\";\r\n //Oggetti per interrogare il db\r\n Statement statement=null;\r\n connection=DBConnection.connect();\r\n ResultSet resultSet=null;\r\n //Lista messaggi\r\n ArrayList<String> tweetsList = new ArrayList<>();\r\n\r\n try {\r\n statement=connection.createStatement();\r\n resultSet = statement.executeQuery(query);\r\n while(resultSet.next()){\r\n String mittente = resultSet.getString(\"mittente\");\r\n String corpo = resultSet.getString(\"corpo\");\r\n tweetsList.add(mittente+\": \"+corpo);\r\n }\r\n\r\n return tweetsList;\r\n }catch (SQLException e){\r\n e.printStackTrace();\r\n }finally {\r\n if (connection!=null) connection.close();\r\n if (statement!=null) statement.close();\r\n if(resultSet!=null) resultSet.close();\r\n }\r\n return null;\r\n }","public boolean search(String word) {\n\t\treturn startsWith(word) && cur.isWord == true;\n\t}","public void getThesaurusMap (String wordTofind) {\r\n\t \tfor (Entry<String, List> entry : tMap.entrySet()) {\r\n\t \t\tList singleListofSynonims = entry.getValue();\r\n\t \t\tif (singleListofSynonims.contains(wordTofind)){\r\n\t \t\t\t\r\n\t \t\t\tmappedList.add(singleListofSynonims);\r\n\t \t\t\tGoogleToThesarus.put(wordTofind,singleListofSynonims);\r\n\t \t\t}\r\n\t \t\telse {\r\n\t \t\t\t//System.out.println(\"value not in map\");\r\n\t \t}\r\n\t \t}\r\n\t }","private void wordSearch(String word, HashMap<String, SearchResult> resultMap, ArrayList<SearchResult> words) {\n\t\tfor (String path : index.get(word).keySet()) {\n\t\t\tint frequency = index.get(word).get(path).size();\n\t\t\tint initialPosition = index.get(word).get(path).first();\n\t\t\t\n\t\t\tif (!resultMap.containsKey(path)) {\n\t\t\t\tresultMap.put(path, new SearchResult(frequency, initialPosition, path));\n\t\t\t\twords.add(resultMap.get(path));\n\t\t\t}\n\t\t\telse {\n\t\t\t\tSearchResult searchResult = resultMap.get(path);\n\t\t\t\tsearchResult.addToFrequency(frequency);\n\t\t\t\tsearchResult.updateInitialPosition(initialPosition);\n\t\t\t}\n\t\t}\n\t}","public static boolean searchWordInTemplateString(TemplateString tStr, String word) {\n\t\tString text = tStr.string;\r\n\t\tint currentIndex = 0;\r\n\t\tfor(int j = 0; j < text.length() && currentIndex < word.length(); j++) {\r\n\t\t\tchar c = text.charAt(j);\r\n\t\t\t// Check uppercase\r\n\t\t\tif(c >= 'A' && c <= 'Z') c = (char) (c + 'a' - 'A');\r\n\t\t\t// Check if equal to current word char\r\n\t\t\tif(c == word.charAt(currentIndex)) {\r\n\t\t\t\t// If last index then the word exists in template\r\n\t\t\t\tif(currentIndex == word.length() - 1) return true;\r\n\t\t\t\t// Otherwise add one to index\r\n\t\t\t\tcurrentIndex++;\r\n\t\t\t\tcontinue;\r\n\t\t\t}\r\n\t\t\tif(currentIndex > 0 && ((c >= 'A' && c <= 'Z') || (c >= 'a' && c <= 'z') || (c >= '0' && c <= '9'))) {\r\n\t\t\t\t// If the char was alphanumerical but unequal, the word train was broken..\r\n\t\t\t\tcurrentIndex = 0;\r\n\t\t\t}\r\n\t\t}\r\n\t\treturn false;\r\n\t}","@RequestMapping(value = \"/search-in-doc/{id}\", \n\t\t\t\t\tmethod = RequestMethod.GET)\n\tpublic ResponseEntity<?> searchInDoc(@PathVariable(\"id\") String id, \n\t\t\t\t\t\t\t\t\t\t\t @RequestParam(value = \"word\", required = true) String word) throws IOException {\n\n\t\tboolean foundFile = false; // denota si el archivo fue encontrado\n\t\t\n\t\tString pageToken = null;\n\t\tdo { // proceso de busqueda\n\t\t\tFileList result = DriveConnection.driveService.files().list() \n\t\t\t\t .setSpaces(\"drive\")\n\t\t\t .setFields(\"nextPageToken, files(id)\") \n\t\t\t .setPageToken(pageToken)\n\t\t\t .execute();\n\t\t\n\t\t\t\t for (File file : result.getFiles()) { \n\t\t\t\t\t if (file.getId().equals(id)) {\n\t\t\t\t\t\t\tfoundFile = true;\n\t\t\t\t\t }\n\t\t\t\t }\n\t\t\t\t \n\t\t\t pageToken = result.getNextPageToken();\n\t\t} while (pageToken != null);\n\t\t\n\t\tif (foundFile) {\n\t\t\t\n\t\t\tFile content = DriveConnection.driveService.files().get(id).execute();\t\n\t\t\tcontent.toString().contains(word);\t\n\t\t\treturn new ResponseEntity<>(\"Found\", HttpStatus.OK); // mostramos rpta en consola\n\t\t\t\t\n\t\t} else {\t\n\t\t\t\n\t\t\treturn new ResponseEntity<>(\"Not found\", HttpStatus.NOT_FOUND); // mostramos rpta en consola\n\t\t\t\n\t\t}\n\t\n\t}","@In String search();","void findAllWords() {\n\t\tScanner in = new Scanner(textEditor.getText());\n\t\tint head = 0;\n\t\twhile (in.hasNext()) {\n\t\t\tString value = in.next();\n\t\t\tif (value.equals(findWord)) {\n\t\t\t\tint tail = value.length();\n\t\t\t\tfinder.add(new WordPosition(head, tail + head +1));\n\t\t\t}\n\t\t\thead += (value.length()+1);\n\t\t}\n\t\tin.close();\n\t}","public int searchWord(File filePath, String s1) throws IOException, NullPointerException\r\n\t{\r\n\t\tint counter = 0;\r\n\t\tString data = \"\";\r\n\t\tBufferedReader bufferReader = new BufferedReader(new FileReader(filePath));\r\n\t\tString line = null;\r\n\t\twhile ((line = bufferReader.readLine()) != null)\r\n\t\t{\r\n\t\t\tdata = data + line;\r\n\t\t}\r\n\t\tbufferReader.close();\r\n\t\tString txt = data;\r\n\t\tBoyerMoore bm = new BoyerMoore(s1);\r\n\t\tint offset = 0;\r\n\t\tfor (int loc = 0; loc <= txt.length(); loc += offset + s1.length())\r\n\t\t{\r\n\t\t\t offset = bm.search(s1, txt.substring(loc));\r\n\t\t\t if ((offset + loc) < txt.length())\r\n\t\t\t { \r\n\t\t\t\t counter++; \r\n\t\t\t\t System.out.printf(\"The word '\"+s1 +\"' is present at the position \" + (offset + loc)+\"\\n\"); //printing position of word \r\n\t\t\t } \r\n\t\t}\r\n\t\tif(counter!=0)\r\n\t\t{ \r\n\t\t\t System.out.println(\" In the FILE: \"+filePath.getName()+\"\\n\");\r\n\t\t}\r\n\t\treturn counter; \r\n\t}","public static String findMultipleOccorancesOfGivenWord(String sentence,String word)\n {\n if(sentence == null || word == null || sentence == \"\" || word == \"\"){\n return \"Please enter valid sentence and word.It should not be empty and null\";\n }\n String result = \"\";\n Pattern pattern = Pattern.compile(word);\n Matcher matcher = pattern.matcher(sentence);\n while(matcher.find()) {\n\n result = result + \"Found at:\"+ matcher.start() + \" - \" + matcher.end() + \" \";\n }\n\n return result.trim();\n\n }","private boolean isTermAppearInQuery(String term) {\n boolean isTermAppear = false;\n query thisQuery = listDocumentRetrievedForThisQuery.getQuery();\n StringTokenizer token = new StringTokenizer(thisQuery.getQueryContent(), \" %&\\\"*#@$^_<>|`+=-1234567890'(){}[]/.:;?!,\\n\");\n while (token.hasMoreTokens()) {\n String keyTerm = token.nextToken();\n if (invertedFile.isStemmingApplied()) {\n keyTerm = StemmingPorter.stripAffixes(keyTerm);\n }\n if (term.equals(keyTerm.toLowerCase())) {\n isTermAppear = true;\n break;\n }\n }\n return isTermAppear;\n }","public String searchTweet(String searchString) {\n\t\treturn restClient.searchTweet(searchString);\n\t}","@Test\n public void findsByKeyword() throws Exception {\n final Base base = new DyBase(\n this.dynamo.region(), new MkSttc().counters().get(\"ttt\")\n );\n final Book book = base.books().add(\n \"@book{best2014, author=\\\"Walter\\\"}\"\n );\n final Quotes quotes = base.quotes();\n quotes.add(\n book, \"never give up and never think about bad things, Bobby\",\n \"99-101, 256-257, 315\"\n );\n MatcherAssert.assertThat(\n quotes.refine(\"bobby\").iterate(),\n Matchers.<Quote>iterableWithSize(1)\n );\n MatcherAssert.assertThat(\n quotes.refine(\"another-something\").iterate(),\n Matchers.<Quote>iterableWithSize(0)\n );\n }","@Test\n\tpublic void phraseGrepTest1() throws Exception {\n\t\t// phrase is \"I am forced\"\n\t\tHashSet<String> grepFound = loadGrepResults(\"i+am+forced\");\n\t\tCollection<Page> index = queryTest.query(\"\\\"I am Forced\\\"\");\n\t\tHashSet<String> indexFound = new HashSet<String>();\n\n\t\tfor (Page p : index)\n\t\t\tindexFound.add(p.getURL().getPath().toLowerCase());\n\t\t\n\t\t// tests set equality \n\t\tassertEquals(indexFound, grepFound);\n\t}","public boolean isNoun (String word){\n for(int i = 0; i< SynSets.length; i++){\n if(SynSets[0][1].contains(\" \"+word+\" \")) return true;\n }\n return false;\n }","public void SearchPhrase(Object_Ord temp) {\n\tif (!Doneloading) {\r\n\t return;\r\n\t}\r\n\tif (temp == null) {\r\n\t return;\r\n\t} else if (temp.Ordet.equals(\"\")) {\r\n\t return;\r\n\t}\r\n\ttemp.Set_Searched();\r\n\t//PrintAction( this.getClass().toString() + \" Searching for phrase \" + temp.Ordet );\r\n\tThread thread = new Thread_PhraseSearcher(this, temp);\r\n\tThreadsRunning++;\r\n\tThreadsStarted++;\r\n }","private String search_words(String word, int index){\n\t\tString found_words = \"\";\n\t\tint local_index = index +1;\n\t\t//We try to find the word within our childs\n\t\tfor(LexiNode child: childs){\n\t\t\tif(local_index > word.length()-1 || word.toLowerCase().charAt(local_index) == Character.toLowerCase(child.getRepresentative_letter()))\n\t\t\t\tfound_words += child.search_words(word, local_index);\n\t\t}\n\t\tif(current_word != null && word.length() > current_word.length())\n\t\t\treturn found_words;\n\t\tif(current_word != null && !found_words.equals(\"\"))\n\t\t\treturn current_word.toLowerCase().equals(word.toLowerCase()) ? current_word +\" & \" + definition + \"#\" + found_words +\"#\" : current_word + \"#\" + found_words;\n\t\telse if(current_word != null && found_words.equals(\"\"))\n\t\t\treturn current_word.toLowerCase().equals(word.toLowerCase()) ? current_word +\" & \" + definition + \"#\": current_word+ \"#\";\n\t\telse //current_word == null && found_words != null\n\t\t\treturn found_words;\n\t}","public interface DocumentRelatedTermsSearcher {\n List<ScoredTerm> getDocumentRelatedTerms(int docId, String term) throws SearchException;\n}","static void allDocumentAnalyzer() throws IOException {\n\t\tFile allFiles = new File(\".\"); // current directory\n\t\tFile[] files = allFiles.listFiles(); // file array\n\n\t\t// recurse through all documents\n\t\tfor (File doc : files) {\n\t\t\t// other files we don't need\n\t\t\tif (doc.getName().contains(\".java\") || doc.getName().contains(\"words\") || doc.getName().contains(\"names\")\n\t\t\t\t\t|| doc.getName().contains(\"phrases\") || doc.getName().contains(\".class\")\n\t\t\t\t\t|| doc.getName().contains(\"Data\") || doc.getName().contains(\".sh\") || doc.isDirectory()\n\t\t\t\t\t|| !doc.getName().contains(\".txt\")) {\n\t\t\t\tcontinue;\n\t\t\t}\n\n\t\t\tString name = doc.getName();\n\t\t\tSystem.out.println(name);\n\t\t\tname = name.substring(0, name.length() - 11);\n\t\t\tSystem.out.println(name);\n\n\t\t\tif (!names.contains(name)) {\n\t\t\t\tcontinue;\n\t\t\t}\n\n\t\t\t// make readers\n\t\t\tFileReader fr = new FileReader(doc);\n\t\t\tBufferedReader br = new BufferedReader(fr);\n\n\t\t\t// phrase list\n\t\t\tArrayList<String> words = new ArrayList<String>();\n\n\t\t\t// retrieve all text, trim, refine and add to phrase list\n\t\t\tString nextLine = br.readLine();\n\t\t\twhile (nextLine != null) {\n\t\t\t\tnextLine = nextLine.replace(\"\\n\", \" \");\n\t\t\t\tnextLine = nextLine.trim();\n\n\t\t\t\tif (nextLine.contains(\"no experience listed\")) {\n\t\t\t\t\tbreak;\n\t\t\t\t}\n\n\t\t\t\tString[] lineArray = nextLine.split(\"\\\\s+\");\n\n\t\t\t\t// recurse through every word to find phrases\n\t\t\t\tfor (int i = 0; i < lineArray.length - 1; i++) {\n\t\t\t\t\t// get the current word and refine\n\t\t\t\t\tString currentWord = lineArray[i];\n\n\t\t\t\t\tcurrentWord = currentWord.trim();\n\t\t\t\t\tcurrentWord = refineWord(currentWord);\n\n\t\t\t\t\tif (currentWord.equals(\"\") || currentWord.isEmpty()) {\n\t\t\t\t\t\tcontinue;\n\t\t\t\t\t}\n\n\t\t\t\t\twords.add(currentWord);\n\t\t\t\t}\n\t\t\t\tnextLine = br.readLine();\n\t\t\t}\n\n\t\t\tbr.close();\n\n\t\t\t// continue if empty\n\t\t\tif (words.size() == 0) {\n\t\t\t\tcontinue;\n\t\t\t}\n\n\t\t\t// otherwise, increment number of files in corpus\n\t\t\tsize++;\n\n\t\t\t// updating the phrase count map for tf\n\t\t\tString fileName = doc.getName();\n\t\t\tphraseCountMap.put(fileName, words.size());\n\n\t\t\t// recurse through every word\n\t\t\tfor (String word : words) {\n\t\t\t\t// get map from string to freq\n\t\t\t\tHashMap<String, Integer> textFreqMap = wordFreqMap.get(fileName);\n\n\t\t\t\t// if it's null, make one\n\t\t\t\tif (textFreqMap == null) {\n\t\t\t\t\ttextFreqMap = new HashMap<String, Integer>();\n\t\t\t\t\t// make freq as 1\n\t\t\t\t\ttextFreqMap.put(word, 1);\n\t\t\t\t\t// put that in wordFreq\n\t\t\t\t\twordFreqMap.put(fileName, textFreqMap);\n\t\t\t\t} else {\n\t\t\t\t\t// otherwise, get the current num\n\t\t\t\t\tInteger currentFreq = textFreqMap.get(word);\n\n\t\t\t\t\t// if it's null,\n\t\t\t\t\tif (currentFreq == null) {\n\t\t\t\t\t\t// the frequency is just 0\n\t\t\t\t\t\tcurrentFreq = 0;\n\t\t\t\t\t}\n\n\t\t\t\t\t// increment the frequency\n\t\t\t\t\tcurrentFreq++;\n\n\t\t\t\t\t// put it in the textFreqMap\n\t\t\t\t\ttextFreqMap.put(word, currentFreq);\n\n\t\t\t\t\t// put that in the wordFreqMap\n\t\t\t\t\twordFreqMap.put(fileName, textFreqMap);\n\t\t\t\t}\n\n\t\t\t\t// add this to record (map from phrases to docs with that\n\t\t\t\t// phrase)\n\t\t\t\tinvertedMap.addValue(word, doc);\n\t\t\t}\n\t\t}\n\t}","private String keywordFound(){\r\n\t\tString rtn = \"\";\r\n\t\tString tmp = \"\";\r\n\t\tint carr_pos = getCaretPosition();\r\n\t\t//estract part of text for keyword search\r\n\t\ttry { \r\n\t\tif(carr_pos>50)\r\n\t\t\ttmp = doc.getText(carr_pos-50,50);\r\n\t\telse\r\n\t\t\ttmp = doc.getText(0,carr_pos);\r\n\t\t}catch(BadLocationException a){\r\n\t\t\tSystem.out.println(\"exception\");\r\n\t\t\treturn rtn;\r\n\t\t};\r\n\t\t//Start check\r\n\t\tint i = 0;\r\n\t\tif(tmp.length() >= 2)i = tmp.length()-2;\t\r\n\t\twhile(checkOperator(tmp.charAt(i)) && i > 0){\r\n\t\t\trtn += tmp.charAt(i);\r\n\t\t\ti--;\r\n\t\t}\r\n\t\tif(i == 0)rtn += tmp.charAt(i);\t\t\r\n\t\treturn mirrorString(rtn);\r\n\t}","private Predicate buildOrPredicatesForWord(CriteriaBuilder builder, Root<Attendee> root, String word) {\n Predicate hasFirstName = builder.like(root.get(\"firstName\"), \"%\" + word + \"%\");\n Predicate hasLastName = builder.like(root.get(\"lastName\"), \"%\" + word + \"%\");\n Predicate hasFanName = builder.like(root.get(\"fanName\"), \"%\" + word + \"%\");\n Predicate hasLegalFirstName = builder.like(root.get(\"legalFirstName\"), \"%\" + word + \"%\");\n Predicate hasLegalLastName = builder.like(root.get(\"legalLastName\"), \"%\" + word + \"%\");\n return builder.or(hasFirstName, hasLastName, hasFanName, hasLegalFirstName, hasLegalLastName);\n }","public static ArrayList<Result> findMatches(Query query, DataManager myVocab){\n\n\t\t//Uncomment this for logging in this class\t\n//\t\tmyLogger.setLevel(Level.INFO); \n\n\t\t// get the term we're going to search for and\n\t\t// take out any leading or trailing whitespaces\n\t\tString querystr = query.getQuery();\n\t\tquerystr = querystr.trim();\n\t\tString uncleaned = querystr;\n\t\t\n\t\t// This is in case of numeric entries. Google Refine doesn't seem\n\t\t// to have int cell types, instead it adds an invisible .0 to all\n\t\t// numbers. This fixes that issue, as it sometimes causes false negatives.\n\t\tif (querystr.endsWith(\".0\")){\n\t\t Pattern p = Pattern.compile(\"[^0-9\\\\.]+\");\n\t\t Matcher m = p.matcher(querystr);\n\t\t boolean result = m.find();\n\t\t if (!result){\n\t\t \t querystr = querystr.substring(0, querystr.length()-2);\n\t\t }\n\t\t}\n\t\t// see if it's in the synonyms map, if it is\n\t\t// replace it with the appropriate term, if it's\n\t\t// not, don't do anything. \n\n\t\tif (myVocab.subMap.get(querystr)!=null){\n\t\t\tquerystr = myVocab.subMap.get(querystr);\n\t\t\tquery.setQuery(querystr);\n\t\t}\n\t\t\n\t\t// Clean up the query string if it isn't case/punctuation sensitive\n\t\tif (!myVocab.capsSensitive()){\t\t\n\t\t\tquerystr = querystr.toLowerCase();\n\t\t}\n\t\tif (! myVocab.punctSensitive()){\t\t\n\t\t\tquerystr = querystr.replaceAll(\"[\\\\W_]\", \"\");\n\t\t}\n\t\t\n\t\t// see if it's in the synonyms map, if it is\n\t\t// replace it with the appropriate term, if it's\n\t\t// not, don't do anything. \n\t\tif(myVocab.subMap.get(querystr)!=null){\n\t\t\tquerystr = myVocab.subMap.get(querystr);\n\t\t\tquery.setQuery(querystr);\n\t\t}\n\n\t\tString type = query.getType();\n\n\t\t// This ArrayList is the results that are going to be returned. \n\t\tArrayList<Result> results = getDirectMatches(myVocab, querystr, uncleaned, type);\n\t\t\n\t\t// If there's a perfect match return it.\n\t\tif (results.size() == 1 && results.get(0).match){\n\t\t\treturn results;\n\t\t}else{\n\t\t\t// Otherwise, add the initial ones and try matching\n\t\t\t// based on distance to vocabulary terms.\n\t\t\tresults.addAll(distanceMatching(query, myVocab));\n\t\t\t\n\t\t\t// Split the original query term by space and non-alphanumeric characters \n\t\t\t// to find how many words there are.\n\t\t\t//querystr = query.getQuery().replaceAll(\"[\\\\W_]\", \" \");\n\t\t\tString [] termList = querystr.split(\" \");\n\t\t\t\n\t\t\t// if there's more than one, run bagOfWords\n\t\t\t// which tries to find a match for each of the words.\n\t\t\tif (termList.length > 1){\n\t\t\t\tresults.addAll(bagOfWords(query, myVocab));\n\t\t\t}\n\t\t}\n\t\t\n\t\t// Clean the results: no duplicates\n\t\t// no extra results to return, and sorted\n\t\t// them by score before returning them\n\t\tresults = removeDuplicates(results);\n\t\t\n\t\t// They do not need to be reduced in \n\t\t// number if there are fewer than \n\t\t// the max results.\n\t\t// The pruneResults sorts them\n\t\t// by score already.\n\t\tif(query.getLimit()!=null){\n\t\t\tresults = pruneResults(results,Integer.parseInt(query.getLimit()));\n\t\t}else{\n\t\t\tresults = pruneResults(results,MAX_RESULTS);\n\t\t}\n\t\t\t\n\t\tresults = sortByScore(results);\n\t\tfor (int i = 0; i< results.size(); i++){\n//\t\t\tmyLogger.log(Level.SEVERE,results.get(i).getScore()+ \" is bigger than 100?\");\n\t\t\tif(results.get(i).getScore() > (double)100){\n\t\t\t\tresults.get(i).setScore((double)100 - (results.get(i).getScore()-(double)100));\n//\t\t\t\tmyLogger.log(Level.SEVERE,results.get(i).getScore()+\" is bigger than 100! and was set to \"+\n//\t\t\t\t\t\t((double)100 - (results.get(i).getScore()-(double)100)));\n\t\t\t}\n\t\t}\n\t\treturn results;\n\t}","public WordList find(String s) {\n \treturn index.get(s);\n }","private List<Query> generateSynonymQueries(Analyzer synonymAnalyzer, SolrParams solrParams) {\n\n\tString origQuery = getQueryStringFromParser();\n\tint queryLen = origQuery.length();\n\t\n // TODO: make the token stream reusable?\n TokenStream tokenStream = synonymAnalyzer.tokenStream(Const.IMPOSSIBLE_FIELD_NAME,\n new StringReader(origQuery));\n \n SortedSetMultimap<Integer, TextInQuery> startPosToTextsInQuery = TreeMultimap.create();\n \n \n boolean constructPhraseQueries = solrParams.getBool(Params.SYNONYMS_CONSTRUCT_PHRASES, false);\n \n boolean bag = solrParams.getBool(Params.SYNONYMS_BAG, false);\n List<String> synonymBag = new ArrayList<>();\n \n try {\n tokenStream.reset();\n while (tokenStream.incrementToken()) {\n CharTermAttribute term = tokenStream.getAttribute(CharTermAttribute.class);\n OffsetAttribute offsetAttribute = tokenStream.getAttribute(OffsetAttribute.class);\n TypeAttribute typeAttribute = tokenStream.getAttribute(TypeAttribute.class);\n \n if (!typeAttribute.type().equals(\"shingle\")) {\n // ignore shingles; we only care about synonyms and the original text\n // TODO: filter other types as well\n \n String termToAdd = term.toString();\n \n if (typeAttribute.type().equals(\"SYNONYM\")) {\n synonymBag.add(termToAdd); \t\n }\n \n //Don't quote sibgle term term synonyms\n\t\t if (constructPhraseQueries && typeAttribute.type().equals(\"SYNONYM\") &&\n\t\t\ttermToAdd.contains(\" \")) \n\t\t {\n\t\t \t//Don't Quote when original is already surrounded by quotes\n\t\t \tif( offsetAttribute.startOffset()==0 || \n\t\t \t offsetAttribute.endOffset() == queryLen ||\n\t\t \t origQuery.charAt(offsetAttribute.startOffset()-1)!='\"' || \n\t\t \t origQuery.charAt(offsetAttribute.endOffset())!='\"')\n\t\t \t{\n\t\t \t // make a phrase out of the synonym\n\t\t \t termToAdd = new StringBuilder(termToAdd).insert(0,'\"').append('\"').toString();\n\t\t \t}\n\t\t }\n if (!bag) {\n // create a graph of all possible synonym combinations,\n // e.g. dog bite, hound bite, dog nibble, hound nibble, etc.\n\t TextInQuery textInQuery = new TextInQuery(termToAdd, \n\t offsetAttribute.startOffset(), \n\t offsetAttribute.endOffset());\n\t \n\t startPosToTextsInQuery.put(offsetAttribute.startOffset(), textInQuery);\n }\n }\n }\n tokenStream.end();\n } catch (IOException e) {\n throw new RuntimeException(\"uncaught exception in synonym processing\", e);\n } finally {\n try {\n tokenStream.close();\n } catch (IOException e) {\n throw new RuntimeException(\"uncaught exception in synonym processing\", e);\n }\n }\n \n List<String> alternateQueries = synonymBag;\n \n if (!bag) {\n // use a graph rather than a bag\n\t List<List<TextInQuery>> sortedTextsInQuery = new ArrayList<>(\n startPosToTextsInQuery.values().size());\n sortedTextsInQuery.addAll(startPosToTextsInQuery.asMap().values().stream().map(ArrayList::new).collect(Collectors.toList()));\n\t \n\t // have to use the start positions and end positions to figure out all possible combinations\n\t alternateQueries = buildUpAlternateQueries(solrParams, sortedTextsInQuery);\n }\n \n // save for debugging purposes\n expandedSynonyms = alternateQueries;\n \n return createSynonymQueries(solrParams, alternateQueries);\n }","public boolean search(String word) {\n TrieNode now = root;\n for(int i = 0; i < word.length(); i++) {\n Character c = word.charAt(i);\n if (!now.children.containsKey(c)) {\n return false;\n }\n now = now.children.get(c);\n }\n return now.hasWord;\n}","public String phraseWords(String input) {\n document = new Annotation(input);\n // run all Annotators on this text\n pipeline.annotate(document);\n String pos = document.get(CoreAnnotations.PhraseWordsTagAnnotation.class);\n\n return pos;\n }","public String search_words(String word){\n\t\tString found_words = \"\";\n\t\t//We try to find the word within our childs\n\t\tfor(LexiNode child: childs)\n\t\t\tif(word.toLowerCase().charAt(0) == Character.toLowerCase(child.getRepresentative_letter()))\n\t\t\t\tfound_words += child.search_words(word, 0);\n\t\t\n\t\treturn found_words;\n\t}","private void termQuerySearch(String[] terms) {\n for (String term : terms) {\n LinkedList<TermPositions> postingLists = indexMap.get(analyzeTerm(term));\n if (postingLists != null) {\n for (TermPositions matches : postingLists) {\n double score = (double) 1 + Math.log((double) matches.getPositionList().size()) *\n Math.log((double) N / (double) postingLists.size());\n resultsCollector.add(new DocCollector(matches.getDocId(), score));\n }\n }\n }\n }","public Cursor getWordMatches(String query, String[] columns) {\n // Search over location names and abbreviations\n String selection = \n LOC_NAME + \" LIKE '%\" + query + \"%'\" + \" OR \" + \n ABBR + \" LIKE '%\" + query + \"%'\";\n\n return query(selection, columns);\n }","@Test\n\tpublic void notPhraseGrepTest() throws Exception {\n\t\t// phrase is \"I am forced\"\n\t\tHashSet<String> grepFound = loadGrepResults(\"!i+am+forced\");\n\t\tCollection<Page> index = queryTest.query(\"! \\\"I am Forced\\\"\");\n\t\tHashSet<String> indexFound = new HashSet<String>();\n\n\t\tfor (Page p : index)\n\t\t\tindexFound.add(p.getURL().getPath().toLowerCase());\n\t\tassertEquals(grepFound, indexFound);\n\t}","public abstract boolean isStopWord(String term);","SpellResponse spellQuery(SearchRequest request, Map<SearchParam, String> params);","public void searchWordToGroup(String title, String word, String groupIns) throws IOException {\r\n\t\tString line;\r\n\t\tBufferedReader in;\r\n\t\tint paragraphs = 1;\r\n\t\tint sentences = 1;\r\n\t\tfound = 0;\r\n\t\ttry {\r\n\t\t\tstatementP = SqlCon.getConnection().prepareStatement(SqlCon.PATH_ACORDING_TITLE);\r\n\t\t\tstatementP.setString(1, title);\r\n\t\t\trs = statementP.executeQuery();\r\n\t\t\twhile (rs.next()) {\r\n\t\t\t\tString path = rs.getString(\"filePath\");\r\n\t\t\t\tin = new BufferedReader(new FileReader(path));\r\n\t\t\t\tline = in.readLine();\r\n\t\t\t\twhile (line != null) {\r\n\t\t\t\t\tif (line.equals(\"\")) {\r\n\t\t\t\t\t\tparagraphs++;\r\n\t\t\t\t\t\tsentences = 1;\r\n\t\t\t\t\t} else {\r\n\t\t\t\t\t\tString[] sentenceList = line.split(\"[!?.:]+\");\r\n\t\t\t\t\t\tfor (int i = 0; i < sentenceList.length; i++) {\r\n\t\t\t\t\t\t\tif (sentenceList[i].contains(word)) {\r\n\t\t\t\t\t\t\t\tint p = paragraphs;\r\n\t\t\t\t\t\t\t\tint s = sentences;\r\n\t\t\t\t\t\t\t\tint is =0;\r\n\t\t\t\t\t\t\t\tinsertTable.insertwordFunc(groupIns, word, title, p, s, is);\r\n\t\t\t\t\t\t\t\tfound = 1;\r\n\t\t\t\t\t\t\t}\r\n\t\t\t\t\t\t}\r\n\t\t\t\t\t}\r\n\t\t\t\t\tsentences++;\r\n\t\t\t\t\tline = in.readLine();\r\n\t\t\t\t}\r\n\t\t\t\tparagraphs = 1;\r\n\t\t\t\tsentences = 1;\r\n\t\t\t}\r\n\t\t} catch (SQLException e) {\r\n\t\t\te.printStackTrace();\r\n\t\t}\r\n\t}","@Override\n public String search(String word) {\n return search(word, root);\n }","public boolean search(String word) {\n TrieTree point = root;\n for(int i = 0; i < word.length(); i++){\n char ch = word.charAt(i);\n if(point.getChild(ch - 'a') == null) return false;\n point = point.getChild(ch - 'a');\n }\n return point.getIsWord();\n }","List<FraseEntidade> getPhrasesByAuthorName(String name);","public void search(Indexer indexer, CityIndexer cityIndexer, Ranker ranker, String query, boolean withSemantic, ArrayList<String> chosenCities, ObservableList<String> citiesByTag, boolean withStemming, String saveInPath, String queryId, String queryDescription) {\n String[] originalQueryTerms = query.split(\" \");\n String originQuery = query;\n docsResults = new HashMap<>();\n parser = new Parse(withStemming, saveInPath, saveInPath);\n HashSet<String> docsOfChosenCities = new HashSet<>();\n query = \"\" + query + queryDescription;\n HashMap<String, Integer> queryTerms = parser.parseQuery(query);\n HashMap<String, ArrayList<Integer>> dictionary = indexer.getDictionary();\n if (!withStemming){\n setDocsInfo(saveInPath + \"\\\\docsInformation.txt\");\n }\n else{\n setDocsInfo(saveInPath + \"\\\\docsInformation_stemming.txt\");\n }\n\n\n //add semantic words of each term in query to 'queryTerms'\n if(withSemantic) {\n HashMap<String,ArrayList<String>> semanticWords = ws.connectToApi(originQuery);\n }\n\n //give an ID to query if it's a regular query (not queries file)\n if(queryId.equals(\"\")){\n queryId = \"\" + Searcher.queryID;\n Searcher.queryID++;\n }\n\n String postingDir;\n if (!withStemming) {\n postingDir = \"\\\\indexResults\\\\postingFiles\";\n } else {\n postingDir = \"\\\\indexResults\\\\postingFiles_Stemming\";\n }\n int pointer = 0;\n\n //find docs that contain the terms in the query in their text\n HashMap<String, Integer> queryTermsIgnoreCase = new HashMap<>();\n for (String term : queryTerms.keySet()) {\n String originTerm = term;\n if (!dictionary.containsKey(term.toUpperCase()) && !dictionary.containsKey(term.toLowerCase())) {\n continue;\n }\n if(dictionary.containsKey(term.toLowerCase())){\n term = term.toLowerCase();\n }\n else {\n term = term.toUpperCase();\n }\n queryTermsIgnoreCase.put(term,queryTerms.get(originTerm));\n pointer = dictionary.get(term).get(2);\n String chunk = (\"\" + term.charAt(0)).toUpperCase();\n\n //get the relevant line from posting file\n BufferedReader br = null;\n try {\n br = new BufferedReader(new FileReader(new File(saveInPath + postingDir + \"\\\\posting_\" + chunk + \".txt\")));\n String line = \"\";\n int i = 1;\n while ((line = (br.readLine())) != null) {\n if (i == pointer) {\n break;\n }\n i++;\n }\n br.close();\n\n //get docs from posting line and add them to the data structure 'docsResults'\n if(line != null) {\n findDocsFromLine(line, term);\n }\n\n } catch (IOException e) {\n e.printStackTrace();\n }\n }\n\n //find docs that contain the chosen cities in their text\n for (String cityTerm : chosenCities) {\n if (!dictionary.containsKey(cityTerm) && !dictionary.containsKey(cityTerm.toLowerCase())) {\n continue;\n }\n if(dictionary.containsKey(cityTerm.toLowerCase())){\n cityTerm = cityTerm.toLowerCase();\n }\n pointer = dictionary.get(cityTerm).get(2);\n // char chunk = indexer.classifyToPosting(term).charAt(0);\n String chunk = (\"\" + cityTerm.charAt(0)).toUpperCase();\n\n //get the relevant line from posting file\n BufferedReader br = null;\n try {\n br = new BufferedReader(new FileReader(new File(saveInPath + postingDir + \"\\\\posting_\" + chunk + \".txt\")));\n String line = \"\";\n int i = 1;\n while ((line = (br.readLine())) != null) {\n if (i == pointer) {\n break;\n }\n i++;\n }\n br.close();\n\n //get docs from posting line and add them to the data structure 'docsOfChosenCities'\n String docs = line.substring(0, line.indexOf(\"[\") - 1); //get 'docsListStr'\n String[] docsArr = docs.split(\";\");\n for (String docInfo : docsArr) {\n String doc = docInfo.substring(0, docInfo.indexOf(\": \"));\n while(doc.charAt(0) == ' '){\n doc = doc.substring(1);\n }\n docsOfChosenCities.add(doc);\n }\n } catch (IOException e) {\n e.printStackTrace();\n }\n }\n\n //find docs that contain the chosen cities in their city tag\n if(!chosenCities.isEmpty()){\n for (String cityDicRec: chosenCities) {\n //get pointer to posting from cityDictionary\n try {\n pointer = cityIndexer.getCitiesDictionary().get(cityDicRec);\n } catch (NumberFormatException e) {\n e.printStackTrace();\n }\n //get the relevant line from posting file\n BufferedReader br = null;\n try {\n br = new BufferedReader(new FileReader(new File(saveInPath + \"\\\\cityIndexResults\" + \"\\\\posting_city\" + \".txt\")));\n String line = \"\";\n int i = 1;\n while ((line = (br.readLine())) != null) {\n if (i == pointer) {\n break;\n }\n i++;\n }\n br.close();\n\n //get docs from posting line and add them to the data structure 'docsOfChosenCities'\n String docs = line.substring(line.indexOf(\"[\") + 1, line.indexOf(\"]\")); //get 'docsListStr'\n String[] docsArr = docs.split(\"; \");\n for (String doc : docsArr) {\n docsOfChosenCities.add(doc);\n }\n } catch (IOException e) {\n e.printStackTrace();\n }\n }\n }\n\n\n ranker.rank(docsResults, docsOfChosenCities, queryTermsIgnoreCase, dictionary, docsInfo,entities, queryId);\n }","public WordInfo searchWord(String word) {\n\t\tSystem.out.println(\"Dic:SearchWord: \"+word);\n\n\t\tDocument doc;\n\t\ttry {\n\t\t\tdoc = Jsoup.connect(\"https://dictionary.cambridge.org/dictionary/english-vietnamese/\" + word).get();\n\t\t} catch(Exception e) {\n\t\t\te.printStackTrace();\n\t\t\treturn null;\n\t\t}\n\n\t\tElements elements = doc.select(\".dpos-h.di-head.normal-entry\");\n\t\tif (elements.isEmpty()) {\n\t\t\tSystem.out.println(\" not found\");\n\t\t\treturn null;\n\t\t}\n\n\t\tWordInfo wordInfo = new WordInfo(word);\n\n\t\t// Word\n\t\telements = doc.select(\".tw-bw.dhw.dpos-h_hw.di-title\");\n\n\t\tif (elements.size() == 0) {\n\t\t\tSystem.out.println(\" word not found in doc!\");\n\t\t\treturn null;\n\t\t}\n\n\t\twordInfo.setWordDictionary(elements.get(0).html());\n\n\t\t// Type\n\t\telements = doc.select(\".pos.dpos\");\n\n\t\tif(elements.size() > 0) {\n\t\t\twordInfo.setType(WordInfo.getTypeShort(elements.get(0).html()));\n//\t\t\tif (wordInfo.getTypeShort().equals(\"\"))\n//\t\t\t\tSystem.out.println(\" typemis: \"+wordInfo.getType());\n\t\t}\n\n\t\t// Pronoun\n\t\telements = doc.select(\".ipa.dipa\");\n\n\t\tif (elements.size() > 0)\n\t\t\twordInfo.setAPI(\"/\"+elements.get(0).html()+\"/\");\n\n\t\t// Trans\n\t\telements = doc.select(\".trans.dtrans\");\n\n\t\tif (elements.size() > 0)\n\t\t\twordInfo.setTrans(elements.get(0).html());\n\n\t\tSystem.out.println(\" found\");\n\t\treturn wordInfo;\n\t}","List findByFilterText(Set<String> words, boolean justIds);","private void find(char[] m, String message, Trie cur, Trie root, int index, List<String> results) {\n // Base case 1. No match with any dictionary word. if cur == null -> no match ; return\n if (cur == null) {\n return;\n }\n // Base case 2. if out of bounds, check previously collected word and return\n if (index == message.length()) {\n // result only in case matches word\n if (cur.word != null) {\n results.add(new String(m));\n }\n return;\n }\n char c = message.charAt(index);\n if (c == SPACE) {\n // matches word or character 'e'\n // check if matches word from dictionary\n if (cur.word != null) {\n m[index] = SPACE;\n // if space - start collecting new word from beginning of Trie\n find(m, message, root, root, index + 1, results);\n }\n // otherwise ' ' -> 'e'\n c = 'e';\n }\n // considered non-space character (backtracking)\n m[index] = c;\n // get next element from try\n Trie next = cur.get(c);\n find(m, message, next, root, index + 1, results);\n }","public boolean search(String word)\n {\n return true;\n }","public boolean search(String word) {\n TrieNode n = root;\n for(char c : word.toCharArray()) {\n if(n.children[c]==null)\n return false;\n n = n.children[c];\n }\n if(n.isWord)\n return true;\n return false;\n }","private List<SearchWord> getSearchWords(Long lastUpdateTime) {\n return new ArrayList<>();\n }","public void IndexADocument(String docno, String content) throws IOException {\n\t\tdocid++;\n\t\tdoc2docid.put(docno, docid);\n\t\tdocid2doc.put(docid, docno);\n\n\t\t// Insert every term in this doc into docid2map\n\t\tString[] terms = content.trim().split(\" \");\n\t\tMap<Integer, Integer> docTerm = new HashMap<>();\n\t\tint thisTermid;\n\t\tfor(String term: terms){\n\t\t\t// get termid\n\t\t\tif(term2termid.get(term)!=null) thisTermid = term2termid.get(term);\n\t\t\telse{\n\t\t\t\tthisTermid = ++termid;\n\t\t\t\tterm2termid.put(term, thisTermid);\n\t\t\t}\n\t\t\tdocTerm.put(thisTermid, docTerm.getOrDefault(thisTermid, 0)+1);\n\t\t\t// Merge this term's information into termid2map\n\t\t\tMap<Integer, Integer> temp = termid2map.getOrDefault(thisTermid, new HashMap());\n\t\t\ttemp.put(docid, temp.getOrDefault(docid, 0)+1);\n\t\t\ttermid2map.put(thisTermid, temp);\n\t\t\ttermid2fre.put(thisTermid, termid2fre.getOrDefault(thisTermid, 0)+1);\n\t\t}\n\t\tdocid2map.put(docid, docTerm);\n\n//\t\t// Merge all the terms' information into termid2map\n//\t\tfor(Long tid: docTerm.keySet()){\n//\t\t\tMap<Long, Long> temp = termid2map.getOrDefault(tid, new HashMap());\n//\t\t\ttemp.put(docid,docTerm.get(tid));\n//\t\t\ttermid2map.put(tid, temp);\n//\t\t\t// update this term's frequency\n//\t\t\ttermid2fre.put(tid, termid2fre.getOrDefault(tid,0L)+docTerm.get(tid));\n//\t\t}\n\n\t\t// When termid2map and docid2map is big enough, put it into disk\n\t\tif(docid%blockSize==0){\n\t\t\tWritePostingFile();\n\t\t\tWriteDocFile();\n\t\t}\n\t}","@Test\n\tpublic void singleWordGrepTest3() throws Exception {\n\t\t// word is 'mistress'\n\t\tHashSet<String> grepFound = loadGrepResults(\"mistress\");\n\t\tCollection<Page> index = queryTest.query(\"mistress\");\n\t\tHashSet<String> indexFound = new HashSet<String>();\n\n\t\tfor (Page p : index)\n\t\t\tindexFound.add(p.getURL().getPath().toLowerCase());\n\t\t\n\t\t// tests set equality \n\t\tassertEquals(indexFound, grepFound);\n\t}","public Utwor search2(String query) {\n for (Utwor utwor : utwory) {\n if (utwor.getTitle().equals(query)) {\n return utwor;\n }\n }\n return null;\n }","public ArrayList<AddressEntry> searchByNote(String text) {\r\n ArrayList<AddressEntry> textMatches = new ArrayList<AddressEntry>();\r\n text = text.toLowerCase();\r\n for (AddressEntry current : contacts) {\r\n String currentname = current.getNote().toLowerCase();\r\n if (currentname.contains(text)) {\r\n textMatches.add(current);\r\n }\r\n }\r\n return textMatches;\r\n }","private String containingWord(String attribute, String word) {\r\n return \"contains(concat(' ',normalize-space(@\" + attribute + \"),' '),' \"\r\n + word + \" ')\";\r\n }","private double countWordLocationScore(Page page, String[] queryWords) {\n double score = 0;\n boolean wasFound = false;\n\n for (String word : queryWords) {\n int queryWordId = this.pb.getIdForWord(word);\n for (int i = 0; i < page.getWords().size(); i++) {\n if (page.getWords().get(i) == queryWordId) {\n score += i;\n wasFound = true;\n break;\n }\n }\n\n if (!wasFound) {\n score += 100000;\n } else {\n wasFound = false;\n }\n }\n return score;\n }","List<Integer> wordFinder(String text, String word) {\n\n List<Integer> indexes = new ArrayList<Integer>();\n String wordProper = \" \" + word + \" \";\n\n int index = 0;\n\n while (index != -1) {\n\n index = text.indexOf(wordProper, index);\n\n if (index != -1) {\n indexes.add(index);\n index++;\n }\n }\n\n return indexes;\n }","List<DataTerm> search(String searchTerm);","private @Nullable static String getQueryForWords(@NonNull List<String> words) {\r\n int numberOfWords = words.size();\r\n if(numberOfWords == 0) {\r\n return null;\r\n }\r\n\r\n String tableName = getTable(words.get(0));\r\n\r\n if(tableName == null) {\r\n return null;\r\n }\r\n\r\n String query = \"select * from \"+tableName+\" where\";\r\n\r\n int ctr = 0;\r\n for (String word:words) {\r\n query += \" word like '\"+word+\"'\";\r\n ctr++;\r\n if(ctr < numberOfWords) {\r\n query += \" OR\";\r\n }\r\n }\r\n\r\n return query;\r\n }","public static void main (String[] args) {\r\n\t\tfindWords(sentence);\r\n\t}","public boolean search(String word) {\n char [] words=word.toCharArray();\n CharTree t=root;\n for (char c : words) {\n t=t.next[c-97];\n if(t==null)return false;\n }\n if (!t.isend)return false;\n return true;\n }","public ArrayList<String> determineSearchedWords(String userCommand) {\n\t\tif (userCommand == null || userCommand.equals(\"\")) {\n\t\t\tlogger.log(Level.WARNING, Global.MESSAGE_ILLEGAL_ARGUMENTS);\n\t\t\treturn null;\n\t\t}\n\n\t\tString userCommandWithoutCommandType = removeCommandType(userCommand);\n\n\t\tArrayList<String> searchedWords = new ArrayList<String>();\n\t\tPattern pattern = Pattern.compile(\"[^\\\\s\\\"']+|\\\"([^\\\"]*)\\\"\");\n\t\tMatcher matcher = pattern.matcher(userCommandWithoutCommandType);\n\n\t\twhile (matcher.find()) {\n\t\t\tif (matcher.group(1) != null) {\n\t\t\t\tsearchedWords.add(matcher.group(1)); // Phrase in double quotes\n\t\t\t} else {\n\t\t\t\tsearchedWords.add(matcher.group()); // Single word\n\t\t\t}\n\t\t}\n\t\treturn searchedWords;\n\t}","private ArrayList<String> matchingWords(String word){\n\t\tArrayList<String> list = new ArrayList<String>();\n\t\tfor(int i=0; i<words.size();i++){\n\t\t\tif(oneCharOff(word,words.get(i))){\n\t\t\t\tlist.add(words.get(i));\n\t\t\t}\n\t\t}\n\t\treturn list;\n\t}","public static void textQueries(List<String> sentences, List<String> queries) {\n // Write your code here\n for(String q: queries){\n boolean a = false;\n int i=0;\n for(String s: sentences){\n if(Arrays.asList(s.split(\" \")).containsAll(Arrays.asList(q.split(\" \")))){\n System.out.print(i+\" \");\n a = true;\n }\n i++;\n }\n if(!a)\n System.out.println(-1);\n else\n System.out.println(\"\");\n }\n \n }","boolean hasWord();","SList oddWords();","private long getTweets(String search, String geocode, Configuration auth) {\r\n TwitterFactory tf = new TwitterFactory(auth);\r\n Twitter twitter = tf.getInstance();\r\n \r\n try {\r\n Query query = new Query(search + \" \" + geocode);\r\n query.setSinceId(starttime);\r\n QueryResult result;\r\n \r\n for (int i = 0; i < blocks; i++) {\r\n if (Abort.getInstance().abort()) {\r\n return -1;\r\n }\r\n \r\n result = twitter.search(query);\r\n \r\n synchronized (this) {\r\n if (!tweets.containsKey(search)) {\r\n tweets.put(search, new HashSet());\r\n }\r\n tweets.get(search).addAll(result.getTweets());\r\n }\r\n \r\n //updateCommon(result.getTweets());\r\n //searched.add(search.toLowerCase());\r\n query.setSinceId(starttime + i * blocks15);\r\n }\r\n } catch (TwitterException te) {\r\n System.out.println(\"Failed to search tweets: \" + te);\r\n System.out.println(\"\\nRetry at: \" + \r\n (new Date(te.getRateLimitStatus()\r\n .getResetTimeInSeconds() * 1000L)));\r\n return te.getRateLimitStatus().getSecondsUntilReset() * 1000L;\r\n }\r\n return 0;\r\n }","public static List<String> query_intersect(List<String> queryWords) throws IOException {\n\t\tif (!initialized) initialize();\n\t\tList<PostingList> pls = new ArrayList<PostingList> ();\n\t\tfor (String queryWord : queryWords) {\n\t\t\tqueryWord = queryWord.toLowerCase();\n\t\t\tif (!termDict.containsKey(queryWord)) {\n\t\t\t\tpls.clear();\n\t\t\t\tbreak;\n\t\t\t}\n\t\t\tPostingList pl = readPosting(fc, termDict.get(queryWord));\n\t\t\tif (pl == null) {\n\t\t\t\tpls.clear();\n\t\t\t\tbreak;\n\t\t\t}\n\t\t\tpls.add(readPosting(fc, termDict.get(queryWord)));\n\t\t}\n\t\tCollections.sort(pls, new Comparator<PostingList>(){\n\t\t public int compare(PostingList p1, PostingList p2) {\n\t\t return p1.size() - p2.size(); // assumes you want biggest to smallest\n\t\t }\n\t\t});\n\t\tif (pls.size() == 0) {\n\t\t\treturn null;\n\t\t} else {\n\t\t\tList<Integer> current = pls.get(0).getList();\n\t\t\tfor (int i = 1; i < pls.size(); i++) {\n\t\t\t\tList<Integer> toBeAdd = pls.get(i).getList();\n\t\t\t\tcurrent = intersect(current, toBeAdd);\n\t\t\t}\n\t\t\tif (current.size() == 0) {\n\t\t\t\treturn null;\n\t\t\t} else {\n\t\t\t\tList<String> result = new ArrayList<String>();\n\t\t\t\tfor (int docId : current) {\n\t\t\t\t\tresult.add(docDict.get(docId));\n\t\t\t\t}\n\t\t\t\treturn result;\n\t\t\t}\n\t\t}\n\t}","@GetMapping(\"/search\")\n\tpublic String search(@RequestParam(name = \"word\") String word, Model model) {\n\t\tList<Note> notes = noteRepository.search(\"%\" + word + \"%\");\n\t\tmodel.addAttribute(\"notes\", notes);\n\t\treturn \"notes\";\n\t}","private WordRecord lookUp(String word)\n {\n int contains = 0;\n boolean check = false;\n //loops through concordance\n for(int i = 0; i < this.concordance.size();i++)\n {\n //checks to see if the words are equal\n if(word.equalsIgnoreCase(this.concordance.get(i).getWord()))\n {\n //gets location of what position the word is true\n contains = i;\n check = true;\n }\n \n }\n //checks to see if it was found in concordance\n if(check)\n return this.concordance.get(contains);\n \n return null;\n }","WordBean getWord(String word);","private void findMatches(String key, String path, boolean caseSensitive, boolean fileName) {\n\t\tfor (String word : document) {\n\t\t\tif (contains(key, word, caseSensitive)) {\n\t\t\t\tif (fileName) {\n\t\t\t\t\tSystem.out.println(path);\n\t\t\t\t\tbreak;\n\t\t\t\t} else {\n\t\t\t\t\tSystem.out.println(word);\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}","public boolean search(String word) {\n TrieNode tn = root;\n int len = word.length();\n for(int i=0; i<len; i++){\n char c = word.charAt(i);\n TrieNode temp = tn.hm.get(c);\n if(temp == null) return false;\n tn = temp;\n }\n return tn.flag;\n }","public String showSearchSynonym(String searchWord, ArrayList<String> words) {\n StringBuilder stringBuilder = new StringBuilder(\"Your word \\\"\" + searchWord + \"\\\" has \" + words.size()\n + (words.size() == 1 ? \" synonym:\\n\" : \" synonyms:\\n\"));\n for (int i = 0; i < words.size(); i++) {\n stringBuilder.append(words.get(i) + \"\\n\");\n }\n return stringBuilder.toString();\n }","public void makeWord(String inputText,String pageId,createIndex createindex,String contentType)\n {\n int length,i;\n char c;\n boolean linkFound=false;\n int count1,count2,count3,count4,count5,count6,count7,count8,count9;\n\n\n\n StringBuilder word=new StringBuilder();\n // String finalWord=null,stemmedWord=null;\n docId=Integer.parseInt(pageId.trim());\n\n ci=createindex;\n // Stemmer st=new Stemmer();\n //createIndex createindex=new createIndex();\n\n length=inputText.length();\n\n for(i=0;i<length;i++)\n {\n c=inputText.charAt(i);\n if(c<123 && c>96)\n {\n word.append(c);\n }\n\n else if(c=='{')\n {\n if ( i+9 < length && inputText.substring(i+1,i+9).equals(\"{infobox\") )\n {\n\n StringBuilder infoboxString = new StringBuilder();\n\n count1 = 0;\n for ( ; i < length ; i++ ) {\n\n c = inputText.charAt(i);\n infoboxString.append(c);\n if ( c == '{') {\n count1++;\n }\n else if ( c == '}') {\n count1--;\n }\n if ( count1 == 0 || (c == '=' && i+1 < length && inputText.charAt(i+1) == '=')) {\n if ( c == '=' ) {infoboxString.deleteCharAt(infoboxString.length()-1);}\n break;\n }\n }\n\n processInfobox(infoboxString);\n\n }\n\n else if ( i+8 < length && inputText.substring(i+1,i+8).equals(\"{geobox\") )\n {\n\n StringBuilder geoboxString = new StringBuilder();\n\n count2 = 0;\n for ( ; i < length ; i++ ) {\n\n c = inputText.charAt(i);\n geoboxString.append(c);\n if ( c == '{') {\n count2++;\n }\n else if ( c == '}') {\n count2--;\n }\n if ( count2 == 0 || (c == '=' && i+1 < length && inputText.charAt(i+1) == '=')) {\n if ( c == '=' ) {geoboxString.deleteCharAt(geoboxString.length()-1);}\n break;\n }\n }\n\n // processGeobox(geoboxString);\n }\n\n else if ( i+6 < length && inputText.substring(i+1,i+6).equals(\"{cite\") )\n {\n\n /*\n * Citations are to be removed.\n */\n\n count3 = 0;\n for ( ; i < length ; i++ ) {\n\n c = inputText.charAt(i);\n if ( c == '{') {\n count3++;\n }\n else if ( c == '}') {\n count3--;\n }\n if ( count3 == 0 || (c == '=' && i+1 < length && inputText.charAt(i+1) == '=')) {\n break;\n }\n }\n\n }\n\n else if ( i+4 < length && inputText.substring(i+1,i+4).equals(\"{gr\") )\n {\n\n /*\n * {{GR .. to be removed\n */\n\n count4 = 0;\n for ( ; i < length ; i++ ) {\n\n c = inputText.charAt(i);\n if ( c == '{') {\n count4++;\n }\n else if ( c == '}') {\n count4--;\n }\n if ( count4 == 0 || (c == '=' && i+1 < length && inputText.charAt(i+1) == '=')) {\n break;\n }\n }\n\n }\n else if ( i+7 < length && inputText.substring(i+1,i+7).equals(\"{coord\") )\n {\n\n /**\n * Coords to be removed\n */\n\n count5 = 0;\n for ( ; i < length ; i++ ) {\n\n c = inputText.charAt(i);\n\n if ( c == '{') {\n count5++;\n }\n else if ( c == '}') {\n count5--;\n }\n if ( count5 == 0 || (c == '=' && i+1 < length && inputText.charAt(i+1) == '=')) {\n break;\n }\n }\n\n }\n\n //System.out.println(\"process infobox\");\n }\n else if(c=='[')\n {\n // System.out.println(\"process square brace\");\n\n if ( i+11 < length && inputText.substring(i+1,i+11).equalsIgnoreCase(\"[category:\"))\n {\n\n StringBuilder categoryString = new StringBuilder();\n\n count6 = 0;\n for ( ; i < length ; i++ ) {\n\n c = inputText.charAt(i);\n categoryString.append(c);\n if ( c == '[') {\n count6++;\n }\n else if ( c == ']') {\n count6--;\n }\n if ( count6 == 0 || (c == '=' && i+1 < length && inputText.charAt(i+1) == '=')) {\n if ( c == '=' ) {categoryString.deleteCharAt(categoryString.length()-1);}\n break;\n }\n }\n\n // System.out.println(\"category string=\"+categoryString.toString());\n processCategories(categoryString);\n\n }\n else if ( i+8 < length && inputText.substring(i+1,i+8).equalsIgnoreCase(\"[image:\") ) {\n\n /**\n * Images to be removed\n */\n\n count7 = 0;\n for ( ; i < length ; i++ ) {\n\n c = inputText.charAt(i);\n if ( c == '[') {\n count7++;\n }\n else if ( c == ']') {\n count7--;\n }\n if ( count7 == 0 || (c == '=' && i+1 < length && inputText.charAt(i+1) == '=')) {\n break;\n }\n }\n\n }\n else if ( i+7 < length && inputText.substring(i+1,i+7).equalsIgnoreCase(\"[file:\") ) {\n\n /**\n * File to be removed\n */\n\n count8 = 0;\n for ( ; i < length ; i++ ) {\n\n c = inputText.charAt(i);\n\n if ( c == '[') {\n count8++;\n }\n else if ( c == ']') {\n count8--;\n }\n if ( count8 == 0 || (c == '=' && i+1 < length && inputText.charAt(i+1) == '=')) {\n break;\n }\n }\n\n }\n\n }\n else if(c=='<')\n {\n //System.out.println(\"Process < >\");\n\n if ( i+4 < length && inputText.substring(i+1,i+4).equalsIgnoreCase(\"!--\") ) {\n\n /**\n * Comments to be removed\n */\n\n int locationClose = inputText.indexOf(\"-->\" , i+1);\n if ( locationClose == -1 || locationClose+2 > length ) {\n i = length-1;\n }\n else {\n i = locationClose+2;\n }\n\n }\n else if ( i+5 < length && inputText.substring(i+1,i+5).equalsIgnoreCase(\"ref>\") ) {\n\n /**\n * References to be removed\n */\n int locationClose = inputText.indexOf(\"</ref>\" , i+1);\n if ( locationClose == -1 || locationClose+5 > length ) {\n i = length-1;\n }\n else {\n i = locationClose+5;\n }\n\n }\n else if ( i+8 < length && inputText.substring(i+1,i+8).equalsIgnoreCase(\"gallery\") ) {\n\n /**\n * Gallery to be removed\n */\n int locationClose = inputText.indexOf(\"</gallery>\" , i+1);\n if ( locationClose == -1 || locationClose+9 > length) {\n i = length-1;\n }\n else {\n i = locationClose+9;\n }\n }\n\n }\n else if ( c == '=' && i+1 < length && inputText.charAt(i+1) == '=')\n {\n\n linkFound = false;\n i+=2;\n while ( i < length && ((c = inputText.charAt(i)) == ' ' || (c = inputText.charAt(i)) == '\\t') )\n {\n i++;\n }\n\n if ( i+14 < length && inputText.substring(i , i+14 ).equals(\"external links\") )\n {\n //System.out.println(\"External link found\");\n linkFound = true;\n i+= 14;\n }\n\n }\n else if ( c == '*' && linkFound == true )\n {\n\n //System.out.println(\"Link found\");\n count9 = 0;\n boolean spaceParsed = false;\n StringBuilder link = new StringBuilder();\n while ( count9 != 2 && i < length )\n {\n c = inputText.charAt(i);\n if ( c == '[' || c == ']' )\n {\n count9++;\n }\n if ( count9 == 1 && spaceParsed == true)\n {\n link.append(c);\n }\n else if ( count9 != 0 && spaceParsed == false && c == ' ')\n {\n spaceParsed = true;\n }\n i++;\n }\n\n StringBuilder linkWord = new StringBuilder();\n for ( int j = 0 ; j < link.length() ; j++ )\n {\n char currentCharTemp = link.charAt(j);\n if ( (int)currentCharTemp >= 'a' && (int)currentCharTemp <= 'z' )\n {\n linkWord.append(currentCharTemp);\n }\n else\n {\n\n // System.out.println(\"link : \" + linkWord.toString());\n processLink(linkWord);\n linkWord.setLength(0);\n }\n }\n if ( linkWord.length() > 1 )\n {\n //System.out.println(\"link : \" + linkWord.toString());\n processLink(linkWord);\n linkWord.setLength(0);\n }\n\n }\n else\n {\n if(word.length()>1)\n filterAndAddWord(word,contentType);\n\n word.setLength(0);\n }\n }\n\n\n if(word.length()>1)\n filterAndAddWord(word,contentType);\n\n word.setLength(0);\n /*\n if(word.length()>0)\n {\n finalWord=new String(word);\n if(!(checkStopword(finalWord)))\n {\n st.add(finalWord.toCharArray(),finalWord.length());\n stemmedWord=st.stem();\n\n createindex.addToTreeSet(stemmedWord,docId);\n\n }\n\n word.delete(0, word.length());\n } */\n\n }","public ArrayList<SearchResult> partialSearch(String[] searchWords) {\n\t\tArrayList<SearchResult> words = new ArrayList<>();\n\t\tHashMap<String, SearchResult> resultMap = new HashMap<>();\n\t\tfor (String word : searchWords) {\n\t\t\tfor (String key : index.tailMap(word, true).navigableKeySet()) {\n\t\t\t\tif (key.startsWith(word)) {\n\t\t\t\t\twordSearch(key, resultMap, words);\n\t\t\t\t}\n\t\t\t\telse {\n\t\t\t\t\tbreak;\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t\t\n\t\tCollections.sort(words);\n\t\treturn words;\n\t}","public FindCommand(WordContainsKeywordsPredicate predicate) {\n this.predicate = predicate;\n }","private static Query computeBooleanQueryNP(String textQuery){\n\t\tBooleanQuery query = new BooleanQuery();\n\n\t\tHmmDecoder mPosTagger = null;\n\t\tTokenizerFactory mTokenizerFactory = null;\n\t\tPhraseChunker pChunker = new PhraseChunker(mPosTagger,mTokenizerFactory);\n\t\tArrayList<String> pchuncker = new ArrayList<String>();\n\n\t\tpchuncker = pChunker.getCHunkNounPhrases(textQuery.toLowerCase());\n\n\t\tfor (int k = 0; k<= pchuncker.size()-1;k++ ){\n\t\t\tString wordInList = ((String) pchuncker.get(k));\n\t\t\twordInList = wordInList.toLowerCase().replaceAll(\"-\",\" \");\n\t\t\tString [] wordInListSplit = wordInList.split(\" \");\n\t\t\tfor (String word: wordInListSplit){\n\n\t\t\t\tquery.add(new TermQuery(new Term(\"content\", word)), Occur.SHOULD );\n\t\t\t}\n\n\t\t}\n\n\t\t/* String[] tQuery = textQuery.split(\" \");\n\t\t for(String s: tQuery )\n\t\t\t query.add(new TermQuery(new Term(\"text\", s)), Occur.SHOULD);*/\n\n\t\treturn query;\n\t}","public byte filter(Manager m, SearchRequest q, ResultSet rs, int DocAtNumber, int DocNo)\n\t{\t\t\n\t\tString originalQuery = q.getOriginalQuery();\n\t\t//highlight query terms only for the queries, \n\t\t//which are not about finding related documents\n\t\t//this check may be removed, because the preparation of the \n\t\t//query terms for highlighting takes into account\n\t\t//the related: operator\n\t\tboolean highlightQueryTerms = true;\n\t\tif (originalQuery.matches(\"\\\\brelated:\\\\d+\\\\b\") || //check if the query uses the related: operator \n\t\t\t!enableQueryTermsHighlight || //check if the highlighting of terms is enabled\n\t\t\thighlight.pattern().equals(\"(\\\\b)()(\\\\b)\")) //check if there are no query terms to highlight\n\t\t\thighlightQueryTerms = false;\n\t\t\n\t\tString[] qTerms = q.getOriginalQuery().replaceAll(\" \\\\w+\\\\p{Punct}\\\\w+ \",\" \").toLowerCase().split(\" \");\n\t\t\n\t\tString[] metadata = null;\n\t\tint tmpSentence;\n\t\tdouble tmpScore;\n\t\tsynchronized(metaCache) {\n\t\t\ttry {\n\t\t\t\tInteger DocNoObject = new Integer(DocNo);\n\t\t\t\tif (metaCache.containsKey(DocNoObject))\n\t\t\t\t\t\tmetadata = (String[]) metaCache.get(DocNoObject);\n\t\t\t\telse {\n\t\t\t\t\tmetadata = metaIndex.getItems(keys, DocNo);\n\t\t\t\t\tmetaCache.put(DocNoObject,metadata);\n\t\t\t\t}\n\t\t\t} catch(IOException ioe) {} \n\t\t}\n\t\n\t\tif (show_snippet)\n\t\t{\n\t\t\tString extract = metadata[1];\n\t\t\tString[] sentences = sentencePattern.split(extract, 50); //use 50 sentences at most\n\t\t\tdouble[] sentenceScores = new double[sentences.length]; \n\t\t\tint frsSentence = -1;\n\t\t\tint sndSentence = -1;\n\t\t\tint top1Sentence = 0;\n\t\t\tint top2Sentence = 0;\n\t\t\tdouble max1Score = -1;\n\t\t\tdouble max2Score = 0;\n\t\t\tfinal int qTermsLength = qTerms.length;\n\t\t\tfor (int i=0; i<qTermsLength; i++) {\n\t\t\t\tqTerms[i] = removeEndings.matcher(qTerms[i]).replaceAll(\"\");\n\t\t\t}\n\t\t\tString lowerCaseSentence;\n\t\t\tint sentenceLength;\n\t\t\tfinal int sentencesLength = sentences.length;\n\n\t\t\tfor (int i=0; i<sentencesLength; i++) {\n\t\t\t\t\n\t\t\t\tlowerCaseSentence = sentences[i].toLowerCase();\n\t\t\t\tsentenceLength=sentences[i].length();\n\t\t\t\tif (sentenceLength < 20 || sentenceLength > 250) {\n\t\t\t\t\tfor (int j=0; j<qTermsLength; j++) {\n\t\t\t\t\t\tif (lowerCaseSentence.indexOf(qTerms[j])>=0) {\n\t\t\t\t\t\t\tsentenceScores[i]+=1.0d + sentenceLength / (20.0d + sentenceLength);\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\n\t\t\t\t\t\n\t\t\t\t} else {\n\t\t\t\t\tfor (int j=0; j<qTermsLength; j++) {\n\t\t\t\t\t\tif (lowerCaseSentence.indexOf(qTerms[j])>=0) {\n\t\t\t\t\t\t\tsentenceScores[i]+=qTerms[j].length() + sentenceLength / (1.0d + sentenceLength);\n\t\t\t\t\t\t}\n\t\t\t\t\t}\t\t\t\t\t\n\t\t\t\t}\n\t\t\t\t\t\t\t\t\n\t\t\t\t//do your best to get at least a second sentence for the snippet, \n\t\t\t\t//after having found the first one\n\t\t\t\tif (frsSentence > -1 && sndSentence == -1 && sentenceLength > 5) {\n\t\t\t\t\tsndSentence = i;\n\t\t\t\t}\n\n\t\t\t\t//do your best to get at least one sentence for the snippet\n\t\t\t\tif (frsSentence == -1 && sentenceLength > 5) { \n\t\t\t\t\tfrsSentence = i;\n\t\t\t\t}\n\n\t\t\t\tif (max2Score < sentenceScores[i]) {\n\t\t\t\t\tmax2Score = sentenceScores[i];\n\t\t\t\t\ttop2Sentence = i;\n\t\t\t\t\t//logger.debug(\"top 2 sentence is \" + i);\n\t\t\t\t\tif (max2Score > max1Score) {\n\t\t\t\t\t\ttmpScore = max1Score; max1Score = max2Score; max2Score = tmpScore;\n\t\t\t\t\t\ttmpSentence = top1Sentence; top1Sentence = top2Sentence; top2Sentence = tmpSentence;\n\t\t\t\t\t}\n\t\t\t\t}\n\n\t\t\t}\n\t\t\tint lastIndexOfSpace = -1;\n\t\t\tString sentence=\"\";\n\t\t\tString secondSentence=\"\";\n\t\t\tString snippet = \"\";\n\t\t\tif (max1Score == -1) {\n\t\t\t\tif (frsSentence>=0) {\n\t\t\t\t\tsentence = sentences[frsSentence];\n\t\t\t\t\tif (sentence.length() > 100) {\n\t\t\t\t\t\tlastIndexOfSpace = sentence.substring(0, 100).lastIndexOf(\" \");\n\t\t\t\t\t\tsentence = sentence.substring(0, lastIndexOfSpace > 0 ? lastIndexOfSpace : 100);\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t\t\n\t\t\t\tif (sndSentence>=0) {\n\t\t\t\t\tsecondSentence = sentences[sndSentence];\n\t\t\t\t\tif (secondSentence.length() > 100) {\n\t\t\t\t\t\tlastIndexOfSpace = secondSentence.substring(0, 100).lastIndexOf(\" \");\n\t\t\t\t\t\tsecondSentence = secondSentence.substring(0, lastIndexOfSpace>0 ? lastIndexOfSpace : 100);\n\t\t\t\t\t}\t\t\t\t\t\n\t\t\t\t}\n\t\t\t\t\n\t\t\t\tif (frsSentence >=0 && sndSentence >= 0) \n\t\t\t\t\tsnippet = sentence.trim() + \"...\" + secondSentence.trim();\n\t\t\t\telse if (frsSentence >= 0 && sndSentence<0) \n\t\t\t\t\tsnippet = sentence.trim();\n\t\t\t\t\n\t\t\t} else if (sentences[top1Sentence].length()<100 && top1Sentence!=top2Sentence) {\n\t\t\t\tsentence = sentences[top1Sentence];\n\t\t\t\tif (sentence.length() > 100) {\n\t\t\t\t\tlastIndexOfSpace = sentence.substring(0, 100).lastIndexOf(\" \");\n\t\t\t\t\tsentence = sentence.substring(0, lastIndexOfSpace > 0 ? lastIndexOfSpace : 100);\n\t\t\t\t}\n\t\t\t\t\t\t\t\t\n\t\t\t\tsecondSentence = sentences[top2Sentence];\n\t\t\t\tif (secondSentence.length() > 100) {\n\t\t\t\t\tlastIndexOfSpace = secondSentence.substring(0, 100).lastIndexOf(\" \");\n\t\t\t\t\tsecondSentence = secondSentence.substring(0, lastIndexOfSpace>0 ? lastIndexOfSpace : 100);\n\t\t\t\t}\n\t\t\t\tsnippet = sentence.trim() + \"...\" + secondSentence.trim();\n\t\t\t} else {\n\t\t\t\tsentence = sentences[top1Sentence];\n\t\t\t\tif (sentence.length()>200) {\n\t\t\t\t\tlastIndexOfSpace = sentence.substring(0, 200).lastIndexOf(\" \");\n\t\t\t\t\tsentence = sentence.substring(0, lastIndexOfSpace > 0 ? lastIndexOfSpace : 200);\n\t\t\t\t}\n\t\t\t\tsnippet = sentence.trim();\n\t\t\t}\n\t\t\t\n\t\t\t//checking and removing any control characters\n\t\t\tcontrolNonVisibleCharactersMatcher.reset(snippet);\n\t\t\tsnippet = controlNonVisibleCharactersMatcher.replaceAll(\"\");\n\t\t\t\n\t\t\t//String escapedSnippet = StringEscapeUtils.escapeHtml(snippet);\n\t\t\t//if (highlightQueryTerms)\n\t\t\t//\tescapedSnippet = highlight.matcher(escapedSnippet).replaceAll(\"$1<b>$2</b>$3\");\n\t\t\tif (highlightQueryTerms)\n\t\t\t\tsnippet = highlight.matcher(snippet).replaceAll(\"$1<b>$2</b>$3\");\n\t\t\t//else \n\t\t\t//\tsnippet = StringEscapeUtils.escapeHtml(snippet);\n\t\t\t\n\t\t\t//change by Vassilis, 20/09/2006\n\t\t\t//disabling the xml escaping in order to move the data into ![CDATA[ ]]\n\t\t\t//the code was:\n\t\t\t//rs.addMetaItem(\"snippet\", DocAtNumber, StringEscapeUtils.escapeXml(snippet));\n\t\t\t//and now it is:\n\t\t\t//snippet.replaceAll(\"[^\\\\u0009\\\\u000A\\\\u000D\\\\u0020-\\\\uD7FF\\\\uE000-\\\\uFFFD\\\\u10000-\\\\u10FFFF]\",\"\");\n\t\t\trs.addMetaItem(\"snippet\", DocAtNumber, snippet);\n\t\t\t\n\t\t}\n\t\tif (show_title)\n\t\t{\n\t\t\tString title = metadata[2];\n\t\t\t\n\t\t\t//checking and removing any control characters\n\t\t\tcontrolNonVisibleCharactersMatcher.reset(title);\n\t\t\ttitle = controlNonVisibleCharactersMatcher.replaceAll(\"\");\n\t\t\ttitle = (highlightQueryTerms)\n\t\t\t\t ? highlight.matcher(metadata[2]).replaceAll(\"$1<b>$2</b>$3\") \n\t\t\t\t : metadata[2];\n\t\t\t\n\t\t\t\n\t\t\t//String escapedTitle = StringEscapeUtils.escapeHtml(metadata[2]);\n\t\t\t//String title = (highlightQueryTerms)\n\t\t\t//\t\t\t ? highlight.matcher(escapedTitle).replaceAll(\"$1<b>$2</b>$3\") \n\t\t\t//\t\t\t : escapedTitle;\n\t\t\t//String title = (highlightQueryTerms) \n\t\t\t//\t\t? highlight.matcher(metadata[2]).replaceAll(\"$1<b>$2</b>$3\") \n\t\t\t//\t\t: metadata[2];\n\n\t\t\t//change by Vassilis, 20/09/2006\n\t\t\t//disabling the xml escaping in order to move the data into ![CDATA[ ]]\n\t\t\t//the code was:\n\t\t\t//rs.addMetaItem(\"title\", DocAtNumber, StringEscapeUtils.escapeXml(title));\n\t\t\t//and now is:\n\t\t\t//title.replaceAll(\"[^\\\\u0009\\\\u000A\\\\u000D\\\\u0020-\\\\uD7FF\\\\uE000-\\\\uFFFD\\\\u10000-\\\\u10FFFF]\",\"\");\n\t\t\trs.addMetaItem(\"title\", DocAtNumber, title);\n\t\t\t\n\t\t}\n\t\tif (!show_docid_early && show_docid)\n\t\t{\n\t\t\trs.addMetaItem(\"docid\", DocAtNumber, docIndex.getDocumentNumber(DocNo));\n\t\t}\n\t\tif (!show_url_early && show_url)\n\t\t{\n\n\t\t\trs.addMetaItem(\"url\", DocAtNumber, StringEscapeUtils.escapeXml(metadata[0]));\n\t\t}\n\t\t\n\t\treturn FILTER_OK;\n\t}","@Test\n\tpublic void singleWordGrepTest2() throws Exception {\n\t\t// word is 'crazy'\n\t\tHashSet<String> grepFound = loadGrepResults(\"crazy\");\n\t\tCollection<Page> index = queryTest.query(\"crazy\");\n\t\tHashSet<String> indexFound = new HashSet<String>();\n\n\t\tfor (Page p : index)\n\t\t\tindexFound.add(p.getURL().getPath().toLowerCase());\n\t\t\n\t\t// tests set equality \n\t\tassertEquals(indexFound, grepFound);\n\t}","public String getSearchString() {\r\n return super.getSearchString();\r\n \r\n// String searchStr = \"\";\r\n// //put exact phrase at the very beginning\r\n// if(exactphrase != null && exactphrase.length() > 0)\r\n// {\r\n// searchStr += \"\\\"\" + exactphrase + \"\\\"\";\r\n// }\r\n//\r\n// String allwordsSearchStr = \"\";\r\n// if(allwords != null && allwords.length() > 0)\r\n// {\r\n// String [] words = allwords.split(\" \");\r\n// if(words.length > 0)\r\n// {\r\n// for(int i=0; i<words.length; i++)\r\n// {\r\n// allwordsSearchStr += \"+\" + words[i];\r\n// }\r\n// }\r\n// }\r\n//\r\n// String withoutwordsSearchStr = \"\";\r\n// if(withoutwords != null && withoutwords.length() > 0)\r\n// {\r\n// String [] words = withoutwords.split(\" \");\r\n// if(words.length > 0)\r\n// {\r\n// for(int i=0; i<words.length; i++)\r\n// {\r\n// withoutwordsSearchStr += \"+-\" + words[i];\r\n// }\r\n// }\r\n// }\r\n//\r\n// searchStr += allwordsSearchStr + withoutwordsSearchStr; //need to add other string\r\n// \r\n// String oneofwordsSearchStr = \"\";\r\n// if(oneofwords != null && oneofwords.length() > 0)\r\n// {\r\n// String [] words = oneofwords.split(\" \");\r\n// if(words.length > 0)\r\n// {\r\n// oneofwordsSearchStr = \"(\";\r\n// for(int i=0; i<words.length; i++)\r\n// {\r\n// oneofwordsSearchStr += words[i] + \" \";\r\n// }\r\n// oneofwordsSearchStr = oneofwordsSearchStr.trim();\r\n// oneofwordsSearchStr += \")\";\r\n// }\r\n// }\r\n// if(oneofwordsSearchStr.length() > 0)\r\n// {\r\n// searchStr += \"+\" + oneofwordsSearchStr;\r\n// }\r\n//\r\n// return searchStr;\r\n }","public static void search(String word){\n if(index.containsKey(word)){\n System.out.println(\"word \" + word + \" displays in :\");\n HashSet<String> list = index.get(word);\n for(String str:list){\n System.out.println(str);\n }\n }\n else{\n System.out.println(\"word \" + word + \" doesn't found!\");\n }\n }","public abstract Set<String> getTerms(Document doc);","@Override\n public boolean search(final String word) {\n final TrieNode p = searchNode(word);\n if (p == null) {\n return false;\n } else {\n return p.isEnd;\n }\n\n }","public void indexCreate()\n {\n try{\n Directory dir = FSDirectory.open(Paths.get(\"indice/\"));\n Analyzer analyzer = new StandardAnalyzer();\n IndexWriterConfig iwc = new IndexWriterConfig(analyzer);\n iwc.setOpenMode(OpenMode.CREATE);\n IndexWriter writer = new IndexWriter(dir,iwc);\n MongoConnection mongo = MongoConnection.getMongo();\n mongo.OpenMongoClient();\n DBCursor cursor = mongo.getTweets();\n Document doc = null;\n\n while (cursor.hasNext()) {\n DBObject cur = cursor.next();\n if (cur.get(\"retweet\").toString().equals(\"false\")) {\n doc = new Document();\n doc.add(new StringField(\"id\", cur.get(\"_id\").toString(), Field.Store.YES));\n doc.add(new TextField(\"text\", cur.get(\"text\").toString(), Field.Store.YES));\n doc.add(new StringField(\"analysis\", cur.get(\"analysis\").toString(), Field.Store.YES));\n //doc.add(new StringField(\"finalCountry\",cur.get(\"finalCountry\").toString(),Field.Store.YES));\n doc.add(new StringField(\"userScreenName\", cur.get(\"userScreenName\").toString(), Field.Store.YES));\n doc.add(new StringField(\"userFollowersCount\", cur.get(\"userFollowersCount\").toString(), Field.Store.YES));\n doc.add(new StringField(\"favoriteCount\", cur.get(\"favoriteCount\").toString(), Field.Store.YES));\n\n if (writer.getConfig().getOpenMode() == OpenMode.CREATE) {\n System.out.println(\"Indexando el tweet: \" + doc.get(\"text\") + \"\\n\");\n writer.addDocument(doc);\n System.out.println(doc);\n } else {\n System.out.println(\"Actualizando el tweet: \" + doc.get(\"text\") + \"\\n\");\n writer.updateDocument(new Term(\"text\" + cur.get(\"text\")), doc);\n System.out.println(doc);\n }\n }\n }\n cursor.close();\n writer.close();\n }\n catch(IOException ioe){\n System.out.println(\" Error en \"+ ioe.getClass() + \"\\n mensaje: \" + ioe.getMessage());\n }\n }","public NavigableSet<Integer> findAllTextIndexes (String words,\n DialogueConstraints constraints)\n {\n\n NavigableSet<Integer> matches = new TreeSet ();\n\n for (Paragraph p : this.paragraphs)\n {\n\n for (Sentence s : p.getSentences ())\n {\n\n int st = s.getAllTextStartOffset ();\n\n // These indexes will be sentence local.\n NavigableSet<Integer> found = s.find (words,\n constraints);\n\n if (found != null)\n {\n\n for (Integer i : found)\n {\n\n matches.add (s.getWord (i).getAllTextStartOffset ());\n\n //matches.add (i + st);\n\n }\n\n }\n\n }\n\n }\n\n return matches;\n\n }","void setVersesWithWord(Word word);","@Override\n public List<DefinitionDTO> findWordsByWord(String query) {\n List<Word> words = wordRepository.findBySearchString(query);\n return DTOMapper.mapWordListToDefinitionDTOList(words);\n }","public boolean search(String word) {\n TrieNode p = searchNode(word);\n if (p == null) {\n return false;\n } else {\n if (p.isEnd)\n return true;\n }\n return false;\n }","@RequestMapping(\"/{words}\")\n\tpublic List<WordMatch> match(@PathVariable(\"words\") String words) {\n\t\tList<WordMatch> matches = new ArrayList<>();\n\t\tfor (String text : words.split(\",\")) {\n\t\t\tmatches.add(service.getMatch(text));\n\t\t}\n\t\treturn matches;\n\t}","public void update_query(TwitterParser tweet)\r\n\t{\r\n\t\tfor(String s : tweet.get_words())\r\n\t\t\tupdate_query(s, tweet.get_date());\r\n\t}","public boolean search(String word) {\n TrieNode tail = match(root, word.toCharArray(), 0);\n return tail != null && tail.isWord;\n }"],"string":"[\n \"@Test\\n public void testPhrase() {\\n assertQ(req(\\\"q\\\",\\\"text:now-cow\\\", \\\"indent\\\",\\\"true\\\")\\n ,\\\"//*[@numFound='1']\\\"\\n );\\n // should generate a query of (now OR cow) and match both docs\\n assertQ(req(\\\"q\\\",\\\"text_np:now-cow\\\", \\\"indent\\\",\\\"true\\\")\\n ,\\\"//*[@numFound='2']\\\"\\n );\\n }\",\n \"private static String lookForSentenceWhichContains(String[] words, String documentPath) throws IOException {\\r\\n\\r\\n File document = new File(documentPath);\\r\\n\\r\\n if (!document.exists()) throw new FileNotFoundException(\\\"File located at \\\"+documentPath+\\\" doesn't exist.\\\\n\\\");\\r\\n\\r\\n FileReader r = new FileReader(document);\\r\\n BufferedReader br = new BufferedReader(r);\\r\\n\\r\\n String line;\\r\\n String documentText = \\\"\\\";\\r\\n while ( (line=br.readLine()) != null) {\\r\\n documentText += line;\\r\\n }\\r\\n\\r\\n documentText = Jsoup.parse(documentText).text();\\r\\n\\r\\n String[] listOfSentences = documentText.split(\\\"\\\\\\\\.\\\");\\r\\n HashMap<String,String> originalToNormalized = new HashMap<>();\\r\\n String original;\\r\\n\\r\\n for (String sentence: listOfSentences){\\r\\n\\r\\n original = sentence;\\r\\n\\r\\n sentence = sentence.toLowerCase();\\r\\n sentence = StringUtils.stripAccents(sentence);\\r\\n sentence = sentence.replaceAll(\\\"[^a-z0-9-._\\\\\\\\n]\\\", \\\" \\\");\\r\\n\\r\\n originalToNormalized.put(original,sentence);\\r\\n }\\r\\n\\r\\n int matches, maxMatches = 0;\\r\\n String output = \\\"\\\";\\r\\n\\r\\n for (Map.Entry<String,String> sentence: originalToNormalized.entrySet()){\\r\\n\\r\\n matches = 0;\\r\\n\\r\\n for (String word: words){\\r\\n if (sentence.getValue().contains(word)) matches++;\\r\\n }\\r\\n\\r\\n if (matches == words.length) return sentence.getKey();\\r\\n if (matches > maxMatches){\\r\\n maxMatches = matches;\\r\\n output = sentence.getKey();\\r\\n }\\r\\n }\\r\\n\\r\\n return output;\\r\\n\\r\\n }\",\n \"private ArrayList<WordDocument> getDocumentsWhereWordExists(String word){\\n try{\\n return dictionary.get(word).getDocumentWhereWordExistsIn();\\n }catch (NullPointerException ex){\\n return new ArrayList<WordDocument>();\\n }\\n }\",\n \"public List<String> findPhrases() {\\n\\t\\t\\n\\t\\tTrie root = new Trie();\\n\\t\\tList<String> result = new ArrayList<>();\\n\\t\\tQueue<TrieNode> queue = new LinkedList<>();\\n\\n\\t\\tfor (String phrase : phrases) {\\n\\t\\t\\t// build the trie\\n\\t\\t\\t\\n\\t\\t\\troot.insert(phrase);\\n\\t\\t}\\n\\t\\t\\n\\t\\t// initialize the queue\\n\\t\\tqueue.offer(root.getRootNode());\\n\\t\\t\\t\\t\\n\\t\\tfor (String word : stream) {\\n\\t\\t\\t\\n\\t\\t\\t// Search one word at a time and store TrieNodes that match this word.\\n\\t\\t\\t// If the current word extends a previous TrieNode, it may be a matching phrase\\n\\t\\t\\t\\n\\t\\t\\t// buffer to store current matches\\n\\t\\t\\tQueue<TrieNode> buffer = new LinkedList<>();\\n\\t\\t\\t\\n\\t\\t\\twhile(!queue.isEmpty()) {\\n\\t\\t\\t\\t// iterate through previous matches\\n\\t\\t\\t\\t\\n\\t\\t\\t\\tTrieNode next = queue.poll().find(word);\\n\\t\\t\\t\\t\\n\\t\\t\\t\\tif (next != null) {\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t// if this word extends the previous word, add it to the buffer\\n\\t\\t\\t\\t\\t// in case the next word can also extend it\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\tbuffer.offer(next);\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\tif (next.isPhrase()) {\\n\\t\\t\\t\\t\\t\\t// if we found a valid phrase node, add it to the result\\t\\n\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\tresult.add(next.getPhrase());\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\n\\t\\t\\t}\\n\\t\\t\\t\\n\\t\\t\\tqueue = buffer;\\n\\t\\t\\tqueue.offer(root.getRootNode());\\n\\t\\t}\\n\\t\\t\\n\\t\\treturn result;\\n\\t}\",\n \"public boolean find(T word);\",\n \"private static String handlePhrases(String PubmedQuery) {\\r\\n //Find phrases \\\"between double quotes\\\"\\r\\n String[] phrases = PubmedQuery.split(\\\"\\\\\\\"\\\");\\r\\n for(int i = 0 ; i < phrases.length ; i++){\\r\\n phrases[i] = phrases[i].trim();\\r\\n if(!phrases[i].equals(\\\"\\\")){ // String not Empty\\r\\n if(i%2 != 0){ // String surrounded by quotes, i.e. a phrase\\r\\n phrases[i] = \\\"\\\\\\\"\\\" + phrases[i] + \\\"\\\\\\\"\\\";\\r\\n } else { // not a phrase, i.e. a bag of terms, operator or [field of index] (inside brackets)\\r\\n if(phrases[i].startsWith(\\\"[\\\")){ //index field of previus component contained (i.e. case: \\\"...\\\"[...])\\r\\n boolean perviusPhraseFound = false; // True if index field was added to previus phrase element\\r\\n // Get index field of previus component and handle proprietly\\r\\n String [] tokens = phrases[i].split(\\\"]\\\");\\r\\n String indexField = tokens[0].replace(\\\"[\\\", \\\"\\\");\\r\\n String luceneField = supportedIndexFields.get(indexField);\\r\\n if(luceneField != null){ \\r\\n //add \\\"indexField:\\\" as a prefix in previus (not empty) phrase\\r\\n int tmp = i-1;\\r\\n while(!perviusPhraseFound & tmp >= 0){\\r\\n if(!phrases[tmp].equals(\\\"\\\")){\\r\\n perviusPhraseFound = true;\\r\\n //TO DO : handle wrong syntax (e.g. ... AND [ArticleTitle])\\r\\n phrases[tmp] = luceneField + \\\":\\\" + phrases[tmp] + \\\"\\\";\\r\\n } else {\\r\\n tmp--;\\r\\n }\\r\\n }\\r\\n } // else : Lucene counterpart not found, unsupported field - do nothing\\r\\n // Remove from current phrase this index field (prefix)\\r\\n phrases[i] = phrases[i].substring(indexField.length()+2 );\\r\\n } \\r\\n // Further handling...\\r\\n phrases[i] = handleNonPhraseToken(phrases[i]);\\r\\n }\\r\\n } //else { /* Empty token, do nothing with this */ System.out.println(\\\"\\\\t\\\\t\\\\t empty\\\"); }\\r\\n }\\r\\n \\r\\n String luceneQuery = \\\"\\\";\\r\\n boolean fisrtPhrase = true;\\r\\n for(int i = 0 ; i < phrases.length ; i ++){\\r\\n if(phrases[i].length() > 0){\\r\\n if(!phrases[i].startsWith(\\\" OR \\\") & !phrases[i].startsWith(\\\" -\\\") & !phrases[i].startsWith(\\\" +\\\") ){\\r\\n if(fisrtPhrase){\\r\\n luceneQuery += \\\" +\\\";\\r\\n fisrtPhrase = false;\\r\\n } else {\\r\\n if(!phrases[i-1].endsWith(\\\" OR \\\") & !phrases[i-1].endsWith(\\\" -\\\") & !phrases[i-1].endsWith(\\\" +\\\")){\\r\\n luceneQuery += \\\" +\\\";\\r\\n }\\r\\n } \\r\\n } // add default operator + when required (no OR or - is present for that term)\\r\\n luceneQuery += phrases[i];\\r\\n }// else empty phrase : skip\\r\\n }\\r\\n return luceneQuery;\\r\\n }\",\n \"@Override\\r\\n\\t\\t\\tpublic boolean containsTerm(Document document, String term) {\\n\\t\\t\\t\\treturn false;\\r\\n\\t\\t\\t}\",\n \"private static List<SearchData> booleanSearchWord(Query query, Indexer si) {\\n Tokenizer tkn = new SimpleTokenizer();\\n tkn.tokenize(query.getStr(), \\\"[a-zA-Z]{3,}\\\", true, true);\\n List<SearchData> searchList = new ArrayList<>();\\n LinkedList<Token> wordsList = tkn.getTokens();\\n Iterator<Token> wordsIt = wordsList.iterator();\\n HashMap<String, LinkedList<Posting>> indexer = si.getIndexer();\\n int idx;\\n SearchData searched_doc;\\n\\n while (wordsIt.hasNext()) {\\n String word = wordsIt.next().getSequence();\\n if (indexer.containsKey(word)) {\\n\\n LinkedList<Posting> posting = indexer.get(word);\\n\\n for (Posting pst : posting) {\\n\\n SearchData sd = new SearchData(query, pst.getDocId());\\n\\n if (!searchList.contains(sd)) {\\n sd.setScore(1);\\n searchList.add(sd);\\n } else {\\n idx = searchList.indexOf(sd);\\n searched_doc = searchList.get(idx);\\n searched_doc.setScore(searched_doc.getScore() + 1);\\n }\\n }\\n\\n }\\n\\n\\n }\\n\\n Collections.sort(searchList);\\n\\n return searchList;\\n }\",\n \"List<String> searchTweets(String keywords) throws TwitterException;\",\n \"public List<String> getRelatedWords(String word) throws IOException {\\n List<String> result = new ArrayList<String>();\\n IDictionary dict = new Dictionary(new File(WORDNET_LOCATION));\\n try {\\n dict.open();\\n IStemmer stemmer = new WordnetStemmer(dict);\\n for (POS pos : EnumSet.of(POS.ADJECTIVE, POS.ADVERB, POS.NOUN, POS.VERB)) {\\n List<String> resultForPos = new ArrayList<String>();\\n List<String> stems = new ArrayList<String>();\\n stems.add(word);\\n for (String stem : stemmer.findStems(word, pos)) {\\n if (!stems.contains(stem))\\n stems.add(stem);\\n }\\n for (String stem : stems) {\\n if (!resultForPos.contains(stem)) {\\n resultForPos.add(stem);\\n IIndexWord idxWord = dict.getIndexWord(stem, pos);\\n if (idxWord == null) continue;\\n List<IWordID> wordIDs = idxWord.getWordIDs();\\n if (wordIDs == null) continue;\\n IWordID wordID = wordIDs.get(0);\\n IWord iword = dict.getWord(wordID);\\n \\n ISynset synonyms = iword.getSynset();\\n List<IWord> iRelatedWords = synonyms.getWords();\\n if (iRelatedWords != null) {\\n for (IWord iRelatedWord : iRelatedWords) {\\n String relatedWord = iRelatedWord.getLemma();\\n if (!resultForPos.contains(relatedWord))\\n resultForPos.add(relatedWord);\\n }\\n }\\n \\n List<ISynsetID> hypernymIDs = synonyms.getRelatedSynsets();\\n if (hypernymIDs != null) {\\n for (ISynsetID relatedSynsetID : hypernymIDs) {\\n ISynset relatedSynset = dict.getSynset(relatedSynsetID);\\n if (relatedSynset != null) {\\n iRelatedWords = relatedSynset.getWords();\\n if (iRelatedWords != null) {\\n for (IWord iRelatedWord : iRelatedWords) {\\n String relatedWord = iRelatedWord.getLemma();\\n if (!resultForPos.contains(relatedWord))\\n resultForPos.add(relatedWord);\\n }\\n }\\n }\\n }\\n }\\n }\\n }\\n for (String relatedWord : resultForPos) {\\n if (relatedWord.length() > 3\\n && !relatedWord.contains(\\\"-\\\")\\n && !result.contains(relatedWord)) {\\n // TODO: Hack alert!\\n // The - check is to prevent lucene from interpreting hyphenated words as negative search terms\\n // Fix!\\n result.add(relatedWord);\\n }\\n }\\n }\\n } finally {\\n dict.close();\\n }\\n return result;\\n }\",\n \"public SearchResult search(String text, String subText);\",\n \"@Test\\n\\tpublic void singleWordGrepTest4() throws Exception {\\n\\t\\t// word is 'undocumented'\\n\\t\\tHashSet<String> grepFound = loadGrepResults(\\\"undocumented\\\");\\n\\t\\tCollection<Page> index = queryTest.query(\\\"undocumented\\\");\\n\\t\\tHashSet<String> indexFound = new HashSet<String>();\\n\\n\\t\\tfor (Page p : index)\\n\\t\\t\\tindexFound.add(p.getURL().getPath().toLowerCase());\\n\\t\\t\\n\\t\\t// tests set equality \\n\\t\\tassertEquals(indexFound, grepFound);\\n\\t}\",\n \"public abstract int search(String[] words, String wordToFind) throws ItemNotFoundException;\",\n \"public Double[] SentiwordsMatch(String tweets) throws IOException\\r\\n {\\r\\n String[] ar=new String[100];\\r\\n \\r\\n ar=tweets.split(\\\" \\\");\\r\\n \\r\\n /* for(String splited_text:ar)\\r\\n System.out.println(splited_text);*/\\r\\n \\r\\n Double price[]=PriceCalculator(ar);\\r\\n \\r\\n \\r\\n return price;\\r\\n \\r\\n }\",\n \"PsiFile[] findFilesWithPlainTextWords( String word);\",\n \"ArrayList<String> searchWordTweet(String word) throws SQLException {\\r\\n //Query che seleziona il mittente e il corpo data una parola\\r\\n String query=\\\"SELECT DISTINCT mittente,corpo FROM tweet WHERE corpo LIKE '%\\\"+word+\\\"%'\\\";\\r\\n //Oggetti per interrogare il db\\r\\n Statement statement=null;\\r\\n connection=DBConnection.connect();\\r\\n ResultSet resultSet=null;\\r\\n //Lista messaggi\\r\\n ArrayList<String> tweetsList = new ArrayList<>();\\r\\n\\r\\n try {\\r\\n statement=connection.createStatement();\\r\\n resultSet = statement.executeQuery(query);\\r\\n while(resultSet.next()){\\r\\n String mittente = resultSet.getString(\\\"mittente\\\");\\r\\n String corpo = resultSet.getString(\\\"corpo\\\");\\r\\n tweetsList.add(mittente+\\\": \\\"+corpo);\\r\\n }\\r\\n\\r\\n return tweetsList;\\r\\n }catch (SQLException e){\\r\\n e.printStackTrace();\\r\\n }finally {\\r\\n if (connection!=null) connection.close();\\r\\n if (statement!=null) statement.close();\\r\\n if(resultSet!=null) resultSet.close();\\r\\n }\\r\\n return null;\\r\\n }\",\n \"public boolean search(String word) {\\n\\t\\treturn startsWith(word) && cur.isWord == true;\\n\\t}\",\n \"public void getThesaurusMap (String wordTofind) {\\r\\n\\t \\tfor (Entry<String, List> entry : tMap.entrySet()) {\\r\\n\\t \\t\\tList singleListofSynonims = entry.getValue();\\r\\n\\t \\t\\tif (singleListofSynonims.contains(wordTofind)){\\r\\n\\t \\t\\t\\t\\r\\n\\t \\t\\t\\tmappedList.add(singleListofSynonims);\\r\\n\\t \\t\\t\\tGoogleToThesarus.put(wordTofind,singleListofSynonims);\\r\\n\\t \\t\\t}\\r\\n\\t \\t\\telse {\\r\\n\\t \\t\\t\\t//System.out.println(\\\"value not in map\\\");\\r\\n\\t \\t}\\r\\n\\t \\t}\\r\\n\\t }\",\n \"private void wordSearch(String word, HashMap<String, SearchResult> resultMap, ArrayList<SearchResult> words) {\\n\\t\\tfor (String path : index.get(word).keySet()) {\\n\\t\\t\\tint frequency = index.get(word).get(path).size();\\n\\t\\t\\tint initialPosition = index.get(word).get(path).first();\\n\\t\\t\\t\\n\\t\\t\\tif (!resultMap.containsKey(path)) {\\n\\t\\t\\t\\tresultMap.put(path, new SearchResult(frequency, initialPosition, path));\\n\\t\\t\\t\\twords.add(resultMap.get(path));\\n\\t\\t\\t}\\n\\t\\t\\telse {\\n\\t\\t\\t\\tSearchResult searchResult = resultMap.get(path);\\n\\t\\t\\t\\tsearchResult.addToFrequency(frequency);\\n\\t\\t\\t\\tsearchResult.updateInitialPosition(initialPosition);\\n\\t\\t\\t}\\n\\t\\t}\\n\\t}\",\n \"public static boolean searchWordInTemplateString(TemplateString tStr, String word) {\\n\\t\\tString text = tStr.string;\\r\\n\\t\\tint currentIndex = 0;\\r\\n\\t\\tfor(int j = 0; j < text.length() && currentIndex < word.length(); j++) {\\r\\n\\t\\t\\tchar c = text.charAt(j);\\r\\n\\t\\t\\t// Check uppercase\\r\\n\\t\\t\\tif(c >= 'A' && c <= 'Z') c = (char) (c + 'a' - 'A');\\r\\n\\t\\t\\t// Check if equal to current word char\\r\\n\\t\\t\\tif(c == word.charAt(currentIndex)) {\\r\\n\\t\\t\\t\\t// If last index then the word exists in template\\r\\n\\t\\t\\t\\tif(currentIndex == word.length() - 1) return true;\\r\\n\\t\\t\\t\\t// Otherwise add one to index\\r\\n\\t\\t\\t\\tcurrentIndex++;\\r\\n\\t\\t\\t\\tcontinue;\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\tif(currentIndex > 0 && ((c >= 'A' && c <= 'Z') || (c >= 'a' && c <= 'z') || (c >= '0' && c <= '9'))) {\\r\\n\\t\\t\\t\\t// If the char was alphanumerical but unequal, the word train was broken..\\r\\n\\t\\t\\t\\tcurrentIndex = 0;\\r\\n\\t\\t\\t}\\r\\n\\t\\t}\\r\\n\\t\\treturn false;\\r\\n\\t}\",\n \"@RequestMapping(value = \\\"/search-in-doc/{id}\\\", \\n\\t\\t\\t\\t\\tmethod = RequestMethod.GET)\\n\\tpublic ResponseEntity<?> searchInDoc(@PathVariable(\\\"id\\\") String id, \\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t @RequestParam(value = \\\"word\\\", required = true) String word) throws IOException {\\n\\n\\t\\tboolean foundFile = false; // denota si el archivo fue encontrado\\n\\t\\t\\n\\t\\tString pageToken = null;\\n\\t\\tdo { // proceso de busqueda\\n\\t\\t\\tFileList result = DriveConnection.driveService.files().list() \\n\\t\\t\\t\\t .setSpaces(\\\"drive\\\")\\n\\t\\t\\t .setFields(\\\"nextPageToken, files(id)\\\") \\n\\t\\t\\t .setPageToken(pageToken)\\n\\t\\t\\t .execute();\\n\\t\\t\\n\\t\\t\\t\\t for (File file : result.getFiles()) { \\n\\t\\t\\t\\t\\t if (file.getId().equals(id)) {\\n\\t\\t\\t\\t\\t\\t\\tfoundFile = true;\\n\\t\\t\\t\\t\\t }\\n\\t\\t\\t\\t }\\n\\t\\t\\t\\t \\n\\t\\t\\t pageToken = result.getNextPageToken();\\n\\t\\t} while (pageToken != null);\\n\\t\\t\\n\\t\\tif (foundFile) {\\n\\t\\t\\t\\n\\t\\t\\tFile content = DriveConnection.driveService.files().get(id).execute();\\t\\n\\t\\t\\tcontent.toString().contains(word);\\t\\n\\t\\t\\treturn new ResponseEntity<>(\\\"Found\\\", HttpStatus.OK); // mostramos rpta en consola\\n\\t\\t\\t\\t\\n\\t\\t} else {\\t\\n\\t\\t\\t\\n\\t\\t\\treturn new ResponseEntity<>(\\\"Not found\\\", HttpStatus.NOT_FOUND); // mostramos rpta en consola\\n\\t\\t\\t\\n\\t\\t}\\n\\t\\n\\t}\",\n \"@In String search();\",\n \"void findAllWords() {\\n\\t\\tScanner in = new Scanner(textEditor.getText());\\n\\t\\tint head = 0;\\n\\t\\twhile (in.hasNext()) {\\n\\t\\t\\tString value = in.next();\\n\\t\\t\\tif (value.equals(findWord)) {\\n\\t\\t\\t\\tint tail = value.length();\\n\\t\\t\\t\\tfinder.add(new WordPosition(head, tail + head +1));\\n\\t\\t\\t}\\n\\t\\t\\thead += (value.length()+1);\\n\\t\\t}\\n\\t\\tin.close();\\n\\t}\",\n \"public int searchWord(File filePath, String s1) throws IOException, NullPointerException\\r\\n\\t{\\r\\n\\t\\tint counter = 0;\\r\\n\\t\\tString data = \\\"\\\";\\r\\n\\t\\tBufferedReader bufferReader = new BufferedReader(new FileReader(filePath));\\r\\n\\t\\tString line = null;\\r\\n\\t\\twhile ((line = bufferReader.readLine()) != null)\\r\\n\\t\\t{\\r\\n\\t\\t\\tdata = data + line;\\r\\n\\t\\t}\\r\\n\\t\\tbufferReader.close();\\r\\n\\t\\tString txt = data;\\r\\n\\t\\tBoyerMoore bm = new BoyerMoore(s1);\\r\\n\\t\\tint offset = 0;\\r\\n\\t\\tfor (int loc = 0; loc <= txt.length(); loc += offset + s1.length())\\r\\n\\t\\t{\\r\\n\\t\\t\\t offset = bm.search(s1, txt.substring(loc));\\r\\n\\t\\t\\t if ((offset + loc) < txt.length())\\r\\n\\t\\t\\t { \\r\\n\\t\\t\\t\\t counter++; \\r\\n\\t\\t\\t\\t System.out.printf(\\\"The word '\\\"+s1 +\\\"' is present at the position \\\" + (offset + loc)+\\\"\\\\n\\\"); //printing position of word \\r\\n\\t\\t\\t } \\r\\n\\t\\t}\\r\\n\\t\\tif(counter!=0)\\r\\n\\t\\t{ \\r\\n\\t\\t\\t System.out.println(\\\" In the FILE: \\\"+filePath.getName()+\\\"\\\\n\\\");\\r\\n\\t\\t}\\r\\n\\t\\treturn counter; \\r\\n\\t}\",\n \"public static String findMultipleOccorancesOfGivenWord(String sentence,String word)\\n {\\n if(sentence == null || word == null || sentence == \\\"\\\" || word == \\\"\\\"){\\n return \\\"Please enter valid sentence and word.It should not be empty and null\\\";\\n }\\n String result = \\\"\\\";\\n Pattern pattern = Pattern.compile(word);\\n Matcher matcher = pattern.matcher(sentence);\\n while(matcher.find()) {\\n\\n result = result + \\\"Found at:\\\"+ matcher.start() + \\\" - \\\" + matcher.end() + \\\" \\\";\\n }\\n\\n return result.trim();\\n\\n }\",\n \"private boolean isTermAppearInQuery(String term) {\\n boolean isTermAppear = false;\\n query thisQuery = listDocumentRetrievedForThisQuery.getQuery();\\n StringTokenizer token = new StringTokenizer(thisQuery.getQueryContent(), \\\" %&\\\\\\\"*#@$^_<>|`+=-1234567890'(){}[]/.:;?!,\\\\n\\\");\\n while (token.hasMoreTokens()) {\\n String keyTerm = token.nextToken();\\n if (invertedFile.isStemmingApplied()) {\\n keyTerm = StemmingPorter.stripAffixes(keyTerm);\\n }\\n if (term.equals(keyTerm.toLowerCase())) {\\n isTermAppear = true;\\n break;\\n }\\n }\\n return isTermAppear;\\n }\",\n \"public String searchTweet(String searchString) {\\n\\t\\treturn restClient.searchTweet(searchString);\\n\\t}\",\n \"@Test\\n public void findsByKeyword() throws Exception {\\n final Base base = new DyBase(\\n this.dynamo.region(), new MkSttc().counters().get(\\\"ttt\\\")\\n );\\n final Book book = base.books().add(\\n \\\"@book{best2014, author=\\\\\\\"Walter\\\\\\\"}\\\"\\n );\\n final Quotes quotes = base.quotes();\\n quotes.add(\\n book, \\\"never give up and never think about bad things, Bobby\\\",\\n \\\"99-101, 256-257, 315\\\"\\n );\\n MatcherAssert.assertThat(\\n quotes.refine(\\\"bobby\\\").iterate(),\\n Matchers.<Quote>iterableWithSize(1)\\n );\\n MatcherAssert.assertThat(\\n quotes.refine(\\\"another-something\\\").iterate(),\\n Matchers.<Quote>iterableWithSize(0)\\n );\\n }\",\n \"@Test\\n\\tpublic void phraseGrepTest1() throws Exception {\\n\\t\\t// phrase is \\\"I am forced\\\"\\n\\t\\tHashSet<String> grepFound = loadGrepResults(\\\"i+am+forced\\\");\\n\\t\\tCollection<Page> index = queryTest.query(\\\"\\\\\\\"I am Forced\\\\\\\"\\\");\\n\\t\\tHashSet<String> indexFound = new HashSet<String>();\\n\\n\\t\\tfor (Page p : index)\\n\\t\\t\\tindexFound.add(p.getURL().getPath().toLowerCase());\\n\\t\\t\\n\\t\\t// tests set equality \\n\\t\\tassertEquals(indexFound, grepFound);\\n\\t}\",\n \"public boolean isNoun (String word){\\n for(int i = 0; i< SynSets.length; i++){\\n if(SynSets[0][1].contains(\\\" \\\"+word+\\\" \\\")) return true;\\n }\\n return false;\\n }\",\n \"public void SearchPhrase(Object_Ord temp) {\\n\\tif (!Doneloading) {\\r\\n\\t return;\\r\\n\\t}\\r\\n\\tif (temp == null) {\\r\\n\\t return;\\r\\n\\t} else if (temp.Ordet.equals(\\\"\\\")) {\\r\\n\\t return;\\r\\n\\t}\\r\\n\\ttemp.Set_Searched();\\r\\n\\t//PrintAction( this.getClass().toString() + \\\" Searching for phrase \\\" + temp.Ordet );\\r\\n\\tThread thread = new Thread_PhraseSearcher(this, temp);\\r\\n\\tThreadsRunning++;\\r\\n\\tThreadsStarted++;\\r\\n }\",\n \"private String search_words(String word, int index){\\n\\t\\tString found_words = \\\"\\\";\\n\\t\\tint local_index = index +1;\\n\\t\\t//We try to find the word within our childs\\n\\t\\tfor(LexiNode child: childs){\\n\\t\\t\\tif(local_index > word.length()-1 || word.toLowerCase().charAt(local_index) == Character.toLowerCase(child.getRepresentative_letter()))\\n\\t\\t\\t\\tfound_words += child.search_words(word, local_index);\\n\\t\\t}\\n\\t\\tif(current_word != null && word.length() > current_word.length())\\n\\t\\t\\treturn found_words;\\n\\t\\tif(current_word != null && !found_words.equals(\\\"\\\"))\\n\\t\\t\\treturn current_word.toLowerCase().equals(word.toLowerCase()) ? current_word +\\\" & \\\" + definition + \\\"#\\\" + found_words +\\\"#\\\" : current_word + \\\"#\\\" + found_words;\\n\\t\\telse if(current_word != null && found_words.equals(\\\"\\\"))\\n\\t\\t\\treturn current_word.toLowerCase().equals(word.toLowerCase()) ? current_word +\\\" & \\\" + definition + \\\"#\\\": current_word+ \\\"#\\\";\\n\\t\\telse //current_word == null && found_words != null\\n\\t\\t\\treturn found_words;\\n\\t}\",\n \"public interface DocumentRelatedTermsSearcher {\\n List<ScoredTerm> getDocumentRelatedTerms(int docId, String term) throws SearchException;\\n}\",\n \"static void allDocumentAnalyzer() throws IOException {\\n\\t\\tFile allFiles = new File(\\\".\\\"); // current directory\\n\\t\\tFile[] files = allFiles.listFiles(); // file array\\n\\n\\t\\t// recurse through all documents\\n\\t\\tfor (File doc : files) {\\n\\t\\t\\t// other files we don't need\\n\\t\\t\\tif (doc.getName().contains(\\\".java\\\") || doc.getName().contains(\\\"words\\\") || doc.getName().contains(\\\"names\\\")\\n\\t\\t\\t\\t\\t|| doc.getName().contains(\\\"phrases\\\") || doc.getName().contains(\\\".class\\\")\\n\\t\\t\\t\\t\\t|| doc.getName().contains(\\\"Data\\\") || doc.getName().contains(\\\".sh\\\") || doc.isDirectory()\\n\\t\\t\\t\\t\\t|| !doc.getName().contains(\\\".txt\\\")) {\\n\\t\\t\\t\\tcontinue;\\n\\t\\t\\t}\\n\\n\\t\\t\\tString name = doc.getName();\\n\\t\\t\\tSystem.out.println(name);\\n\\t\\t\\tname = name.substring(0, name.length() - 11);\\n\\t\\t\\tSystem.out.println(name);\\n\\n\\t\\t\\tif (!names.contains(name)) {\\n\\t\\t\\t\\tcontinue;\\n\\t\\t\\t}\\n\\n\\t\\t\\t// make readers\\n\\t\\t\\tFileReader fr = new FileReader(doc);\\n\\t\\t\\tBufferedReader br = new BufferedReader(fr);\\n\\n\\t\\t\\t// phrase list\\n\\t\\t\\tArrayList<String> words = new ArrayList<String>();\\n\\n\\t\\t\\t// retrieve all text, trim, refine and add to phrase list\\n\\t\\t\\tString nextLine = br.readLine();\\n\\t\\t\\twhile (nextLine != null) {\\n\\t\\t\\t\\tnextLine = nextLine.replace(\\\"\\\\n\\\", \\\" \\\");\\n\\t\\t\\t\\tnextLine = nextLine.trim();\\n\\n\\t\\t\\t\\tif (nextLine.contains(\\\"no experience listed\\\")) {\\n\\t\\t\\t\\t\\tbreak;\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\tString[] lineArray = nextLine.split(\\\"\\\\\\\\s+\\\");\\n\\n\\t\\t\\t\\t// recurse through every word to find phrases\\n\\t\\t\\t\\tfor (int i = 0; i < lineArray.length - 1; i++) {\\n\\t\\t\\t\\t\\t// get the current word and refine\\n\\t\\t\\t\\t\\tString currentWord = lineArray[i];\\n\\n\\t\\t\\t\\t\\tcurrentWord = currentWord.trim();\\n\\t\\t\\t\\t\\tcurrentWord = refineWord(currentWord);\\n\\n\\t\\t\\t\\t\\tif (currentWord.equals(\\\"\\\") || currentWord.isEmpty()) {\\n\\t\\t\\t\\t\\t\\tcontinue;\\n\\t\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\t\\twords.add(currentWord);\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\tnextLine = br.readLine();\\n\\t\\t\\t}\\n\\n\\t\\t\\tbr.close();\\n\\n\\t\\t\\t// continue if empty\\n\\t\\t\\tif (words.size() == 0) {\\n\\t\\t\\t\\tcontinue;\\n\\t\\t\\t}\\n\\n\\t\\t\\t// otherwise, increment number of files in corpus\\n\\t\\t\\tsize++;\\n\\n\\t\\t\\t// updating the phrase count map for tf\\n\\t\\t\\tString fileName = doc.getName();\\n\\t\\t\\tphraseCountMap.put(fileName, words.size());\\n\\n\\t\\t\\t// recurse through every word\\n\\t\\t\\tfor (String word : words) {\\n\\t\\t\\t\\t// get map from string to freq\\n\\t\\t\\t\\tHashMap<String, Integer> textFreqMap = wordFreqMap.get(fileName);\\n\\n\\t\\t\\t\\t// if it's null, make one\\n\\t\\t\\t\\tif (textFreqMap == null) {\\n\\t\\t\\t\\t\\ttextFreqMap = new HashMap<String, Integer>();\\n\\t\\t\\t\\t\\t// make freq as 1\\n\\t\\t\\t\\t\\ttextFreqMap.put(word, 1);\\n\\t\\t\\t\\t\\t// put that in wordFreq\\n\\t\\t\\t\\t\\twordFreqMap.put(fileName, textFreqMap);\\n\\t\\t\\t\\t} else {\\n\\t\\t\\t\\t\\t// otherwise, get the current num\\n\\t\\t\\t\\t\\tInteger currentFreq = textFreqMap.get(word);\\n\\n\\t\\t\\t\\t\\t// if it's null,\\n\\t\\t\\t\\t\\tif (currentFreq == null) {\\n\\t\\t\\t\\t\\t\\t// the frequency is just 0\\n\\t\\t\\t\\t\\t\\tcurrentFreq = 0;\\n\\t\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\t\\t// increment the frequency\\n\\t\\t\\t\\t\\tcurrentFreq++;\\n\\n\\t\\t\\t\\t\\t// put it in the textFreqMap\\n\\t\\t\\t\\t\\ttextFreqMap.put(word, currentFreq);\\n\\n\\t\\t\\t\\t\\t// put that in the wordFreqMap\\n\\t\\t\\t\\t\\twordFreqMap.put(fileName, textFreqMap);\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\t// add this to record (map from phrases to docs with that\\n\\t\\t\\t\\t// phrase)\\n\\t\\t\\t\\tinvertedMap.addValue(word, doc);\\n\\t\\t\\t}\\n\\t\\t}\\n\\t}\",\n \"private String keywordFound(){\\r\\n\\t\\tString rtn = \\\"\\\";\\r\\n\\t\\tString tmp = \\\"\\\";\\r\\n\\t\\tint carr_pos = getCaretPosition();\\r\\n\\t\\t//estract part of text for keyword search\\r\\n\\t\\ttry { \\r\\n\\t\\tif(carr_pos>50)\\r\\n\\t\\t\\ttmp = doc.getText(carr_pos-50,50);\\r\\n\\t\\telse\\r\\n\\t\\t\\ttmp = doc.getText(0,carr_pos);\\r\\n\\t\\t}catch(BadLocationException a){\\r\\n\\t\\t\\tSystem.out.println(\\\"exception\\\");\\r\\n\\t\\t\\treturn rtn;\\r\\n\\t\\t};\\r\\n\\t\\t//Start check\\r\\n\\t\\tint i = 0;\\r\\n\\t\\tif(tmp.length() >= 2)i = tmp.length()-2;\\t\\r\\n\\t\\twhile(checkOperator(tmp.charAt(i)) && i > 0){\\r\\n\\t\\t\\trtn += tmp.charAt(i);\\r\\n\\t\\t\\ti--;\\r\\n\\t\\t}\\r\\n\\t\\tif(i == 0)rtn += tmp.charAt(i);\\t\\t\\r\\n\\t\\treturn mirrorString(rtn);\\r\\n\\t}\",\n \"private Predicate buildOrPredicatesForWord(CriteriaBuilder builder, Root<Attendee> root, String word) {\\n Predicate hasFirstName = builder.like(root.get(\\\"firstName\\\"), \\\"%\\\" + word + \\\"%\\\");\\n Predicate hasLastName = builder.like(root.get(\\\"lastName\\\"), \\\"%\\\" + word + \\\"%\\\");\\n Predicate hasFanName = builder.like(root.get(\\\"fanName\\\"), \\\"%\\\" + word + \\\"%\\\");\\n Predicate hasLegalFirstName = builder.like(root.get(\\\"legalFirstName\\\"), \\\"%\\\" + word + \\\"%\\\");\\n Predicate hasLegalLastName = builder.like(root.get(\\\"legalLastName\\\"), \\\"%\\\" + word + \\\"%\\\");\\n return builder.or(hasFirstName, hasLastName, hasFanName, hasLegalFirstName, hasLegalLastName);\\n }\",\n \"public static ArrayList<Result> findMatches(Query query, DataManager myVocab){\\n\\n\\t\\t//Uncomment this for logging in this class\\t\\n//\\t\\tmyLogger.setLevel(Level.INFO); \\n\\n\\t\\t// get the term we're going to search for and\\n\\t\\t// take out any leading or trailing whitespaces\\n\\t\\tString querystr = query.getQuery();\\n\\t\\tquerystr = querystr.trim();\\n\\t\\tString uncleaned = querystr;\\n\\t\\t\\n\\t\\t// This is in case of numeric entries. Google Refine doesn't seem\\n\\t\\t// to have int cell types, instead it adds an invisible .0 to all\\n\\t\\t// numbers. This fixes that issue, as it sometimes causes false negatives.\\n\\t\\tif (querystr.endsWith(\\\".0\\\")){\\n\\t\\t Pattern p = Pattern.compile(\\\"[^0-9\\\\\\\\.]+\\\");\\n\\t\\t Matcher m = p.matcher(querystr);\\n\\t\\t boolean result = m.find();\\n\\t\\t if (!result){\\n\\t\\t \\t querystr = querystr.substring(0, querystr.length()-2);\\n\\t\\t }\\n\\t\\t}\\n\\t\\t// see if it's in the synonyms map, if it is\\n\\t\\t// replace it with the appropriate term, if it's\\n\\t\\t// not, don't do anything. \\n\\n\\t\\tif (myVocab.subMap.get(querystr)!=null){\\n\\t\\t\\tquerystr = myVocab.subMap.get(querystr);\\n\\t\\t\\tquery.setQuery(querystr);\\n\\t\\t}\\n\\t\\t\\n\\t\\t// Clean up the query string if it isn't case/punctuation sensitive\\n\\t\\tif (!myVocab.capsSensitive()){\\t\\t\\n\\t\\t\\tquerystr = querystr.toLowerCase();\\n\\t\\t}\\n\\t\\tif (! myVocab.punctSensitive()){\\t\\t\\n\\t\\t\\tquerystr = querystr.replaceAll(\\\"[\\\\\\\\W_]\\\", \\\"\\\");\\n\\t\\t}\\n\\t\\t\\n\\t\\t// see if it's in the synonyms map, if it is\\n\\t\\t// replace it with the appropriate term, if it's\\n\\t\\t// not, don't do anything. \\n\\t\\tif(myVocab.subMap.get(querystr)!=null){\\n\\t\\t\\tquerystr = myVocab.subMap.get(querystr);\\n\\t\\t\\tquery.setQuery(querystr);\\n\\t\\t}\\n\\n\\t\\tString type = query.getType();\\n\\n\\t\\t// This ArrayList is the results that are going to be returned. \\n\\t\\tArrayList<Result> results = getDirectMatches(myVocab, querystr, uncleaned, type);\\n\\t\\t\\n\\t\\t// If there's a perfect match return it.\\n\\t\\tif (results.size() == 1 && results.get(0).match){\\n\\t\\t\\treturn results;\\n\\t\\t}else{\\n\\t\\t\\t// Otherwise, add the initial ones and try matching\\n\\t\\t\\t// based on distance to vocabulary terms.\\n\\t\\t\\tresults.addAll(distanceMatching(query, myVocab));\\n\\t\\t\\t\\n\\t\\t\\t// Split the original query term by space and non-alphanumeric characters \\n\\t\\t\\t// to find how many words there are.\\n\\t\\t\\t//querystr = query.getQuery().replaceAll(\\\"[\\\\\\\\W_]\\\", \\\" \\\");\\n\\t\\t\\tString [] termList = querystr.split(\\\" \\\");\\n\\t\\t\\t\\n\\t\\t\\t// if there's more than one, run bagOfWords\\n\\t\\t\\t// which tries to find a match for each of the words.\\n\\t\\t\\tif (termList.length > 1){\\n\\t\\t\\t\\tresults.addAll(bagOfWords(query, myVocab));\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\t\\n\\t\\t// Clean the results: no duplicates\\n\\t\\t// no extra results to return, and sorted\\n\\t\\t// them by score before returning them\\n\\t\\tresults = removeDuplicates(results);\\n\\t\\t\\n\\t\\t// They do not need to be reduced in \\n\\t\\t// number if there are fewer than \\n\\t\\t// the max results.\\n\\t\\t// The pruneResults sorts them\\n\\t\\t// by score already.\\n\\t\\tif(query.getLimit()!=null){\\n\\t\\t\\tresults = pruneResults(results,Integer.parseInt(query.getLimit()));\\n\\t\\t}else{\\n\\t\\t\\tresults = pruneResults(results,MAX_RESULTS);\\n\\t\\t}\\n\\t\\t\\t\\n\\t\\tresults = sortByScore(results);\\n\\t\\tfor (int i = 0; i< results.size(); i++){\\n//\\t\\t\\tmyLogger.log(Level.SEVERE,results.get(i).getScore()+ \\\" is bigger than 100?\\\");\\n\\t\\t\\tif(results.get(i).getScore() > (double)100){\\n\\t\\t\\t\\tresults.get(i).setScore((double)100 - (results.get(i).getScore()-(double)100));\\n//\\t\\t\\t\\tmyLogger.log(Level.SEVERE,results.get(i).getScore()+\\\" is bigger than 100! and was set to \\\"+\\n//\\t\\t\\t\\t\\t\\t((double)100 - (results.get(i).getScore()-(double)100)));\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\treturn results;\\n\\t}\",\n \"public WordList find(String s) {\\n \\treturn index.get(s);\\n }\",\n \"private List<Query> generateSynonymQueries(Analyzer synonymAnalyzer, SolrParams solrParams) {\\n\\n\\tString origQuery = getQueryStringFromParser();\\n\\tint queryLen = origQuery.length();\\n\\t\\n // TODO: make the token stream reusable?\\n TokenStream tokenStream = synonymAnalyzer.tokenStream(Const.IMPOSSIBLE_FIELD_NAME,\\n new StringReader(origQuery));\\n \\n SortedSetMultimap<Integer, TextInQuery> startPosToTextsInQuery = TreeMultimap.create();\\n \\n \\n boolean constructPhraseQueries = solrParams.getBool(Params.SYNONYMS_CONSTRUCT_PHRASES, false);\\n \\n boolean bag = solrParams.getBool(Params.SYNONYMS_BAG, false);\\n List<String> synonymBag = new ArrayList<>();\\n \\n try {\\n tokenStream.reset();\\n while (tokenStream.incrementToken()) {\\n CharTermAttribute term = tokenStream.getAttribute(CharTermAttribute.class);\\n OffsetAttribute offsetAttribute = tokenStream.getAttribute(OffsetAttribute.class);\\n TypeAttribute typeAttribute = tokenStream.getAttribute(TypeAttribute.class);\\n \\n if (!typeAttribute.type().equals(\\\"shingle\\\")) {\\n // ignore shingles; we only care about synonyms and the original text\\n // TODO: filter other types as well\\n \\n String termToAdd = term.toString();\\n \\n if (typeAttribute.type().equals(\\\"SYNONYM\\\")) {\\n synonymBag.add(termToAdd); \\t\\n }\\n \\n //Don't quote sibgle term term synonyms\\n\\t\\t if (constructPhraseQueries && typeAttribute.type().equals(\\\"SYNONYM\\\") &&\\n\\t\\t\\ttermToAdd.contains(\\\" \\\")) \\n\\t\\t {\\n\\t\\t \\t//Don't Quote when original is already surrounded by quotes\\n\\t\\t \\tif( offsetAttribute.startOffset()==0 || \\n\\t\\t \\t offsetAttribute.endOffset() == queryLen ||\\n\\t\\t \\t origQuery.charAt(offsetAttribute.startOffset()-1)!='\\\"' || \\n\\t\\t \\t origQuery.charAt(offsetAttribute.endOffset())!='\\\"')\\n\\t\\t \\t{\\n\\t\\t \\t // make a phrase out of the synonym\\n\\t\\t \\t termToAdd = new StringBuilder(termToAdd).insert(0,'\\\"').append('\\\"').toString();\\n\\t\\t \\t}\\n\\t\\t }\\n if (!bag) {\\n // create a graph of all possible synonym combinations,\\n // e.g. dog bite, hound bite, dog nibble, hound nibble, etc.\\n\\t TextInQuery textInQuery = new TextInQuery(termToAdd, \\n\\t offsetAttribute.startOffset(), \\n\\t offsetAttribute.endOffset());\\n\\t \\n\\t startPosToTextsInQuery.put(offsetAttribute.startOffset(), textInQuery);\\n }\\n }\\n }\\n tokenStream.end();\\n } catch (IOException e) {\\n throw new RuntimeException(\\\"uncaught exception in synonym processing\\\", e);\\n } finally {\\n try {\\n tokenStream.close();\\n } catch (IOException e) {\\n throw new RuntimeException(\\\"uncaught exception in synonym processing\\\", e);\\n }\\n }\\n \\n List<String> alternateQueries = synonymBag;\\n \\n if (!bag) {\\n // use a graph rather than a bag\\n\\t List<List<TextInQuery>> sortedTextsInQuery = new ArrayList<>(\\n startPosToTextsInQuery.values().size());\\n sortedTextsInQuery.addAll(startPosToTextsInQuery.asMap().values().stream().map(ArrayList::new).collect(Collectors.toList()));\\n\\t \\n\\t // have to use the start positions and end positions to figure out all possible combinations\\n\\t alternateQueries = buildUpAlternateQueries(solrParams, sortedTextsInQuery);\\n }\\n \\n // save for debugging purposes\\n expandedSynonyms = alternateQueries;\\n \\n return createSynonymQueries(solrParams, alternateQueries);\\n }\",\n \"public boolean search(String word) {\\n TrieNode now = root;\\n for(int i = 0; i < word.length(); i++) {\\n Character c = word.charAt(i);\\n if (!now.children.containsKey(c)) {\\n return false;\\n }\\n now = now.children.get(c);\\n }\\n return now.hasWord;\\n}\",\n \"public String phraseWords(String input) {\\n document = new Annotation(input);\\n // run all Annotators on this text\\n pipeline.annotate(document);\\n String pos = document.get(CoreAnnotations.PhraseWordsTagAnnotation.class);\\n\\n return pos;\\n }\",\n \"public String search_words(String word){\\n\\t\\tString found_words = \\\"\\\";\\n\\t\\t//We try to find the word within our childs\\n\\t\\tfor(LexiNode child: childs)\\n\\t\\t\\tif(word.toLowerCase().charAt(0) == Character.toLowerCase(child.getRepresentative_letter()))\\n\\t\\t\\t\\tfound_words += child.search_words(word, 0);\\n\\t\\t\\n\\t\\treturn found_words;\\n\\t}\",\n \"private void termQuerySearch(String[] terms) {\\n for (String term : terms) {\\n LinkedList<TermPositions> postingLists = indexMap.get(analyzeTerm(term));\\n if (postingLists != null) {\\n for (TermPositions matches : postingLists) {\\n double score = (double) 1 + Math.log((double) matches.getPositionList().size()) *\\n Math.log((double) N / (double) postingLists.size());\\n resultsCollector.add(new DocCollector(matches.getDocId(), score));\\n }\\n }\\n }\\n }\",\n \"public Cursor getWordMatches(String query, String[] columns) {\\n // Search over location names and abbreviations\\n String selection = \\n LOC_NAME + \\\" LIKE '%\\\" + query + \\\"%'\\\" + \\\" OR \\\" + \\n ABBR + \\\" LIKE '%\\\" + query + \\\"%'\\\";\\n\\n return query(selection, columns);\\n }\",\n \"@Test\\n\\tpublic void notPhraseGrepTest() throws Exception {\\n\\t\\t// phrase is \\\"I am forced\\\"\\n\\t\\tHashSet<String> grepFound = loadGrepResults(\\\"!i+am+forced\\\");\\n\\t\\tCollection<Page> index = queryTest.query(\\\"! \\\\\\\"I am Forced\\\\\\\"\\\");\\n\\t\\tHashSet<String> indexFound = new HashSet<String>();\\n\\n\\t\\tfor (Page p : index)\\n\\t\\t\\tindexFound.add(p.getURL().getPath().toLowerCase());\\n\\t\\tassertEquals(grepFound, indexFound);\\n\\t}\",\n \"public abstract boolean isStopWord(String term);\",\n \"SpellResponse spellQuery(SearchRequest request, Map<SearchParam, String> params);\",\n \"public void searchWordToGroup(String title, String word, String groupIns) throws IOException {\\r\\n\\t\\tString line;\\r\\n\\t\\tBufferedReader in;\\r\\n\\t\\tint paragraphs = 1;\\r\\n\\t\\tint sentences = 1;\\r\\n\\t\\tfound = 0;\\r\\n\\t\\ttry {\\r\\n\\t\\t\\tstatementP = SqlCon.getConnection().prepareStatement(SqlCon.PATH_ACORDING_TITLE);\\r\\n\\t\\t\\tstatementP.setString(1, title);\\r\\n\\t\\t\\trs = statementP.executeQuery();\\r\\n\\t\\t\\twhile (rs.next()) {\\r\\n\\t\\t\\t\\tString path = rs.getString(\\\"filePath\\\");\\r\\n\\t\\t\\t\\tin = new BufferedReader(new FileReader(path));\\r\\n\\t\\t\\t\\tline = in.readLine();\\r\\n\\t\\t\\t\\twhile (line != null) {\\r\\n\\t\\t\\t\\t\\tif (line.equals(\\\"\\\")) {\\r\\n\\t\\t\\t\\t\\t\\tparagraphs++;\\r\\n\\t\\t\\t\\t\\t\\tsentences = 1;\\r\\n\\t\\t\\t\\t\\t} else {\\r\\n\\t\\t\\t\\t\\t\\tString[] sentenceList = line.split(\\\"[!?.:]+\\\");\\r\\n\\t\\t\\t\\t\\t\\tfor (int i = 0; i < sentenceList.length; i++) {\\r\\n\\t\\t\\t\\t\\t\\t\\tif (sentenceList[i].contains(word)) {\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tint p = paragraphs;\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tint s = sentences;\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tint is =0;\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tinsertTable.insertwordFunc(groupIns, word, title, p, s, is);\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tfound = 1;\\r\\n\\t\\t\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\tsentences++;\\r\\n\\t\\t\\t\\t\\tline = in.readLine();\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\tparagraphs = 1;\\r\\n\\t\\t\\t\\tsentences = 1;\\r\\n\\t\\t\\t}\\r\\n\\t\\t} catch (SQLException e) {\\r\\n\\t\\t\\te.printStackTrace();\\r\\n\\t\\t}\\r\\n\\t}\",\n \"@Override\\n public String search(String word) {\\n return search(word, root);\\n }\",\n \"public boolean search(String word) {\\n TrieTree point = root;\\n for(int i = 0; i < word.length(); i++){\\n char ch = word.charAt(i);\\n if(point.getChild(ch - 'a') == null) return false;\\n point = point.getChild(ch - 'a');\\n }\\n return point.getIsWord();\\n }\",\n \"List<FraseEntidade> getPhrasesByAuthorName(String name);\",\n \"public void search(Indexer indexer, CityIndexer cityIndexer, Ranker ranker, String query, boolean withSemantic, ArrayList<String> chosenCities, ObservableList<String> citiesByTag, boolean withStemming, String saveInPath, String queryId, String queryDescription) {\\n String[] originalQueryTerms = query.split(\\\" \\\");\\n String originQuery = query;\\n docsResults = new HashMap<>();\\n parser = new Parse(withStemming, saveInPath, saveInPath);\\n HashSet<String> docsOfChosenCities = new HashSet<>();\\n query = \\\"\\\" + query + queryDescription;\\n HashMap<String, Integer> queryTerms = parser.parseQuery(query);\\n HashMap<String, ArrayList<Integer>> dictionary = indexer.getDictionary();\\n if (!withStemming){\\n setDocsInfo(saveInPath + \\\"\\\\\\\\docsInformation.txt\\\");\\n }\\n else{\\n setDocsInfo(saveInPath + \\\"\\\\\\\\docsInformation_stemming.txt\\\");\\n }\\n\\n\\n //add semantic words of each term in query to 'queryTerms'\\n if(withSemantic) {\\n HashMap<String,ArrayList<String>> semanticWords = ws.connectToApi(originQuery);\\n }\\n\\n //give an ID to query if it's a regular query (not queries file)\\n if(queryId.equals(\\\"\\\")){\\n queryId = \\\"\\\" + Searcher.queryID;\\n Searcher.queryID++;\\n }\\n\\n String postingDir;\\n if (!withStemming) {\\n postingDir = \\\"\\\\\\\\indexResults\\\\\\\\postingFiles\\\";\\n } else {\\n postingDir = \\\"\\\\\\\\indexResults\\\\\\\\postingFiles_Stemming\\\";\\n }\\n int pointer = 0;\\n\\n //find docs that contain the terms in the query in their text\\n HashMap<String, Integer> queryTermsIgnoreCase = new HashMap<>();\\n for (String term : queryTerms.keySet()) {\\n String originTerm = term;\\n if (!dictionary.containsKey(term.toUpperCase()) && !dictionary.containsKey(term.toLowerCase())) {\\n continue;\\n }\\n if(dictionary.containsKey(term.toLowerCase())){\\n term = term.toLowerCase();\\n }\\n else {\\n term = term.toUpperCase();\\n }\\n queryTermsIgnoreCase.put(term,queryTerms.get(originTerm));\\n pointer = dictionary.get(term).get(2);\\n String chunk = (\\\"\\\" + term.charAt(0)).toUpperCase();\\n\\n //get the relevant line from posting file\\n BufferedReader br = null;\\n try {\\n br = new BufferedReader(new FileReader(new File(saveInPath + postingDir + \\\"\\\\\\\\posting_\\\" + chunk + \\\".txt\\\")));\\n String line = \\\"\\\";\\n int i = 1;\\n while ((line = (br.readLine())) != null) {\\n if (i == pointer) {\\n break;\\n }\\n i++;\\n }\\n br.close();\\n\\n //get docs from posting line and add them to the data structure 'docsResults'\\n if(line != null) {\\n findDocsFromLine(line, term);\\n }\\n\\n } catch (IOException e) {\\n e.printStackTrace();\\n }\\n }\\n\\n //find docs that contain the chosen cities in their text\\n for (String cityTerm : chosenCities) {\\n if (!dictionary.containsKey(cityTerm) && !dictionary.containsKey(cityTerm.toLowerCase())) {\\n continue;\\n }\\n if(dictionary.containsKey(cityTerm.toLowerCase())){\\n cityTerm = cityTerm.toLowerCase();\\n }\\n pointer = dictionary.get(cityTerm).get(2);\\n // char chunk = indexer.classifyToPosting(term).charAt(0);\\n String chunk = (\\\"\\\" + cityTerm.charAt(0)).toUpperCase();\\n\\n //get the relevant line from posting file\\n BufferedReader br = null;\\n try {\\n br = new BufferedReader(new FileReader(new File(saveInPath + postingDir + \\\"\\\\\\\\posting_\\\" + chunk + \\\".txt\\\")));\\n String line = \\\"\\\";\\n int i = 1;\\n while ((line = (br.readLine())) != null) {\\n if (i == pointer) {\\n break;\\n }\\n i++;\\n }\\n br.close();\\n\\n //get docs from posting line and add them to the data structure 'docsOfChosenCities'\\n String docs = line.substring(0, line.indexOf(\\\"[\\\") - 1); //get 'docsListStr'\\n String[] docsArr = docs.split(\\\";\\\");\\n for (String docInfo : docsArr) {\\n String doc = docInfo.substring(0, docInfo.indexOf(\\\": \\\"));\\n while(doc.charAt(0) == ' '){\\n doc = doc.substring(1);\\n }\\n docsOfChosenCities.add(doc);\\n }\\n } catch (IOException e) {\\n e.printStackTrace();\\n }\\n }\\n\\n //find docs that contain the chosen cities in their city tag\\n if(!chosenCities.isEmpty()){\\n for (String cityDicRec: chosenCities) {\\n //get pointer to posting from cityDictionary\\n try {\\n pointer = cityIndexer.getCitiesDictionary().get(cityDicRec);\\n } catch (NumberFormatException e) {\\n e.printStackTrace();\\n }\\n //get the relevant line from posting file\\n BufferedReader br = null;\\n try {\\n br = new BufferedReader(new FileReader(new File(saveInPath + \\\"\\\\\\\\cityIndexResults\\\" + \\\"\\\\\\\\posting_city\\\" + \\\".txt\\\")));\\n String line = \\\"\\\";\\n int i = 1;\\n while ((line = (br.readLine())) != null) {\\n if (i == pointer) {\\n break;\\n }\\n i++;\\n }\\n br.close();\\n\\n //get docs from posting line and add them to the data structure 'docsOfChosenCities'\\n String docs = line.substring(line.indexOf(\\\"[\\\") + 1, line.indexOf(\\\"]\\\")); //get 'docsListStr'\\n String[] docsArr = docs.split(\\\"; \\\");\\n for (String doc : docsArr) {\\n docsOfChosenCities.add(doc);\\n }\\n } catch (IOException e) {\\n e.printStackTrace();\\n }\\n }\\n }\\n\\n\\n ranker.rank(docsResults, docsOfChosenCities, queryTermsIgnoreCase, dictionary, docsInfo,entities, queryId);\\n }\",\n \"public WordInfo searchWord(String word) {\\n\\t\\tSystem.out.println(\\\"Dic:SearchWord: \\\"+word);\\n\\n\\t\\tDocument doc;\\n\\t\\ttry {\\n\\t\\t\\tdoc = Jsoup.connect(\\\"https://dictionary.cambridge.org/dictionary/english-vietnamese/\\\" + word).get();\\n\\t\\t} catch(Exception e) {\\n\\t\\t\\te.printStackTrace();\\n\\t\\t\\treturn null;\\n\\t\\t}\\n\\n\\t\\tElements elements = doc.select(\\\".dpos-h.di-head.normal-entry\\\");\\n\\t\\tif (elements.isEmpty()) {\\n\\t\\t\\tSystem.out.println(\\\" not found\\\");\\n\\t\\t\\treturn null;\\n\\t\\t}\\n\\n\\t\\tWordInfo wordInfo = new WordInfo(word);\\n\\n\\t\\t// Word\\n\\t\\telements = doc.select(\\\".tw-bw.dhw.dpos-h_hw.di-title\\\");\\n\\n\\t\\tif (elements.size() == 0) {\\n\\t\\t\\tSystem.out.println(\\\" word not found in doc!\\\");\\n\\t\\t\\treturn null;\\n\\t\\t}\\n\\n\\t\\twordInfo.setWordDictionary(elements.get(0).html());\\n\\n\\t\\t// Type\\n\\t\\telements = doc.select(\\\".pos.dpos\\\");\\n\\n\\t\\tif(elements.size() > 0) {\\n\\t\\t\\twordInfo.setType(WordInfo.getTypeShort(elements.get(0).html()));\\n//\\t\\t\\tif (wordInfo.getTypeShort().equals(\\\"\\\"))\\n//\\t\\t\\t\\tSystem.out.println(\\\" typemis: \\\"+wordInfo.getType());\\n\\t\\t}\\n\\n\\t\\t// Pronoun\\n\\t\\telements = doc.select(\\\".ipa.dipa\\\");\\n\\n\\t\\tif (elements.size() > 0)\\n\\t\\t\\twordInfo.setAPI(\\\"/\\\"+elements.get(0).html()+\\\"/\\\");\\n\\n\\t\\t// Trans\\n\\t\\telements = doc.select(\\\".trans.dtrans\\\");\\n\\n\\t\\tif (elements.size() > 0)\\n\\t\\t\\twordInfo.setTrans(elements.get(0).html());\\n\\n\\t\\tSystem.out.println(\\\" found\\\");\\n\\t\\treturn wordInfo;\\n\\t}\",\n \"List findByFilterText(Set<String> words, boolean justIds);\",\n \"private void find(char[] m, String message, Trie cur, Trie root, int index, List<String> results) {\\n // Base case 1. No match with any dictionary word. if cur == null -> no match ; return\\n if (cur == null) {\\n return;\\n }\\n // Base case 2. if out of bounds, check previously collected word and return\\n if (index == message.length()) {\\n // result only in case matches word\\n if (cur.word != null) {\\n results.add(new String(m));\\n }\\n return;\\n }\\n char c = message.charAt(index);\\n if (c == SPACE) {\\n // matches word or character 'e'\\n // check if matches word from dictionary\\n if (cur.word != null) {\\n m[index] = SPACE;\\n // if space - start collecting new word from beginning of Trie\\n find(m, message, root, root, index + 1, results);\\n }\\n // otherwise ' ' -> 'e'\\n c = 'e';\\n }\\n // considered non-space character (backtracking)\\n m[index] = c;\\n // get next element from try\\n Trie next = cur.get(c);\\n find(m, message, next, root, index + 1, results);\\n }\",\n \"public boolean search(String word)\\n {\\n return true;\\n }\",\n \"public boolean search(String word) {\\n TrieNode n = root;\\n for(char c : word.toCharArray()) {\\n if(n.children[c]==null)\\n return false;\\n n = n.children[c];\\n }\\n if(n.isWord)\\n return true;\\n return false;\\n }\",\n \"private List<SearchWord> getSearchWords(Long lastUpdateTime) {\\n return new ArrayList<>();\\n }\",\n \"public void IndexADocument(String docno, String content) throws IOException {\\n\\t\\tdocid++;\\n\\t\\tdoc2docid.put(docno, docid);\\n\\t\\tdocid2doc.put(docid, docno);\\n\\n\\t\\t// Insert every term in this doc into docid2map\\n\\t\\tString[] terms = content.trim().split(\\\" \\\");\\n\\t\\tMap<Integer, Integer> docTerm = new HashMap<>();\\n\\t\\tint thisTermid;\\n\\t\\tfor(String term: terms){\\n\\t\\t\\t// get termid\\n\\t\\t\\tif(term2termid.get(term)!=null) thisTermid = term2termid.get(term);\\n\\t\\t\\telse{\\n\\t\\t\\t\\tthisTermid = ++termid;\\n\\t\\t\\t\\tterm2termid.put(term, thisTermid);\\n\\t\\t\\t}\\n\\t\\t\\tdocTerm.put(thisTermid, docTerm.getOrDefault(thisTermid, 0)+1);\\n\\t\\t\\t// Merge this term's information into termid2map\\n\\t\\t\\tMap<Integer, Integer> temp = termid2map.getOrDefault(thisTermid, new HashMap());\\n\\t\\t\\ttemp.put(docid, temp.getOrDefault(docid, 0)+1);\\n\\t\\t\\ttermid2map.put(thisTermid, temp);\\n\\t\\t\\ttermid2fre.put(thisTermid, termid2fre.getOrDefault(thisTermid, 0)+1);\\n\\t\\t}\\n\\t\\tdocid2map.put(docid, docTerm);\\n\\n//\\t\\t// Merge all the terms' information into termid2map\\n//\\t\\tfor(Long tid: docTerm.keySet()){\\n//\\t\\t\\tMap<Long, Long> temp = termid2map.getOrDefault(tid, new HashMap());\\n//\\t\\t\\ttemp.put(docid,docTerm.get(tid));\\n//\\t\\t\\ttermid2map.put(tid, temp);\\n//\\t\\t\\t// update this term's frequency\\n//\\t\\t\\ttermid2fre.put(tid, termid2fre.getOrDefault(tid,0L)+docTerm.get(tid));\\n//\\t\\t}\\n\\n\\t\\t// When termid2map and docid2map is big enough, put it into disk\\n\\t\\tif(docid%blockSize==0){\\n\\t\\t\\tWritePostingFile();\\n\\t\\t\\tWriteDocFile();\\n\\t\\t}\\n\\t}\",\n \"@Test\\n\\tpublic void singleWordGrepTest3() throws Exception {\\n\\t\\t// word is 'mistress'\\n\\t\\tHashSet<String> grepFound = loadGrepResults(\\\"mistress\\\");\\n\\t\\tCollection<Page> index = queryTest.query(\\\"mistress\\\");\\n\\t\\tHashSet<String> indexFound = new HashSet<String>();\\n\\n\\t\\tfor (Page p : index)\\n\\t\\t\\tindexFound.add(p.getURL().getPath().toLowerCase());\\n\\t\\t\\n\\t\\t// tests set equality \\n\\t\\tassertEquals(indexFound, grepFound);\\n\\t}\",\n \"public Utwor search2(String query) {\\n for (Utwor utwor : utwory) {\\n if (utwor.getTitle().equals(query)) {\\n return utwor;\\n }\\n }\\n return null;\\n }\",\n \"public ArrayList<AddressEntry> searchByNote(String text) {\\r\\n ArrayList<AddressEntry> textMatches = new ArrayList<AddressEntry>();\\r\\n text = text.toLowerCase();\\r\\n for (AddressEntry current : contacts) {\\r\\n String currentname = current.getNote().toLowerCase();\\r\\n if (currentname.contains(text)) {\\r\\n textMatches.add(current);\\r\\n }\\r\\n }\\r\\n return textMatches;\\r\\n }\",\n \"private String containingWord(String attribute, String word) {\\r\\n return \\\"contains(concat(' ',normalize-space(@\\\" + attribute + \\\"),' '),' \\\"\\r\\n + word + \\\" ')\\\";\\r\\n }\",\n \"private double countWordLocationScore(Page page, String[] queryWords) {\\n double score = 0;\\n boolean wasFound = false;\\n\\n for (String word : queryWords) {\\n int queryWordId = this.pb.getIdForWord(word);\\n for (int i = 0; i < page.getWords().size(); i++) {\\n if (page.getWords().get(i) == queryWordId) {\\n score += i;\\n wasFound = true;\\n break;\\n }\\n }\\n\\n if (!wasFound) {\\n score += 100000;\\n } else {\\n wasFound = false;\\n }\\n }\\n return score;\\n }\",\n \"List<Integer> wordFinder(String text, String word) {\\n\\n List<Integer> indexes = new ArrayList<Integer>();\\n String wordProper = \\\" \\\" + word + \\\" \\\";\\n\\n int index = 0;\\n\\n while (index != -1) {\\n\\n index = text.indexOf(wordProper, index);\\n\\n if (index != -1) {\\n indexes.add(index);\\n index++;\\n }\\n }\\n\\n return indexes;\\n }\",\n \"List<DataTerm> search(String searchTerm);\",\n \"private @Nullable static String getQueryForWords(@NonNull List<String> words) {\\r\\n int numberOfWords = words.size();\\r\\n if(numberOfWords == 0) {\\r\\n return null;\\r\\n }\\r\\n\\r\\n String tableName = getTable(words.get(0));\\r\\n\\r\\n if(tableName == null) {\\r\\n return null;\\r\\n }\\r\\n\\r\\n String query = \\\"select * from \\\"+tableName+\\\" where\\\";\\r\\n\\r\\n int ctr = 0;\\r\\n for (String word:words) {\\r\\n query += \\\" word like '\\\"+word+\\\"'\\\";\\r\\n ctr++;\\r\\n if(ctr < numberOfWords) {\\r\\n query += \\\" OR\\\";\\r\\n }\\r\\n }\\r\\n\\r\\n return query;\\r\\n }\",\n \"public static void main (String[] args) {\\r\\n\\t\\tfindWords(sentence);\\r\\n\\t}\",\n \"public boolean search(String word) {\\n char [] words=word.toCharArray();\\n CharTree t=root;\\n for (char c : words) {\\n t=t.next[c-97];\\n if(t==null)return false;\\n }\\n if (!t.isend)return false;\\n return true;\\n }\",\n \"public ArrayList<String> determineSearchedWords(String userCommand) {\\n\\t\\tif (userCommand == null || userCommand.equals(\\\"\\\")) {\\n\\t\\t\\tlogger.log(Level.WARNING, Global.MESSAGE_ILLEGAL_ARGUMENTS);\\n\\t\\t\\treturn null;\\n\\t\\t}\\n\\n\\t\\tString userCommandWithoutCommandType = removeCommandType(userCommand);\\n\\n\\t\\tArrayList<String> searchedWords = new ArrayList<String>();\\n\\t\\tPattern pattern = Pattern.compile(\\\"[^\\\\\\\\s\\\\\\\"']+|\\\\\\\"([^\\\\\\\"]*)\\\\\\\"\\\");\\n\\t\\tMatcher matcher = pattern.matcher(userCommandWithoutCommandType);\\n\\n\\t\\twhile (matcher.find()) {\\n\\t\\t\\tif (matcher.group(1) != null) {\\n\\t\\t\\t\\tsearchedWords.add(matcher.group(1)); // Phrase in double quotes\\n\\t\\t\\t} else {\\n\\t\\t\\t\\tsearchedWords.add(matcher.group()); // Single word\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\treturn searchedWords;\\n\\t}\",\n \"private ArrayList<String> matchingWords(String word){\\n\\t\\tArrayList<String> list = new ArrayList<String>();\\n\\t\\tfor(int i=0; i<words.size();i++){\\n\\t\\t\\tif(oneCharOff(word,words.get(i))){\\n\\t\\t\\t\\tlist.add(words.get(i));\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\treturn list;\\n\\t}\",\n \"public static void textQueries(List<String> sentences, List<String> queries) {\\n // Write your code here\\n for(String q: queries){\\n boolean a = false;\\n int i=0;\\n for(String s: sentences){\\n if(Arrays.asList(s.split(\\\" \\\")).containsAll(Arrays.asList(q.split(\\\" \\\")))){\\n System.out.print(i+\\\" \\\");\\n a = true;\\n }\\n i++;\\n }\\n if(!a)\\n System.out.println(-1);\\n else\\n System.out.println(\\\"\\\");\\n }\\n \\n }\",\n \"boolean hasWord();\",\n \"SList oddWords();\",\n \"private long getTweets(String search, String geocode, Configuration auth) {\\r\\n TwitterFactory tf = new TwitterFactory(auth);\\r\\n Twitter twitter = tf.getInstance();\\r\\n \\r\\n try {\\r\\n Query query = new Query(search + \\\" \\\" + geocode);\\r\\n query.setSinceId(starttime);\\r\\n QueryResult result;\\r\\n \\r\\n for (int i = 0; i < blocks; i++) {\\r\\n if (Abort.getInstance().abort()) {\\r\\n return -1;\\r\\n }\\r\\n \\r\\n result = twitter.search(query);\\r\\n \\r\\n synchronized (this) {\\r\\n if (!tweets.containsKey(search)) {\\r\\n tweets.put(search, new HashSet());\\r\\n }\\r\\n tweets.get(search).addAll(result.getTweets());\\r\\n }\\r\\n \\r\\n //updateCommon(result.getTweets());\\r\\n //searched.add(search.toLowerCase());\\r\\n query.setSinceId(starttime + i * blocks15);\\r\\n }\\r\\n } catch (TwitterException te) {\\r\\n System.out.println(\\\"Failed to search tweets: \\\" + te);\\r\\n System.out.println(\\\"\\\\nRetry at: \\\" + \\r\\n (new Date(te.getRateLimitStatus()\\r\\n .getResetTimeInSeconds() * 1000L)));\\r\\n return te.getRateLimitStatus().getSecondsUntilReset() * 1000L;\\r\\n }\\r\\n return 0;\\r\\n }\",\n \"public static List<String> query_intersect(List<String> queryWords) throws IOException {\\n\\t\\tif (!initialized) initialize();\\n\\t\\tList<PostingList> pls = new ArrayList<PostingList> ();\\n\\t\\tfor (String queryWord : queryWords) {\\n\\t\\t\\tqueryWord = queryWord.toLowerCase();\\n\\t\\t\\tif (!termDict.containsKey(queryWord)) {\\n\\t\\t\\t\\tpls.clear();\\n\\t\\t\\t\\tbreak;\\n\\t\\t\\t}\\n\\t\\t\\tPostingList pl = readPosting(fc, termDict.get(queryWord));\\n\\t\\t\\tif (pl == null) {\\n\\t\\t\\t\\tpls.clear();\\n\\t\\t\\t\\tbreak;\\n\\t\\t\\t}\\n\\t\\t\\tpls.add(readPosting(fc, termDict.get(queryWord)));\\n\\t\\t}\\n\\t\\tCollections.sort(pls, new Comparator<PostingList>(){\\n\\t\\t public int compare(PostingList p1, PostingList p2) {\\n\\t\\t return p1.size() - p2.size(); // assumes you want biggest to smallest\\n\\t\\t }\\n\\t\\t});\\n\\t\\tif (pls.size() == 0) {\\n\\t\\t\\treturn null;\\n\\t\\t} else {\\n\\t\\t\\tList<Integer> current = pls.get(0).getList();\\n\\t\\t\\tfor (int i = 1; i < pls.size(); i++) {\\n\\t\\t\\t\\tList<Integer> toBeAdd = pls.get(i).getList();\\n\\t\\t\\t\\tcurrent = intersect(current, toBeAdd);\\n\\t\\t\\t}\\n\\t\\t\\tif (current.size() == 0) {\\n\\t\\t\\t\\treturn null;\\n\\t\\t\\t} else {\\n\\t\\t\\t\\tList<String> result = new ArrayList<String>();\\n\\t\\t\\t\\tfor (int docId : current) {\\n\\t\\t\\t\\t\\tresult.add(docDict.get(docId));\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\treturn result;\\n\\t\\t\\t}\\n\\t\\t}\\n\\t}\",\n \"@GetMapping(\\\"/search\\\")\\n\\tpublic String search(@RequestParam(name = \\\"word\\\") String word, Model model) {\\n\\t\\tList<Note> notes = noteRepository.search(\\\"%\\\" + word + \\\"%\\\");\\n\\t\\tmodel.addAttribute(\\\"notes\\\", notes);\\n\\t\\treturn \\\"notes\\\";\\n\\t}\",\n \"private WordRecord lookUp(String word)\\n {\\n int contains = 0;\\n boolean check = false;\\n //loops through concordance\\n for(int i = 0; i < this.concordance.size();i++)\\n {\\n //checks to see if the words are equal\\n if(word.equalsIgnoreCase(this.concordance.get(i).getWord()))\\n {\\n //gets location of what position the word is true\\n contains = i;\\n check = true;\\n }\\n \\n }\\n //checks to see if it was found in concordance\\n if(check)\\n return this.concordance.get(contains);\\n \\n return null;\\n }\",\n \"WordBean getWord(String word);\",\n \"private void findMatches(String key, String path, boolean caseSensitive, boolean fileName) {\\n\\t\\tfor (String word : document) {\\n\\t\\t\\tif (contains(key, word, caseSensitive)) {\\n\\t\\t\\t\\tif (fileName) {\\n\\t\\t\\t\\t\\tSystem.out.println(path);\\n\\t\\t\\t\\t\\tbreak;\\n\\t\\t\\t\\t} else {\\n\\t\\t\\t\\t\\tSystem.out.println(word);\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t}\\n\\t}\",\n \"public boolean search(String word) {\\n TrieNode tn = root;\\n int len = word.length();\\n for(int i=0; i<len; i++){\\n char c = word.charAt(i);\\n TrieNode temp = tn.hm.get(c);\\n if(temp == null) return false;\\n tn = temp;\\n }\\n return tn.flag;\\n }\",\n \"public String showSearchSynonym(String searchWord, ArrayList<String> words) {\\n StringBuilder stringBuilder = new StringBuilder(\\\"Your word \\\\\\\"\\\" + searchWord + \\\"\\\\\\\" has \\\" + words.size()\\n + (words.size() == 1 ? \\\" synonym:\\\\n\\\" : \\\" synonyms:\\\\n\\\"));\\n for (int i = 0; i < words.size(); i++) {\\n stringBuilder.append(words.get(i) + \\\"\\\\n\\\");\\n }\\n return stringBuilder.toString();\\n }\",\n \"public void makeWord(String inputText,String pageId,createIndex createindex,String contentType)\\n {\\n int length,i;\\n char c;\\n boolean linkFound=false;\\n int count1,count2,count3,count4,count5,count6,count7,count8,count9;\\n\\n\\n\\n StringBuilder word=new StringBuilder();\\n // String finalWord=null,stemmedWord=null;\\n docId=Integer.parseInt(pageId.trim());\\n\\n ci=createindex;\\n // Stemmer st=new Stemmer();\\n //createIndex createindex=new createIndex();\\n\\n length=inputText.length();\\n\\n for(i=0;i<length;i++)\\n {\\n c=inputText.charAt(i);\\n if(c<123 && c>96)\\n {\\n word.append(c);\\n }\\n\\n else if(c=='{')\\n {\\n if ( i+9 < length && inputText.substring(i+1,i+9).equals(\\\"{infobox\\\") )\\n {\\n\\n StringBuilder infoboxString = new StringBuilder();\\n\\n count1 = 0;\\n for ( ; i < length ; i++ ) {\\n\\n c = inputText.charAt(i);\\n infoboxString.append(c);\\n if ( c == '{') {\\n count1++;\\n }\\n else if ( c == '}') {\\n count1--;\\n }\\n if ( count1 == 0 || (c == '=' && i+1 < length && inputText.charAt(i+1) == '=')) {\\n if ( c == '=' ) {infoboxString.deleteCharAt(infoboxString.length()-1);}\\n break;\\n }\\n }\\n\\n processInfobox(infoboxString);\\n\\n }\\n\\n else if ( i+8 < length && inputText.substring(i+1,i+8).equals(\\\"{geobox\\\") )\\n {\\n\\n StringBuilder geoboxString = new StringBuilder();\\n\\n count2 = 0;\\n for ( ; i < length ; i++ ) {\\n\\n c = inputText.charAt(i);\\n geoboxString.append(c);\\n if ( c == '{') {\\n count2++;\\n }\\n else if ( c == '}') {\\n count2--;\\n }\\n if ( count2 == 0 || (c == '=' && i+1 < length && inputText.charAt(i+1) == '=')) {\\n if ( c == '=' ) {geoboxString.deleteCharAt(geoboxString.length()-1);}\\n break;\\n }\\n }\\n\\n // processGeobox(geoboxString);\\n }\\n\\n else if ( i+6 < length && inputText.substring(i+1,i+6).equals(\\\"{cite\\\") )\\n {\\n\\n /*\\n * Citations are to be removed.\\n */\\n\\n count3 = 0;\\n for ( ; i < length ; i++ ) {\\n\\n c = inputText.charAt(i);\\n if ( c == '{') {\\n count3++;\\n }\\n else if ( c == '}') {\\n count3--;\\n }\\n if ( count3 == 0 || (c == '=' && i+1 < length && inputText.charAt(i+1) == '=')) {\\n break;\\n }\\n }\\n\\n }\\n\\n else if ( i+4 < length && inputText.substring(i+1,i+4).equals(\\\"{gr\\\") )\\n {\\n\\n /*\\n * {{GR .. to be removed\\n */\\n\\n count4 = 0;\\n for ( ; i < length ; i++ ) {\\n\\n c = inputText.charAt(i);\\n if ( c == '{') {\\n count4++;\\n }\\n else if ( c == '}') {\\n count4--;\\n }\\n if ( count4 == 0 || (c == '=' && i+1 < length && inputText.charAt(i+1) == '=')) {\\n break;\\n }\\n }\\n\\n }\\n else if ( i+7 < length && inputText.substring(i+1,i+7).equals(\\\"{coord\\\") )\\n {\\n\\n /**\\n * Coords to be removed\\n */\\n\\n count5 = 0;\\n for ( ; i < length ; i++ ) {\\n\\n c = inputText.charAt(i);\\n\\n if ( c == '{') {\\n count5++;\\n }\\n else if ( c == '}') {\\n count5--;\\n }\\n if ( count5 == 0 || (c == '=' && i+1 < length && inputText.charAt(i+1) == '=')) {\\n break;\\n }\\n }\\n\\n }\\n\\n //System.out.println(\\\"process infobox\\\");\\n }\\n else if(c=='[')\\n {\\n // System.out.println(\\\"process square brace\\\");\\n\\n if ( i+11 < length && inputText.substring(i+1,i+11).equalsIgnoreCase(\\\"[category:\\\"))\\n {\\n\\n StringBuilder categoryString = new StringBuilder();\\n\\n count6 = 0;\\n for ( ; i < length ; i++ ) {\\n\\n c = inputText.charAt(i);\\n categoryString.append(c);\\n if ( c == '[') {\\n count6++;\\n }\\n else if ( c == ']') {\\n count6--;\\n }\\n if ( count6 == 0 || (c == '=' && i+1 < length && inputText.charAt(i+1) == '=')) {\\n if ( c == '=' ) {categoryString.deleteCharAt(categoryString.length()-1);}\\n break;\\n }\\n }\\n\\n // System.out.println(\\\"category string=\\\"+categoryString.toString());\\n processCategories(categoryString);\\n\\n }\\n else if ( i+8 < length && inputText.substring(i+1,i+8).equalsIgnoreCase(\\\"[image:\\\") ) {\\n\\n /**\\n * Images to be removed\\n */\\n\\n count7 = 0;\\n for ( ; i < length ; i++ ) {\\n\\n c = inputText.charAt(i);\\n if ( c == '[') {\\n count7++;\\n }\\n else if ( c == ']') {\\n count7--;\\n }\\n if ( count7 == 0 || (c == '=' && i+1 < length && inputText.charAt(i+1) == '=')) {\\n break;\\n }\\n }\\n\\n }\\n else if ( i+7 < length && inputText.substring(i+1,i+7).equalsIgnoreCase(\\\"[file:\\\") ) {\\n\\n /**\\n * File to be removed\\n */\\n\\n count8 = 0;\\n for ( ; i < length ; i++ ) {\\n\\n c = inputText.charAt(i);\\n\\n if ( c == '[') {\\n count8++;\\n }\\n else if ( c == ']') {\\n count8--;\\n }\\n if ( count8 == 0 || (c == '=' && i+1 < length && inputText.charAt(i+1) == '=')) {\\n break;\\n }\\n }\\n\\n }\\n\\n }\\n else if(c=='<')\\n {\\n //System.out.println(\\\"Process < >\\\");\\n\\n if ( i+4 < length && inputText.substring(i+1,i+4).equalsIgnoreCase(\\\"!--\\\") ) {\\n\\n /**\\n * Comments to be removed\\n */\\n\\n int locationClose = inputText.indexOf(\\\"-->\\\" , i+1);\\n if ( locationClose == -1 || locationClose+2 > length ) {\\n i = length-1;\\n }\\n else {\\n i = locationClose+2;\\n }\\n\\n }\\n else if ( i+5 < length && inputText.substring(i+1,i+5).equalsIgnoreCase(\\\"ref>\\\") ) {\\n\\n /**\\n * References to be removed\\n */\\n int locationClose = inputText.indexOf(\\\"</ref>\\\" , i+1);\\n if ( locationClose == -1 || locationClose+5 > length ) {\\n i = length-1;\\n }\\n else {\\n i = locationClose+5;\\n }\\n\\n }\\n else if ( i+8 < length && inputText.substring(i+1,i+8).equalsIgnoreCase(\\\"gallery\\\") ) {\\n\\n /**\\n * Gallery to be removed\\n */\\n int locationClose = inputText.indexOf(\\\"</gallery>\\\" , i+1);\\n if ( locationClose == -1 || locationClose+9 > length) {\\n i = length-1;\\n }\\n else {\\n i = locationClose+9;\\n }\\n }\\n\\n }\\n else if ( c == '=' && i+1 < length && inputText.charAt(i+1) == '=')\\n {\\n\\n linkFound = false;\\n i+=2;\\n while ( i < length && ((c = inputText.charAt(i)) == ' ' || (c = inputText.charAt(i)) == '\\\\t') )\\n {\\n i++;\\n }\\n\\n if ( i+14 < length && inputText.substring(i , i+14 ).equals(\\\"external links\\\") )\\n {\\n //System.out.println(\\\"External link found\\\");\\n linkFound = true;\\n i+= 14;\\n }\\n\\n }\\n else if ( c == '*' && linkFound == true )\\n {\\n\\n //System.out.println(\\\"Link found\\\");\\n count9 = 0;\\n boolean spaceParsed = false;\\n StringBuilder link = new StringBuilder();\\n while ( count9 != 2 && i < length )\\n {\\n c = inputText.charAt(i);\\n if ( c == '[' || c == ']' )\\n {\\n count9++;\\n }\\n if ( count9 == 1 && spaceParsed == true)\\n {\\n link.append(c);\\n }\\n else if ( count9 != 0 && spaceParsed == false && c == ' ')\\n {\\n spaceParsed = true;\\n }\\n i++;\\n }\\n\\n StringBuilder linkWord = new StringBuilder();\\n for ( int j = 0 ; j < link.length() ; j++ )\\n {\\n char currentCharTemp = link.charAt(j);\\n if ( (int)currentCharTemp >= 'a' && (int)currentCharTemp <= 'z' )\\n {\\n linkWord.append(currentCharTemp);\\n }\\n else\\n {\\n\\n // System.out.println(\\\"link : \\\" + linkWord.toString());\\n processLink(linkWord);\\n linkWord.setLength(0);\\n }\\n }\\n if ( linkWord.length() > 1 )\\n {\\n //System.out.println(\\\"link : \\\" + linkWord.toString());\\n processLink(linkWord);\\n linkWord.setLength(0);\\n }\\n\\n }\\n else\\n {\\n if(word.length()>1)\\n filterAndAddWord(word,contentType);\\n\\n word.setLength(0);\\n }\\n }\\n\\n\\n if(word.length()>1)\\n filterAndAddWord(word,contentType);\\n\\n word.setLength(0);\\n /*\\n if(word.length()>0)\\n {\\n finalWord=new String(word);\\n if(!(checkStopword(finalWord)))\\n {\\n st.add(finalWord.toCharArray(),finalWord.length());\\n stemmedWord=st.stem();\\n\\n createindex.addToTreeSet(stemmedWord,docId);\\n\\n }\\n\\n word.delete(0, word.length());\\n } */\\n\\n }\",\n \"public ArrayList<SearchResult> partialSearch(String[] searchWords) {\\n\\t\\tArrayList<SearchResult> words = new ArrayList<>();\\n\\t\\tHashMap<String, SearchResult> resultMap = new HashMap<>();\\n\\t\\tfor (String word : searchWords) {\\n\\t\\t\\tfor (String key : index.tailMap(word, true).navigableKeySet()) {\\n\\t\\t\\t\\tif (key.startsWith(word)) {\\n\\t\\t\\t\\t\\twordSearch(key, resultMap, words);\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\telse {\\n\\t\\t\\t\\t\\tbreak;\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\t\\n\\t\\tCollections.sort(words);\\n\\t\\treturn words;\\n\\t}\",\n \"public FindCommand(WordContainsKeywordsPredicate predicate) {\\n this.predicate = predicate;\\n }\",\n \"private static Query computeBooleanQueryNP(String textQuery){\\n\\t\\tBooleanQuery query = new BooleanQuery();\\n\\n\\t\\tHmmDecoder mPosTagger = null;\\n\\t\\tTokenizerFactory mTokenizerFactory = null;\\n\\t\\tPhraseChunker pChunker = new PhraseChunker(mPosTagger,mTokenizerFactory);\\n\\t\\tArrayList<String> pchuncker = new ArrayList<String>();\\n\\n\\t\\tpchuncker = pChunker.getCHunkNounPhrases(textQuery.toLowerCase());\\n\\n\\t\\tfor (int k = 0; k<= pchuncker.size()-1;k++ ){\\n\\t\\t\\tString wordInList = ((String) pchuncker.get(k));\\n\\t\\t\\twordInList = wordInList.toLowerCase().replaceAll(\\\"-\\\",\\\" \\\");\\n\\t\\t\\tString [] wordInListSplit = wordInList.split(\\\" \\\");\\n\\t\\t\\tfor (String word: wordInListSplit){\\n\\n\\t\\t\\t\\tquery.add(new TermQuery(new Term(\\\"content\\\", word)), Occur.SHOULD );\\n\\t\\t\\t}\\n\\n\\t\\t}\\n\\n\\t\\t/* String[] tQuery = textQuery.split(\\\" \\\");\\n\\t\\t for(String s: tQuery )\\n\\t\\t\\t query.add(new TermQuery(new Term(\\\"text\\\", s)), Occur.SHOULD);*/\\n\\n\\t\\treturn query;\\n\\t}\",\n \"public byte filter(Manager m, SearchRequest q, ResultSet rs, int DocAtNumber, int DocNo)\\n\\t{\\t\\t\\n\\t\\tString originalQuery = q.getOriginalQuery();\\n\\t\\t//highlight query terms only for the queries, \\n\\t\\t//which are not about finding related documents\\n\\t\\t//this check may be removed, because the preparation of the \\n\\t\\t//query terms for highlighting takes into account\\n\\t\\t//the related: operator\\n\\t\\tboolean highlightQueryTerms = true;\\n\\t\\tif (originalQuery.matches(\\\"\\\\\\\\brelated:\\\\\\\\d+\\\\\\\\b\\\") || //check if the query uses the related: operator \\n\\t\\t\\t!enableQueryTermsHighlight || //check if the highlighting of terms is enabled\\n\\t\\t\\thighlight.pattern().equals(\\\"(\\\\\\\\b)()(\\\\\\\\b)\\\")) //check if there are no query terms to highlight\\n\\t\\t\\thighlightQueryTerms = false;\\n\\t\\t\\n\\t\\tString[] qTerms = q.getOriginalQuery().replaceAll(\\\" \\\\\\\\w+\\\\\\\\p{Punct}\\\\\\\\w+ \\\",\\\" \\\").toLowerCase().split(\\\" \\\");\\n\\t\\t\\n\\t\\tString[] metadata = null;\\n\\t\\tint tmpSentence;\\n\\t\\tdouble tmpScore;\\n\\t\\tsynchronized(metaCache) {\\n\\t\\t\\ttry {\\n\\t\\t\\t\\tInteger DocNoObject = new Integer(DocNo);\\n\\t\\t\\t\\tif (metaCache.containsKey(DocNoObject))\\n\\t\\t\\t\\t\\t\\tmetadata = (String[]) metaCache.get(DocNoObject);\\n\\t\\t\\t\\telse {\\n\\t\\t\\t\\t\\tmetadata = metaIndex.getItems(keys, DocNo);\\n\\t\\t\\t\\t\\tmetaCache.put(DocNoObject,metadata);\\n\\t\\t\\t\\t}\\n\\t\\t\\t} catch(IOException ioe) {} \\n\\t\\t}\\n\\t\\n\\t\\tif (show_snippet)\\n\\t\\t{\\n\\t\\t\\tString extract = metadata[1];\\n\\t\\t\\tString[] sentences = sentencePattern.split(extract, 50); //use 50 sentences at most\\n\\t\\t\\tdouble[] sentenceScores = new double[sentences.length]; \\n\\t\\t\\tint frsSentence = -1;\\n\\t\\t\\tint sndSentence = -1;\\n\\t\\t\\tint top1Sentence = 0;\\n\\t\\t\\tint top2Sentence = 0;\\n\\t\\t\\tdouble max1Score = -1;\\n\\t\\t\\tdouble max2Score = 0;\\n\\t\\t\\tfinal int qTermsLength = qTerms.length;\\n\\t\\t\\tfor (int i=0; i<qTermsLength; i++) {\\n\\t\\t\\t\\tqTerms[i] = removeEndings.matcher(qTerms[i]).replaceAll(\\\"\\\");\\n\\t\\t\\t}\\n\\t\\t\\tString lowerCaseSentence;\\n\\t\\t\\tint sentenceLength;\\n\\t\\t\\tfinal int sentencesLength = sentences.length;\\n\\n\\t\\t\\tfor (int i=0; i<sentencesLength; i++) {\\n\\t\\t\\t\\t\\n\\t\\t\\t\\tlowerCaseSentence = sentences[i].toLowerCase();\\n\\t\\t\\t\\tsentenceLength=sentences[i].length();\\n\\t\\t\\t\\tif (sentenceLength < 20 || sentenceLength > 250) {\\n\\t\\t\\t\\t\\tfor (int j=0; j<qTermsLength; j++) {\\n\\t\\t\\t\\t\\t\\tif (lowerCaseSentence.indexOf(qTerms[j])>=0) {\\n\\t\\t\\t\\t\\t\\t\\tsentenceScores[i]+=1.0d + sentenceLength / (20.0d + sentenceLength);\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t} else {\\n\\t\\t\\t\\t\\tfor (int j=0; j<qTermsLength; j++) {\\n\\t\\t\\t\\t\\t\\tif (lowerCaseSentence.indexOf(qTerms[j])>=0) {\\n\\t\\t\\t\\t\\t\\t\\tsentenceScores[i]+=qTerms[j].length() + sentenceLength / (1.0d + sentenceLength);\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t}\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t//do your best to get at least a second sentence for the snippet, \\n\\t\\t\\t\\t//after having found the first one\\n\\t\\t\\t\\tif (frsSentence > -1 && sndSentence == -1 && sentenceLength > 5) {\\n\\t\\t\\t\\t\\tsndSentence = i;\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\t//do your best to get at least one sentence for the snippet\\n\\t\\t\\t\\tif (frsSentence == -1 && sentenceLength > 5) { \\n\\t\\t\\t\\t\\tfrsSentence = i;\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\tif (max2Score < sentenceScores[i]) {\\n\\t\\t\\t\\t\\tmax2Score = sentenceScores[i];\\n\\t\\t\\t\\t\\ttop2Sentence = i;\\n\\t\\t\\t\\t\\t//logger.debug(\\\"top 2 sentence is \\\" + i);\\n\\t\\t\\t\\t\\tif (max2Score > max1Score) {\\n\\t\\t\\t\\t\\t\\ttmpScore = max1Score; max1Score = max2Score; max2Score = tmpScore;\\n\\t\\t\\t\\t\\t\\ttmpSentence = top1Sentence; top1Sentence = top2Sentence; top2Sentence = tmpSentence;\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t}\\n\\t\\t\\tint lastIndexOfSpace = -1;\\n\\t\\t\\tString sentence=\\\"\\\";\\n\\t\\t\\tString secondSentence=\\\"\\\";\\n\\t\\t\\tString snippet = \\\"\\\";\\n\\t\\t\\tif (max1Score == -1) {\\n\\t\\t\\t\\tif (frsSentence>=0) {\\n\\t\\t\\t\\t\\tsentence = sentences[frsSentence];\\n\\t\\t\\t\\t\\tif (sentence.length() > 100) {\\n\\t\\t\\t\\t\\t\\tlastIndexOfSpace = sentence.substring(0, 100).lastIndexOf(\\\" \\\");\\n\\t\\t\\t\\t\\t\\tsentence = sentence.substring(0, lastIndexOfSpace > 0 ? lastIndexOfSpace : 100);\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\n\\t\\t\\t\\tif (sndSentence>=0) {\\n\\t\\t\\t\\t\\tsecondSentence = sentences[sndSentence];\\n\\t\\t\\t\\t\\tif (secondSentence.length() > 100) {\\n\\t\\t\\t\\t\\t\\tlastIndexOfSpace = secondSentence.substring(0, 100).lastIndexOf(\\\" \\\");\\n\\t\\t\\t\\t\\t\\tsecondSentence = secondSentence.substring(0, lastIndexOfSpace>0 ? lastIndexOfSpace : 100);\\n\\t\\t\\t\\t\\t}\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\n\\t\\t\\t\\tif (frsSentence >=0 && sndSentence >= 0) \\n\\t\\t\\t\\t\\tsnippet = sentence.trim() + \\\"...\\\" + secondSentence.trim();\\n\\t\\t\\t\\telse if (frsSentence >= 0 && sndSentence<0) \\n\\t\\t\\t\\t\\tsnippet = sentence.trim();\\n\\t\\t\\t\\t\\n\\t\\t\\t} else if (sentences[top1Sentence].length()<100 && top1Sentence!=top2Sentence) {\\n\\t\\t\\t\\tsentence = sentences[top1Sentence];\\n\\t\\t\\t\\tif (sentence.length() > 100) {\\n\\t\\t\\t\\t\\tlastIndexOfSpace = sentence.substring(0, 100).lastIndexOf(\\\" \\\");\\n\\t\\t\\t\\t\\tsentence = sentence.substring(0, lastIndexOfSpace > 0 ? lastIndexOfSpace : 100);\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\tsecondSentence = sentences[top2Sentence];\\n\\t\\t\\t\\tif (secondSentence.length() > 100) {\\n\\t\\t\\t\\t\\tlastIndexOfSpace = secondSentence.substring(0, 100).lastIndexOf(\\\" \\\");\\n\\t\\t\\t\\t\\tsecondSentence = secondSentence.substring(0, lastIndexOfSpace>0 ? lastIndexOfSpace : 100);\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\tsnippet = sentence.trim() + \\\"...\\\" + secondSentence.trim();\\n\\t\\t\\t} else {\\n\\t\\t\\t\\tsentence = sentences[top1Sentence];\\n\\t\\t\\t\\tif (sentence.length()>200) {\\n\\t\\t\\t\\t\\tlastIndexOfSpace = sentence.substring(0, 200).lastIndexOf(\\\" \\\");\\n\\t\\t\\t\\t\\tsentence = sentence.substring(0, lastIndexOfSpace > 0 ? lastIndexOfSpace : 200);\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\tsnippet = sentence.trim();\\n\\t\\t\\t}\\n\\t\\t\\t\\n\\t\\t\\t//checking and removing any control characters\\n\\t\\t\\tcontrolNonVisibleCharactersMatcher.reset(snippet);\\n\\t\\t\\tsnippet = controlNonVisibleCharactersMatcher.replaceAll(\\\"\\\");\\n\\t\\t\\t\\n\\t\\t\\t//String escapedSnippet = StringEscapeUtils.escapeHtml(snippet);\\n\\t\\t\\t//if (highlightQueryTerms)\\n\\t\\t\\t//\\tescapedSnippet = highlight.matcher(escapedSnippet).replaceAll(\\\"$1<b>$2</b>$3\\\");\\n\\t\\t\\tif (highlightQueryTerms)\\n\\t\\t\\t\\tsnippet = highlight.matcher(snippet).replaceAll(\\\"$1<b>$2</b>$3\\\");\\n\\t\\t\\t//else \\n\\t\\t\\t//\\tsnippet = StringEscapeUtils.escapeHtml(snippet);\\n\\t\\t\\t\\n\\t\\t\\t//change by Vassilis, 20/09/2006\\n\\t\\t\\t//disabling the xml escaping in order to move the data into ![CDATA[ ]]\\n\\t\\t\\t//the code was:\\n\\t\\t\\t//rs.addMetaItem(\\\"snippet\\\", DocAtNumber, StringEscapeUtils.escapeXml(snippet));\\n\\t\\t\\t//and now it is:\\n\\t\\t\\t//snippet.replaceAll(\\\"[^\\\\\\\\u0009\\\\\\\\u000A\\\\\\\\u000D\\\\\\\\u0020-\\\\\\\\uD7FF\\\\\\\\uE000-\\\\\\\\uFFFD\\\\\\\\u10000-\\\\\\\\u10FFFF]\\\",\\\"\\\");\\n\\t\\t\\trs.addMetaItem(\\\"snippet\\\", DocAtNumber, snippet);\\n\\t\\t\\t\\n\\t\\t}\\n\\t\\tif (show_title)\\n\\t\\t{\\n\\t\\t\\tString title = metadata[2];\\n\\t\\t\\t\\n\\t\\t\\t//checking and removing any control characters\\n\\t\\t\\tcontrolNonVisibleCharactersMatcher.reset(title);\\n\\t\\t\\ttitle = controlNonVisibleCharactersMatcher.replaceAll(\\\"\\\");\\n\\t\\t\\ttitle = (highlightQueryTerms)\\n\\t\\t\\t\\t ? highlight.matcher(metadata[2]).replaceAll(\\\"$1<b>$2</b>$3\\\") \\n\\t\\t\\t\\t : metadata[2];\\n\\t\\t\\t\\n\\t\\t\\t\\n\\t\\t\\t//String escapedTitle = StringEscapeUtils.escapeHtml(metadata[2]);\\n\\t\\t\\t//String title = (highlightQueryTerms)\\n\\t\\t\\t//\\t\\t\\t ? highlight.matcher(escapedTitle).replaceAll(\\\"$1<b>$2</b>$3\\\") \\n\\t\\t\\t//\\t\\t\\t : escapedTitle;\\n\\t\\t\\t//String title = (highlightQueryTerms) \\n\\t\\t\\t//\\t\\t? highlight.matcher(metadata[2]).replaceAll(\\\"$1<b>$2</b>$3\\\") \\n\\t\\t\\t//\\t\\t: metadata[2];\\n\\n\\t\\t\\t//change by Vassilis, 20/09/2006\\n\\t\\t\\t//disabling the xml escaping in order to move the data into ![CDATA[ ]]\\n\\t\\t\\t//the code was:\\n\\t\\t\\t//rs.addMetaItem(\\\"title\\\", DocAtNumber, StringEscapeUtils.escapeXml(title));\\n\\t\\t\\t//and now is:\\n\\t\\t\\t//title.replaceAll(\\\"[^\\\\\\\\u0009\\\\\\\\u000A\\\\\\\\u000D\\\\\\\\u0020-\\\\\\\\uD7FF\\\\\\\\uE000-\\\\\\\\uFFFD\\\\\\\\u10000-\\\\\\\\u10FFFF]\\\",\\\"\\\");\\n\\t\\t\\trs.addMetaItem(\\\"title\\\", DocAtNumber, title);\\n\\t\\t\\t\\n\\t\\t}\\n\\t\\tif (!show_docid_early && show_docid)\\n\\t\\t{\\n\\t\\t\\trs.addMetaItem(\\\"docid\\\", DocAtNumber, docIndex.getDocumentNumber(DocNo));\\n\\t\\t}\\n\\t\\tif (!show_url_early && show_url)\\n\\t\\t{\\n\\n\\t\\t\\trs.addMetaItem(\\\"url\\\", DocAtNumber, StringEscapeUtils.escapeXml(metadata[0]));\\n\\t\\t}\\n\\t\\t\\n\\t\\treturn FILTER_OK;\\n\\t}\",\n \"@Test\\n\\tpublic void singleWordGrepTest2() throws Exception {\\n\\t\\t// word is 'crazy'\\n\\t\\tHashSet<String> grepFound = loadGrepResults(\\\"crazy\\\");\\n\\t\\tCollection<Page> index = queryTest.query(\\\"crazy\\\");\\n\\t\\tHashSet<String> indexFound = new HashSet<String>();\\n\\n\\t\\tfor (Page p : index)\\n\\t\\t\\tindexFound.add(p.getURL().getPath().toLowerCase());\\n\\t\\t\\n\\t\\t// tests set equality \\n\\t\\tassertEquals(indexFound, grepFound);\\n\\t}\",\n \"public String getSearchString() {\\r\\n return super.getSearchString();\\r\\n \\r\\n// String searchStr = \\\"\\\";\\r\\n// //put exact phrase at the very beginning\\r\\n// if(exactphrase != null && exactphrase.length() > 0)\\r\\n// {\\r\\n// searchStr += \\\"\\\\\\\"\\\" + exactphrase + \\\"\\\\\\\"\\\";\\r\\n// }\\r\\n//\\r\\n// String allwordsSearchStr = \\\"\\\";\\r\\n// if(allwords != null && allwords.length() > 0)\\r\\n// {\\r\\n// String [] words = allwords.split(\\\" \\\");\\r\\n// if(words.length > 0)\\r\\n// {\\r\\n// for(int i=0; i<words.length; i++)\\r\\n// {\\r\\n// allwordsSearchStr += \\\"+\\\" + words[i];\\r\\n// }\\r\\n// }\\r\\n// }\\r\\n//\\r\\n// String withoutwordsSearchStr = \\\"\\\";\\r\\n// if(withoutwords != null && withoutwords.length() > 0)\\r\\n// {\\r\\n// String [] words = withoutwords.split(\\\" \\\");\\r\\n// if(words.length > 0)\\r\\n// {\\r\\n// for(int i=0; i<words.length; i++)\\r\\n// {\\r\\n// withoutwordsSearchStr += \\\"+-\\\" + words[i];\\r\\n// }\\r\\n// }\\r\\n// }\\r\\n//\\r\\n// searchStr += allwordsSearchStr + withoutwordsSearchStr; //need to add other string\\r\\n// \\r\\n// String oneofwordsSearchStr = \\\"\\\";\\r\\n// if(oneofwords != null && oneofwords.length() > 0)\\r\\n// {\\r\\n// String [] words = oneofwords.split(\\\" \\\");\\r\\n// if(words.length > 0)\\r\\n// {\\r\\n// oneofwordsSearchStr = \\\"(\\\";\\r\\n// for(int i=0; i<words.length; i++)\\r\\n// {\\r\\n// oneofwordsSearchStr += words[i] + \\\" \\\";\\r\\n// }\\r\\n// oneofwordsSearchStr = oneofwordsSearchStr.trim();\\r\\n// oneofwordsSearchStr += \\\")\\\";\\r\\n// }\\r\\n// }\\r\\n// if(oneofwordsSearchStr.length() > 0)\\r\\n// {\\r\\n// searchStr += \\\"+\\\" + oneofwordsSearchStr;\\r\\n// }\\r\\n//\\r\\n// return searchStr;\\r\\n }\",\n \"public static void search(String word){\\n if(index.containsKey(word)){\\n System.out.println(\\\"word \\\" + word + \\\" displays in :\\\");\\n HashSet<String> list = index.get(word);\\n for(String str:list){\\n System.out.println(str);\\n }\\n }\\n else{\\n System.out.println(\\\"word \\\" + word + \\\" doesn't found!\\\");\\n }\\n }\",\n \"public abstract Set<String> getTerms(Document doc);\",\n \"@Override\\n public boolean search(final String word) {\\n final TrieNode p = searchNode(word);\\n if (p == null) {\\n return false;\\n } else {\\n return p.isEnd;\\n }\\n\\n }\",\n \"public void indexCreate()\\n {\\n try{\\n Directory dir = FSDirectory.open(Paths.get(\\\"indice/\\\"));\\n Analyzer analyzer = new StandardAnalyzer();\\n IndexWriterConfig iwc = new IndexWriterConfig(analyzer);\\n iwc.setOpenMode(OpenMode.CREATE);\\n IndexWriter writer = new IndexWriter(dir,iwc);\\n MongoConnection mongo = MongoConnection.getMongo();\\n mongo.OpenMongoClient();\\n DBCursor cursor = mongo.getTweets();\\n Document doc = null;\\n\\n while (cursor.hasNext()) {\\n DBObject cur = cursor.next();\\n if (cur.get(\\\"retweet\\\").toString().equals(\\\"false\\\")) {\\n doc = new Document();\\n doc.add(new StringField(\\\"id\\\", cur.get(\\\"_id\\\").toString(), Field.Store.YES));\\n doc.add(new TextField(\\\"text\\\", cur.get(\\\"text\\\").toString(), Field.Store.YES));\\n doc.add(new StringField(\\\"analysis\\\", cur.get(\\\"analysis\\\").toString(), Field.Store.YES));\\n //doc.add(new StringField(\\\"finalCountry\\\",cur.get(\\\"finalCountry\\\").toString(),Field.Store.YES));\\n doc.add(new StringField(\\\"userScreenName\\\", cur.get(\\\"userScreenName\\\").toString(), Field.Store.YES));\\n doc.add(new StringField(\\\"userFollowersCount\\\", cur.get(\\\"userFollowersCount\\\").toString(), Field.Store.YES));\\n doc.add(new StringField(\\\"favoriteCount\\\", cur.get(\\\"favoriteCount\\\").toString(), Field.Store.YES));\\n\\n if (writer.getConfig().getOpenMode() == OpenMode.CREATE) {\\n System.out.println(\\\"Indexando el tweet: \\\" + doc.get(\\\"text\\\") + \\\"\\\\n\\\");\\n writer.addDocument(doc);\\n System.out.println(doc);\\n } else {\\n System.out.println(\\\"Actualizando el tweet: \\\" + doc.get(\\\"text\\\") + \\\"\\\\n\\\");\\n writer.updateDocument(new Term(\\\"text\\\" + cur.get(\\\"text\\\")), doc);\\n System.out.println(doc);\\n }\\n }\\n }\\n cursor.close();\\n writer.close();\\n }\\n catch(IOException ioe){\\n System.out.println(\\\" Error en \\\"+ ioe.getClass() + \\\"\\\\n mensaje: \\\" + ioe.getMessage());\\n }\\n }\",\n \"public NavigableSet<Integer> findAllTextIndexes (String words,\\n DialogueConstraints constraints)\\n {\\n\\n NavigableSet<Integer> matches = new TreeSet ();\\n\\n for (Paragraph p : this.paragraphs)\\n {\\n\\n for (Sentence s : p.getSentences ())\\n {\\n\\n int st = s.getAllTextStartOffset ();\\n\\n // These indexes will be sentence local.\\n NavigableSet<Integer> found = s.find (words,\\n constraints);\\n\\n if (found != null)\\n {\\n\\n for (Integer i : found)\\n {\\n\\n matches.add (s.getWord (i).getAllTextStartOffset ());\\n\\n //matches.add (i + st);\\n\\n }\\n\\n }\\n\\n }\\n\\n }\\n\\n return matches;\\n\\n }\",\n \"void setVersesWithWord(Word word);\",\n \"@Override\\n public List<DefinitionDTO> findWordsByWord(String query) {\\n List<Word> words = wordRepository.findBySearchString(query);\\n return DTOMapper.mapWordListToDefinitionDTOList(words);\\n }\",\n \"public boolean search(String word) {\\n TrieNode p = searchNode(word);\\n if (p == null) {\\n return false;\\n } else {\\n if (p.isEnd)\\n return true;\\n }\\n return false;\\n }\",\n \"@RequestMapping(\\\"/{words}\\\")\\n\\tpublic List<WordMatch> match(@PathVariable(\\\"words\\\") String words) {\\n\\t\\tList<WordMatch> matches = new ArrayList<>();\\n\\t\\tfor (String text : words.split(\\\",\\\")) {\\n\\t\\t\\tmatches.add(service.getMatch(text));\\n\\t\\t}\\n\\t\\treturn matches;\\n\\t}\",\n \"public void update_query(TwitterParser tweet)\\r\\n\\t{\\r\\n\\t\\tfor(String s : tweet.get_words())\\r\\n\\t\\t\\tupdate_query(s, tweet.get_date());\\r\\n\\t}\",\n \"public boolean search(String word) {\\n TrieNode tail = match(root, word.toCharArray(), 0);\\n return tail != null && tail.isWord;\\n }\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.68965036","0.60956764","0.59332526","0.5928022","0.58062935","0.57813257","0.57707757","0.5745215","0.5720394","0.5696968","0.5672093","0.5598769","0.55674994","0.5545627","0.551981","0.5488837","0.5467346","0.5463441","0.5459747","0.54115915","0.54083467","0.53953767","0.5391441","0.53906476","0.53725624","0.5353626","0.5352088","0.5350505","0.5335609","0.5330886","0.5328691","0.5327778","0.5325446","0.5319408","0.5317524","0.5294895","0.5285359","0.5281712","0.52505815","0.5246937","0.52438176","0.52434886","0.52383024","0.52372134","0.523431","0.5232757","0.5225849","0.5224117","0.52222437","0.5219486","0.5218335","0.521531","0.52151436","0.52111137","0.52080995","0.5202601","0.519827","0.51914936","0.51902807","0.51823294","0.5179358","0.5177864","0.51771694","0.51712996","0.5164564","0.51634604","0.5152826","0.5144986","0.5144545","0.5143623","0.51334417","0.51252866","0.5123423","0.51116735","0.51089877","0.5108332","0.51031905","0.5101254","0.5100895","0.509325","0.5088569","0.5084975","0.5077453","0.5075403","0.50709534","0.50593686","0.50579244","0.50556076","0.50508076","0.5047578","0.50396097","0.50298953","0.5028033","0.50276726","0.50243247","0.50175154","0.50169563","0.5012295","0.49946234","0.49869072"],"string":"[\n \"0.68965036\",\n \"0.60956764\",\n \"0.59332526\",\n \"0.5928022\",\n \"0.58062935\",\n \"0.57813257\",\n \"0.57707757\",\n \"0.5745215\",\n \"0.5720394\",\n \"0.5696968\",\n \"0.5672093\",\n \"0.5598769\",\n \"0.55674994\",\n \"0.5545627\",\n \"0.551981\",\n \"0.5488837\",\n \"0.5467346\",\n \"0.5463441\",\n \"0.5459747\",\n \"0.54115915\",\n \"0.54083467\",\n \"0.53953767\",\n \"0.5391441\",\n \"0.53906476\",\n \"0.53725624\",\n \"0.5353626\",\n \"0.5352088\",\n \"0.5350505\",\n \"0.5335609\",\n \"0.5330886\",\n \"0.5328691\",\n \"0.5327778\",\n \"0.5325446\",\n \"0.5319408\",\n \"0.5317524\",\n \"0.5294895\",\n \"0.5285359\",\n \"0.5281712\",\n \"0.52505815\",\n \"0.5246937\",\n \"0.52438176\",\n \"0.52434886\",\n \"0.52383024\",\n \"0.52372134\",\n \"0.523431\",\n \"0.5232757\",\n \"0.5225849\",\n \"0.5224117\",\n \"0.52222437\",\n \"0.5219486\",\n \"0.5218335\",\n \"0.521531\",\n \"0.52151436\",\n \"0.52111137\",\n \"0.52080995\",\n \"0.5202601\",\n \"0.519827\",\n \"0.51914936\",\n \"0.51902807\",\n \"0.51823294\",\n \"0.5179358\",\n \"0.5177864\",\n \"0.51771694\",\n \"0.51712996\",\n \"0.5164564\",\n \"0.51634604\",\n \"0.5152826\",\n \"0.5144986\",\n \"0.5144545\",\n \"0.5143623\",\n \"0.51334417\",\n \"0.51252866\",\n \"0.5123423\",\n \"0.51116735\",\n \"0.51089877\",\n \"0.5108332\",\n \"0.51031905\",\n \"0.5101254\",\n \"0.5100895\",\n \"0.509325\",\n \"0.5088569\",\n \"0.5084975\",\n \"0.5077453\",\n \"0.5075403\",\n \"0.50709534\",\n \"0.50593686\",\n \"0.50579244\",\n \"0.50556076\",\n \"0.50508076\",\n \"0.5047578\",\n \"0.50396097\",\n \"0.50298953\",\n \"0.5028033\",\n \"0.50276726\",\n \"0.50243247\",\n \"0.50175154\",\n \"0.50169563\",\n \"0.5012295\",\n \"0.49946234\",\n \"0.49869072\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.56311864"},"document_rank":{"kind":"string","value":"11"}}},{"rowIdx":13892,"cells":{"query":{"kind":"string","value":"[NEW] Intersects a set of queries TODO: Skip pointer"},"document":{"kind":"string","value":"public PostingsList intersect(Query query){\n\n LinkedList<PostingsList> listQueriedPostings = new LinkedList<PostingsList>();\n // List with postings corresponding to the queries\n for (int i = 0; i<query.size(); i++){\n // If any query has zero matches, return 0 results\n //if(!(new File(\"postings/t\"+hash(query.terms.get(i))+\".json\")).exists()){\n if (!this.index.containsKey(query.terms.get(i))){\n return null;\n }\n // Otherwise store postings in the list\n listQueriedPostings.add(this.getPostings(query.terms.get(i)));\n }\n\n // Order the posting list by increasing document frequency\n listQueriedPostings = sortByIncreasingFrequency(listQueriedPostings);\n\n PostingsList result = (PostingsList)listQueriedPostings.get(0);\n\n // In case only one word is queried\n if (listQueriedPostings.size() == 1){\n return result;\n }\n\n // Apply algorithm as many times as words in the query\n for(int i = 1; i < listQueriedPostings.size(); i++){\n result = intersect(result, listQueriedPostings.get(i));\n if (result.isEmpty()){\n return null;\n }\n }\n return result;\n }"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["@Test\r\n\t\tpublic void testIntersection() {\n\t\t\ttestingSet = new IntegerSet(list1);\r\n\t\t\ttestingSet2= new IntegerSet(list2);\r\n\t\t\t// create 3rdset = to the intersection list \r\n\t\t\ttestingSet3= new IntegerSet(intersection);\r\n\t\t\t// create 4th set =to the intersection of set1 and set2\r\n\t\t\ttestingSet4= testingSet.intersection(testingSet, testingSet2);\r\n\t\t\t// sets 3 and set 4 should be equal \r\n\t\t\t// assertEquals for these parameters is a deprecated method \r\n\t\t\tassertArrayEquals(testingSet3.toArray(),testingSet4.toArray());\t \r\n\t\t}","private void addQueries(String query){\n ArrayList <String> idsFullSet = new ArrayList <String>(searchIDs);\n while(idsFullSet.size() > 0){\n ArrayList <String> idsSmallSet = new ArrayList <String>(); \n if(debugMode) {\n System.out.println(\"\\t Pmids not used in query available : \" + idsFullSet.size());\n }\n idsSmallSet.addAll(idsFullSet.subList(0,Math.min(getSearchIdsLimit(), idsFullSet.size())));\n idsFullSet.removeAll(idsSmallSet);\n String idsConstrain =\"\";\n idsConstrain = idsConstrain(idsSmallSet);\n addQuery(query,idsConstrain);\n }\n }","private static Set<Item> multiSetIntersection(List<Set<Item>> setList) {\n Set<Item> interQrels = new HashSet<>(setList.get(0));\r\n \r\n for (int i = 1; i< setList.size();i++) {\r\n interQrels.retainAll(setList.get(i)); // intersection with two (and one)\r\n }\r\n\r\n return interQrels;\r\n }","private static Set<Dataset> findDatasets(Datasource d, String query) {\n String[] words = query.split(\"\\\\+\");\n Set<String> keyWords = new HashSet<String>();\n for (String word : words) {\n keyWords.add(word.toLowerCase());\n }\n Set<Dataset> ret = new HashSet<Dataset>();\n String tags;\n for (Dataset set : d.getDatasets()) {\n tags = set.getTags();\n if (intersects(tags, keyWords)) {\n ret.add(set);\n }\n } \n return ret;\n }","@Test\n public void testIntersection3()\n {\n List<Integer> expected = new ArrayList<>();\n ConciseSet set1 = new ConciseSet();\n ConciseSet set2 = new ConciseSet();\n for (int i = 0; i < 1000; i++) {\n set1.add(i);\n set2.add(i);\n expected.add(i);\n }\n\n verifyIntersection(expected, set1, set2);\n }","protected abstract NativeSQLStatement createNativeIntersectsStatement(Geometry geom);","protected abstract Iterable<E> getIntersecting(D lower, D upper);","@Test\n public void testIntersection4()\n {\n List<Integer> expected = new ArrayList<>();\n ConciseSet set1 = new ConciseSet();\n ConciseSet set2 = new ConciseSet();\n for (int i = 0; i < 1000; i++) {\n set1.add(i);\n if (i != 500) {\n set2.add(i);\n expected.add(i);\n }\n }\n\n verifyIntersection(expected, set1, set2);\n }","@Test\n public void testIntersection6()\n {\n List<Integer> expected = new ArrayList<>();\n ConciseSet set1 = new ConciseSet();\n for (int i = 0; i < 5; i++) {\n set1.add(i);\n }\n for (int i = 1000; i < 1005; i++) {\n set1.add(i);\n }\n\n ConciseSet set2 = new ConciseSet();\n for (int i = 800; i < 805; i++) {\n set2.add(i);\n }\n for (int i = 806; i < 1005; i++) {\n set2.add(i);\n }\n\n for (int i = 1000; i < 1005; i++) {\n expected.add(i);\n }\n\n verifyIntersection(expected, set1, set2);\n }","@Test\n public void testIntersection5()\n {\n final int[] ints1 = {33, 100000};\n final int[] ints2 = {34, 200000};\n List<Integer> expected = new ArrayList<>();\n\n ConciseSet set1 = new ConciseSet();\n for (int i : ints1) {\n set1.add(i);\n }\n ConciseSet set2 = new ConciseSet();\n for (int i : ints2) {\n set2.add(i);\n }\n\n verifyIntersection(expected, set1, set2);\n }","public static List<String> query_intersect(List<String> queryWords) throws IOException {\n\t\tif (!initialized) initialize();\n\t\tList<PostingList> pls = new ArrayList<PostingList> ();\n\t\tfor (String queryWord : queryWords) {\n\t\t\tqueryWord = queryWord.toLowerCase();\n\t\t\tif (!termDict.containsKey(queryWord)) {\n\t\t\t\tpls.clear();\n\t\t\t\tbreak;\n\t\t\t}\n\t\t\tPostingList pl = readPosting(fc, termDict.get(queryWord));\n\t\t\tif (pl == null) {\n\t\t\t\tpls.clear();\n\t\t\t\tbreak;\n\t\t\t}\n\t\t\tpls.add(readPosting(fc, termDict.get(queryWord)));\n\t\t}\n\t\tCollections.sort(pls, new Comparator<PostingList>(){\n\t\t public int compare(PostingList p1, PostingList p2) {\n\t\t return p1.size() - p2.size(); // assumes you want biggest to smallest\n\t\t }\n\t\t});\n\t\tif (pls.size() == 0) {\n\t\t\treturn null;\n\t\t} else {\n\t\t\tList<Integer> current = pls.get(0).getList();\n\t\t\tfor (int i = 1; i < pls.size(); i++) {\n\t\t\t\tList<Integer> toBeAdd = pls.get(i).getList();\n\t\t\t\tcurrent = intersect(current, toBeAdd);\n\t\t\t}\n\t\t\tif (current.size() == 0) {\n\t\t\t\treturn null;\n\t\t\t} else {\n\t\t\t\tList<String> result = new ArrayList<String>();\n\t\t\t\tfor (int docId : current) {\n\t\t\t\t\tresult.add(docDict.get(docId));\n\t\t\t\t}\n\t\t\t\treturn result;\n\t\t\t}\n\t\t}\n\t}","@Test\n public void testIntersection1()\n {\n final int[] ints1 = {33, 100000};\n final int[] ints2 = {33, 100000};\n List<Integer> expected = Arrays.asList(33, 100000);\n\n ConciseSet set1 = new ConciseSet();\n for (int i : ints1) {\n set1.add(i);\n }\n ConciseSet set2 = new ConciseSet();\n for (int i : ints2) {\n set2.add(i);\n }\n\n verifyIntersection(expected, set1, set2);\n }","public ArrayList<ArrayList> intersection (ArrayList<ArrayList> data, ArrayList<ArrayList> data2)\n {\n ArrayList<Document> docs = data.get(0);\n ArrayList<Double> relevance = data.get(1);\n ArrayList<Integer> occurrence = data.get(2);\n ArrayList<Integer> popularity = data.get(3);\n \n ArrayList<Document> docs2 = data2.get(0);\n ArrayList<Double> relevance2 = data2.get(1);\n ArrayList<Integer> occurrence2 = data2.get(2);\n ArrayList<Integer> popularity2 = data2.get(3);\n \n ArrayList<Document> docs3 = new ArrayList<>();\n ArrayList<Double> relevance3 = new ArrayList<>();\n ArrayList<Integer> occurrence3 = new ArrayList<>();\n ArrayList<Integer> popularity3 = new ArrayList<>();\n \n for(Document d: docs)\n {\n if(docs2.contains(d))\n {\n docs3.add(d);\n int docIndex = docs.indexOf(d);\n int docIndex2 = docs2.indexOf(d);\n double oldRel = (double) relevance.get(docIndex);\n int oldOcc = (int) occurrence.get(docIndex);\n relevance3.add(oldRel+relevance2.get(docIndex2));\n if(oldOcc > occurrence2.get(docIndex2))\n {\n occurrence3.add(occurrence2.get(docIndex2));\n }\n else\n {\n occurrence3.add(oldOcc);\n }\n popularity3.add(d.popularity);\n }\n \n }\n data = new ArrayList<ArrayList> ();\n data.add(docs3);\n data.add(relevance3);\n data.add(occurrence3);\n data.add(popularity3);\n \n return data;\n }","@Test\n public void testIntersection2()\n {\n final int[] ints1 = {33, 100000};\n final int[] ints2 = {34, 100000};\n List<Integer> expected = Collections.singletonList(100000);\n\n ConciseSet set1 = new ConciseSet();\n for (int i : ints1) {\n set1.add(i);\n }\n ConciseSet set2 = new ConciseSet();\n for (int i : ints2) {\n set2.add(i);\n }\n\n verifyIntersection(expected, set1, set2);\n }","public ArrayList<SearchResult> partialSearch(Collection<String> queries) {\n\t\tArrayList<SearchResult> results = new ArrayList<>();\n\t\tHashMap<String, SearchResult> track = new HashMap<>();\n\n\t\tfor (String query : queries) {\n\t\t\tfor (String word : this.invertedIndex.tailMap(query).keySet()) {\n\t\t\t\tif (word.startsWith(query)) {\n\t\t\t\t\tsearchHelper(results, word, track);\n\t\t\t\t} else {\n\t\t\t\t\tbreak;\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t\tCollections.sort(results);\n\t\treturn results;\n\t}","public static void main(String[] args) {\n\t\tInteger[] firstArray = {0,2,4,6,8};\n\t Integer[] secondArray = {1,3,10,4,7,8,9};\n\t \n\t intersectionUsingSet(firstArray, secondArray);\n\n\t System.out.println();\n\t \n\t // Array with duplicate elements in the array\n\t Integer[] firstArray1 = {0,2,2,4,6,6,8};\n\t Integer[] secondArray2 = {1,3,10,10,4,7,8,9};\n\t \n\t intersectionUsingSet(firstArray1, secondArray2);\n\t}","public intersection(){}","QueryResult(Pair<Integer, String>[] queries) {\n results = new ConcurrentHashMap<>(queries.length);\n for (Pair<Integer, String> query : queries)\n results.put(query.first, new int[0]);\n }","public static void main(String[] args) {\n\t\tint [] a = {3,4,5,6};\n\t\tint [] b = {1,2,3};\t\n\t\tint [] c = {7,8,9};\t\n\t\tint [] d = {};\n\t\tSystem.out.println(intersection(a,b)); //true\n\t\tSystem.out.println(intersection(b,c)); //false\n\t\tSystem.out.println(intersection(a,c)); //false\n\t\tSystem.out.println(intersection(a,d)); //false\n\t\t}","public void intersect(Collection<String> ids) {\n mSelection.retainAll(ids);\n mProvisionalSelection.retainAll(ids);\n }","@Test\n public void mapContains() {\n check(MAPCONT);\n query(MAPCONT.args(MAPNEW.args(), 1), false);\n query(MAPCONT.args(MAPENTRY.args(1, 2), 1), true);\n }","public static void main(String[] args) {\n\t\tSystem.out.println(Arrays.toString(intersect(new int[]{1, 2, 3, 4}, new int[]{1, 2, 3, 4, 1, 2, 3, 4})));\n\t}","@Test(expected = NullPointerException.class)\r\n\t\tpublic void testIntersectionWithNullInput() {\r\n\t\t\ttestingSet = new IntegerSet(null);\r\n\t\t\ttestingSet2= new IntegerSet(null); \r\n\t\t\t\r\n\t\t\t// union of 2 null sets \r\n\t\t\ttestingSet3= testingSet.intersection(testingSet, testingSet2);\r\n\t\t}","@Test\n public void testBatchedInQuery() {\n TestDataCreator creator = new TestDataCreator(getSessionFactory());\n Town town = creator.createTestTown();\n\n int n = 10;\n List<Long> ids = new ArrayList<>(n);\n for (long i=0; i < n; i++) {\n Person savedPerson = creator.createTestPerson(town, \"P\" + i);\n ids.add(savedPerson.getId());\n }\n for (long i=0; i < n; i++) {\n creator.createTestPerson(town, \"P\" + i);\n }\n\n Person person = query.from(Person.class);\n query.where(person.getId()).in(ids, 2);\n\n validate(\"from Person hobj1 where hobj1.id in (:np1)\", ids);\n assertEquals(n, doQueryResult.size());\n }","public static void main(String[] args) {\n\t\tIntersection l5=new Intersection(5,null);\n\t\tIntersection l4=new Intersection(4,l5);\n\t\tIntersection l3=new Intersection(3,l4);\n\t\tIntersection l2=new Intersection(2,l3);\n\t\tIntersection l1=new Intersection(1,l2);\n\t\t\n\t\tIntersection m7=new Intersection(7,l3);\n\t\tIntersection m6=new Intersection(6,m7);\n\t\tint flag=0;\n\t\twhile(m6!=null && l1!=null){\n\t\t\tif(m6!=l1){\n\t\t\t\tm6=m6.next;\n\t\t\t\tl1=l1.next;\n\t\t\t}\n\t\t\telse{\n\t\t\t\tflag=1;\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\tif(flag==1){\n\t\t\tSystem.out.println(\"They Intersect!\");\n\t\t}\n\t\telse{\n\t\t\tSystem.out.println(\"They don't!\");\n\t\t}\n\t}","public static void intersectionUsingSet(Integer[] firstArray, Integer[] secondArray)\n\t{\n\t LinkedHashSet<Integer> set = new LinkedHashSet<Integer>();\n\t \n\t set.addAll(Arrays.asList(firstArray));\n\t \n\t set.retainAll(Arrays.asList(secondArray));\n\t \n\t Integer[] intersectionArray = set.toArray(new Integer[set.size()]);\n\t \n\t System.out.println(\"Intersection of two arrays using set is : \");\n\t \n\t for(int i=0; i<intersectionArray.length; i++)\n\t {\n\t \tSystem.out.print(intersectionArray[i]+\" \");\n\t }\n\t}","public Set intersection(Set intersect){\n Set newSet = new Set();\n for(int element = 0; element < intersect.size(); element++){\n if(elementOf(intersect.getSet()[element]))\n newSet.add(intersect.getSet()[element]);\n }\n return newSet;\n }","private Set<String> getIntersection( Set<String> a, Set<String> b ) {\n\t\tSet<String> intersection = new HashSet<String>(a);\n\t\tintersection.retainAll(b);\n\t\treturn intersection;\n\t}","public ZYSet<ElementType> intersection(ZYSet<ElementType> otherSet){\n ZYSet<ElementType> result = new ZYArraySet<ElementType>();\n for(ElementType e :this){\n if(otherSet.contains(e)){\n result.add(e);\n }\n }\n return result;\n }","@Test\n\tpublic void integrationTest2() throws Exception {\n\t\tHashSet<String> mistress = loadGrepResults(\"mistress\");\n\t\tHashSet<String> undocumented = loadGrepResults(\"undocumented\");\n\t\tHashSet<String> insane = loadGrepResults(\"insane\");\n\t\tHashSet<String> crazy = loadGrepResults(\"crazy\");\n\t\tHashSet<String> forced = loadGrepResults(\"!i+am+forced\");\n\t\t\n\t\tHashSet<String> grepFound = new HashSet<String>(mistress);\n\t\tgrepFound.retainAll(undocumented);\n\t\tHashSet<String> temp = new HashSet<String>(crazy);\n\t\ttemp.retainAll(forced);\n\t\tgrepFound.addAll(temp);\n\t\tgrepFound.addAll(insane);\n\t\t\n\t\tCollection<Page> index = queryTest.query(\"insane | crazy & !\\\"I am forced\\\" | mistress & undocumented\");\n\t\tHashSet<String> indexFound = new HashSet<String>();\n\n\t\tfor (Page p : index)\n\t\t\tindexFound.add(p.getURL().getPath().toLowerCase());\n\t\t\n\t\tassertEquals(indexFound, grepFound);\n\t}","public void testUsingQueriesFromQueryManger(){\n\t\tSet<String> names = testDataMap.keySet();\n\t\tUtils.prtObMess(this.getClass(), \"atm query\");\n\t\tDseInputQuery<BigDecimal> atmq = \n\t\t\t\tqm.getQuery(new AtmDiot());\n\t\tMap<String, ComplexQueryResult<BigDecimal>> bdResult = \n\t\t\t\tatmq.get(names, 1, TimeUnit.SECONDS);\n\t\tCollectionsStaticMethods.prtMapItems(bdResult);\n\n\t\tUtils.prtObMess(this.getClass(), \"vol query\");\n\t\tDseInputQuery<BigDecimal> volq = \n\t\t\t\tqm.getQuery(new VolDiotForTest());\n\t\tMap<String, ComplexQueryResult<BigDecimal>> dbResult = \n\t\t\t\tvolq.get(names, 1, TimeUnit.SECONDS);\n\t\tCollectionsStaticMethods.prtMapItems(dbResult);\n\t\n\t\tUtils.prtObMess(this.getClass(), \"integer query\");\n\t\tDseInputQuery<BigDecimal> strikeq = \n\t\t\t\tqm.getQuery(new StrikeDiotForTest());\n\t\tMap<String, ComplexQueryResult<BigDecimal>> strikeResult = \n\t\t\t\tstrikeq.get(names, 1, TimeUnit.SECONDS);\n\t\tCollectionsStaticMethods.prtMapItems(strikeResult);\n\t\n\t}","public void getIntersection(int[] A, int[] B, ArrayList<int[]> intersections) \n {\n if (A[0] >= B[0] && A[0] <= B[1]) \n {\n if (A[1] >= B[0] && A[1] <= B[1]) \n {\n // Take the entirety of A\n intersections.add(A);\n } \n else \n {\n // Take the start of A to end of B\n int[] intersection = new int[]{A[0], B[1]};\n intersections.add(intersection);\n }\n } \n else \n {\n if (A[1] >= B[0] && A[1] <= B[1]) \n {\n // Take start of B to end of A\n int[] intersection = new int[]{B[0], A[1]};\n intersections.add(intersection);\n } \n else \n {\n if (A[0] < B[0] && A[1] > B[1]) \n {\n // Take the entirety of B\n intersections.add(B);\n } \n else \n {\n // No intersection at all\n return;\n }\n }\n }\n }","public static void main(String[] args) {\n\t\t\n\tint[] firstArr =\t{1,2,3,4,5};\n\tint[] secondArr =\t{2,3,4,9,6,10};\n\tSet<Integer> set = new HashSet<Integer>();\n\tfor(int i=0; i<secondArr.length; i++) {\n\t\tset.add(secondArr[i]);\n\t}\n\tfor(int i=0; i<firstArr.length; i++) {\n\t\tboolean status =set.add(firstArr[i]);\n\t\tif(status==false) {\n\t\t\tSystem.out.println(\"Intersection Elements :\"+firstArr[i]);\n\t }\n\t}\n }","public void sensibleMatches1() \n { \n Map<String, Set<String>> clientMap = new HashMap<>();\n Set<String> interests = new HashSet<>();\n\n interests.add(\"Food\");\n interests.add(\"Wine\");\n interests.add(\"Tandems\");\n clientMap.put(\"Hal\", interests);\n\t \n interests = new HashSet<>();\n interests.add(\"Food\");\n interests.add(\"Walking\");\n interests.add(\"Welding\");\n clientMap.put(\"Gemma\", interests);\n\t \n interests = new HashSet<>();\n interests.add(\"Food\");\n interests.add(\"Cinema\");\n interests.add(\"Wine\");\n clientMap.put(\"Caroline\", interests);\n\n Set<String> halsInterests = clientMap.get(\"Hal\");\n String outputString;\n Set<String> eachClientInterests;\n Set<String> intersection ;\n\n Map<String, Set<String>> mapWithoutHal = new HashMap<>(clientMap);\n mapWithoutHal.remove(\"Hal\");\n for (String eachClient : mapWithoutHal.keySet()) \n {\n eachClientInterests = clientMap.get(eachClient);\n intersection = new HashSet<>(halsInterests);\n intersection.retainAll(eachClientInterests);\n outputString = \"Hal and \" + eachClient \n + \" have common interests: \"\n + intersection;\n System.out.println(outputString);\n }\n }","private Set<String> intersection(Set<String> s1, Set<String> s2) {\n Set<String> intersection = new HashSet<>(s1);\n intersection.retainAll(s2);\n return intersection;\n }","public PostingsList intersect(PostingsList l1, PostingsList l2){\n\n PostingsList intersection = new PostingsList();\n\n // Counters to iterate docIDs\n int count1 = 0;\n int count2 = 0;\n\n // First posting\n PostingsEntry p1 = l1.get(0);\n PostingsEntry p2 = l2.get(0);\n\n while(true){\n // Match - EUREKA! //\n if (p1.docID == p2.docID){\n // Add match\n intersection.insert(p1.docID);\n // Increase counters\n count1++;\n count2++;\n // Go to next postings (check for nullpointer)\n if (count1<l1.size() && count2<l2.size()){\n p1 = l1.get(count1);\n p2 = l2.get(count2);\n }\n else\n break;\n }\n // No match\n else if (p1.docID < p2.docID){\n count1++;\n if (count1<l1.size())\n p1 = l1.get(count1);\n else\n break;\n }\n // No match\n else{\n count2++;\n if (count2<l2.size())\n p2 = l2.get(count2);\n else\n break;\n }\n }\n\n return intersection;\n }","@Override\r\n public void intersect( Ray ray, IntersectResult result ) {\n\t\r\n }","public void matchesDemo() \n {\n Map<String, Set<String>> clientMap = new HashMap<>();\n Set<String> interests = new HashSet<>();\n\n interests.add(\"Food\");\n interests.add(\"Wine\");\n interests.add(\"Tandems\");\n clientMap.put(\"Hal\", interests);\n\t \n interests = new HashSet<>();\n interests.add(\"Food\");\n interests.add(\"Walking\");\n interests.add(\"Welding\");\n clientMap.put(\"Gemma\", interests);\n\t \n interests = new HashSet<>();\n interests.add(\"Food\");\n interests.add(\"Cinema\");\n interests.add(\"Wine\");\n clientMap.put(\"Caroline\", interests);\n\n Set<String> halsInterests = clientMap.get(\"Hal\");\n String outputString;\n Set<String> eachClientInterests;\n Set<String> intersection;\n\n for (String eachClient : clientMap.keySet()) \n {\n eachClientInterests = clientMap.get(eachClient);\n intersection = new HashSet<>(halsInterests);\n intersection.retainAll(eachClientInterests);\n outputString = \"Hal and \" + eachClient \n + \" have common interests: \"\n + intersection;\n System.out.println(outputString) ;\n }\n }","void findMatchings(boolean isProtein) {\n\n GraphDatabaseFactory dbFactory = new GraphDatabaseFactory();\n HashSet<String > searchSpaceList = new HashSet<>();\n GraphDatabaseService databaseService = dbFactory.newEmbeddedDatabase(graphFile);\n for (int id: queryGraphNodes.keySet()) {\n if(isProtein)\n searchSpaceList.add(queryGraphNodes.get(id).label);\n else\n searchSpaceList.add(String.valueOf(queryGraphNodes.get(id).labels.get(0)));\n }\n for(String x: searchSpaceList) {\n ResourceIterator<Node> xNodes;\n try(Transaction tx = databaseService.beginTx()) {\n xNodes = databaseService.findNodes(Label.label(x));\n tx.success();\n }\n\n while (xNodes.hasNext()) {\n Node node = xNodes.next();\n if (searchSpaceProtein.containsKey(x))\n searchSpaceProtein.get(x).add(node.getId());\n else {\n HashSet<Long> set = new HashSet<>();\n set.add(node.getId());\n searchSpaceProtein.put(x, set);\n }\n }\n\n }\n\n if(isProtein)\n search(0, databaseService, true);\n else\n search(0, databaseService, false);\n databaseService.shutdown();\n }","public int[] intersection(int[] nums1, int[] nums2) {\n \n HashSet<Integer> set = new HashSet<>();\n ArrayList<Integer> inter = new ArrayList<>();\n if(nums1.length > nums2.length)\n {\n for(int i = 0; i < nums1.length ;i ++)\n set.add(nums1[i]);\n\n for(int i = 0; i < nums2.length ;i ++)\n if(set.contains(nums2[i])&& !inter.contains(nums2[i]))\n inter.add(nums2[i]);\n }\n else {\n for(int i = 0; i < nums2.length ;i ++)\n set.add(nums2[i]);\n\n for(int i = 0; i < nums1.length ;i ++)\n if(set.contains(nums1[i]) && !inter.contains(nums1[i]))\n inter.add(nums1[i]);\n }\n\n int [] arr = new int[inter.size()];\n for(int i = 0; i < arr.length ;i ++)\n arr[i] = inter.get(i);\n return arr;\n\n }","public ArrayList<SearchResult> exactSearch(Collection<String> queries) {\n\t\tArrayList<SearchResult> results = new ArrayList<>();\n\t\tHashMap<String, SearchResult> track = new HashMap<>();\n\n\t\tfor (String query : queries) {\n\t\t\tif (invertedIndex.containsKey(query)) {\n\t\t\t\tsearchHelper(results, query, track);\n\t\t\t}\n\t\t}\n\t\tCollections.sort(results);\n\t\treturn results;\n\t}","public void testQuery() throws Exception {\n DummyApprovalRequest req1 = new DummyApprovalRequest(reqadmin, null, caid, SecConst.EMPTY_ENDENTITYPROFILE, false);\n DummyApprovalRequest req2 = new DummyApprovalRequest(admin1, null, caid, SecConst.EMPTY_ENDENTITYPROFILE, false);\n DummyApprovalRequest req3 = new DummyApprovalRequest(admin2, null, 3, 2, false);\n\n approvalSessionRemote.addApprovalRequest(admin1, req1, gc);\n approvalSessionRemote.addApprovalRequest(admin1, req2, gc);\n approvalSessionRemote.addApprovalRequest(admin1, req3, gc);\n\n // Make som queries\n Query q1 = new Query(Query.TYPE_APPROVALQUERY);\n q1.add(ApprovalMatch.MATCH_WITH_APPROVALTYPE, BasicMatch.MATCH_TYPE_EQUALS, \"\" + req1.getApprovalType());\n\n List result = approvalSessionRemote.query(admin1, q1, 0, 3, \"cAId=\" + caid, \"(endEntityProfileId=\" + SecConst.EMPTY_ENDENTITYPROFILE + \")\");\n assertTrue(\"Result size \" + result.size(), result.size() >= 2 && result.size() <= 3);\n\n result = approvalSessionRemote.query(admin1, q1, 1, 3, \"cAId=\" + caid, \"(endEntityProfileId=\" + SecConst.EMPTY_ENDENTITYPROFILE + \")\");\n assertTrue(\"Result size \" + result.size(), result.size() >= 1 && result.size() <= 3);\n\n result = approvalSessionRemote.query(admin1, q1, 0, 1, \"cAId=\" + caid, \"(endEntityProfileId=\" + SecConst.EMPTY_ENDENTITYPROFILE + \")\");\n assertTrue(\"Result size \" + result.size(), result.size() == 1);\n\n Query q2 = new Query(Query.TYPE_APPROVALQUERY);\n q2.add(ApprovalMatch.MATCH_WITH_STATUS, BasicMatch.MATCH_TYPE_EQUALS, \"\" + ApprovalDataVO.STATUS_WAITINGFORAPPROVAL, Query.CONNECTOR_AND);\n q2.add(ApprovalMatch.MATCH_WITH_REQUESTADMINCERTSERIALNUMBER, BasicMatch.MATCH_TYPE_EQUALS, reqadmincert.getSerialNumber().toString(16));\n\n result = approvalSessionRemote.query(admin1, q1, 1, 3, \"cAId=\" + caid, \"(endEntityProfileId=\" + SecConst.EMPTY_ENDENTITYPROFILE + \")\");\n assertTrue(\"Result size \" + result.size(), result.size() >= 1 && result.size() <= 3);\n\n // Remove the requests\n int id1 = ((ApprovalDataVO) approvalSessionRemote.findApprovalDataVO(admin1, req1.generateApprovalId()).iterator().next()).getId();\n int id2 = ((ApprovalDataVO) approvalSessionRemote.findApprovalDataVO(admin1, req2.generateApprovalId()).iterator().next()).getId();\n int id3 = ((ApprovalDataVO) approvalSessionRemote.findApprovalDataVO(admin1, req3.generateApprovalId()).iterator().next()).getId();\n approvalSessionRemote.removeApprovalRequest(admin1, id1);\n approvalSessionRemote.removeApprovalRequest(admin1, id2);\n approvalSessionRemote.removeApprovalRequest(admin1, id3);\n }","public static void main(String[] args) {\n\t\tint[] nums1 = {4,9,5};\r\n\t\tint[] nums2 = {9,4,9,8,4};\r\n\t\t//System.out.println(intersection(nums1, nums2));\r\n\t\tArrays.sort(nums1);\r\n\t\tArrays.sort(nums2);\r\n\t\tif (nums1.length>nums2.length) {\r\n\t\t\tint[] temp = nums2;\r\n\t\t\tnums2 = nums1;\r\n\t\t\tnums1 = temp;\r\n\t\t}\r\n\t\tHashSet<Integer> mSet1 = new HashSet<Integer>();\r\n\t\tHashSet<Integer> mSet2 = new HashSet<Integer>();\r\n\t\tfor (Integer i : nums2) {\r\n\t\t\tmSet1.add(i);\r\n\t\t}\r\n\t\tfor (Integer x: nums1) {\r\n\t\t\tif (mSet1.contains(x)) {\r\n\t\t\t\tmSet2.add(x);\r\n\t\t\t}\r\n\t\t}\r\n\t\tint[] r = new int[mSet2.size()];\r\n\t\tint index = 0;\r\n\t\tfor (Integer g: mSet2) {\r\n\t\t\tr[index] = g;\r\n\t\t\tindex++;\r\n\t\t}\r\n\t}","public static int[] intersection(int[] nums1, int[] nums2) {\n if(nums1 == null || nums2 == null){\n return null;\n }\n HashSet<Integer> set = new HashSet<>();\n for (int aNubs1 : nums1) {\n set.add(aNubs1);\n }\n HashSet<Integer> result = new HashSet<>();\n for (int aNubs2 : nums2) {\n if (set.contains(aNubs2) && !result.contains(aNubs2)) {\n result.add(aNubs2);\n }\n }\n int [] intersection = new int[result.size()];\n int index = 0;\n for(int temp : result){\n intersection[index++] = temp;\n }\n return intersection;\n }","public void sensibleMatches2() \n { \n Map<String, Set<String>> clientMap = new HashMap<>();\n Set<String> interests = new HashSet<>();\n\n interests.add(\"Food\");\n interests.add(\"Wine\");\n interests.add(\"Tandems\");\n clientMap.put(\"Hal\", interests);\n\t \n interests = new HashSet<>();\n interests.add(\"Food\");\n interests.add(\"Walking\");\n interests.add(\"Welding\");\n clientMap.put(\"Gemma\", interests);\n\n interests = new HashSet<>();\n interests.add(\"Food\");\n interests.add(\"Cinema\");\n interests.add(\"Wine\");\n clientMap.put(\"Caroline\", interests);\n\n Set<String> halsInterests = clientMap.get(\"Hal\");\n String outputString;\n Set<String> eachClientInterests;\n Set<String> intersection ;\n\n for (String eachClient : clientMap.keySet()) \n {\n if (!eachClient.equals(\"Hal\")) \n {\n eachClientInterests = clientMap.get(eachClient);\n intersection = new HashSet<>(halsInterests);\n intersection.retainAll(eachClientInterests);\n outputString = \"Hal and \" + eachClient \n + \" have common interests: \"\n + intersection;\n System.out.println(outputString);\n }\n }\n }","protected <Ty> HashSet<Ty> intersection(HashSet<Ty> setA, HashSet<Ty> setB) {\n HashSet<Ty> retSet = new HashSet<>();\n for (Ty t : setA) {\n if (setB.contains(t)) {\n retSet.add(t);\n }\n }\n return retSet;\n }","QueryResult(String... queries) {\n results = new ConcurrentHashMap<>(queries.length);\n for (String query : queries)\n results.put(query.hashCode(), new int[0]);\n }","public int[] intersection1(int[] nums1, int[] nums2) {\n Set<Integer> nums1Set = new HashSet<>();\n Set<Integer> nums2Set = new HashSet<>();\n\n for (int i = 0; i < nums1.length; i++) {\n nums1Set.add(nums1[i]);\n }\n for (int i = 0; i < nums2.length; i++) {\n nums2Set.add(nums2[i]);\n }\n\n nums1Set.retainAll(nums2Set);\n\n int[] res = new int[nums1Set.size()];\n int i = 0;\n for (int s: nums1Set) {\n res[i++] = s;\n }\n return res;\n }","public int[] intersectionUsingSets(int[] nums1, int[] nums2) {\n Set<Integer> setA = new HashSet<>();\n Set<Integer> intersection = new HashSet<>();\n for (int num : nums1) {\n setA.add(num);\n }\n\n for (int num : nums2) {\n if (setA.contains(num)) {\n intersection.add(num);\n }\n }\n\n return getIntersectionResult(intersection);\n }","public void intersectionOf(IntegerSet set1, IntegerSet set2) {\n get = new int[0];\n for (int i : set1.get)\n if (set2.hasElement(i))\n insertElement(i);\n }","@Test\n public void testBoundsAsCompositesWithMultiEqRestrictions()\n {\n CFMetaData cfMetaData = newCFMetaData(Sort.ASC, Sort.ASC);\n\n ByteBuffer value1 = ByteBufferUtil.bytes(1);\n ByteBuffer value2 = ByteBufferUtil.bytes(2);\n Restriction eq = newMultiEq(cfMetaData, 0, value1, value2);\n PrimaryKeyRestrictions restrictions = new PrimaryKeyRestrictionSet(cfMetaData.comparator);\n restrictions = restrictions.mergeWith(eq);\n\n List<Composite> bounds = restrictions.boundsAsComposites(cfMetaData, Bound.START, QueryOptions.DEFAULT);\n assertEquals(1, bounds.size());\n assertComposite(bounds.get(0), value1, value2, EOC.START);\n\n bounds = restrictions.boundsAsComposites(cfMetaData, Bound.END, QueryOptions.DEFAULT);\n assertEquals(1, bounds.size());\n assertComposite(bounds.get(0), value1, value2, EOC.END);\n }","public void searchArea(Connection connection, String city, String state, int zip) throws SQLException {\n\n ResultSet rs = null;\n PreparedStatement pStmt = null;\n String sql1 = \"SELECT hotel_name, branch_id FROM Hotel_Address WHERE city = ?\";\n String sql2 = \"SELECT hotel_name, branch_id FROM Hotel_Address WHERE state = ?\";\n String sql3 = \"SELECT hotel_name, branch_id FROM Hotel_Address WHERE zip = ?\";\n\n // City and State combination:\n if (city != null && state != null){\n\n pStmt = connection.prepareStatement(sql1 + \" INTERSECT \" + sql2);\n pStmt.clearParameters();\n\n setCity(city);\n pStmt.setString(1, getCity());\n setState(state);\n pStmt.setString(2, getState());\n }\n\n // City and ZIP combination:\n else if (city != null){\n\n pStmt = connection.prepareStatement(sql1 + \" INTERSECT \" + sql3);\n pStmt.clearParameters();\n\n setCity(city);\n pStmt.setString(1, getCity());\n setZip(zip);\n pStmt.setInt(2, getZip());\n }\n\n // State and ZIP combination:\n else {\n\n pStmt = connection.prepareStatement(sql2 + \" INTERSECT \" + sql3);\n pStmt.clearParameters();\n\n setState(state);\n pStmt.setString(1, getState());\n setZip(zip);\n pStmt.setInt(2, getZip());\n }\n\n try {\n\n System.out.println(\" Hotels in area:\");\n System.out.println(\"+------------------------------------------------------------------------------+\");\n\n rs = pStmt.executeQuery();\n String result;\n\n while (rs.next()) {\n\n System.out.println(rs.getString(1) + \" \" + rs.getInt(2));\n }\n }\n catch (SQLException e) { throw e; }\n finally {\n pStmt.close();\n if(rs != null) { rs.close(); }\n }\n }","public static Set<Doc> and(Set<Doc> set1, Set<Doc> set2) {\r\n \t\t\r\n \t\tif((set1 == null) || (set2 == null)) {\r\n\t\t\tSystem.err.println(\"Doc.and() returning null!\");\r\n \t\t\treturn new TreeSet<Doc>();\r\n \t\t}\r\n \t\t//set1.retainAll(set2);\r\n \t\t//return set1;\r\n \t\t\r\n \t\tTreeSet<Doc> result = new TreeSet<Doc>();\r\n \t\tIterator<Doc> op1 = set1.iterator();\r\n \t\tIterator<Doc> op2 = set2.iterator();\r\n \t\t\r\n \t\tDoc current1 = getNext(op1);\r\n \t\tDoc current2 = getNext(op2);\r\n \r\n \t\twhile(current1!=null && current2!=null) {\r\n \t\t\t//If is the same document\r\n \t\t\tif(current1.getID() == current2.getID()) {\r\n \t\t\t\tresult.add(current1);\r\n \t\t\t\tcurrent1 = getNext(op1);\r\n \t\t\t\tcurrent2 = getNext(op2);\r\n \t\t\t}\r\n \t\t\t//If op2 is ahead of op1\r\n \t\t\telse if(current1.getID() < current2.getID()) \r\n \t\t\t\tcurrent1 = getNext(op1);\r\n \t\t\t//If op1 is ahead of op2\r\n \t\t\telse\r\n \t\t\t\tcurrent2 = getNext(op2);\r\n \t\t}\r\n \t\t\r\n \t\treturn result;\r\n \t}","@Test\n public void test1() {\n final List<String> listA = Arrays.asList(\"Fremont\", \"Dublin\", \"anamole\", \"San Jose\" , \"SFO\", \"Dublin\", \"San Jose\", \"paramount\", \"y\");\n final List<String> listB = Arrays.asList(\"Dublin\", \"san mateo\", \"los angeles\", \"san mateo\", \"fremont\", \"anamole\", \"x\", \"x\", \"Y\");\n final List<String> common = FindIntersection.findCommonLists(listA, listB);\n System.out.println(Arrays.toString(FindIntersection.findCommonLists(listA, listB).toArray()));\n\n }","private boolean intersectsAggregate( Aggregate mprim ) throws Exception {\n boolean inter = false;\n\n int cnt = mprim.getSize();\n\n for ( int i = 0; i < cnt; i++ ) {\n if ( intersects( mprim.getObjectAt( i ) ) ) {\n inter = true;\n break;\n }\n }\n\n return inter;\n }","public static void main(String[] args) {\n\t\t\r\n\t\tint arr1[] = {3,2,11,4,6,7};\r\n\t\tint arr2[] = {1,2,8,4,9,7};\r\n\t\t\r\n\t\tList<Integer> list1 = new ArrayList<Integer>();\r\n\t\t\r\n\t\tList<Integer> list2 = new ArrayList<Integer>();\r\n\t\t\r\n\t\tfor (int a : arr1) {\r\n\t\t\tlist1.add(a);\r\n\t\t}\r\n\t\tfor (int b : arr2) {\r\n\t\t\tlist2.add(b);\r\n\t\t}\r\n\t\t\r\n\t\tSystem.out.println(list1);\r\n System.out.println(list2);\r\n \r\n list1.retainAll(list2);\r\n System.out.println(\"The Intersection values : \" + list1);\r\n \r\n\t}","public abstract boolean intersect(BoundingBox bbox);","public static void main (String[] args) {\n System.out.println(findIntersection(new String[] {\"1, 3, 4, 7, 13\", \"1, 2, 4, 13, 15\"})); \n System.out.println(findIntersection(new String[] {\"2, 3, 4\", \"3\"})); \n System.out.println(findIntersection(new String[] {\"1, 5, 6, 7, 10, 11, 12\", \"5, 6, 8, 11, 17\"})); \n System.out.println(findIntersection(new String[] {\"1, 2, 3, 4, 5\", \"6, 7, 8, 9, 10\"})); \n System.out.println(findIntersection(new String[] {\"1, 2, 4, 5, 6, 9\", \"2, 3, 4, 8, 10\"})); \n System.out.println(findIntersection(new String[] {\"21, 22, 23, 25, 27, 28\", \"21, 24, 25, 29\"})); \n }","void intersect(String firstSourcePath, String secondSourcePath, String resultPath) {\n log.info(\"Start intersect files: {}, {}. Result will be written to {}\", firstSourcePath, secondSourcePath, resultPath);\n\n File firstSourceFile = new File(firstSourcePath);\n File secondSourceFile = new File(secondSourcePath);\n\n if (firstSourceFile.length() == 0 || secondSourceFile.length() == 0) {\n log.info(\"Empty file in input. First source size = {}, second source size = {}\", firstSourceFile.length(), secondSourceFile.length());\n createEmptyFile(resultPath);\n return;\n }\n\n boolean sourcesSwapped = false;\n if (firstSourceFile.length() > secondSourceFile.length()) {\n sourcesSwapped = true;\n File tmp = firstSourceFile;\n firstSourceFile = secondSourceFile;\n secondSourceFile = tmp;\n }\n\n long intersectIdsNumber = 0;\n\n try (DataByIdAccessor firstSourceAccessor = new DataByIdAccessor(firstSourceFile.getAbsolutePath())) {\n try (BufferedReader secondFileReader = new BufferedReader(new FileReader(secondSourceFile))) {\n try (BufferedWriter resultWriter = new BufferedWriter(new FileWriter(resultPath))) {\n String currentId;\n\n while ((currentId = secondFileReader.readLine()) != null) {\n String parsedId = Utils.parseId(currentId);\n String secondSourceData = secondFileReader.readLine();\n\n String firstSourceData = firstSourceAccessor.getDataById(parsedId);\n if (firstSourceData != null) {\n resultWriter.write(currentId);\n resultWriter.newLine();\n\n if (sourcesSwapped) {\n writeData(resultWriter, secondSourceData, firstSourceData);\n } else {\n writeData(resultWriter, firstSourceData, secondSourceData);\n }\n\n intersectIdsNumber++;\n }\n }\n }\n }\n log.info(\"Finished intersect files {}, {}. Result file {}. Intersect ids number = {}\", firstSourcePath, secondSourcePath, resultPath, intersectIdsNumber);\n } catch (IOException e) {\n log.error(\"Intersect files error\", e);\n }\n\n }","void include(Set<S> segments);","@Test\n public void sharedFilterEnsuresUniqueResults() {\n Filter filter = new Filter(\"test-filter\");\n final Dataset dataset1 = new Dataset(\"TEST1\", \"sql\", filter);\n final Dataset dataset2 = new Dataset(\"TEST2\", \"sql2\", filter); // shared same filter\n\n List<String> entry1 = new ArrayList<>();\n entry1.add(\"001\");\n entry1.add(\"aaa\");\n\n List<String> entry2 = new ArrayList<>();\n entry2.add(\"002\");\n entry2.add(\"bbb\");\n\n List<String> entry3 = new ArrayList<>();\n entry3.add(\"003\");\n entry3.add(\"ccc\");\n\n List<String> entry4 = new ArrayList<>();\n entry4.add(\"004\");\n entry4.add(\"ddd\");\n\n List<List<String>> queryResults1 = new ArrayList<>();\n queryResults1.add(entry1);\n queryResults1.add(entry2);\n queryResults1.add(entry3);\n queryResults1.add(entry4);\n\n List<String> entry5 = new ArrayList<>();\n entry5.add(\"005\"); // different\n entry5.add(\"eee\");\n\n List<String> entry6 = new ArrayList<>();\n entry6.add(\"002\"); // same\n entry6.add(\"bbb\");\n\n List<String> entry7 = new ArrayList<>();\n entry7.add(\"007\"); // different\n entry7.add(\"fff\");\n\n List<String> entry8 = new ArrayList<>();\n entry8.add(\"004\"); // same\n entry8.add(\"ddd\");\n\n List<List<String>> queryResults2 = new ArrayList<>();\n queryResults2.add(entry5);\n queryResults2.add(entry6);\n queryResults2.add(entry7);\n queryResults2.add(entry8);\n\n // given\n dataset1.populateCache(queryResults1, 200L);\n dataset2.populateCache(queryResults2, 300L);\n\n // when\n final List<String> result1 = dataset1.getCachedResult();\n final List<String> result2 = dataset1.getCachedResult();\n final List<String> result3 = dataset1.getCachedResult();\n final List<String> result4 = dataset1.getCachedResult();\n final List<String> result5 = dataset2.getCachedResult();\n final List<String> result6 = dataset2.getCachedResult();\n\n // then\n assertEquals(\"Wrong result 1\", entry1, result1); // first datset is as-is\n assertEquals(\"Wrong result 2\", entry2, result2); // first datset is as-is\n assertEquals(\"Wrong result 3\", entry3, result3); // first datset is as-is\n assertEquals(\"Wrong result 4\", entry4, result4); // first datset is as-is\n assertEquals(\"Wrong result 3\", entry5, result5); // second datset, not filtered out\n assertEquals(\"Wrong result 3\", entry7, result6); // second dataset, entry6 is filtered out\n\n // and\n try {\n dataset1.getCachedResult();\n fail(\"Expected to run out of data\");\n\n } catch (IllegalStateException ex) {\n assertEquals(\"Wrong error\", \"No more data available for dataset: TEST1\", ex.getMessage());\n }\n\n try {\n // entry7 should be filtered out, resulting in no more data\n dataset2.getCachedResult();\n fail(\"Expected to run out of data\");\n\n } catch (IllegalStateException ex) {\n assertEquals(\"Wrong error\", \"No more data available for dataset: TEST2\", ex.getMessage());\n }\n\n // and\n assertEquals(\"Wrong cache size\", Optional.of(4), dataset1.getMetrics().getCacheSize());\n assertEquals(\"Wrong timing\", Optional.of(200L), dataset1.getMetrics().getTimingMilliseconds());\n assertEquals(\"Wrong cache requested\", Optional.of(5), dataset1.getMetrics().getCacheRequested());\n assertEquals(\"Wrong filtered out\", Optional.empty(), dataset1.getMetrics().getFilteredOut());\n\n // and\n assertEquals(\"Wrong cache size\", Optional.of(4), dataset2.getMetrics().getCacheSize());\n assertEquals(\"Wrong timing\", Optional.of(300L), dataset2.getMetrics().getTimingMilliseconds());\n assertEquals(\"Wrong cache requested\", Optional.of(3), dataset2.getMetrics().getCacheRequested());\n assertEquals(\"Wrong filtered out\", Optional.of(2), dataset2.getMetrics().getFilteredOut());\n }","public void intersectRoads() {\r\n\t\tfor (Road road : this.roads) {\r\n\t\t\tfor (Integer id : road.getIntersectionIDs()) {\r\n\t\t\t\tfor (Road link : this.roads) {\r\n\t\t\t\t\tif (id == link.getID()) {\r\n\t\t\t\t\t\troad.intersectRoad(link);\r\n\t\t\t\t\t}\r\n\t\t\t\t}\r\n\t\t\t}\r\n\t\t}\r\n\t}","Multimap<String, String> intersects(RectangleLatLng bounds);","@Override\n public SetInterface<T> intersection(SetInterface<T> rhs) {\n //Declare return SetInterface\n SetInterface<T> result = new ArraySet();\n //If the item is in both sets, add it to the result\n //Iterate through the calling Set\n for (int i = 0; i < numItems; i++){\n //if the item is also in RHS, add it to the result\n if(rhs.contains(arr[i]))\n result.addItem(arr[i]);\n }\n return result;\n }","protected abstract NativeSQLStatement createNativeIntersectionStatement(Geometry geom);","public Map<Integer, Boolean> getIntersects(Geometry geom) throws SQLException {\n return retrieveExpected(createNativeIntersectsStatement(geom), BOOLEAN);\n }","@Test\n\tpublic void testRetainAll() {\n\t Set<Integer> setA = new HashSet<>(Arrays.asList(1, 2, 3, 4, 5));\n\t\tSet<Integer> setB = new HashSet<>(Arrays.asList(9, 8, 7, 6, 5, 4, 3));\n\t setA.retainAll(setB);\n\t Set<Integer> intersection = new HashSet<>(Arrays.asList(3, 4, 5));\n\t assertEquals(setA, intersection);\n }","protected abstract List performQuery(String[] ids);","@gw.internal.gosu.parser.ExtendedProperty\n public java.lang.Boolean isIntersection();","Pair<Boolean, List<Result>> execQuery(int matchLimit);","public static void intersection(ArrayList<String> x, ArrayList<String> y, ArrayList<String> z, JTextArea ta) {\n\t\t\n\t\t//This is the loop to add items from list 1 to results array, if the elements are present in both the lists\n\t\tfor (int i=0; i<x.size(); i++)\n\t\t{\n\t\t\tfor (int j=0; j<y.size(); j++)\n\t\t\t{\n\t\t\t\tif (x.get(i).equals(y.get(j))&&!z.contains(x.get(i)))\n\t\t\t\t{\n\t\t\t\t\tz.add(x.get(i));\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t\t\n\t\t\n\t\t//This is the loop to print all the items of the results array list\n\t\tta.setText(\"{ \");\n\t\tfor (int i=0; i<z.size(); i++)\n\t\t{\n\t\t\tta.append(z.get(i)+\" \");\n\t\t}\n\t\tta.append(\"}\");\n\t}","public static void main(String[] args) {\n\t\tArray6 test = new Array6();\n\t\tint[] num1 = { 3, 1, 2 };\n\t\tint[] num2 = { 1 };\n\t\ttest.intersect(num1, num2);\n\t}","static AnalysisResult analyseQueryComponents(ArrayList<String> components) {\n if (components != null && components.size() > 0) {\n for (int i = 0; i < components.size(); i++) {\n String component = components.get(i).toLowerCase();\n for (String attack : commonAttacks) {\n attack = attack.toLowerCase();\n if (trim(component).contains(trim(attack))) {\n return new AnalysisResult(true, i, attack, false);\n }\n }\n }\n }\n return new AnalysisResult(false, null, null, false);\n }","@Override\n public void processElement(ProcessContext c) {\n List<LdVariant> queryList = null;\n List<LdVariant> targetList = null;\n int inputListCount = 0;\n for (KV<Boolean, List<LdVariant>> vl : c.element().getValue()) {\n if (vl.getKey()) {\n queryList = vl.getValue();\n } else {\n targetList = vl.getValue();\n }\n inputListCount++;\n }\n\n if (inputListCount != 2 || queryList == null || targetList == null) {\n throw new IllegalArgumentException(\"There should be exactly two lists.\");\n }\n\n Iterator<LdVariant> targetIter = targetList.iterator();\n\n // Our working set of variants from the target shard that could be within window of variants\n // read in from the query shard.\n LinkedList<LdVariant> storedTarget = new LinkedList<>();\n\n for (LdVariant queryVar : queryList) {\n // Fill in storedTarget until we are past window from queryVar.\n while (targetIter.hasNext()\n && (storedTarget.isEmpty() || (queryVar.getInfo().getEnd() + window) > storedTarget\n .getLast().getInfo().getStart())) {\n storedTarget.add(targetIter.next());\n }\n\n ListIterator<LdVariant> storedTargetIter = storedTarget.listIterator(0);\n while (storedTargetIter.hasNext()) {\n LdVariant targetVar = storedTargetIter.next();\n\n if (queryVar.getInfo().compareTo(targetVar.getInfo()) != -1) {\n // Only do comparisons where query is before target. If query is past target then\n // we are done with target. Note: targetVar > queryVar implies targetVar start >= queryVar\n // start.\n storedTargetIter.remove();\n } else if (targetVar.getInfo().getStart() >= (queryVar.getInfo().getEnd() + window)) {\n // If the next query starts more than window from when target starts, we are done\n // with the rest of storedTarget for this query.\n break;\n } else {\n // If target starts >= query starts and target starts < window from query end, then they\n // must overlap.\n c.output(KV.of(queryVar, targetVar));\n }\n }\n }\n }","List<ProtocolPo> queryByUnion(ProtocolPo query);","public void intersectFromClipboard() { genericClipboard(SetOp.INTERSECT); }","private boolean isIntersectWithSource(List<Pair<Tuple,String>> list1, List<Pair<Tuple,String>> list2) {\n\t\tboolean intersect = false;\n\t\t\n\t\tfor (Pair<Tuple,String> tuple : list1) {\n\t\t\tif (list2.contains(tuple)) {\n\t\t\t\tintersect = true;\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\treturn intersect;\n\t}","public interface SearchQuerySet extends QuerySet\n{\n\n // for AbstractSearch\n public static final int STAT_MODELS = 1;\n public static final int STAT_CLUSTERS = 2;\n public static final int STAT_GENOMES = 4;\n public static final int STAT_MODEL_CLUSTERS = 8;\n\n public String getStatsById(Collection data);\n public String getStatsByQuery(String query);\n public String getStatsById(Collection data,int stats);\n public String getStatsByQuery(String query,int stats);\n \n // for BlastSearch\n public String getBlastSearchQuery(Collection dbNames, Collection keys, KeyTypeUser.KeyType keyType);\n \n //for ClusterIDSearch\n public String getClusterIDSearchQuery(Collection input, int limit, int[] DBs, KeyTypeUser.KeyType keyType);\n \n // for ClusterNameSearch\n public String getClusterNameSearchQuery(Collection input, int limit, int[] DBs, KeyTypeUser.KeyType keyType);\n \n // for DescriptionSearch\n public String getDescriptionSearchQuery(Collection input, int limit, int[] DBs, KeyTypeUser.KeyType keyType);\n \n // for GoSearch \n public String getGoSearchQuery(Collection input, int limit, KeyTypeUser.KeyType keyType);\n \n // for GoTextSearch\n public String getGoTextSearchQuery(Collection input, int limit, KeyTypeUser.KeyType keyType);\n \n // for IdSearch\n public String getIdSearchQuery(Collection input, int limit, int[] DBs, KeyTypeUser.KeyType keyType);\n \n // for QueryCompSearch\n public String getQueryCompSearchQuery(String comp_id, String status, KeyTypeUser.KeyType keyType);\n \n // for QuerySearch\n public String getQuerySearchQuery(String queries_id, KeyTypeUser.KeyType keyType); \n \n // for SeqModelSearch\n public String getSeqModelSearchQuery(Collection model_ids, KeyTypeUser.KeyType keyType);\n \n // for UnknowclusterIdSearch\n public String getUnknownClusterIdSearchQuery(int cluster_id, KeyTypeUser.KeyType keyType);\n \n // for ProbeSetSearch\n public String getProbeSetSearchQuery(Collection input, int limit, KeyTypeUser.KeyType keyType);\n \n // for ProbeSetKeySearch\n public String getProbeSetKeySearchQuery(Collection input, int limit, KeyTypeUser.KeyType keyType);\n \n // for QueryTestSearch\n public String getQueryTestSearchQuery(String query_id, String version, String genome_id);\n \n // for QueryStatsSearch\n public String getQueryStatsSearchQuery(List query_ids,List DBs);\n \n // for PskClusterSearch\n public String getPskClusterSearchQuery(int cluster_id,KeyTypeUser.KeyType keyType);\n \n // for ClusterCorrSearch\n public String getClusterCorrSearchQuery(int cluster_id, int psk_id, KeyTypeUser.KeyType keyType);\n \n // for UnknownGenesSearch\n public String getUnknownGenesSearchQuery(Collection sources, KeyTypeUser.KeyType keyType);\n \n}","public int[] intersect(int[] nums1, int[] nums2) {\n Arrays.sort(nums1);\n Arrays.sort(nums2);\n List<Integer> li = new ArrayList<>();\n int index=0;\n for(int num : nums1){\n int bsIndex = binarySearch(nums2, num, index, nums2.length-1);\n if(bsIndex!=-1){\n li.add(num);\n index=bsIndex+1;\n }\t\n }\n int []ar = new int[li.size()];\n for(int i=0;i<ar.length;i++){\n ar[i]=li.get(i);\n }\n return ar;\n }","private void positionIntersects(LinkedList<TermPositions> p1, LinkedList<TermPositions> p2, int k) {\n if (p1 != null && p2 != null) {\n int df1 = p1.size();\n int df2 = p2.size();\n while (!p1.isEmpty() && !p2.isEmpty()) {\n int tf1 = p1.peek().getPositionList().size();\n int tf2 = p1.peek().getPositionList().size();\n if (p1.peek().getDocId() == p2.peek().getDocId()) {\n LinkedList<Integer> pp1 = p1.peek().getPositionList();\n while (!pp1.isEmpty()) {\n for (Integer integer : p2.peek().getPositionList()) {\n if ((pp1.peek() - integer) < 0 && Math.abs(pp1.peek() - integer) <= (k + 1)) {\n double score = (1 + Math.log(tf1) * Math.log(N / df1)) + (1 + Math.log(tf2) * Math.log(N / df2));\n resultsCollector.add(new DocCollector(p1.peek().getDocId(), score));\n break;\n }\n }\n pp1.pop();\n }\n } else if (p1.peek().getDocId() < p2.peek().getDocId())\n p1.pop();\n else\n p2.pop();\n\n p1.pop();\n p2.pop();\n\n }\n\n }\n\n\n }","public VertexSet intersection(VertexSet ot) {\r\n\t\tVertexSet ans = new VertexSet();\r\n\t\tint i1=0,i2=0;\r\n\t\twhile(i1<this.size() & i2 < ot.size()) {\r\n\t\t\tint a1=this.at(i1), a2 = ot.at(i2);\r\n\t\t\tif(a1==a2) {\r\n\t\t\t\tans.add(a1); i1++; i2++;}\r\n\t\t\telse if(a1<a2) {i1++;}\r\n\t\t\telse i2++;\r\n\t\t}\r\n\t\treturn ans;\r\n\t}","public static <T> Spec<T> intersect(Collection<? extends Spec<T>> specs) {\n if (specs.size() == 0) {\n return satisfyAll();\n }\n return doIntersect(specs);\n }","public Intersection(ListExpression expr1, ListExpression expr2) {\n this.expr1 = expr1;\n this.expr2 = expr2;\n }","private DocFile[] search (String[] queries, String[] filters, BooleanClause.Occur filterOccur) throws ParseException {\n // create a master query builder\n BooleanQuery.Builder masterQueryBuilder = new BooleanQuery.Builder();\n // loop through all queries\n for (String query : queries) {\n if (query.equals(\"\")) continue;\n // create a boolean query for the each query\n BooleanQuery.Builder queryBuilder = new BooleanQuery.Builder();\n // loop through all filters\n for (String filter : filters) {\n if (filter.equals(\"\")) continue;\n QueryParser parser = new QueryParser(filter, analyzer);\n parser.setAllowLeadingWildcard(true);\n if (!filter.equals(Constants.INDEX_KEY_OWNER)) {\n Query parsedQ = parser.parse(query);\n queryBuilder.add(parsedQ, filterOccur);\n }\n else {\n queryBuilder.add(new PhraseQuery(filter, queries), filterOccur);\n }\n }\n masterQueryBuilder.add(queryBuilder.build(), BooleanClause.Occur.SHOULD);\n }\n\n // build the masterQuery\n BooleanQuery masterQuery = masterQueryBuilder.build();\n\n return searchResponse(searchExec(masterQuery), masterQuery);\n }","StatementChain and(ProfileStatement... statements);","@Test\n\tpublic void integrationTest1() throws Exception {\n\t\tHashSet<String> mistress = loadGrepResults(\"mistress\");\n\t\tHashSet<String> undocumented = loadGrepResults(\"undocumented\");\n\t\tHashSet<String> forced = loadGrepResults(\"!i+am+forced\");\n\t\t\n\t\tHashSet<String> grepFound = new HashSet<String>(mistress);\n\t\tgrepFound.retainAll(undocumented);\n\t\tgrepFound.addAll(forced);\n\t\t\n\t\tCollection<Page> index = queryTest.query(\"mistress & undocumented | (!\\\"I am forced\\\")\");\n\t\tHashSet<String> indexFound = new HashSet<String>();\n\n\t\tfor (Page p : index)\n\t\t\tindexFound.add(p.getURL().getPath().toLowerCase());\n\t\t\n\t\tassertEquals(indexFound, grepFound);\n\t}","private void searchHashMap(String[] searchKey, String callNumber,int startYear, int endYear) {\n\t\t/* Temporarily stores next 'values' for a title keyword */\n\t\tArrayList<Integer> tempStore = new ArrayList<Integer>();\n\t\t/* Stores only the intersection 'values' of title keywords */\n\t\tCollection<Integer> intersection = new ArrayList<Integer>();\n\t\t/* Counts number of keywords found */\n\t\tint foundKeys = 0;\n\n\t\t/* Loop to iterate through title keywords and get key-value pair intersection */\n\t\tfor (String key : searchKey) {\n\t\t\tif (titleHashMap.containsKey(key)) {\n\t\t\t\tfoundKeys = foundKeys + 1;\n\t\t\t\ttempStore.addAll((titleHashMap.get(key))); /* Stores all found values */\n\t\t\t\tif (intersection.size() == 0) {\n\t\t\t\t\tintersection.addAll(titleHashMap.get(key));\n\t\t\t\t}\n\t\t\t\tintersection.retainAll(tempStore); /* Stores only common 'values' */\n\t\t\t\ttempStore.clear(); /* Clears temporary array*/\n\t\t\t}\n\t\t}\n\n\t\t/* Checks if all keywords were found */\n\t\tif(searchKey.length == foundKeys){\n\t\t/* Performs search of other fields via the reduced list of 'values' for matched record */\n\t\tfor (Integer i : intersection) {\n\t\t\tif ((callNumber.equals(\"\") || items.get(i.intValue()).getCallNumber().equalsIgnoreCase(callNumber))\n\t\t\t\t\t&& (items.get(i.intValue()).getYear() >= startYear && items.get(i.intValue()).getYear() <= endYear)) {\n\t\t\t\tSystem.out.println(\"--------------------------------------------\");\n\t\t\t\tSystem.out.println(items.get(i.intValue())); /* Prints found records from master list 'Reference' */\n\t\t\t\tSystem.out.println(\"--------------------------------------------\");\n\t\t\t}\n\t\t}\n\t\t}\n\t}","public void queryTaskUnionSet1() {\r\n\t\t// task 1\r\n\t\tTask task1 = new Task();\r\n\t\ttask1.setName(\"DEFECTS\");\r\n\t\ttask1.setDisplayName(\"Defects\");\r\n\t\ttask1.setDescription(\"User story to address product defects\");\r\n\t\ttask1 = (Task) aggregateService.create(task1, new Settings());\t\r\n\r\n\t\t// task 2\r\n\t\tTask task2 = new Task();\r\n\t\ttask2.setName(\"FIX_DEFECTS\");\r\n\t\ttask2.setDisplayName(\"Fix defects\");\r\n\t\ttask2.setDescription(\"Task to track the defect fixing effort\");\r\n\t\ttask2 = (Task) aggregateService.create(task2, new Settings());\r\n\r\n\t\t// task 3\r\n\t\tTask task3 = new Task();\r\n\t\ttask3.setName(\"PRIORITIZE_DEFECTS\");\r\n\t\ttask3.setDisplayName(\"Prioritize defects\");\r\n\t\ttask3.setDescription(\"Based upon the effort required for the defects prioritize them\");\r\n\t\ttask3 = (Task) aggregateService.create(task3, new Settings());\r\n\r\n\t\ttask1 = (Task) aggregateService.read(task1, getSettings());\t\t\r\n\r\n\t\t// query the task object\r\n\t\tSettings settings = new Settings();\r\n\t\tsettings.setParam(\"name1\", \"FIX_DEFECTS\");\r\n\t\tsettings.setParam(\"name2\", \"PRIORITIZE_DEFECTS\");\r\n\t\tsettings.setView(aggregateService.getView(\"TASKUNIONSET\"));\t\t\r\n\t\tList<?> toList = aggregateService.query(new Task(), settings);\r\n\r\n\t\tassert(toList.size() == 2);\r\n\r\n\t\tObject obj1 = toList.get(0);\r\n\t\tObject obj2 = toList.get(1);\r\n\r\n\t\tassert(Task.class.isAssignableFrom(obj1.getClass()));\r\n\t\tassert(Task.class.isAssignableFrom(obj2.getClass()));\r\n\t\t\r\n\t\tTask t1 = (Task) obj1;\r\n\t\tTask t2 = (Task) obj2;\t\t\r\n\t\t\r\n\t\tassert( (t1.getName().equals(\"FIX_DEFECTS\") && t2.getName().equals(\"PRIORITIZE_DEFECTS\")) ||\r\n\t\t\t\t(t2.getName().equals(\"FIX_DEFECTS\") && t1.getName().equals(\"PRIORITIZE_DEFECTS\")) );\r\n\t}","public void testSearchByContent() {\n Message m1 = new Message(\"test\",\"bla bla david moshe\",_u1);\n Message.incId();\n try {\n Thread.sleep(10);\n } catch (InterruptedException ex) {\n ex.printStackTrace();\n }\n Message m2 = new Message(\"test2\",\"bla2 bla david tikva moshe\",_u1);\n Message.incId();\n Message m3 = new Message(\"test2\",\"moshe cohen\",_u1);\n Message.incId();\n\n this.allMsgs.put(m1.getMsg_id(), m1);\n this.allMsgs.put(m2.getMsg_id(), m2);\n this.allMsgs.put(m3.getMsg_id(), m3);\n\n this.searchEngine.addData(m1);\n this.searchEngine.addData(m2);\n this.searchEngine.addData(m3);\n\n /* SearchHit[] result = this.searchEngine.searchByContent(\"bla2\", 0,1);\n assertTrue(result.length==1);\n assertTrue(result[0].getMessage().equals(m2));\n\n SearchHit[] result2 = this.searchEngine.searchByContent(\"bla david tikva\", 0,2);\n assertTrue(result2.length==1);\n assertEquals(result2[0].getScore(),3.0);\n //assertEquals(result2[1].getScore(),2.0);\n assertTrue(result2[0].getMessage().equals(m2));\n //assertTrue(result2[1].getMessage().equals(m1));\n\n SearchHit[] result3 = this.searchEngine.searchByContent(\"bla2 tikva\", 0, 5);\n assertTrue(result3.length==0);\n */\n\n/*\n SearchHit[] result4 = this.searchEngine.searchByContent(\"bla OR tikva\", 0, 5);\n assertTrue(result4.length==2);\n assertTrue(result4[0].getMessage().equals(m2));\n assertTrue(result4[1].getMessage().equals(m1));\n\n SearchHit[] result5 = this.searchEngine.searchByContent(\"bla AND cohen\", 0, 5);\n assertTrue(result5.length==0);\n\n result5 = this.searchEngine.searchByContent(\"bla AND moshe\",0,5);\n assertTrue(result5.length==2);\n assertTrue(result5[0].getScore() == result5[1].getScore());\n assertTrue(result5[0].getMessage().equals(m2));\n assertTrue(result5[1].getMessage().equals(m1));\n\n result5 = this.searchEngine.searchByContent(\"bla AND moshe\", 10, 11);\n assertTrue(result5.length==0);\n */\n\n }","public void queryTaskUnionSet2() {\r\n\t\t// task 1\r\n\t\tTask task1 = new Task();\r\n\t\ttask1.setName(\"DEFECTS\");\r\n\t\ttask1.setDisplayName(\"Defects\");\r\n\t\ttask1.setDescription(\"User story to address product defects\");\r\n\t\t\r\n\t\tTask d1 = new Task();\r\n\t\td1.setName(\"DEFECT 1\");\r\n\t\td1.setDisplayName(\"Defect 1\");\r\n\t\td1.setDescription(\"First defect\");\r\n\t\tTask d2 = new Task();\r\n\t\td2.setName(\"DEFECT 2\");\r\n\t\td2.setDisplayName(\"Defect 2\");\r\n\t\td2.setDescription(\"Second defect\");\r\n\t\tSet<Task> c = new HashSet<Task>();\r\n\t\tc.add(d1);\r\n\t\tc.add(d2);\r\n\t\ttask1.setTaskChildren(c);\r\n\t\ttask1 = (Task) aggregateService.create(task1, new Settings());\r\n\r\n\t\t\tSystem.out.println(\"Name: \" + task1.getName() + \", Id: \" + task1.getId());\r\n\r\n\t\t// task 2\r\n\t\tTask task2 = new Task();\r\n\t\ttask2.setName(\"FIX_DEFECTS\");\r\n\t\ttask2.setDisplayName(\"Fix defects\");\r\n\t\ttask2.setDescription(\"Task to track the defect fixing effort\");\r\n\t\ttask2 = (Task) aggregateService.create(task2, new Settings());\r\n\r\n\t\t// task 3\r\n\t\tTask task3 = new Task();\r\n\t\ttask3.setName(\"PRIORITIZE_DEFECTS\");\r\n\t\ttask3.setDisplayName(\"Prioritize defects\");\r\n\t\ttask3.setDescription(\"Based upon the effort required for the defects prioritize them\");\r\n\t\ttask3 = (Task) aggregateService.create(task3, new Settings());\r\n\r\n\t\ttask1 = (Task) aggregateService.read(task1, getSettings());\t\t\r\n\r\n\t\t// query the task object\r\n\t\tSettings settings = new Settings();\r\n\t\tsettings.setParam(\"name1\", \"DEFECTS\");\r\n\t\tsettings.setParam(\"name2\", \"PRIORITIZE_DEFECTS\");\r\n\t\tsettings.setParam(\"name3\", \"FIX_DEFECTS\");\r\n\t\tsettings.addFunction(FunctionHandler.NE, \"name\", \"name3\");\r\n\t\tsettings.addFunction(FunctionType.ASC, \"name\");\r\n\t\tsettings.setView(aggregateService.getView(\"TASKUNIONSET\"));\t\t\r\n\t\tList<?> toList = aggregateService.query(new Task(), settings);\r\n\r\n\t\tSystem.out.println(\"SIZE : \" + toList.size());\r\n\t\tfor(Object o: toList) {\r\n\t\t\tTask t = (Task) o;\r\n\t\t\tSystem.out.println(\"Name: \" + t.getName() + \", Id: \" + t.getId());\r\n\t\t}\r\n\t\tassert(toList.size() == 2);\r\n\r\n\t\tObject obj1 = toList.get(0);\r\n\t\tObject obj2 = toList.get(1);\r\n\r\n\t\tassert(Task.class.isAssignableFrom(obj1.getClass()));\r\n\t\tassert(Task.class.isAssignableFrom(obj2.getClass()));\r\n\t\t\r\n\t\tTask t1 = (Task) obj1;\r\n\t\tTask t2 = (Task) obj2;\r\n\r\n\t\tassert ((t1.getName().equals(\"DEFECTS\") && t2.getName().equals(\"PRIORITIZE_DEFECTS\")) ||\r\n\t\t\t(t2.getName().equals(\"DEFECTS\") && t1.getName().equals(\"PRIORITIZE_DEFECTS\")));\r\n\r\n\t\tTask d = t1.getName().equals(\"DEFECTS\") ? t1 : t2;\r\n\t\tassert (d.getTaskChildren() != null && d.getTaskChildren().size() == 2);\r\n\r\n//\t\tSystem.out.println(\"Task 1: \" + t1.getName() + \", Task 2: \" + t2.getName());\r\n//\t\tassert (t1.getName().equals(\"DEFECTS\") && t2.getName().equals(\"DEFECT 1\"));\r\n//\t\tassert(t1.getTaskChildren() != null && t1.getTaskChildren().size() == 2);\r\n\t}","public void multipleQueriesASync(List<IndexQuery> queries, APIClientListener listener) {\n TaskParams.Client params = new TaskParams.Client(listener, APIMethod.MultipleQueries, queries, \"none\");\n new ASyncClientTask().execute(params);\n }","public static ArrayList<Integer> getIntersection(int[] array1,int[] array2){\n HashMap<Integer,Boolean> map=new HashMap<>();\n ArrayList<Integer> list=new ArrayList<>();\n for(int i=0;i<array1.length;i++){\n map.put(array1[i],false);\n }\n for(int j=0;j<array2.length;j++){\n if(map.containsKey(array2[j])){\n map.put(array2[j],true); \n }\n }\n Set<Map.Entry<Integer,Boolean>> entries=map.entrySet();\n for(Map.Entry<Integer,Boolean> entry:entries){\n if(entry.getValue()){\n list.add(entry.getKey());\n }\n }\n\n return list;\n }","private List<Object[]> executeDayQuery(\n List<Object> segments, List<Object> workplaces,\n String Eq1startTime, String Eq1endTime,\n String Eq2startTime, String Eq2endTime,\n String Eq3startTime, String Eq3endTime) {\n try {\n //Clear all tables\n //################# Declared Harness Data #################### \n Helper.startSession();\n\n String query_str_1 = \"(SELECT 'Matin' as shift,'%s' As start_time, '%s' as end_time, \"\n + \"bh.segment AS segment, \"\n + \"bh.workplace AS workplace, \"\n + \"bh.harness_part AS harness_part, \"\n + \"bh.std_time AS std_time, \"\n + \"COUNT(bh.harness_part) AS produced_qty, \"\n + \"SUM(bh.std_time) AS produced_hours \"\n + \"FROM base_harness bh, base_container bc \"\n + \"WHERE bc.id = bh.container_id \"\n + \"AND bh.create_time BETWEEN '%s' AND '%s' \"\n + \"AND bh.segment IN (:segments) \"\n + \"AND bh.workplace IN (:workplaces) \"\n + \"GROUP BY bh.segment, bh.workplace, bh.harness_part, bh.std_time)\";\n\n query_str_1 = String.format(query_str_1, Eq1startTime, Eq1endTime, Eq1startTime, Eq1endTime);\n\n String query_str_2 = \"(SELECT 'Soir' as shift,'%s' As start_time, '%s' as end_time, \"\n + \"bh.segment AS segment, \"\n + \"bh.workplace AS workplace, \"\n + \"bh.harness_part AS harness_part, \"\n + \"bh.std_time AS std_time, \"\n + \"COUNT(bh.harness_part) AS produced_qty, \"\n + \"SUM(bh.std_time) AS produced_hours \"\n + \"FROM base_harness bh, base_container bc \"\n + \"WHERE bc.id = bh.container_id \"\n + \"AND bh.create_time BETWEEN '%s' AND '%s' \"\n + \"AND bh.segment IN (:segments) \"\n + \"AND bh.workplace IN (:workplaces) \"\n + \"GROUP BY bh.segment, bh.workplace, bh.harness_part, bh.std_time)\";\n\n query_str_2 = String.format(query_str_2, Eq2startTime, Eq2endTime, Eq2startTime, Eq2endTime);\n\n String query_str_3 = \"(SELECT 'Nuit' as shift,'%s' As start_time, '%s' as end_time, \"\n + \"bh.segment AS segment, \"\n + \"bh.workplace AS workplace, \"\n + \"bh.harness_part AS harness_part, \"\n + \"bh.std_time AS std_time, \"\n + \"COUNT(bh.harness_part) AS produced_qty, \"\n + \"SUM(bh.std_time) AS produced_hours \"\n + \"FROM base_harness bh, base_container bc \"\n + \"WHERE bc.id = bh.container_id \"\n + \"AND bh.create_time BETWEEN '%s' AND '%s' \"\n + \"AND bh.segment IN (:segments) \"\n + \"AND bh.workplace IN (:workplaces)\"\n + \"GROUP BY bh.segment, bh.workplace, bh.harness_part, bh.std_time) \";\n\n query_str_3 = String.format(query_str_3, Eq3startTime, Eq3endTime, Eq3startTime, Eq3endTime);\n\n String query_str = \"SELECT * FROM (\"\n + query_str_1 + \" UNION \"\n + query_str_2 + \" UNION \"\n + query_str_3\n + \") results ORDER BY start_time ASC, segment ASC, workplace ASC, harness_part ASC\";\n\n SQLQuery query = Helper.sess.createSQLQuery(query_str);\n\n query.addScalar(\"shift\", StandardBasicTypes.STRING)\n .addScalar(\"start_time\", StandardBasicTypes.STRING)\n .addScalar(\"end_time\", StandardBasicTypes.STRING)\n .addScalar(\"segment\", StandardBasicTypes.STRING)\n .addScalar(\"workplace\", StandardBasicTypes.STRING)\n .addScalar(\"harness_part\", StandardBasicTypes.STRING)\n .addScalar(\"std_time\", StandardBasicTypes.DOUBLE)\n .addScalar(\"produced_qty\", StandardBasicTypes.INTEGER)\n .addScalar(\"produced_hours\", StandardBasicTypes.DOUBLE)\n .setParameterList(\"segments\", segments)\n .setParameterList(\"workplaces\", workplaces);\n\n this.dataResultList = query.list();\n\n Helper.sess.getTransaction().commit();\n\n return this.dataResultList;\n\n } catch (HibernateException e) {\n if (Helper.sess.getTransaction() != null) {\n Helper.sess.getTransaction().rollback();\n }\n }\n\n return this.dataResultList;\n }","public void test_containsII() {\n\tfinal int COUNT = 60000000;\n\t\n\tRectangle r = new Rectangle(1, 2, 3, 4);\n\n\tPerformanceMeter meter = createMeter(\"contains\");\n\tmeter.start();\n\tfor (int i = 0; i < COUNT; i++) {\n\t\tr.contains(2, 3);\t// does contain\n\t}\n\tmeter.stop();\n\t\n\tdisposeMeter(meter);\n\t\n\tmeter = createMeter(\"disjoint\");\n\tmeter.start();\n\tfor (int i = 0; i < COUNT; i++) {\n\t\tr.contains(9, 12);\t// does not contain\n\t}\n\tmeter.stop();\n\t\n\tdisposeMeter(meter);\n}","@Test\n public void testBoundsAsCompositesWithSingleEqAndMultiINRestrictions()\n {\n CFMetaData cfMetaData = newCFMetaData(Sort.ASC, Sort.ASC, Sort.ASC, Sort.ASC);\n\n ByteBuffer value1 = ByteBufferUtil.bytes(1);\n ByteBuffer value2 = ByteBufferUtil.bytes(2);\n ByteBuffer value3 = ByteBufferUtil.bytes(3);\n ByteBuffer value4 = ByteBufferUtil.bytes(4);\n ByteBuffer value5 = ByteBufferUtil.bytes(5);\n\n // clustering_0 = 1 AND (clustering_1, clustering_2) IN ((2, 3), (4, 5))\n Restriction singleEq = newSingleEq(cfMetaData, 0, value1);\n Restriction multiIN = newMultiIN(cfMetaData, 1, asList(value2, value3), asList(value4, value5));\n PrimaryKeyRestrictions restrictions = new PrimaryKeyRestrictionSet(cfMetaData.comparator);\n restrictions = restrictions.mergeWith(singleEq).mergeWith(multiIN);\n\n List<Composite> bounds = restrictions.boundsAsComposites(cfMetaData, Bound.START, QueryOptions.DEFAULT);\n assertEquals(2, bounds.size());\n assertComposite(bounds.get(0), value1, value2, value3, EOC.START);\n assertComposite(bounds.get(1), value1, value4, value5, EOC.START);\n\n bounds = restrictions.boundsAsComposites(cfMetaData, Bound.END, QueryOptions.DEFAULT);\n assertEquals(2, bounds.size());\n assertComposite(bounds.get(0), value1, value2, value3, EOC.END);\n assertComposite(bounds.get(1), value1, value4, value5, EOC.END);\n\n // clustering_0 = 1 AND (clustering_1, clustering_2) IN ((2, 3))\n singleEq = newSingleEq(cfMetaData, 0, value1);\n multiIN = newMultiIN(cfMetaData, 1, asList(value2, value3));\n restrictions = new PrimaryKeyRestrictionSet(cfMetaData.comparator);\n restrictions = restrictions.mergeWith(multiIN).mergeWith(singleEq);\n\n bounds = restrictions.boundsAsComposites(cfMetaData, Bound.START, QueryOptions.DEFAULT);\n assertEquals(1, bounds.size());\n assertComposite(bounds.get(0), value1, value2, value3, EOC.START);\n\n bounds = restrictions.boundsAsComposites(cfMetaData, Bound.END, QueryOptions.DEFAULT);\n assertEquals(1, bounds.size());\n assertComposite(bounds.get(0), value1, value2, value3, EOC.END);\n\n // clustering_0 = 1 AND clustering_1 = 5 AND (clustering_2, clustering_3) IN ((2, 3), (4, 5))\n singleEq = newSingleEq(cfMetaData, 0, value1);\n Restriction singleEq2 = newSingleEq(cfMetaData, 1, value5);\n multiIN = newMultiIN(cfMetaData, 2, asList(value2, value3), asList(value4, value5));\n restrictions = new PrimaryKeyRestrictionSet(cfMetaData.comparator);\n restrictions = restrictions.mergeWith(singleEq).mergeWith(multiIN).mergeWith(singleEq2);\n\n bounds = restrictions.boundsAsComposites(cfMetaData, Bound.START, QueryOptions.DEFAULT);\n assertEquals(2, bounds.size());\n assertComposite(bounds.get(0), value1, value5, value2, value3, EOC.START);\n assertComposite(bounds.get(1), value1, value5, value4, value5, EOC.START);\n\n bounds = restrictions.boundsAsComposites(cfMetaData, Bound.END, QueryOptions.DEFAULT);\n assertEquals(2, bounds.size());\n assertComposite(bounds.get(0), value1, value5, value2, value3, EOC.END);\n assertComposite(bounds.get(1), value1, value5, value4, value5, EOC.END);\n }","private <T> ArrayList<T> intersection(ArrayList<T> list1, ArrayList<T> list2) {\n ArrayList<T> list = new ArrayList<T>();\n\n for (T t : list1) {\n if (list2.contains(t)) {\n list.add(t);\n }\n }\n\n return list;\n }","private ExampleSetBuilder performInnerJoin(ExampleSet leftExampleSet, ExampleSet rightExampleSet,\n\t\t\tList<AttributeSource> originalAttributeSources, List<Attribute> unionAttributeList,\n\t\t\tPair<Attribute[], Attribute[]> keyAttributes) throws ProcessStoppedException {\n\t\tExampleSetBuilder builder = ExampleSets.from(unionAttributeList);\n\n\t\tAttribute[] leftKeyAttributes = null;\n\t\tAttribute[] rightKeyAttributes = null;\n\t\tMap<DoubleArrayWrapper, List<Example>> rightKeyMapping = null;\n\t\tboolean useId = getParameterAsBoolean(PARAMETER_USE_ID);\n\n\t\tif (!useId) {\n\t\t\t// create key mapping for right example set\n\t\t\tleftKeyAttributes = keyAttributes.getFirst();\n\t\t\trightKeyAttributes = keyAttributes.getSecond();\n\t\t\trightKeyMapping = createKeyMapping(rightExampleSet, rightKeyAttributes, leftKeyAttributes);\n\t\t}\n\n\t\tint progressCounter = 0;\n\t\t// iterate over all example from left table and search for matching examples in right table:\n\t\tfor (Example leftExample : leftExampleSet) {\n\n\t\t\tList<Example> matchingRightExamples = getMatchingExamples(leftExampleSet, rightExampleSet, leftKeyAttributes,\n\t\t\t\t\trightKeyMapping, useId, leftExample);\n\n\t\t\tif (matchingRightExamples != null) {\n\t\t\t\tfor (Example rightExample : matchingRightExamples) {\n\t\t\t\t\taddCombinedOccurence(originalAttributeSources, unionAttributeList, builder, leftExample, rightExample);\n\t\t\t\t}\n\t\t\t}\n\n\t\t\t// trigger operator progress every 100 examples\n\t\t\t++progressCounter;\n\t\t\tif (progressCounter % 100 == 0) {\n\t\t\t\tgetProgress().step(100);\n\t\t\t\tprogressCounter = 0;\n\t\t\t}\n\t\t}\n\t\treturn builder;\n\t}","public static ArrayList<Card> intersection(ArrayList<Meld> melds) {\n\t\tArrayList<Card> intersections = new ArrayList<Card>();\n\n\t\t// check every combination of two melds\n\t\tfor (int i = 0; i < melds.size(); i++) {\n\t\t\tfor (int j = i; j < melds.size(); j++) {\n\t\t\t\tif (i != j) {\n\t\t\t\t\tMeld m1 = melds.get(i);\n\t\t\t\t\tMeld m2 = melds.get(j);\n\t\t\t\t\tfor (int k = 0; k < 3; k++) {\n\t\t\t\t\t\tCard c1 = m1.cards[k];\n\t\t\t\t\t\tfor (int l = 0; l < 3; l++) {\n\t\t\t\t\t\t\tCard c2 = m2.cards[l];\n\n\t\t\t\t\t\t\t// if the card is in both melds, add it to the list\n\t\t\t\t\t\t\tif (c1.equals(c2)) intersections.add(c1);\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t\treturn intersections;\n\t}","private Range<Token> intersect(Range<Token> serverRange, AbstractBounds<Token> requestedRange)\n {\n if (serverRange.contains(requestedRange.left) && serverRange.contains(requestedRange.right)) {\n //case 1: serverRange fully encompasses requestedRange\n return new Range<Token>(requestedRange.left, requestedRange.right, partitioner);\n } else if (requestedRange.contains(serverRange.left) && requestedRange.contains(serverRange.right)) {\n //case 2: serverRange is fully encompasses by requestedRange\n //serverRange is already the intersection\n return new Range<Token>(serverRange.left, serverRange.right);\n } else if (serverRange.contains(requestedRange.left) && requestedRange.contains(serverRange.right)) {\n //case 3: serverRange overlaps on the left: sR.left < rR.left < sR.right < rR.right\n return new Range<Token>(requestedRange.left, serverRange.right, partitioner);\n } else if (requestedRange.contains(serverRange.left) && serverRange.contains(requestedRange.right)) {\n //case 4: serverRange overlaps on the right rR.left < sR.left < rR.right < sR.right\n return new Range<Token>(serverRange.left, requestedRange.right, partitioner);\n } else if (!serverRange.contains(requestedRange.left) && !serverRange.contains(requestedRange.right) &&\n !requestedRange.contains(serverRange.left) && !requestedRange.contains(serverRange.right)) {\n //case 5: totally disjoint\n return null;\n } else {\n assert false : \"Failed intersecting serverRange = (\" + serverRange.left + \", \" + serverRange.right + \") and requestedRange = (\" + requestedRange.left + \", \" + requestedRange.right + \")\";\n return null;\n }\n }","private static boolean intersect(\n\t\tDateTime start1, DateTime end1,\n\t\tDateTime start2, DateTime end2)\n\t{\n\t\tif (DateTime.op_LessThanOrEqual(end2, start1) || DateTime.op_LessThanOrEqual(end1, start2))\n\t\t\treturn false;\n\n\t\treturn true;\n\t}"],"string":"[\n \"@Test\\r\\n\\t\\tpublic void testIntersection() {\\n\\t\\t\\ttestingSet = new IntegerSet(list1);\\r\\n\\t\\t\\ttestingSet2= new IntegerSet(list2);\\r\\n\\t\\t\\t// create 3rdset = to the intersection list \\r\\n\\t\\t\\ttestingSet3= new IntegerSet(intersection);\\r\\n\\t\\t\\t// create 4th set =to the intersection of set1 and set2\\r\\n\\t\\t\\ttestingSet4= testingSet.intersection(testingSet, testingSet2);\\r\\n\\t\\t\\t// sets 3 and set 4 should be equal \\r\\n\\t\\t\\t// assertEquals for these parameters is a deprecated method \\r\\n\\t\\t\\tassertArrayEquals(testingSet3.toArray(),testingSet4.toArray());\\t \\r\\n\\t\\t}\",\n \"private void addQueries(String query){\\n ArrayList <String> idsFullSet = new ArrayList <String>(searchIDs);\\n while(idsFullSet.size() > 0){\\n ArrayList <String> idsSmallSet = new ArrayList <String>(); \\n if(debugMode) {\\n System.out.println(\\\"\\\\t Pmids not used in query available : \\\" + idsFullSet.size());\\n }\\n idsSmallSet.addAll(idsFullSet.subList(0,Math.min(getSearchIdsLimit(), idsFullSet.size())));\\n idsFullSet.removeAll(idsSmallSet);\\n String idsConstrain =\\\"\\\";\\n idsConstrain = idsConstrain(idsSmallSet);\\n addQuery(query,idsConstrain);\\n }\\n }\",\n \"private static Set<Item> multiSetIntersection(List<Set<Item>> setList) {\\n Set<Item> interQrels = new HashSet<>(setList.get(0));\\r\\n \\r\\n for (int i = 1; i< setList.size();i++) {\\r\\n interQrels.retainAll(setList.get(i)); // intersection with two (and one)\\r\\n }\\r\\n\\r\\n return interQrels;\\r\\n }\",\n \"private static Set<Dataset> findDatasets(Datasource d, String query) {\\n String[] words = query.split(\\\"\\\\\\\\+\\\");\\n Set<String> keyWords = new HashSet<String>();\\n for (String word : words) {\\n keyWords.add(word.toLowerCase());\\n }\\n Set<Dataset> ret = new HashSet<Dataset>();\\n String tags;\\n for (Dataset set : d.getDatasets()) {\\n tags = set.getTags();\\n if (intersects(tags, keyWords)) {\\n ret.add(set);\\n }\\n } \\n return ret;\\n }\",\n \"@Test\\n public void testIntersection3()\\n {\\n List<Integer> expected = new ArrayList<>();\\n ConciseSet set1 = new ConciseSet();\\n ConciseSet set2 = new ConciseSet();\\n for (int i = 0; i < 1000; i++) {\\n set1.add(i);\\n set2.add(i);\\n expected.add(i);\\n }\\n\\n verifyIntersection(expected, set1, set2);\\n }\",\n \"protected abstract NativeSQLStatement createNativeIntersectsStatement(Geometry geom);\",\n \"protected abstract Iterable<E> getIntersecting(D lower, D upper);\",\n \"@Test\\n public void testIntersection4()\\n {\\n List<Integer> expected = new ArrayList<>();\\n ConciseSet set1 = new ConciseSet();\\n ConciseSet set2 = new ConciseSet();\\n for (int i = 0; i < 1000; i++) {\\n set1.add(i);\\n if (i != 500) {\\n set2.add(i);\\n expected.add(i);\\n }\\n }\\n\\n verifyIntersection(expected, set1, set2);\\n }\",\n \"@Test\\n public void testIntersection6()\\n {\\n List<Integer> expected = new ArrayList<>();\\n ConciseSet set1 = new ConciseSet();\\n for (int i = 0; i < 5; i++) {\\n set1.add(i);\\n }\\n for (int i = 1000; i < 1005; i++) {\\n set1.add(i);\\n }\\n\\n ConciseSet set2 = new ConciseSet();\\n for (int i = 800; i < 805; i++) {\\n set2.add(i);\\n }\\n for (int i = 806; i < 1005; i++) {\\n set2.add(i);\\n }\\n\\n for (int i = 1000; i < 1005; i++) {\\n expected.add(i);\\n }\\n\\n verifyIntersection(expected, set1, set2);\\n }\",\n \"@Test\\n public void testIntersection5()\\n {\\n final int[] ints1 = {33, 100000};\\n final int[] ints2 = {34, 200000};\\n List<Integer> expected = new ArrayList<>();\\n\\n ConciseSet set1 = new ConciseSet();\\n for (int i : ints1) {\\n set1.add(i);\\n }\\n ConciseSet set2 = new ConciseSet();\\n for (int i : ints2) {\\n set2.add(i);\\n }\\n\\n verifyIntersection(expected, set1, set2);\\n }\",\n \"public static List<String> query_intersect(List<String> queryWords) throws IOException {\\n\\t\\tif (!initialized) initialize();\\n\\t\\tList<PostingList> pls = new ArrayList<PostingList> ();\\n\\t\\tfor (String queryWord : queryWords) {\\n\\t\\t\\tqueryWord = queryWord.toLowerCase();\\n\\t\\t\\tif (!termDict.containsKey(queryWord)) {\\n\\t\\t\\t\\tpls.clear();\\n\\t\\t\\t\\tbreak;\\n\\t\\t\\t}\\n\\t\\t\\tPostingList pl = readPosting(fc, termDict.get(queryWord));\\n\\t\\t\\tif (pl == null) {\\n\\t\\t\\t\\tpls.clear();\\n\\t\\t\\t\\tbreak;\\n\\t\\t\\t}\\n\\t\\t\\tpls.add(readPosting(fc, termDict.get(queryWord)));\\n\\t\\t}\\n\\t\\tCollections.sort(pls, new Comparator<PostingList>(){\\n\\t\\t public int compare(PostingList p1, PostingList p2) {\\n\\t\\t return p1.size() - p2.size(); // assumes you want biggest to smallest\\n\\t\\t }\\n\\t\\t});\\n\\t\\tif (pls.size() == 0) {\\n\\t\\t\\treturn null;\\n\\t\\t} else {\\n\\t\\t\\tList<Integer> current = pls.get(0).getList();\\n\\t\\t\\tfor (int i = 1; i < pls.size(); i++) {\\n\\t\\t\\t\\tList<Integer> toBeAdd = pls.get(i).getList();\\n\\t\\t\\t\\tcurrent = intersect(current, toBeAdd);\\n\\t\\t\\t}\\n\\t\\t\\tif (current.size() == 0) {\\n\\t\\t\\t\\treturn null;\\n\\t\\t\\t} else {\\n\\t\\t\\t\\tList<String> result = new ArrayList<String>();\\n\\t\\t\\t\\tfor (int docId : current) {\\n\\t\\t\\t\\t\\tresult.add(docDict.get(docId));\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\treturn result;\\n\\t\\t\\t}\\n\\t\\t}\\n\\t}\",\n \"@Test\\n public void testIntersection1()\\n {\\n final int[] ints1 = {33, 100000};\\n final int[] ints2 = {33, 100000};\\n List<Integer> expected = Arrays.asList(33, 100000);\\n\\n ConciseSet set1 = new ConciseSet();\\n for (int i : ints1) {\\n set1.add(i);\\n }\\n ConciseSet set2 = new ConciseSet();\\n for (int i : ints2) {\\n set2.add(i);\\n }\\n\\n verifyIntersection(expected, set1, set2);\\n }\",\n \"public ArrayList<ArrayList> intersection (ArrayList<ArrayList> data, ArrayList<ArrayList> data2)\\n {\\n ArrayList<Document> docs = data.get(0);\\n ArrayList<Double> relevance = data.get(1);\\n ArrayList<Integer> occurrence = data.get(2);\\n ArrayList<Integer> popularity = data.get(3);\\n \\n ArrayList<Document> docs2 = data2.get(0);\\n ArrayList<Double> relevance2 = data2.get(1);\\n ArrayList<Integer> occurrence2 = data2.get(2);\\n ArrayList<Integer> popularity2 = data2.get(3);\\n \\n ArrayList<Document> docs3 = new ArrayList<>();\\n ArrayList<Double> relevance3 = new ArrayList<>();\\n ArrayList<Integer> occurrence3 = new ArrayList<>();\\n ArrayList<Integer> popularity3 = new ArrayList<>();\\n \\n for(Document d: docs)\\n {\\n if(docs2.contains(d))\\n {\\n docs3.add(d);\\n int docIndex = docs.indexOf(d);\\n int docIndex2 = docs2.indexOf(d);\\n double oldRel = (double) relevance.get(docIndex);\\n int oldOcc = (int) occurrence.get(docIndex);\\n relevance3.add(oldRel+relevance2.get(docIndex2));\\n if(oldOcc > occurrence2.get(docIndex2))\\n {\\n occurrence3.add(occurrence2.get(docIndex2));\\n }\\n else\\n {\\n occurrence3.add(oldOcc);\\n }\\n popularity3.add(d.popularity);\\n }\\n \\n }\\n data = new ArrayList<ArrayList> ();\\n data.add(docs3);\\n data.add(relevance3);\\n data.add(occurrence3);\\n data.add(popularity3);\\n \\n return data;\\n }\",\n \"@Test\\n public void testIntersection2()\\n {\\n final int[] ints1 = {33, 100000};\\n final int[] ints2 = {34, 100000};\\n List<Integer> expected = Collections.singletonList(100000);\\n\\n ConciseSet set1 = new ConciseSet();\\n for (int i : ints1) {\\n set1.add(i);\\n }\\n ConciseSet set2 = new ConciseSet();\\n for (int i : ints2) {\\n set2.add(i);\\n }\\n\\n verifyIntersection(expected, set1, set2);\\n }\",\n \"public ArrayList<SearchResult> partialSearch(Collection<String> queries) {\\n\\t\\tArrayList<SearchResult> results = new ArrayList<>();\\n\\t\\tHashMap<String, SearchResult> track = new HashMap<>();\\n\\n\\t\\tfor (String query : queries) {\\n\\t\\t\\tfor (String word : this.invertedIndex.tailMap(query).keySet()) {\\n\\t\\t\\t\\tif (word.startsWith(query)) {\\n\\t\\t\\t\\t\\tsearchHelper(results, word, track);\\n\\t\\t\\t\\t} else {\\n\\t\\t\\t\\t\\tbreak;\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\tCollections.sort(results);\\n\\t\\treturn results;\\n\\t}\",\n \"public static void main(String[] args) {\\n\\t\\tInteger[] firstArray = {0,2,4,6,8};\\n\\t Integer[] secondArray = {1,3,10,4,7,8,9};\\n\\t \\n\\t intersectionUsingSet(firstArray, secondArray);\\n\\n\\t System.out.println();\\n\\t \\n\\t // Array with duplicate elements in the array\\n\\t Integer[] firstArray1 = {0,2,2,4,6,6,8};\\n\\t Integer[] secondArray2 = {1,3,10,10,4,7,8,9};\\n\\t \\n\\t intersectionUsingSet(firstArray1, secondArray2);\\n\\t}\",\n \"public intersection(){}\",\n \"QueryResult(Pair<Integer, String>[] queries) {\\n results = new ConcurrentHashMap<>(queries.length);\\n for (Pair<Integer, String> query : queries)\\n results.put(query.first, new int[0]);\\n }\",\n \"public static void main(String[] args) {\\n\\t\\tint [] a = {3,4,5,6};\\n\\t\\tint [] b = {1,2,3};\\t\\n\\t\\tint [] c = {7,8,9};\\t\\n\\t\\tint [] d = {};\\n\\t\\tSystem.out.println(intersection(a,b)); //true\\n\\t\\tSystem.out.println(intersection(b,c)); //false\\n\\t\\tSystem.out.println(intersection(a,c)); //false\\n\\t\\tSystem.out.println(intersection(a,d)); //false\\n\\t\\t}\",\n \"public void intersect(Collection<String> ids) {\\n mSelection.retainAll(ids);\\n mProvisionalSelection.retainAll(ids);\\n }\",\n \"@Test\\n public void mapContains() {\\n check(MAPCONT);\\n query(MAPCONT.args(MAPNEW.args(), 1), false);\\n query(MAPCONT.args(MAPENTRY.args(1, 2), 1), true);\\n }\",\n \"public static void main(String[] args) {\\n\\t\\tSystem.out.println(Arrays.toString(intersect(new int[]{1, 2, 3, 4}, new int[]{1, 2, 3, 4, 1, 2, 3, 4})));\\n\\t}\",\n \"@Test(expected = NullPointerException.class)\\r\\n\\t\\tpublic void testIntersectionWithNullInput() {\\r\\n\\t\\t\\ttestingSet = new IntegerSet(null);\\r\\n\\t\\t\\ttestingSet2= new IntegerSet(null); \\r\\n\\t\\t\\t\\r\\n\\t\\t\\t// union of 2 null sets \\r\\n\\t\\t\\ttestingSet3= testingSet.intersection(testingSet, testingSet2);\\r\\n\\t\\t}\",\n \"@Test\\n public void testBatchedInQuery() {\\n TestDataCreator creator = new TestDataCreator(getSessionFactory());\\n Town town = creator.createTestTown();\\n\\n int n = 10;\\n List<Long> ids = new ArrayList<>(n);\\n for (long i=0; i < n; i++) {\\n Person savedPerson = creator.createTestPerson(town, \\\"P\\\" + i);\\n ids.add(savedPerson.getId());\\n }\\n for (long i=0; i < n; i++) {\\n creator.createTestPerson(town, \\\"P\\\" + i);\\n }\\n\\n Person person = query.from(Person.class);\\n query.where(person.getId()).in(ids, 2);\\n\\n validate(\\\"from Person hobj1 where hobj1.id in (:np1)\\\", ids);\\n assertEquals(n, doQueryResult.size());\\n }\",\n \"public static void main(String[] args) {\\n\\t\\tIntersection l5=new Intersection(5,null);\\n\\t\\tIntersection l4=new Intersection(4,l5);\\n\\t\\tIntersection l3=new Intersection(3,l4);\\n\\t\\tIntersection l2=new Intersection(2,l3);\\n\\t\\tIntersection l1=new Intersection(1,l2);\\n\\t\\t\\n\\t\\tIntersection m7=new Intersection(7,l3);\\n\\t\\tIntersection m6=new Intersection(6,m7);\\n\\t\\tint flag=0;\\n\\t\\twhile(m6!=null && l1!=null){\\n\\t\\t\\tif(m6!=l1){\\n\\t\\t\\t\\tm6=m6.next;\\n\\t\\t\\t\\tl1=l1.next;\\n\\t\\t\\t}\\n\\t\\t\\telse{\\n\\t\\t\\t\\tflag=1;\\n\\t\\t\\t\\tbreak;\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\tif(flag==1){\\n\\t\\t\\tSystem.out.println(\\\"They Intersect!\\\");\\n\\t\\t}\\n\\t\\telse{\\n\\t\\t\\tSystem.out.println(\\\"They don't!\\\");\\n\\t\\t}\\n\\t}\",\n \"public static void intersectionUsingSet(Integer[] firstArray, Integer[] secondArray)\\n\\t{\\n\\t LinkedHashSet<Integer> set = new LinkedHashSet<Integer>();\\n\\t \\n\\t set.addAll(Arrays.asList(firstArray));\\n\\t \\n\\t set.retainAll(Arrays.asList(secondArray));\\n\\t \\n\\t Integer[] intersectionArray = set.toArray(new Integer[set.size()]);\\n\\t \\n\\t System.out.println(\\\"Intersection of two arrays using set is : \\\");\\n\\t \\n\\t for(int i=0; i<intersectionArray.length; i++)\\n\\t {\\n\\t \\tSystem.out.print(intersectionArray[i]+\\\" \\\");\\n\\t }\\n\\t}\",\n \"public Set intersection(Set intersect){\\n Set newSet = new Set();\\n for(int element = 0; element < intersect.size(); element++){\\n if(elementOf(intersect.getSet()[element]))\\n newSet.add(intersect.getSet()[element]);\\n }\\n return newSet;\\n }\",\n \"private Set<String> getIntersection( Set<String> a, Set<String> b ) {\\n\\t\\tSet<String> intersection = new HashSet<String>(a);\\n\\t\\tintersection.retainAll(b);\\n\\t\\treturn intersection;\\n\\t}\",\n \"public ZYSet<ElementType> intersection(ZYSet<ElementType> otherSet){\\n ZYSet<ElementType> result = new ZYArraySet<ElementType>();\\n for(ElementType e :this){\\n if(otherSet.contains(e)){\\n result.add(e);\\n }\\n }\\n return result;\\n }\",\n \"@Test\\n\\tpublic void integrationTest2() throws Exception {\\n\\t\\tHashSet<String> mistress = loadGrepResults(\\\"mistress\\\");\\n\\t\\tHashSet<String> undocumented = loadGrepResults(\\\"undocumented\\\");\\n\\t\\tHashSet<String> insane = loadGrepResults(\\\"insane\\\");\\n\\t\\tHashSet<String> crazy = loadGrepResults(\\\"crazy\\\");\\n\\t\\tHashSet<String> forced = loadGrepResults(\\\"!i+am+forced\\\");\\n\\t\\t\\n\\t\\tHashSet<String> grepFound = new HashSet<String>(mistress);\\n\\t\\tgrepFound.retainAll(undocumented);\\n\\t\\tHashSet<String> temp = new HashSet<String>(crazy);\\n\\t\\ttemp.retainAll(forced);\\n\\t\\tgrepFound.addAll(temp);\\n\\t\\tgrepFound.addAll(insane);\\n\\t\\t\\n\\t\\tCollection<Page> index = queryTest.query(\\\"insane | crazy & !\\\\\\\"I am forced\\\\\\\" | mistress & undocumented\\\");\\n\\t\\tHashSet<String> indexFound = new HashSet<String>();\\n\\n\\t\\tfor (Page p : index)\\n\\t\\t\\tindexFound.add(p.getURL().getPath().toLowerCase());\\n\\t\\t\\n\\t\\tassertEquals(indexFound, grepFound);\\n\\t}\",\n \"public void testUsingQueriesFromQueryManger(){\\n\\t\\tSet<String> names = testDataMap.keySet();\\n\\t\\tUtils.prtObMess(this.getClass(), \\\"atm query\\\");\\n\\t\\tDseInputQuery<BigDecimal> atmq = \\n\\t\\t\\t\\tqm.getQuery(new AtmDiot());\\n\\t\\tMap<String, ComplexQueryResult<BigDecimal>> bdResult = \\n\\t\\t\\t\\tatmq.get(names, 1, TimeUnit.SECONDS);\\n\\t\\tCollectionsStaticMethods.prtMapItems(bdResult);\\n\\n\\t\\tUtils.prtObMess(this.getClass(), \\\"vol query\\\");\\n\\t\\tDseInputQuery<BigDecimal> volq = \\n\\t\\t\\t\\tqm.getQuery(new VolDiotForTest());\\n\\t\\tMap<String, ComplexQueryResult<BigDecimal>> dbResult = \\n\\t\\t\\t\\tvolq.get(names, 1, TimeUnit.SECONDS);\\n\\t\\tCollectionsStaticMethods.prtMapItems(dbResult);\\n\\t\\n\\t\\tUtils.prtObMess(this.getClass(), \\\"integer query\\\");\\n\\t\\tDseInputQuery<BigDecimal> strikeq = \\n\\t\\t\\t\\tqm.getQuery(new StrikeDiotForTest());\\n\\t\\tMap<String, ComplexQueryResult<BigDecimal>> strikeResult = \\n\\t\\t\\t\\tstrikeq.get(names, 1, TimeUnit.SECONDS);\\n\\t\\tCollectionsStaticMethods.prtMapItems(strikeResult);\\n\\t\\n\\t}\",\n \"public void getIntersection(int[] A, int[] B, ArrayList<int[]> intersections) \\n {\\n if (A[0] >= B[0] && A[0] <= B[1]) \\n {\\n if (A[1] >= B[0] && A[1] <= B[1]) \\n {\\n // Take the entirety of A\\n intersections.add(A);\\n } \\n else \\n {\\n // Take the start of A to end of B\\n int[] intersection = new int[]{A[0], B[1]};\\n intersections.add(intersection);\\n }\\n } \\n else \\n {\\n if (A[1] >= B[0] && A[1] <= B[1]) \\n {\\n // Take start of B to end of A\\n int[] intersection = new int[]{B[0], A[1]};\\n intersections.add(intersection);\\n } \\n else \\n {\\n if (A[0] < B[0] && A[1] > B[1]) \\n {\\n // Take the entirety of B\\n intersections.add(B);\\n } \\n else \\n {\\n // No intersection at all\\n return;\\n }\\n }\\n }\\n }\",\n \"public static void main(String[] args) {\\n\\t\\t\\n\\tint[] firstArr =\\t{1,2,3,4,5};\\n\\tint[] secondArr =\\t{2,3,4,9,6,10};\\n\\tSet<Integer> set = new HashSet<Integer>();\\n\\tfor(int i=0; i<secondArr.length; i++) {\\n\\t\\tset.add(secondArr[i]);\\n\\t}\\n\\tfor(int i=0; i<firstArr.length; i++) {\\n\\t\\tboolean status =set.add(firstArr[i]);\\n\\t\\tif(status==false) {\\n\\t\\t\\tSystem.out.println(\\\"Intersection Elements :\\\"+firstArr[i]);\\n\\t }\\n\\t}\\n }\",\n \"public void sensibleMatches1() \\n { \\n Map<String, Set<String>> clientMap = new HashMap<>();\\n Set<String> interests = new HashSet<>();\\n\\n interests.add(\\\"Food\\\");\\n interests.add(\\\"Wine\\\");\\n interests.add(\\\"Tandems\\\");\\n clientMap.put(\\\"Hal\\\", interests);\\n\\t \\n interests = new HashSet<>();\\n interests.add(\\\"Food\\\");\\n interests.add(\\\"Walking\\\");\\n interests.add(\\\"Welding\\\");\\n clientMap.put(\\\"Gemma\\\", interests);\\n\\t \\n interests = new HashSet<>();\\n interests.add(\\\"Food\\\");\\n interests.add(\\\"Cinema\\\");\\n interests.add(\\\"Wine\\\");\\n clientMap.put(\\\"Caroline\\\", interests);\\n\\n Set<String> halsInterests = clientMap.get(\\\"Hal\\\");\\n String outputString;\\n Set<String> eachClientInterests;\\n Set<String> intersection ;\\n\\n Map<String, Set<String>> mapWithoutHal = new HashMap<>(clientMap);\\n mapWithoutHal.remove(\\\"Hal\\\");\\n for (String eachClient : mapWithoutHal.keySet()) \\n {\\n eachClientInterests = clientMap.get(eachClient);\\n intersection = new HashSet<>(halsInterests);\\n intersection.retainAll(eachClientInterests);\\n outputString = \\\"Hal and \\\" + eachClient \\n + \\\" have common interests: \\\"\\n + intersection;\\n System.out.println(outputString);\\n }\\n }\",\n \"private Set<String> intersection(Set<String> s1, Set<String> s2) {\\n Set<String> intersection = new HashSet<>(s1);\\n intersection.retainAll(s2);\\n return intersection;\\n }\",\n \"public PostingsList intersect(PostingsList l1, PostingsList l2){\\n\\n PostingsList intersection = new PostingsList();\\n\\n // Counters to iterate docIDs\\n int count1 = 0;\\n int count2 = 0;\\n\\n // First posting\\n PostingsEntry p1 = l1.get(0);\\n PostingsEntry p2 = l2.get(0);\\n\\n while(true){\\n // Match - EUREKA! //\\n if (p1.docID == p2.docID){\\n // Add match\\n intersection.insert(p1.docID);\\n // Increase counters\\n count1++;\\n count2++;\\n // Go to next postings (check for nullpointer)\\n if (count1<l1.size() && count2<l2.size()){\\n p1 = l1.get(count1);\\n p2 = l2.get(count2);\\n }\\n else\\n break;\\n }\\n // No match\\n else if (p1.docID < p2.docID){\\n count1++;\\n if (count1<l1.size())\\n p1 = l1.get(count1);\\n else\\n break;\\n }\\n // No match\\n else{\\n count2++;\\n if (count2<l2.size())\\n p2 = l2.get(count2);\\n else\\n break;\\n }\\n }\\n\\n return intersection;\\n }\",\n \"@Override\\r\\n public void intersect( Ray ray, IntersectResult result ) {\\n\\t\\r\\n }\",\n \"public void matchesDemo() \\n {\\n Map<String, Set<String>> clientMap = new HashMap<>();\\n Set<String> interests = new HashSet<>();\\n\\n interests.add(\\\"Food\\\");\\n interests.add(\\\"Wine\\\");\\n interests.add(\\\"Tandems\\\");\\n clientMap.put(\\\"Hal\\\", interests);\\n\\t \\n interests = new HashSet<>();\\n interests.add(\\\"Food\\\");\\n interests.add(\\\"Walking\\\");\\n interests.add(\\\"Welding\\\");\\n clientMap.put(\\\"Gemma\\\", interests);\\n\\t \\n interests = new HashSet<>();\\n interests.add(\\\"Food\\\");\\n interests.add(\\\"Cinema\\\");\\n interests.add(\\\"Wine\\\");\\n clientMap.put(\\\"Caroline\\\", interests);\\n\\n Set<String> halsInterests = clientMap.get(\\\"Hal\\\");\\n String outputString;\\n Set<String> eachClientInterests;\\n Set<String> intersection;\\n\\n for (String eachClient : clientMap.keySet()) \\n {\\n eachClientInterests = clientMap.get(eachClient);\\n intersection = new HashSet<>(halsInterests);\\n intersection.retainAll(eachClientInterests);\\n outputString = \\\"Hal and \\\" + eachClient \\n + \\\" have common interests: \\\"\\n + intersection;\\n System.out.println(outputString) ;\\n }\\n }\",\n \"void findMatchings(boolean isProtein) {\\n\\n GraphDatabaseFactory dbFactory = new GraphDatabaseFactory();\\n HashSet<String > searchSpaceList = new HashSet<>();\\n GraphDatabaseService databaseService = dbFactory.newEmbeddedDatabase(graphFile);\\n for (int id: queryGraphNodes.keySet()) {\\n if(isProtein)\\n searchSpaceList.add(queryGraphNodes.get(id).label);\\n else\\n searchSpaceList.add(String.valueOf(queryGraphNodes.get(id).labels.get(0)));\\n }\\n for(String x: searchSpaceList) {\\n ResourceIterator<Node> xNodes;\\n try(Transaction tx = databaseService.beginTx()) {\\n xNodes = databaseService.findNodes(Label.label(x));\\n tx.success();\\n }\\n\\n while (xNodes.hasNext()) {\\n Node node = xNodes.next();\\n if (searchSpaceProtein.containsKey(x))\\n searchSpaceProtein.get(x).add(node.getId());\\n else {\\n HashSet<Long> set = new HashSet<>();\\n set.add(node.getId());\\n searchSpaceProtein.put(x, set);\\n }\\n }\\n\\n }\\n\\n if(isProtein)\\n search(0, databaseService, true);\\n else\\n search(0, databaseService, false);\\n databaseService.shutdown();\\n }\",\n \"public int[] intersection(int[] nums1, int[] nums2) {\\n \\n HashSet<Integer> set = new HashSet<>();\\n ArrayList<Integer> inter = new ArrayList<>();\\n if(nums1.length > nums2.length)\\n {\\n for(int i = 0; i < nums1.length ;i ++)\\n set.add(nums1[i]);\\n\\n for(int i = 0; i < nums2.length ;i ++)\\n if(set.contains(nums2[i])&& !inter.contains(nums2[i]))\\n inter.add(nums2[i]);\\n }\\n else {\\n for(int i = 0; i < nums2.length ;i ++)\\n set.add(nums2[i]);\\n\\n for(int i = 0; i < nums1.length ;i ++)\\n if(set.contains(nums1[i]) && !inter.contains(nums1[i]))\\n inter.add(nums1[i]);\\n }\\n\\n int [] arr = new int[inter.size()];\\n for(int i = 0; i < arr.length ;i ++)\\n arr[i] = inter.get(i);\\n return arr;\\n\\n }\",\n \"public ArrayList<SearchResult> exactSearch(Collection<String> queries) {\\n\\t\\tArrayList<SearchResult> results = new ArrayList<>();\\n\\t\\tHashMap<String, SearchResult> track = new HashMap<>();\\n\\n\\t\\tfor (String query : queries) {\\n\\t\\t\\tif (invertedIndex.containsKey(query)) {\\n\\t\\t\\t\\tsearchHelper(results, query, track);\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\tCollections.sort(results);\\n\\t\\treturn results;\\n\\t}\",\n \"public void testQuery() throws Exception {\\n DummyApprovalRequest req1 = new DummyApprovalRequest(reqadmin, null, caid, SecConst.EMPTY_ENDENTITYPROFILE, false);\\n DummyApprovalRequest req2 = new DummyApprovalRequest(admin1, null, caid, SecConst.EMPTY_ENDENTITYPROFILE, false);\\n DummyApprovalRequest req3 = new DummyApprovalRequest(admin2, null, 3, 2, false);\\n\\n approvalSessionRemote.addApprovalRequest(admin1, req1, gc);\\n approvalSessionRemote.addApprovalRequest(admin1, req2, gc);\\n approvalSessionRemote.addApprovalRequest(admin1, req3, gc);\\n\\n // Make som queries\\n Query q1 = new Query(Query.TYPE_APPROVALQUERY);\\n q1.add(ApprovalMatch.MATCH_WITH_APPROVALTYPE, BasicMatch.MATCH_TYPE_EQUALS, \\\"\\\" + req1.getApprovalType());\\n\\n List result = approvalSessionRemote.query(admin1, q1, 0, 3, \\\"cAId=\\\" + caid, \\\"(endEntityProfileId=\\\" + SecConst.EMPTY_ENDENTITYPROFILE + \\\")\\\");\\n assertTrue(\\\"Result size \\\" + result.size(), result.size() >= 2 && result.size() <= 3);\\n\\n result = approvalSessionRemote.query(admin1, q1, 1, 3, \\\"cAId=\\\" + caid, \\\"(endEntityProfileId=\\\" + SecConst.EMPTY_ENDENTITYPROFILE + \\\")\\\");\\n assertTrue(\\\"Result size \\\" + result.size(), result.size() >= 1 && result.size() <= 3);\\n\\n result = approvalSessionRemote.query(admin1, q1, 0, 1, \\\"cAId=\\\" + caid, \\\"(endEntityProfileId=\\\" + SecConst.EMPTY_ENDENTITYPROFILE + \\\")\\\");\\n assertTrue(\\\"Result size \\\" + result.size(), result.size() == 1);\\n\\n Query q2 = new Query(Query.TYPE_APPROVALQUERY);\\n q2.add(ApprovalMatch.MATCH_WITH_STATUS, BasicMatch.MATCH_TYPE_EQUALS, \\\"\\\" + ApprovalDataVO.STATUS_WAITINGFORAPPROVAL, Query.CONNECTOR_AND);\\n q2.add(ApprovalMatch.MATCH_WITH_REQUESTADMINCERTSERIALNUMBER, BasicMatch.MATCH_TYPE_EQUALS, reqadmincert.getSerialNumber().toString(16));\\n\\n result = approvalSessionRemote.query(admin1, q1, 1, 3, \\\"cAId=\\\" + caid, \\\"(endEntityProfileId=\\\" + SecConst.EMPTY_ENDENTITYPROFILE + \\\")\\\");\\n assertTrue(\\\"Result size \\\" + result.size(), result.size() >= 1 && result.size() <= 3);\\n\\n // Remove the requests\\n int id1 = ((ApprovalDataVO) approvalSessionRemote.findApprovalDataVO(admin1, req1.generateApprovalId()).iterator().next()).getId();\\n int id2 = ((ApprovalDataVO) approvalSessionRemote.findApprovalDataVO(admin1, req2.generateApprovalId()).iterator().next()).getId();\\n int id3 = ((ApprovalDataVO) approvalSessionRemote.findApprovalDataVO(admin1, req3.generateApprovalId()).iterator().next()).getId();\\n approvalSessionRemote.removeApprovalRequest(admin1, id1);\\n approvalSessionRemote.removeApprovalRequest(admin1, id2);\\n approvalSessionRemote.removeApprovalRequest(admin1, id3);\\n }\",\n \"public static void main(String[] args) {\\n\\t\\tint[] nums1 = {4,9,5};\\r\\n\\t\\tint[] nums2 = {9,4,9,8,4};\\r\\n\\t\\t//System.out.println(intersection(nums1, nums2));\\r\\n\\t\\tArrays.sort(nums1);\\r\\n\\t\\tArrays.sort(nums2);\\r\\n\\t\\tif (nums1.length>nums2.length) {\\r\\n\\t\\t\\tint[] temp = nums2;\\r\\n\\t\\t\\tnums2 = nums1;\\r\\n\\t\\t\\tnums1 = temp;\\r\\n\\t\\t}\\r\\n\\t\\tHashSet<Integer> mSet1 = new HashSet<Integer>();\\r\\n\\t\\tHashSet<Integer> mSet2 = new HashSet<Integer>();\\r\\n\\t\\tfor (Integer i : nums2) {\\r\\n\\t\\t\\tmSet1.add(i);\\r\\n\\t\\t}\\r\\n\\t\\tfor (Integer x: nums1) {\\r\\n\\t\\t\\tif (mSet1.contains(x)) {\\r\\n\\t\\t\\t\\tmSet2.add(x);\\r\\n\\t\\t\\t}\\r\\n\\t\\t}\\r\\n\\t\\tint[] r = new int[mSet2.size()];\\r\\n\\t\\tint index = 0;\\r\\n\\t\\tfor (Integer g: mSet2) {\\r\\n\\t\\t\\tr[index] = g;\\r\\n\\t\\t\\tindex++;\\r\\n\\t\\t}\\r\\n\\t}\",\n \"public static int[] intersection(int[] nums1, int[] nums2) {\\n if(nums1 == null || nums2 == null){\\n return null;\\n }\\n HashSet<Integer> set = new HashSet<>();\\n for (int aNubs1 : nums1) {\\n set.add(aNubs1);\\n }\\n HashSet<Integer> result = new HashSet<>();\\n for (int aNubs2 : nums2) {\\n if (set.contains(aNubs2) && !result.contains(aNubs2)) {\\n result.add(aNubs2);\\n }\\n }\\n int [] intersection = new int[result.size()];\\n int index = 0;\\n for(int temp : result){\\n intersection[index++] = temp;\\n }\\n return intersection;\\n }\",\n \"public void sensibleMatches2() \\n { \\n Map<String, Set<String>> clientMap = new HashMap<>();\\n Set<String> interests = new HashSet<>();\\n\\n interests.add(\\\"Food\\\");\\n interests.add(\\\"Wine\\\");\\n interests.add(\\\"Tandems\\\");\\n clientMap.put(\\\"Hal\\\", interests);\\n\\t \\n interests = new HashSet<>();\\n interests.add(\\\"Food\\\");\\n interests.add(\\\"Walking\\\");\\n interests.add(\\\"Welding\\\");\\n clientMap.put(\\\"Gemma\\\", interests);\\n\\n interests = new HashSet<>();\\n interests.add(\\\"Food\\\");\\n interests.add(\\\"Cinema\\\");\\n interests.add(\\\"Wine\\\");\\n clientMap.put(\\\"Caroline\\\", interests);\\n\\n Set<String> halsInterests = clientMap.get(\\\"Hal\\\");\\n String outputString;\\n Set<String> eachClientInterests;\\n Set<String> intersection ;\\n\\n for (String eachClient : clientMap.keySet()) \\n {\\n if (!eachClient.equals(\\\"Hal\\\")) \\n {\\n eachClientInterests = clientMap.get(eachClient);\\n intersection = new HashSet<>(halsInterests);\\n intersection.retainAll(eachClientInterests);\\n outputString = \\\"Hal and \\\" + eachClient \\n + \\\" have common interests: \\\"\\n + intersection;\\n System.out.println(outputString);\\n }\\n }\\n }\",\n \"protected <Ty> HashSet<Ty> intersection(HashSet<Ty> setA, HashSet<Ty> setB) {\\n HashSet<Ty> retSet = new HashSet<>();\\n for (Ty t : setA) {\\n if (setB.contains(t)) {\\n retSet.add(t);\\n }\\n }\\n return retSet;\\n }\",\n \"QueryResult(String... queries) {\\n results = new ConcurrentHashMap<>(queries.length);\\n for (String query : queries)\\n results.put(query.hashCode(), new int[0]);\\n }\",\n \"public int[] intersection1(int[] nums1, int[] nums2) {\\n Set<Integer> nums1Set = new HashSet<>();\\n Set<Integer> nums2Set = new HashSet<>();\\n\\n for (int i = 0; i < nums1.length; i++) {\\n nums1Set.add(nums1[i]);\\n }\\n for (int i = 0; i < nums2.length; i++) {\\n nums2Set.add(nums2[i]);\\n }\\n\\n nums1Set.retainAll(nums2Set);\\n\\n int[] res = new int[nums1Set.size()];\\n int i = 0;\\n for (int s: nums1Set) {\\n res[i++] = s;\\n }\\n return res;\\n }\",\n \"public int[] intersectionUsingSets(int[] nums1, int[] nums2) {\\n Set<Integer> setA = new HashSet<>();\\n Set<Integer> intersection = new HashSet<>();\\n for (int num : nums1) {\\n setA.add(num);\\n }\\n\\n for (int num : nums2) {\\n if (setA.contains(num)) {\\n intersection.add(num);\\n }\\n }\\n\\n return getIntersectionResult(intersection);\\n }\",\n \"public void intersectionOf(IntegerSet set1, IntegerSet set2) {\\n get = new int[0];\\n for (int i : set1.get)\\n if (set2.hasElement(i))\\n insertElement(i);\\n }\",\n \"@Test\\n public void testBoundsAsCompositesWithMultiEqRestrictions()\\n {\\n CFMetaData cfMetaData = newCFMetaData(Sort.ASC, Sort.ASC);\\n\\n ByteBuffer value1 = ByteBufferUtil.bytes(1);\\n ByteBuffer value2 = ByteBufferUtil.bytes(2);\\n Restriction eq = newMultiEq(cfMetaData, 0, value1, value2);\\n PrimaryKeyRestrictions restrictions = new PrimaryKeyRestrictionSet(cfMetaData.comparator);\\n restrictions = restrictions.mergeWith(eq);\\n\\n List<Composite> bounds = restrictions.boundsAsComposites(cfMetaData, Bound.START, QueryOptions.DEFAULT);\\n assertEquals(1, bounds.size());\\n assertComposite(bounds.get(0), value1, value2, EOC.START);\\n\\n bounds = restrictions.boundsAsComposites(cfMetaData, Bound.END, QueryOptions.DEFAULT);\\n assertEquals(1, bounds.size());\\n assertComposite(bounds.get(0), value1, value2, EOC.END);\\n }\",\n \"public void searchArea(Connection connection, String city, String state, int zip) throws SQLException {\\n\\n ResultSet rs = null;\\n PreparedStatement pStmt = null;\\n String sql1 = \\\"SELECT hotel_name, branch_id FROM Hotel_Address WHERE city = ?\\\";\\n String sql2 = \\\"SELECT hotel_name, branch_id FROM Hotel_Address WHERE state = ?\\\";\\n String sql3 = \\\"SELECT hotel_name, branch_id FROM Hotel_Address WHERE zip = ?\\\";\\n\\n // City and State combination:\\n if (city != null && state != null){\\n\\n pStmt = connection.prepareStatement(sql1 + \\\" INTERSECT \\\" + sql2);\\n pStmt.clearParameters();\\n\\n setCity(city);\\n pStmt.setString(1, getCity());\\n setState(state);\\n pStmt.setString(2, getState());\\n }\\n\\n // City and ZIP combination:\\n else if (city != null){\\n\\n pStmt = connection.prepareStatement(sql1 + \\\" INTERSECT \\\" + sql3);\\n pStmt.clearParameters();\\n\\n setCity(city);\\n pStmt.setString(1, getCity());\\n setZip(zip);\\n pStmt.setInt(2, getZip());\\n }\\n\\n // State and ZIP combination:\\n else {\\n\\n pStmt = connection.prepareStatement(sql2 + \\\" INTERSECT \\\" + sql3);\\n pStmt.clearParameters();\\n\\n setState(state);\\n pStmt.setString(1, getState());\\n setZip(zip);\\n pStmt.setInt(2, getZip());\\n }\\n\\n try {\\n\\n System.out.println(\\\" Hotels in area:\\\");\\n System.out.println(\\\"+------------------------------------------------------------------------------+\\\");\\n\\n rs = pStmt.executeQuery();\\n String result;\\n\\n while (rs.next()) {\\n\\n System.out.println(rs.getString(1) + \\\" \\\" + rs.getInt(2));\\n }\\n }\\n catch (SQLException e) { throw e; }\\n finally {\\n pStmt.close();\\n if(rs != null) { rs.close(); }\\n }\\n }\",\n \"public static Set<Doc> and(Set<Doc> set1, Set<Doc> set2) {\\r\\n \\t\\t\\r\\n \\t\\tif((set1 == null) || (set2 == null)) {\\r\\n\\t\\t\\tSystem.err.println(\\\"Doc.and() returning null!\\\");\\r\\n \\t\\t\\treturn new TreeSet<Doc>();\\r\\n \\t\\t}\\r\\n \\t\\t//set1.retainAll(set2);\\r\\n \\t\\t//return set1;\\r\\n \\t\\t\\r\\n \\t\\tTreeSet<Doc> result = new TreeSet<Doc>();\\r\\n \\t\\tIterator<Doc> op1 = set1.iterator();\\r\\n \\t\\tIterator<Doc> op2 = set2.iterator();\\r\\n \\t\\t\\r\\n \\t\\tDoc current1 = getNext(op1);\\r\\n \\t\\tDoc current2 = getNext(op2);\\r\\n \\r\\n \\t\\twhile(current1!=null && current2!=null) {\\r\\n \\t\\t\\t//If is the same document\\r\\n \\t\\t\\tif(current1.getID() == current2.getID()) {\\r\\n \\t\\t\\t\\tresult.add(current1);\\r\\n \\t\\t\\t\\tcurrent1 = getNext(op1);\\r\\n \\t\\t\\t\\tcurrent2 = getNext(op2);\\r\\n \\t\\t\\t}\\r\\n \\t\\t\\t//If op2 is ahead of op1\\r\\n \\t\\t\\telse if(current1.getID() < current2.getID()) \\r\\n \\t\\t\\t\\tcurrent1 = getNext(op1);\\r\\n \\t\\t\\t//If op1 is ahead of op2\\r\\n \\t\\t\\telse\\r\\n \\t\\t\\t\\tcurrent2 = getNext(op2);\\r\\n \\t\\t}\\r\\n \\t\\t\\r\\n \\t\\treturn result;\\r\\n \\t}\",\n \"@Test\\n public void test1() {\\n final List<String> listA = Arrays.asList(\\\"Fremont\\\", \\\"Dublin\\\", \\\"anamole\\\", \\\"San Jose\\\" , \\\"SFO\\\", \\\"Dublin\\\", \\\"San Jose\\\", \\\"paramount\\\", \\\"y\\\");\\n final List<String> listB = Arrays.asList(\\\"Dublin\\\", \\\"san mateo\\\", \\\"los angeles\\\", \\\"san mateo\\\", \\\"fremont\\\", \\\"anamole\\\", \\\"x\\\", \\\"x\\\", \\\"Y\\\");\\n final List<String> common = FindIntersection.findCommonLists(listA, listB);\\n System.out.println(Arrays.toString(FindIntersection.findCommonLists(listA, listB).toArray()));\\n\\n }\",\n \"private boolean intersectsAggregate( Aggregate mprim ) throws Exception {\\n boolean inter = false;\\n\\n int cnt = mprim.getSize();\\n\\n for ( int i = 0; i < cnt; i++ ) {\\n if ( intersects( mprim.getObjectAt( i ) ) ) {\\n inter = true;\\n break;\\n }\\n }\\n\\n return inter;\\n }\",\n \"public static void main(String[] args) {\\n\\t\\t\\r\\n\\t\\tint arr1[] = {3,2,11,4,6,7};\\r\\n\\t\\tint arr2[] = {1,2,8,4,9,7};\\r\\n\\t\\t\\r\\n\\t\\tList<Integer> list1 = new ArrayList<Integer>();\\r\\n\\t\\t\\r\\n\\t\\tList<Integer> list2 = new ArrayList<Integer>();\\r\\n\\t\\t\\r\\n\\t\\tfor (int a : arr1) {\\r\\n\\t\\t\\tlist1.add(a);\\r\\n\\t\\t}\\r\\n\\t\\tfor (int b : arr2) {\\r\\n\\t\\t\\tlist2.add(b);\\r\\n\\t\\t}\\r\\n\\t\\t\\r\\n\\t\\tSystem.out.println(list1);\\r\\n System.out.println(list2);\\r\\n \\r\\n list1.retainAll(list2);\\r\\n System.out.println(\\\"The Intersection values : \\\" + list1);\\r\\n \\r\\n\\t}\",\n \"public abstract boolean intersect(BoundingBox bbox);\",\n \"public static void main (String[] args) {\\n System.out.println(findIntersection(new String[] {\\\"1, 3, 4, 7, 13\\\", \\\"1, 2, 4, 13, 15\\\"})); \\n System.out.println(findIntersection(new String[] {\\\"2, 3, 4\\\", \\\"3\\\"})); \\n System.out.println(findIntersection(new String[] {\\\"1, 5, 6, 7, 10, 11, 12\\\", \\\"5, 6, 8, 11, 17\\\"})); \\n System.out.println(findIntersection(new String[] {\\\"1, 2, 3, 4, 5\\\", \\\"6, 7, 8, 9, 10\\\"})); \\n System.out.println(findIntersection(new String[] {\\\"1, 2, 4, 5, 6, 9\\\", \\\"2, 3, 4, 8, 10\\\"})); \\n System.out.println(findIntersection(new String[] {\\\"21, 22, 23, 25, 27, 28\\\", \\\"21, 24, 25, 29\\\"})); \\n }\",\n \"void intersect(String firstSourcePath, String secondSourcePath, String resultPath) {\\n log.info(\\\"Start intersect files: {}, {}. Result will be written to {}\\\", firstSourcePath, secondSourcePath, resultPath);\\n\\n File firstSourceFile = new File(firstSourcePath);\\n File secondSourceFile = new File(secondSourcePath);\\n\\n if (firstSourceFile.length() == 0 || secondSourceFile.length() == 0) {\\n log.info(\\\"Empty file in input. First source size = {}, second source size = {}\\\", firstSourceFile.length(), secondSourceFile.length());\\n createEmptyFile(resultPath);\\n return;\\n }\\n\\n boolean sourcesSwapped = false;\\n if (firstSourceFile.length() > secondSourceFile.length()) {\\n sourcesSwapped = true;\\n File tmp = firstSourceFile;\\n firstSourceFile = secondSourceFile;\\n secondSourceFile = tmp;\\n }\\n\\n long intersectIdsNumber = 0;\\n\\n try (DataByIdAccessor firstSourceAccessor = new DataByIdAccessor(firstSourceFile.getAbsolutePath())) {\\n try (BufferedReader secondFileReader = new BufferedReader(new FileReader(secondSourceFile))) {\\n try (BufferedWriter resultWriter = new BufferedWriter(new FileWriter(resultPath))) {\\n String currentId;\\n\\n while ((currentId = secondFileReader.readLine()) != null) {\\n String parsedId = Utils.parseId(currentId);\\n String secondSourceData = secondFileReader.readLine();\\n\\n String firstSourceData = firstSourceAccessor.getDataById(parsedId);\\n if (firstSourceData != null) {\\n resultWriter.write(currentId);\\n resultWriter.newLine();\\n\\n if (sourcesSwapped) {\\n writeData(resultWriter, secondSourceData, firstSourceData);\\n } else {\\n writeData(resultWriter, firstSourceData, secondSourceData);\\n }\\n\\n intersectIdsNumber++;\\n }\\n }\\n }\\n }\\n log.info(\\\"Finished intersect files {}, {}. Result file {}. Intersect ids number = {}\\\", firstSourcePath, secondSourcePath, resultPath, intersectIdsNumber);\\n } catch (IOException e) {\\n log.error(\\\"Intersect files error\\\", e);\\n }\\n\\n }\",\n \"void include(Set<S> segments);\",\n \"@Test\\n public void sharedFilterEnsuresUniqueResults() {\\n Filter filter = new Filter(\\\"test-filter\\\");\\n final Dataset dataset1 = new Dataset(\\\"TEST1\\\", \\\"sql\\\", filter);\\n final Dataset dataset2 = new Dataset(\\\"TEST2\\\", \\\"sql2\\\", filter); // shared same filter\\n\\n List<String> entry1 = new ArrayList<>();\\n entry1.add(\\\"001\\\");\\n entry1.add(\\\"aaa\\\");\\n\\n List<String> entry2 = new ArrayList<>();\\n entry2.add(\\\"002\\\");\\n entry2.add(\\\"bbb\\\");\\n\\n List<String> entry3 = new ArrayList<>();\\n entry3.add(\\\"003\\\");\\n entry3.add(\\\"ccc\\\");\\n\\n List<String> entry4 = new ArrayList<>();\\n entry4.add(\\\"004\\\");\\n entry4.add(\\\"ddd\\\");\\n\\n List<List<String>> queryResults1 = new ArrayList<>();\\n queryResults1.add(entry1);\\n queryResults1.add(entry2);\\n queryResults1.add(entry3);\\n queryResults1.add(entry4);\\n\\n List<String> entry5 = new ArrayList<>();\\n entry5.add(\\\"005\\\"); // different\\n entry5.add(\\\"eee\\\");\\n\\n List<String> entry6 = new ArrayList<>();\\n entry6.add(\\\"002\\\"); // same\\n entry6.add(\\\"bbb\\\");\\n\\n List<String> entry7 = new ArrayList<>();\\n entry7.add(\\\"007\\\"); // different\\n entry7.add(\\\"fff\\\");\\n\\n List<String> entry8 = new ArrayList<>();\\n entry8.add(\\\"004\\\"); // same\\n entry8.add(\\\"ddd\\\");\\n\\n List<List<String>> queryResults2 = new ArrayList<>();\\n queryResults2.add(entry5);\\n queryResults2.add(entry6);\\n queryResults2.add(entry7);\\n queryResults2.add(entry8);\\n\\n // given\\n dataset1.populateCache(queryResults1, 200L);\\n dataset2.populateCache(queryResults2, 300L);\\n\\n // when\\n final List<String> result1 = dataset1.getCachedResult();\\n final List<String> result2 = dataset1.getCachedResult();\\n final List<String> result3 = dataset1.getCachedResult();\\n final List<String> result4 = dataset1.getCachedResult();\\n final List<String> result5 = dataset2.getCachedResult();\\n final List<String> result6 = dataset2.getCachedResult();\\n\\n // then\\n assertEquals(\\\"Wrong result 1\\\", entry1, result1); // first datset is as-is\\n assertEquals(\\\"Wrong result 2\\\", entry2, result2); // first datset is as-is\\n assertEquals(\\\"Wrong result 3\\\", entry3, result3); // first datset is as-is\\n assertEquals(\\\"Wrong result 4\\\", entry4, result4); // first datset is as-is\\n assertEquals(\\\"Wrong result 3\\\", entry5, result5); // second datset, not filtered out\\n assertEquals(\\\"Wrong result 3\\\", entry7, result6); // second dataset, entry6 is filtered out\\n\\n // and\\n try {\\n dataset1.getCachedResult();\\n fail(\\\"Expected to run out of data\\\");\\n\\n } catch (IllegalStateException ex) {\\n assertEquals(\\\"Wrong error\\\", \\\"No more data available for dataset: TEST1\\\", ex.getMessage());\\n }\\n\\n try {\\n // entry7 should be filtered out, resulting in no more data\\n dataset2.getCachedResult();\\n fail(\\\"Expected to run out of data\\\");\\n\\n } catch (IllegalStateException ex) {\\n assertEquals(\\\"Wrong error\\\", \\\"No more data available for dataset: TEST2\\\", ex.getMessage());\\n }\\n\\n // and\\n assertEquals(\\\"Wrong cache size\\\", Optional.of(4), dataset1.getMetrics().getCacheSize());\\n assertEquals(\\\"Wrong timing\\\", Optional.of(200L), dataset1.getMetrics().getTimingMilliseconds());\\n assertEquals(\\\"Wrong cache requested\\\", Optional.of(5), dataset1.getMetrics().getCacheRequested());\\n assertEquals(\\\"Wrong filtered out\\\", Optional.empty(), dataset1.getMetrics().getFilteredOut());\\n\\n // and\\n assertEquals(\\\"Wrong cache size\\\", Optional.of(4), dataset2.getMetrics().getCacheSize());\\n assertEquals(\\\"Wrong timing\\\", Optional.of(300L), dataset2.getMetrics().getTimingMilliseconds());\\n assertEquals(\\\"Wrong cache requested\\\", Optional.of(3), dataset2.getMetrics().getCacheRequested());\\n assertEquals(\\\"Wrong filtered out\\\", Optional.of(2), dataset2.getMetrics().getFilteredOut());\\n }\",\n \"public void intersectRoads() {\\r\\n\\t\\tfor (Road road : this.roads) {\\r\\n\\t\\t\\tfor (Integer id : road.getIntersectionIDs()) {\\r\\n\\t\\t\\t\\tfor (Road link : this.roads) {\\r\\n\\t\\t\\t\\t\\tif (id == link.getID()) {\\r\\n\\t\\t\\t\\t\\t\\troad.intersectRoad(link);\\r\\n\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t}\\r\\n\\t\\t}\\r\\n\\t}\",\n \"Multimap<String, String> intersects(RectangleLatLng bounds);\",\n \"@Override\\n public SetInterface<T> intersection(SetInterface<T> rhs) {\\n //Declare return SetInterface\\n SetInterface<T> result = new ArraySet();\\n //If the item is in both sets, add it to the result\\n //Iterate through the calling Set\\n for (int i = 0; i < numItems; i++){\\n //if the item is also in RHS, add it to the result\\n if(rhs.contains(arr[i]))\\n result.addItem(arr[i]);\\n }\\n return result;\\n }\",\n \"protected abstract NativeSQLStatement createNativeIntersectionStatement(Geometry geom);\",\n \"public Map<Integer, Boolean> getIntersects(Geometry geom) throws SQLException {\\n return retrieveExpected(createNativeIntersectsStatement(geom), BOOLEAN);\\n }\",\n \"@Test\\n\\tpublic void testRetainAll() {\\n\\t Set<Integer> setA = new HashSet<>(Arrays.asList(1, 2, 3, 4, 5));\\n\\t\\tSet<Integer> setB = new HashSet<>(Arrays.asList(9, 8, 7, 6, 5, 4, 3));\\n\\t setA.retainAll(setB);\\n\\t Set<Integer> intersection = new HashSet<>(Arrays.asList(3, 4, 5));\\n\\t assertEquals(setA, intersection);\\n }\",\n \"protected abstract List performQuery(String[] ids);\",\n \"@gw.internal.gosu.parser.ExtendedProperty\\n public java.lang.Boolean isIntersection();\",\n \"Pair<Boolean, List<Result>> execQuery(int matchLimit);\",\n \"public static void intersection(ArrayList<String> x, ArrayList<String> y, ArrayList<String> z, JTextArea ta) {\\n\\t\\t\\n\\t\\t//This is the loop to add items from list 1 to results array, if the elements are present in both the lists\\n\\t\\tfor (int i=0; i<x.size(); i++)\\n\\t\\t{\\n\\t\\t\\tfor (int j=0; j<y.size(); j++)\\n\\t\\t\\t{\\n\\t\\t\\t\\tif (x.get(i).equals(y.get(j))&&!z.contains(x.get(i)))\\n\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\tz.add(x.get(i));\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\t\\n\\t\\t\\n\\t\\t//This is the loop to print all the items of the results array list\\n\\t\\tta.setText(\\\"{ \\\");\\n\\t\\tfor (int i=0; i<z.size(); i++)\\n\\t\\t{\\n\\t\\t\\tta.append(z.get(i)+\\\" \\\");\\n\\t\\t}\\n\\t\\tta.append(\\\"}\\\");\\n\\t}\",\n \"public static void main(String[] args) {\\n\\t\\tArray6 test = new Array6();\\n\\t\\tint[] num1 = { 3, 1, 2 };\\n\\t\\tint[] num2 = { 1 };\\n\\t\\ttest.intersect(num1, num2);\\n\\t}\",\n \"static AnalysisResult analyseQueryComponents(ArrayList<String> components) {\\n if (components != null && components.size() > 0) {\\n for (int i = 0; i < components.size(); i++) {\\n String component = components.get(i).toLowerCase();\\n for (String attack : commonAttacks) {\\n attack = attack.toLowerCase();\\n if (trim(component).contains(trim(attack))) {\\n return new AnalysisResult(true, i, attack, false);\\n }\\n }\\n }\\n }\\n return new AnalysisResult(false, null, null, false);\\n }\",\n \"@Override\\n public void processElement(ProcessContext c) {\\n List<LdVariant> queryList = null;\\n List<LdVariant> targetList = null;\\n int inputListCount = 0;\\n for (KV<Boolean, List<LdVariant>> vl : c.element().getValue()) {\\n if (vl.getKey()) {\\n queryList = vl.getValue();\\n } else {\\n targetList = vl.getValue();\\n }\\n inputListCount++;\\n }\\n\\n if (inputListCount != 2 || queryList == null || targetList == null) {\\n throw new IllegalArgumentException(\\\"There should be exactly two lists.\\\");\\n }\\n\\n Iterator<LdVariant> targetIter = targetList.iterator();\\n\\n // Our working set of variants from the target shard that could be within window of variants\\n // read in from the query shard.\\n LinkedList<LdVariant> storedTarget = new LinkedList<>();\\n\\n for (LdVariant queryVar : queryList) {\\n // Fill in storedTarget until we are past window from queryVar.\\n while (targetIter.hasNext()\\n && (storedTarget.isEmpty() || (queryVar.getInfo().getEnd() + window) > storedTarget\\n .getLast().getInfo().getStart())) {\\n storedTarget.add(targetIter.next());\\n }\\n\\n ListIterator<LdVariant> storedTargetIter = storedTarget.listIterator(0);\\n while (storedTargetIter.hasNext()) {\\n LdVariant targetVar = storedTargetIter.next();\\n\\n if (queryVar.getInfo().compareTo(targetVar.getInfo()) != -1) {\\n // Only do comparisons where query is before target. If query is past target then\\n // we are done with target. Note: targetVar > queryVar implies targetVar start >= queryVar\\n // start.\\n storedTargetIter.remove();\\n } else if (targetVar.getInfo().getStart() >= (queryVar.getInfo().getEnd() + window)) {\\n // If the next query starts more than window from when target starts, we are done\\n // with the rest of storedTarget for this query.\\n break;\\n } else {\\n // If target starts >= query starts and target starts < window from query end, then they\\n // must overlap.\\n c.output(KV.of(queryVar, targetVar));\\n }\\n }\\n }\\n }\",\n \"List<ProtocolPo> queryByUnion(ProtocolPo query);\",\n \"public void intersectFromClipboard() { genericClipboard(SetOp.INTERSECT); }\",\n \"private boolean isIntersectWithSource(List<Pair<Tuple,String>> list1, List<Pair<Tuple,String>> list2) {\\n\\t\\tboolean intersect = false;\\n\\t\\t\\n\\t\\tfor (Pair<Tuple,String> tuple : list1) {\\n\\t\\t\\tif (list2.contains(tuple)) {\\n\\t\\t\\t\\tintersect = true;\\n\\t\\t\\t\\tbreak;\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\treturn intersect;\\n\\t}\",\n \"public interface SearchQuerySet extends QuerySet\\n{\\n\\n // for AbstractSearch\\n public static final int STAT_MODELS = 1;\\n public static final int STAT_CLUSTERS = 2;\\n public static final int STAT_GENOMES = 4;\\n public static final int STAT_MODEL_CLUSTERS = 8;\\n\\n public String getStatsById(Collection data);\\n public String getStatsByQuery(String query);\\n public String getStatsById(Collection data,int stats);\\n public String getStatsByQuery(String query,int stats);\\n \\n // for BlastSearch\\n public String getBlastSearchQuery(Collection dbNames, Collection keys, KeyTypeUser.KeyType keyType);\\n \\n //for ClusterIDSearch\\n public String getClusterIDSearchQuery(Collection input, int limit, int[] DBs, KeyTypeUser.KeyType keyType);\\n \\n // for ClusterNameSearch\\n public String getClusterNameSearchQuery(Collection input, int limit, int[] DBs, KeyTypeUser.KeyType keyType);\\n \\n // for DescriptionSearch\\n public String getDescriptionSearchQuery(Collection input, int limit, int[] DBs, KeyTypeUser.KeyType keyType);\\n \\n // for GoSearch \\n public String getGoSearchQuery(Collection input, int limit, KeyTypeUser.KeyType keyType);\\n \\n // for GoTextSearch\\n public String getGoTextSearchQuery(Collection input, int limit, KeyTypeUser.KeyType keyType);\\n \\n // for IdSearch\\n public String getIdSearchQuery(Collection input, int limit, int[] DBs, KeyTypeUser.KeyType keyType);\\n \\n // for QueryCompSearch\\n public String getQueryCompSearchQuery(String comp_id, String status, KeyTypeUser.KeyType keyType);\\n \\n // for QuerySearch\\n public String getQuerySearchQuery(String queries_id, KeyTypeUser.KeyType keyType); \\n \\n // for SeqModelSearch\\n public String getSeqModelSearchQuery(Collection model_ids, KeyTypeUser.KeyType keyType);\\n \\n // for UnknowclusterIdSearch\\n public String getUnknownClusterIdSearchQuery(int cluster_id, KeyTypeUser.KeyType keyType);\\n \\n // for ProbeSetSearch\\n public String getProbeSetSearchQuery(Collection input, int limit, KeyTypeUser.KeyType keyType);\\n \\n // for ProbeSetKeySearch\\n public String getProbeSetKeySearchQuery(Collection input, int limit, KeyTypeUser.KeyType keyType);\\n \\n // for QueryTestSearch\\n public String getQueryTestSearchQuery(String query_id, String version, String genome_id);\\n \\n // for QueryStatsSearch\\n public String getQueryStatsSearchQuery(List query_ids,List DBs);\\n \\n // for PskClusterSearch\\n public String getPskClusterSearchQuery(int cluster_id,KeyTypeUser.KeyType keyType);\\n \\n // for ClusterCorrSearch\\n public String getClusterCorrSearchQuery(int cluster_id, int psk_id, KeyTypeUser.KeyType keyType);\\n \\n // for UnknownGenesSearch\\n public String getUnknownGenesSearchQuery(Collection sources, KeyTypeUser.KeyType keyType);\\n \\n}\",\n \"public int[] intersect(int[] nums1, int[] nums2) {\\n Arrays.sort(nums1);\\n Arrays.sort(nums2);\\n List<Integer> li = new ArrayList<>();\\n int index=0;\\n for(int num : nums1){\\n int bsIndex = binarySearch(nums2, num, index, nums2.length-1);\\n if(bsIndex!=-1){\\n li.add(num);\\n index=bsIndex+1;\\n }\\t\\n }\\n int []ar = new int[li.size()];\\n for(int i=0;i<ar.length;i++){\\n ar[i]=li.get(i);\\n }\\n return ar;\\n }\",\n \"private void positionIntersects(LinkedList<TermPositions> p1, LinkedList<TermPositions> p2, int k) {\\n if (p1 != null && p2 != null) {\\n int df1 = p1.size();\\n int df2 = p2.size();\\n while (!p1.isEmpty() && !p2.isEmpty()) {\\n int tf1 = p1.peek().getPositionList().size();\\n int tf2 = p1.peek().getPositionList().size();\\n if (p1.peek().getDocId() == p2.peek().getDocId()) {\\n LinkedList<Integer> pp1 = p1.peek().getPositionList();\\n while (!pp1.isEmpty()) {\\n for (Integer integer : p2.peek().getPositionList()) {\\n if ((pp1.peek() - integer) < 0 && Math.abs(pp1.peek() - integer) <= (k + 1)) {\\n double score = (1 + Math.log(tf1) * Math.log(N / df1)) + (1 + Math.log(tf2) * Math.log(N / df2));\\n resultsCollector.add(new DocCollector(p1.peek().getDocId(), score));\\n break;\\n }\\n }\\n pp1.pop();\\n }\\n } else if (p1.peek().getDocId() < p2.peek().getDocId())\\n p1.pop();\\n else\\n p2.pop();\\n\\n p1.pop();\\n p2.pop();\\n\\n }\\n\\n }\\n\\n\\n }\",\n \"public VertexSet intersection(VertexSet ot) {\\r\\n\\t\\tVertexSet ans = new VertexSet();\\r\\n\\t\\tint i1=0,i2=0;\\r\\n\\t\\twhile(i1<this.size() & i2 < ot.size()) {\\r\\n\\t\\t\\tint a1=this.at(i1), a2 = ot.at(i2);\\r\\n\\t\\t\\tif(a1==a2) {\\r\\n\\t\\t\\t\\tans.add(a1); i1++; i2++;}\\r\\n\\t\\t\\telse if(a1<a2) {i1++;}\\r\\n\\t\\t\\telse i2++;\\r\\n\\t\\t}\\r\\n\\t\\treturn ans;\\r\\n\\t}\",\n \"public static <T> Spec<T> intersect(Collection<? extends Spec<T>> specs) {\\n if (specs.size() == 0) {\\n return satisfyAll();\\n }\\n return doIntersect(specs);\\n }\",\n \"public Intersection(ListExpression expr1, ListExpression expr2) {\\n this.expr1 = expr1;\\n this.expr2 = expr2;\\n }\",\n \"private DocFile[] search (String[] queries, String[] filters, BooleanClause.Occur filterOccur) throws ParseException {\\n // create a master query builder\\n BooleanQuery.Builder masterQueryBuilder = new BooleanQuery.Builder();\\n // loop through all queries\\n for (String query : queries) {\\n if (query.equals(\\\"\\\")) continue;\\n // create a boolean query for the each query\\n BooleanQuery.Builder queryBuilder = new BooleanQuery.Builder();\\n // loop through all filters\\n for (String filter : filters) {\\n if (filter.equals(\\\"\\\")) continue;\\n QueryParser parser = new QueryParser(filter, analyzer);\\n parser.setAllowLeadingWildcard(true);\\n if (!filter.equals(Constants.INDEX_KEY_OWNER)) {\\n Query parsedQ = parser.parse(query);\\n queryBuilder.add(parsedQ, filterOccur);\\n }\\n else {\\n queryBuilder.add(new PhraseQuery(filter, queries), filterOccur);\\n }\\n }\\n masterQueryBuilder.add(queryBuilder.build(), BooleanClause.Occur.SHOULD);\\n }\\n\\n // build the masterQuery\\n BooleanQuery masterQuery = masterQueryBuilder.build();\\n\\n return searchResponse(searchExec(masterQuery), masterQuery);\\n }\",\n \"StatementChain and(ProfileStatement... statements);\",\n \"@Test\\n\\tpublic void integrationTest1() throws Exception {\\n\\t\\tHashSet<String> mistress = loadGrepResults(\\\"mistress\\\");\\n\\t\\tHashSet<String> undocumented = loadGrepResults(\\\"undocumented\\\");\\n\\t\\tHashSet<String> forced = loadGrepResults(\\\"!i+am+forced\\\");\\n\\t\\t\\n\\t\\tHashSet<String> grepFound = new HashSet<String>(mistress);\\n\\t\\tgrepFound.retainAll(undocumented);\\n\\t\\tgrepFound.addAll(forced);\\n\\t\\t\\n\\t\\tCollection<Page> index = queryTest.query(\\\"mistress & undocumented | (!\\\\\\\"I am forced\\\\\\\")\\\");\\n\\t\\tHashSet<String> indexFound = new HashSet<String>();\\n\\n\\t\\tfor (Page p : index)\\n\\t\\t\\tindexFound.add(p.getURL().getPath().toLowerCase());\\n\\t\\t\\n\\t\\tassertEquals(indexFound, grepFound);\\n\\t}\",\n \"private void searchHashMap(String[] searchKey, String callNumber,int startYear, int endYear) {\\n\\t\\t/* Temporarily stores next 'values' for a title keyword */\\n\\t\\tArrayList<Integer> tempStore = new ArrayList<Integer>();\\n\\t\\t/* Stores only the intersection 'values' of title keywords */\\n\\t\\tCollection<Integer> intersection = new ArrayList<Integer>();\\n\\t\\t/* Counts number of keywords found */\\n\\t\\tint foundKeys = 0;\\n\\n\\t\\t/* Loop to iterate through title keywords and get key-value pair intersection */\\n\\t\\tfor (String key : searchKey) {\\n\\t\\t\\tif (titleHashMap.containsKey(key)) {\\n\\t\\t\\t\\tfoundKeys = foundKeys + 1;\\n\\t\\t\\t\\ttempStore.addAll((titleHashMap.get(key))); /* Stores all found values */\\n\\t\\t\\t\\tif (intersection.size() == 0) {\\n\\t\\t\\t\\t\\tintersection.addAll(titleHashMap.get(key));\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\tintersection.retainAll(tempStore); /* Stores only common 'values' */\\n\\t\\t\\t\\ttempStore.clear(); /* Clears temporary array*/\\n\\t\\t\\t}\\n\\t\\t}\\n\\n\\t\\t/* Checks if all keywords were found */\\n\\t\\tif(searchKey.length == foundKeys){\\n\\t\\t/* Performs search of other fields via the reduced list of 'values' for matched record */\\n\\t\\tfor (Integer i : intersection) {\\n\\t\\t\\tif ((callNumber.equals(\\\"\\\") || items.get(i.intValue()).getCallNumber().equalsIgnoreCase(callNumber))\\n\\t\\t\\t\\t\\t&& (items.get(i.intValue()).getYear() >= startYear && items.get(i.intValue()).getYear() <= endYear)) {\\n\\t\\t\\t\\tSystem.out.println(\\\"--------------------------------------------\\\");\\n\\t\\t\\t\\tSystem.out.println(items.get(i.intValue())); /* Prints found records from master list 'Reference' */\\n\\t\\t\\t\\tSystem.out.println(\\\"--------------------------------------------\\\");\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\t}\\n\\t}\",\n \"public void queryTaskUnionSet1() {\\r\\n\\t\\t// task 1\\r\\n\\t\\tTask task1 = new Task();\\r\\n\\t\\ttask1.setName(\\\"DEFECTS\\\");\\r\\n\\t\\ttask1.setDisplayName(\\\"Defects\\\");\\r\\n\\t\\ttask1.setDescription(\\\"User story to address product defects\\\");\\r\\n\\t\\ttask1 = (Task) aggregateService.create(task1, new Settings());\\t\\r\\n\\r\\n\\t\\t// task 2\\r\\n\\t\\tTask task2 = new Task();\\r\\n\\t\\ttask2.setName(\\\"FIX_DEFECTS\\\");\\r\\n\\t\\ttask2.setDisplayName(\\\"Fix defects\\\");\\r\\n\\t\\ttask2.setDescription(\\\"Task to track the defect fixing effort\\\");\\r\\n\\t\\ttask2 = (Task) aggregateService.create(task2, new Settings());\\r\\n\\r\\n\\t\\t// task 3\\r\\n\\t\\tTask task3 = new Task();\\r\\n\\t\\ttask3.setName(\\\"PRIORITIZE_DEFECTS\\\");\\r\\n\\t\\ttask3.setDisplayName(\\\"Prioritize defects\\\");\\r\\n\\t\\ttask3.setDescription(\\\"Based upon the effort required for the defects prioritize them\\\");\\r\\n\\t\\ttask3 = (Task) aggregateService.create(task3, new Settings());\\r\\n\\r\\n\\t\\ttask1 = (Task) aggregateService.read(task1, getSettings());\\t\\t\\r\\n\\r\\n\\t\\t// query the task object\\r\\n\\t\\tSettings settings = new Settings();\\r\\n\\t\\tsettings.setParam(\\\"name1\\\", \\\"FIX_DEFECTS\\\");\\r\\n\\t\\tsettings.setParam(\\\"name2\\\", \\\"PRIORITIZE_DEFECTS\\\");\\r\\n\\t\\tsettings.setView(aggregateService.getView(\\\"TASKUNIONSET\\\"));\\t\\t\\r\\n\\t\\tList<?> toList = aggregateService.query(new Task(), settings);\\r\\n\\r\\n\\t\\tassert(toList.size() == 2);\\r\\n\\r\\n\\t\\tObject obj1 = toList.get(0);\\r\\n\\t\\tObject obj2 = toList.get(1);\\r\\n\\r\\n\\t\\tassert(Task.class.isAssignableFrom(obj1.getClass()));\\r\\n\\t\\tassert(Task.class.isAssignableFrom(obj2.getClass()));\\r\\n\\t\\t\\r\\n\\t\\tTask t1 = (Task) obj1;\\r\\n\\t\\tTask t2 = (Task) obj2;\\t\\t\\r\\n\\t\\t\\r\\n\\t\\tassert( (t1.getName().equals(\\\"FIX_DEFECTS\\\") && t2.getName().equals(\\\"PRIORITIZE_DEFECTS\\\")) ||\\r\\n\\t\\t\\t\\t(t2.getName().equals(\\\"FIX_DEFECTS\\\") && t1.getName().equals(\\\"PRIORITIZE_DEFECTS\\\")) );\\r\\n\\t}\",\n \"public void testSearchByContent() {\\n Message m1 = new Message(\\\"test\\\",\\\"bla bla david moshe\\\",_u1);\\n Message.incId();\\n try {\\n Thread.sleep(10);\\n } catch (InterruptedException ex) {\\n ex.printStackTrace();\\n }\\n Message m2 = new Message(\\\"test2\\\",\\\"bla2 bla david tikva moshe\\\",_u1);\\n Message.incId();\\n Message m3 = new Message(\\\"test2\\\",\\\"moshe cohen\\\",_u1);\\n Message.incId();\\n\\n this.allMsgs.put(m1.getMsg_id(), m1);\\n this.allMsgs.put(m2.getMsg_id(), m2);\\n this.allMsgs.put(m3.getMsg_id(), m3);\\n\\n this.searchEngine.addData(m1);\\n this.searchEngine.addData(m2);\\n this.searchEngine.addData(m3);\\n\\n /* SearchHit[] result = this.searchEngine.searchByContent(\\\"bla2\\\", 0,1);\\n assertTrue(result.length==1);\\n assertTrue(result[0].getMessage().equals(m2));\\n\\n SearchHit[] result2 = this.searchEngine.searchByContent(\\\"bla david tikva\\\", 0,2);\\n assertTrue(result2.length==1);\\n assertEquals(result2[0].getScore(),3.0);\\n //assertEquals(result2[1].getScore(),2.0);\\n assertTrue(result2[0].getMessage().equals(m2));\\n //assertTrue(result2[1].getMessage().equals(m1));\\n\\n SearchHit[] result3 = this.searchEngine.searchByContent(\\\"bla2 tikva\\\", 0, 5);\\n assertTrue(result3.length==0);\\n */\\n\\n/*\\n SearchHit[] result4 = this.searchEngine.searchByContent(\\\"bla OR tikva\\\", 0, 5);\\n assertTrue(result4.length==2);\\n assertTrue(result4[0].getMessage().equals(m2));\\n assertTrue(result4[1].getMessage().equals(m1));\\n\\n SearchHit[] result5 = this.searchEngine.searchByContent(\\\"bla AND cohen\\\", 0, 5);\\n assertTrue(result5.length==0);\\n\\n result5 = this.searchEngine.searchByContent(\\\"bla AND moshe\\\",0,5);\\n assertTrue(result5.length==2);\\n assertTrue(result5[0].getScore() == result5[1].getScore());\\n assertTrue(result5[0].getMessage().equals(m2));\\n assertTrue(result5[1].getMessage().equals(m1));\\n\\n result5 = this.searchEngine.searchByContent(\\\"bla AND moshe\\\", 10, 11);\\n assertTrue(result5.length==0);\\n */\\n\\n }\",\n \"public void queryTaskUnionSet2() {\\r\\n\\t\\t// task 1\\r\\n\\t\\tTask task1 = new Task();\\r\\n\\t\\ttask1.setName(\\\"DEFECTS\\\");\\r\\n\\t\\ttask1.setDisplayName(\\\"Defects\\\");\\r\\n\\t\\ttask1.setDescription(\\\"User story to address product defects\\\");\\r\\n\\t\\t\\r\\n\\t\\tTask d1 = new Task();\\r\\n\\t\\td1.setName(\\\"DEFECT 1\\\");\\r\\n\\t\\td1.setDisplayName(\\\"Defect 1\\\");\\r\\n\\t\\td1.setDescription(\\\"First defect\\\");\\r\\n\\t\\tTask d2 = new Task();\\r\\n\\t\\td2.setName(\\\"DEFECT 2\\\");\\r\\n\\t\\td2.setDisplayName(\\\"Defect 2\\\");\\r\\n\\t\\td2.setDescription(\\\"Second defect\\\");\\r\\n\\t\\tSet<Task> c = new HashSet<Task>();\\r\\n\\t\\tc.add(d1);\\r\\n\\t\\tc.add(d2);\\r\\n\\t\\ttask1.setTaskChildren(c);\\r\\n\\t\\ttask1 = (Task) aggregateService.create(task1, new Settings());\\r\\n\\r\\n\\t\\t\\tSystem.out.println(\\\"Name: \\\" + task1.getName() + \\\", Id: \\\" + task1.getId());\\r\\n\\r\\n\\t\\t// task 2\\r\\n\\t\\tTask task2 = new Task();\\r\\n\\t\\ttask2.setName(\\\"FIX_DEFECTS\\\");\\r\\n\\t\\ttask2.setDisplayName(\\\"Fix defects\\\");\\r\\n\\t\\ttask2.setDescription(\\\"Task to track the defect fixing effort\\\");\\r\\n\\t\\ttask2 = (Task) aggregateService.create(task2, new Settings());\\r\\n\\r\\n\\t\\t// task 3\\r\\n\\t\\tTask task3 = new Task();\\r\\n\\t\\ttask3.setName(\\\"PRIORITIZE_DEFECTS\\\");\\r\\n\\t\\ttask3.setDisplayName(\\\"Prioritize defects\\\");\\r\\n\\t\\ttask3.setDescription(\\\"Based upon the effort required for the defects prioritize them\\\");\\r\\n\\t\\ttask3 = (Task) aggregateService.create(task3, new Settings());\\r\\n\\r\\n\\t\\ttask1 = (Task) aggregateService.read(task1, getSettings());\\t\\t\\r\\n\\r\\n\\t\\t// query the task object\\r\\n\\t\\tSettings settings = new Settings();\\r\\n\\t\\tsettings.setParam(\\\"name1\\\", \\\"DEFECTS\\\");\\r\\n\\t\\tsettings.setParam(\\\"name2\\\", \\\"PRIORITIZE_DEFECTS\\\");\\r\\n\\t\\tsettings.setParam(\\\"name3\\\", \\\"FIX_DEFECTS\\\");\\r\\n\\t\\tsettings.addFunction(FunctionHandler.NE, \\\"name\\\", \\\"name3\\\");\\r\\n\\t\\tsettings.addFunction(FunctionType.ASC, \\\"name\\\");\\r\\n\\t\\tsettings.setView(aggregateService.getView(\\\"TASKUNIONSET\\\"));\\t\\t\\r\\n\\t\\tList<?> toList = aggregateService.query(new Task(), settings);\\r\\n\\r\\n\\t\\tSystem.out.println(\\\"SIZE : \\\" + toList.size());\\r\\n\\t\\tfor(Object o: toList) {\\r\\n\\t\\t\\tTask t = (Task) o;\\r\\n\\t\\t\\tSystem.out.println(\\\"Name: \\\" + t.getName() + \\\", Id: \\\" + t.getId());\\r\\n\\t\\t}\\r\\n\\t\\tassert(toList.size() == 2);\\r\\n\\r\\n\\t\\tObject obj1 = toList.get(0);\\r\\n\\t\\tObject obj2 = toList.get(1);\\r\\n\\r\\n\\t\\tassert(Task.class.isAssignableFrom(obj1.getClass()));\\r\\n\\t\\tassert(Task.class.isAssignableFrom(obj2.getClass()));\\r\\n\\t\\t\\r\\n\\t\\tTask t1 = (Task) obj1;\\r\\n\\t\\tTask t2 = (Task) obj2;\\r\\n\\r\\n\\t\\tassert ((t1.getName().equals(\\\"DEFECTS\\\") && t2.getName().equals(\\\"PRIORITIZE_DEFECTS\\\")) ||\\r\\n\\t\\t\\t(t2.getName().equals(\\\"DEFECTS\\\") && t1.getName().equals(\\\"PRIORITIZE_DEFECTS\\\")));\\r\\n\\r\\n\\t\\tTask d = t1.getName().equals(\\\"DEFECTS\\\") ? t1 : t2;\\r\\n\\t\\tassert (d.getTaskChildren() != null && d.getTaskChildren().size() == 2);\\r\\n\\r\\n//\\t\\tSystem.out.println(\\\"Task 1: \\\" + t1.getName() + \\\", Task 2: \\\" + t2.getName());\\r\\n//\\t\\tassert (t1.getName().equals(\\\"DEFECTS\\\") && t2.getName().equals(\\\"DEFECT 1\\\"));\\r\\n//\\t\\tassert(t1.getTaskChildren() != null && t1.getTaskChildren().size() == 2);\\r\\n\\t}\",\n \"public void multipleQueriesASync(List<IndexQuery> queries, APIClientListener listener) {\\n TaskParams.Client params = new TaskParams.Client(listener, APIMethod.MultipleQueries, queries, \\\"none\\\");\\n new ASyncClientTask().execute(params);\\n }\",\n \"public static ArrayList<Integer> getIntersection(int[] array1,int[] array2){\\n HashMap<Integer,Boolean> map=new HashMap<>();\\n ArrayList<Integer> list=new ArrayList<>();\\n for(int i=0;i<array1.length;i++){\\n map.put(array1[i],false);\\n }\\n for(int j=0;j<array2.length;j++){\\n if(map.containsKey(array2[j])){\\n map.put(array2[j],true); \\n }\\n }\\n Set<Map.Entry<Integer,Boolean>> entries=map.entrySet();\\n for(Map.Entry<Integer,Boolean> entry:entries){\\n if(entry.getValue()){\\n list.add(entry.getKey());\\n }\\n }\\n\\n return list;\\n }\",\n \"private List<Object[]> executeDayQuery(\\n List<Object> segments, List<Object> workplaces,\\n String Eq1startTime, String Eq1endTime,\\n String Eq2startTime, String Eq2endTime,\\n String Eq3startTime, String Eq3endTime) {\\n try {\\n //Clear all tables\\n //################# Declared Harness Data #################### \\n Helper.startSession();\\n\\n String query_str_1 = \\\"(SELECT 'Matin' as shift,'%s' As start_time, '%s' as end_time, \\\"\\n + \\\"bh.segment AS segment, \\\"\\n + \\\"bh.workplace AS workplace, \\\"\\n + \\\"bh.harness_part AS harness_part, \\\"\\n + \\\"bh.std_time AS std_time, \\\"\\n + \\\"COUNT(bh.harness_part) AS produced_qty, \\\"\\n + \\\"SUM(bh.std_time) AS produced_hours \\\"\\n + \\\"FROM base_harness bh, base_container bc \\\"\\n + \\\"WHERE bc.id = bh.container_id \\\"\\n + \\\"AND bh.create_time BETWEEN '%s' AND '%s' \\\"\\n + \\\"AND bh.segment IN (:segments) \\\"\\n + \\\"AND bh.workplace IN (:workplaces) \\\"\\n + \\\"GROUP BY bh.segment, bh.workplace, bh.harness_part, bh.std_time)\\\";\\n\\n query_str_1 = String.format(query_str_1, Eq1startTime, Eq1endTime, Eq1startTime, Eq1endTime);\\n\\n String query_str_2 = \\\"(SELECT 'Soir' as shift,'%s' As start_time, '%s' as end_time, \\\"\\n + \\\"bh.segment AS segment, \\\"\\n + \\\"bh.workplace AS workplace, \\\"\\n + \\\"bh.harness_part AS harness_part, \\\"\\n + \\\"bh.std_time AS std_time, \\\"\\n + \\\"COUNT(bh.harness_part) AS produced_qty, \\\"\\n + \\\"SUM(bh.std_time) AS produced_hours \\\"\\n + \\\"FROM base_harness bh, base_container bc \\\"\\n + \\\"WHERE bc.id = bh.container_id \\\"\\n + \\\"AND bh.create_time BETWEEN '%s' AND '%s' \\\"\\n + \\\"AND bh.segment IN (:segments) \\\"\\n + \\\"AND bh.workplace IN (:workplaces) \\\"\\n + \\\"GROUP BY bh.segment, bh.workplace, bh.harness_part, bh.std_time)\\\";\\n\\n query_str_2 = String.format(query_str_2, Eq2startTime, Eq2endTime, Eq2startTime, Eq2endTime);\\n\\n String query_str_3 = \\\"(SELECT 'Nuit' as shift,'%s' As start_time, '%s' as end_time, \\\"\\n + \\\"bh.segment AS segment, \\\"\\n + \\\"bh.workplace AS workplace, \\\"\\n + \\\"bh.harness_part AS harness_part, \\\"\\n + \\\"bh.std_time AS std_time, \\\"\\n + \\\"COUNT(bh.harness_part) AS produced_qty, \\\"\\n + \\\"SUM(bh.std_time) AS produced_hours \\\"\\n + \\\"FROM base_harness bh, base_container bc \\\"\\n + \\\"WHERE bc.id = bh.container_id \\\"\\n + \\\"AND bh.create_time BETWEEN '%s' AND '%s' \\\"\\n + \\\"AND bh.segment IN (:segments) \\\"\\n + \\\"AND bh.workplace IN (:workplaces)\\\"\\n + \\\"GROUP BY bh.segment, bh.workplace, bh.harness_part, bh.std_time) \\\";\\n\\n query_str_3 = String.format(query_str_3, Eq3startTime, Eq3endTime, Eq3startTime, Eq3endTime);\\n\\n String query_str = \\\"SELECT * FROM (\\\"\\n + query_str_1 + \\\" UNION \\\"\\n + query_str_2 + \\\" UNION \\\"\\n + query_str_3\\n + \\\") results ORDER BY start_time ASC, segment ASC, workplace ASC, harness_part ASC\\\";\\n\\n SQLQuery query = Helper.sess.createSQLQuery(query_str);\\n\\n query.addScalar(\\\"shift\\\", StandardBasicTypes.STRING)\\n .addScalar(\\\"start_time\\\", StandardBasicTypes.STRING)\\n .addScalar(\\\"end_time\\\", StandardBasicTypes.STRING)\\n .addScalar(\\\"segment\\\", StandardBasicTypes.STRING)\\n .addScalar(\\\"workplace\\\", StandardBasicTypes.STRING)\\n .addScalar(\\\"harness_part\\\", StandardBasicTypes.STRING)\\n .addScalar(\\\"std_time\\\", StandardBasicTypes.DOUBLE)\\n .addScalar(\\\"produced_qty\\\", StandardBasicTypes.INTEGER)\\n .addScalar(\\\"produced_hours\\\", StandardBasicTypes.DOUBLE)\\n .setParameterList(\\\"segments\\\", segments)\\n .setParameterList(\\\"workplaces\\\", workplaces);\\n\\n this.dataResultList = query.list();\\n\\n Helper.sess.getTransaction().commit();\\n\\n return this.dataResultList;\\n\\n } catch (HibernateException e) {\\n if (Helper.sess.getTransaction() != null) {\\n Helper.sess.getTransaction().rollback();\\n }\\n }\\n\\n return this.dataResultList;\\n }\",\n \"public void test_containsII() {\\n\\tfinal int COUNT = 60000000;\\n\\t\\n\\tRectangle r = new Rectangle(1, 2, 3, 4);\\n\\n\\tPerformanceMeter meter = createMeter(\\\"contains\\\");\\n\\tmeter.start();\\n\\tfor (int i = 0; i < COUNT; i++) {\\n\\t\\tr.contains(2, 3);\\t// does contain\\n\\t}\\n\\tmeter.stop();\\n\\t\\n\\tdisposeMeter(meter);\\n\\t\\n\\tmeter = createMeter(\\\"disjoint\\\");\\n\\tmeter.start();\\n\\tfor (int i = 0; i < COUNT; i++) {\\n\\t\\tr.contains(9, 12);\\t// does not contain\\n\\t}\\n\\tmeter.stop();\\n\\t\\n\\tdisposeMeter(meter);\\n}\",\n \"@Test\\n public void testBoundsAsCompositesWithSingleEqAndMultiINRestrictions()\\n {\\n CFMetaData cfMetaData = newCFMetaData(Sort.ASC, Sort.ASC, Sort.ASC, Sort.ASC);\\n\\n ByteBuffer value1 = ByteBufferUtil.bytes(1);\\n ByteBuffer value2 = ByteBufferUtil.bytes(2);\\n ByteBuffer value3 = ByteBufferUtil.bytes(3);\\n ByteBuffer value4 = ByteBufferUtil.bytes(4);\\n ByteBuffer value5 = ByteBufferUtil.bytes(5);\\n\\n // clustering_0 = 1 AND (clustering_1, clustering_2) IN ((2, 3), (4, 5))\\n Restriction singleEq = newSingleEq(cfMetaData, 0, value1);\\n Restriction multiIN = newMultiIN(cfMetaData, 1, asList(value2, value3), asList(value4, value5));\\n PrimaryKeyRestrictions restrictions = new PrimaryKeyRestrictionSet(cfMetaData.comparator);\\n restrictions = restrictions.mergeWith(singleEq).mergeWith(multiIN);\\n\\n List<Composite> bounds = restrictions.boundsAsComposites(cfMetaData, Bound.START, QueryOptions.DEFAULT);\\n assertEquals(2, bounds.size());\\n assertComposite(bounds.get(0), value1, value2, value3, EOC.START);\\n assertComposite(bounds.get(1), value1, value4, value5, EOC.START);\\n\\n bounds = restrictions.boundsAsComposites(cfMetaData, Bound.END, QueryOptions.DEFAULT);\\n assertEquals(2, bounds.size());\\n assertComposite(bounds.get(0), value1, value2, value3, EOC.END);\\n assertComposite(bounds.get(1), value1, value4, value5, EOC.END);\\n\\n // clustering_0 = 1 AND (clustering_1, clustering_2) IN ((2, 3))\\n singleEq = newSingleEq(cfMetaData, 0, value1);\\n multiIN = newMultiIN(cfMetaData, 1, asList(value2, value3));\\n restrictions = new PrimaryKeyRestrictionSet(cfMetaData.comparator);\\n restrictions = restrictions.mergeWith(multiIN).mergeWith(singleEq);\\n\\n bounds = restrictions.boundsAsComposites(cfMetaData, Bound.START, QueryOptions.DEFAULT);\\n assertEquals(1, bounds.size());\\n assertComposite(bounds.get(0), value1, value2, value3, EOC.START);\\n\\n bounds = restrictions.boundsAsComposites(cfMetaData, Bound.END, QueryOptions.DEFAULT);\\n assertEquals(1, bounds.size());\\n assertComposite(bounds.get(0), value1, value2, value3, EOC.END);\\n\\n // clustering_0 = 1 AND clustering_1 = 5 AND (clustering_2, clustering_3) IN ((2, 3), (4, 5))\\n singleEq = newSingleEq(cfMetaData, 0, value1);\\n Restriction singleEq2 = newSingleEq(cfMetaData, 1, value5);\\n multiIN = newMultiIN(cfMetaData, 2, asList(value2, value3), asList(value4, value5));\\n restrictions = new PrimaryKeyRestrictionSet(cfMetaData.comparator);\\n restrictions = restrictions.mergeWith(singleEq).mergeWith(multiIN).mergeWith(singleEq2);\\n\\n bounds = restrictions.boundsAsComposites(cfMetaData, Bound.START, QueryOptions.DEFAULT);\\n assertEquals(2, bounds.size());\\n assertComposite(bounds.get(0), value1, value5, value2, value3, EOC.START);\\n assertComposite(bounds.get(1), value1, value5, value4, value5, EOC.START);\\n\\n bounds = restrictions.boundsAsComposites(cfMetaData, Bound.END, QueryOptions.DEFAULT);\\n assertEquals(2, bounds.size());\\n assertComposite(bounds.get(0), value1, value5, value2, value3, EOC.END);\\n assertComposite(bounds.get(1), value1, value5, value4, value5, EOC.END);\\n }\",\n \"private <T> ArrayList<T> intersection(ArrayList<T> list1, ArrayList<T> list2) {\\n ArrayList<T> list = new ArrayList<T>();\\n\\n for (T t : list1) {\\n if (list2.contains(t)) {\\n list.add(t);\\n }\\n }\\n\\n return list;\\n }\",\n \"private ExampleSetBuilder performInnerJoin(ExampleSet leftExampleSet, ExampleSet rightExampleSet,\\n\\t\\t\\tList<AttributeSource> originalAttributeSources, List<Attribute> unionAttributeList,\\n\\t\\t\\tPair<Attribute[], Attribute[]> keyAttributes) throws ProcessStoppedException {\\n\\t\\tExampleSetBuilder builder = ExampleSets.from(unionAttributeList);\\n\\n\\t\\tAttribute[] leftKeyAttributes = null;\\n\\t\\tAttribute[] rightKeyAttributes = null;\\n\\t\\tMap<DoubleArrayWrapper, List<Example>> rightKeyMapping = null;\\n\\t\\tboolean useId = getParameterAsBoolean(PARAMETER_USE_ID);\\n\\n\\t\\tif (!useId) {\\n\\t\\t\\t// create key mapping for right example set\\n\\t\\t\\tleftKeyAttributes = keyAttributes.getFirst();\\n\\t\\t\\trightKeyAttributes = keyAttributes.getSecond();\\n\\t\\t\\trightKeyMapping = createKeyMapping(rightExampleSet, rightKeyAttributes, leftKeyAttributes);\\n\\t\\t}\\n\\n\\t\\tint progressCounter = 0;\\n\\t\\t// iterate over all example from left table and search for matching examples in right table:\\n\\t\\tfor (Example leftExample : leftExampleSet) {\\n\\n\\t\\t\\tList<Example> matchingRightExamples = getMatchingExamples(leftExampleSet, rightExampleSet, leftKeyAttributes,\\n\\t\\t\\t\\t\\trightKeyMapping, useId, leftExample);\\n\\n\\t\\t\\tif (matchingRightExamples != null) {\\n\\t\\t\\t\\tfor (Example rightExample : matchingRightExamples) {\\n\\t\\t\\t\\t\\taddCombinedOccurence(originalAttributeSources, unionAttributeList, builder, leftExample, rightExample);\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\n\\t\\t\\t// trigger operator progress every 100 examples\\n\\t\\t\\t++progressCounter;\\n\\t\\t\\tif (progressCounter % 100 == 0) {\\n\\t\\t\\t\\tgetProgress().step(100);\\n\\t\\t\\t\\tprogressCounter = 0;\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\treturn builder;\\n\\t}\",\n \"public static ArrayList<Card> intersection(ArrayList<Meld> melds) {\\n\\t\\tArrayList<Card> intersections = new ArrayList<Card>();\\n\\n\\t\\t// check every combination of two melds\\n\\t\\tfor (int i = 0; i < melds.size(); i++) {\\n\\t\\t\\tfor (int j = i; j < melds.size(); j++) {\\n\\t\\t\\t\\tif (i != j) {\\n\\t\\t\\t\\t\\tMeld m1 = melds.get(i);\\n\\t\\t\\t\\t\\tMeld m2 = melds.get(j);\\n\\t\\t\\t\\t\\tfor (int k = 0; k < 3; k++) {\\n\\t\\t\\t\\t\\t\\tCard c1 = m1.cards[k];\\n\\t\\t\\t\\t\\t\\tfor (int l = 0; l < 3; l++) {\\n\\t\\t\\t\\t\\t\\t\\tCard c2 = m2.cards[l];\\n\\n\\t\\t\\t\\t\\t\\t\\t// if the card is in both melds, add it to the list\\n\\t\\t\\t\\t\\t\\t\\tif (c1.equals(c2)) intersections.add(c1);\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\treturn intersections;\\n\\t}\",\n \"private Range<Token> intersect(Range<Token> serverRange, AbstractBounds<Token> requestedRange)\\n {\\n if (serverRange.contains(requestedRange.left) && serverRange.contains(requestedRange.right)) {\\n //case 1: serverRange fully encompasses requestedRange\\n return new Range<Token>(requestedRange.left, requestedRange.right, partitioner);\\n } else if (requestedRange.contains(serverRange.left) && requestedRange.contains(serverRange.right)) {\\n //case 2: serverRange is fully encompasses by requestedRange\\n //serverRange is already the intersection\\n return new Range<Token>(serverRange.left, serverRange.right);\\n } else if (serverRange.contains(requestedRange.left) && requestedRange.contains(serverRange.right)) {\\n //case 3: serverRange overlaps on the left: sR.left < rR.left < sR.right < rR.right\\n return new Range<Token>(requestedRange.left, serverRange.right, partitioner);\\n } else if (requestedRange.contains(serverRange.left) && serverRange.contains(requestedRange.right)) {\\n //case 4: serverRange overlaps on the right rR.left < sR.left < rR.right < sR.right\\n return new Range<Token>(serverRange.left, requestedRange.right, partitioner);\\n } else if (!serverRange.contains(requestedRange.left) && !serverRange.contains(requestedRange.right) &&\\n !requestedRange.contains(serverRange.left) && !requestedRange.contains(serverRange.right)) {\\n //case 5: totally disjoint\\n return null;\\n } else {\\n assert false : \\\"Failed intersecting serverRange = (\\\" + serverRange.left + \\\", \\\" + serverRange.right + \\\") and requestedRange = (\\\" + requestedRange.left + \\\", \\\" + requestedRange.right + \\\")\\\";\\n return null;\\n }\\n }\",\n \"private static boolean intersect(\\n\\t\\tDateTime start1, DateTime end1,\\n\\t\\tDateTime start2, DateTime end2)\\n\\t{\\n\\t\\tif (DateTime.op_LessThanOrEqual(end2, start1) || DateTime.op_LessThanOrEqual(end1, start2))\\n\\t\\t\\treturn false;\\n\\n\\t\\treturn true;\\n\\t}\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.601857","0.5893896","0.575646","0.56862754","0.5679482","0.5663984","0.56257683","0.5607326","0.5603596","0.5601509","0.5576574","0.55470616","0.55435514","0.5515671","0.55070364","0.5502553","0.5489338","0.54770523","0.5475129","0.5470427","0.5450035","0.54446936","0.5408048","0.5401522","0.5399978","0.53934526","0.53848284","0.5340105","0.53393424","0.53084314","0.5287358","0.5283747","0.52581","0.52568555","0.52480286","0.52354676","0.52164197","0.5213959","0.51984346","0.5192227","0.5184684","0.51771957","0.5159704","0.5159178","0.5124164","0.51218426","0.51148605","0.5108193","0.5091938","0.5091849","0.5091172","0.5084893","0.5061867","0.5058592","0.5044699","0.5041851","0.5038374","0.50355905","0.5029191","0.5020648","0.50171846","0.5014847","0.5001266","0.4996497","0.4982533","0.49779436","0.49557963","0.49537805","0.49493805","0.49421465","0.49387473","0.49319023","0.49272868","0.49214607","0.49002063","0.48971665","0.48834237","0.4882071","0.48811847","0.48798484","0.48766506","0.48754376","0.4873489","0.48677903","0.4864947","0.48630542","0.48628417","0.48627225","0.48569584","0.48557517","0.48503733","0.484666","0.48458445","0.48433658","0.4834894","0.48300502","0.48300096","0.48201352","0.48197442","0.48181358"],"string":"[\n \"0.601857\",\n \"0.5893896\",\n \"0.575646\",\n \"0.56862754\",\n \"0.5679482\",\n \"0.5663984\",\n \"0.56257683\",\n \"0.5607326\",\n \"0.5603596\",\n \"0.5601509\",\n \"0.5576574\",\n \"0.55470616\",\n \"0.55435514\",\n \"0.5515671\",\n \"0.55070364\",\n \"0.5502553\",\n \"0.5489338\",\n \"0.54770523\",\n \"0.5475129\",\n \"0.5470427\",\n \"0.5450035\",\n \"0.54446936\",\n \"0.5408048\",\n \"0.5401522\",\n \"0.5399978\",\n \"0.53934526\",\n \"0.53848284\",\n \"0.5340105\",\n \"0.53393424\",\n \"0.53084314\",\n \"0.5287358\",\n \"0.5283747\",\n \"0.52581\",\n \"0.52568555\",\n \"0.52480286\",\n \"0.52354676\",\n \"0.52164197\",\n \"0.5213959\",\n \"0.51984346\",\n \"0.5192227\",\n \"0.5184684\",\n \"0.51771957\",\n \"0.5159704\",\n \"0.5159178\",\n \"0.5124164\",\n \"0.51218426\",\n \"0.51148605\",\n \"0.5108193\",\n \"0.5091938\",\n \"0.5091849\",\n \"0.5091172\",\n \"0.5084893\",\n \"0.5061867\",\n \"0.5058592\",\n \"0.5044699\",\n \"0.5041851\",\n \"0.5038374\",\n \"0.50355905\",\n \"0.5029191\",\n \"0.5020648\",\n \"0.50171846\",\n \"0.5014847\",\n \"0.5001266\",\n \"0.4996497\",\n \"0.4982533\",\n \"0.49779436\",\n \"0.49557963\",\n \"0.49537805\",\n \"0.49493805\",\n \"0.49421465\",\n \"0.49387473\",\n \"0.49319023\",\n \"0.49272868\",\n \"0.49214607\",\n \"0.49002063\",\n \"0.48971665\",\n \"0.48834237\",\n \"0.4882071\",\n \"0.48811847\",\n \"0.48798484\",\n \"0.48766506\",\n \"0.48754376\",\n \"0.4873489\",\n \"0.48677903\",\n \"0.4864947\",\n \"0.48630542\",\n \"0.48628417\",\n \"0.48627225\",\n \"0.48569584\",\n \"0.48557517\",\n \"0.48503733\",\n \"0.484666\",\n \"0.48458445\",\n \"0.48433658\",\n \"0.4834894\",\n \"0.48300502\",\n \"0.48300096\",\n \"0.48201352\",\n \"0.48197442\",\n \"0.48181358\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.6197183"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":13893,"cells":{"query":{"kind":"string","value":"[NEW] Intersects two queries (represented by the postingslist)"},"document":{"kind":"string","value":"public PostingsList intersect(PostingsList l1, PostingsList l2){\n\n PostingsList intersection = new PostingsList();\n\n // Counters to iterate docIDs\n int count1 = 0;\n int count2 = 0;\n\n // First posting\n PostingsEntry p1 = l1.get(0);\n PostingsEntry p2 = l2.get(0);\n\n while(true){\n // Match - EUREKA! //\n if (p1.docID == p2.docID){\n // Add match\n intersection.insert(p1.docID);\n // Increase counters\n count1++;\n count2++;\n // Go to next postings (check for nullpointer)\n if (count1<l1.size() && count2<l2.size()){\n p1 = l1.get(count1);\n p2 = l2.get(count2);\n }\n else\n break;\n }\n // No match\n else if (p1.docID < p2.docID){\n count1++;\n if (count1<l1.size())\n p1 = l1.get(count1);\n else\n break;\n }\n // No match\n else{\n count2++;\n if (count2<l2.size())\n p2 = l2.get(count2);\n else\n break;\n }\n }\n\n return intersection;\n }"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["public PostingsList intersect(Query query){\n\n LinkedList<PostingsList> listQueriedPostings = new LinkedList<PostingsList>();\n // List with postings corresponding to the queries\n for (int i = 0; i<query.size(); i++){\n // If any query has zero matches, return 0 results\n //if(!(new File(\"postings/t\"+hash(query.terms.get(i))+\".json\")).exists()){\n if (!this.index.containsKey(query.terms.get(i))){\n return null;\n }\n // Otherwise store postings in the list\n listQueriedPostings.add(this.getPostings(query.terms.get(i)));\n }\n\n // Order the posting list by increasing document frequency\n listQueriedPostings = sortByIncreasingFrequency(listQueriedPostings);\n\n PostingsList result = (PostingsList)listQueriedPostings.get(0);\n\n // In case only one word is queried\n if (listQueriedPostings.size() == 1){\n return result;\n }\n\n // Apply algorithm as many times as words in the query\n for(int i = 1; i < listQueriedPostings.size(); i++){\n result = intersect(result, listQueriedPostings.get(i));\n if (result.isEmpty()){\n return null;\n }\n }\n return result;\n }","public PostingsList phrase_query(PostingsList l1, PostingsList l2){\n\n PostingsList phrase = new PostingsList();\n\n // Counters to iterate docIDs\n int count1 = 0;\n int count2 = 0;\n // Counters to iterate positional indices\n int subcount1 = 0;\n int subcount2 = 0;\n\n // First posting\n PostingsEntry p1 = l1.get(0);\n PostingsEntry p2 = l2.get(0);\n\n // List of positional indices (changes at each iteration)\n LinkedList<Integer> ll1;\n LinkedList<Integer> ll2;\n\n // Used to store positional index\n int pp1;\n int pp2;\n\n while(true){\n // docID match (1/2) //\n if (p1.docID == p2.docID){\n // Obtain list of positional indices\n ll1 = p1.positions;\n ll2 = p2.positions;\n // First positional indices\n pp1 = ll1.get(0);\n pp2 = ll2.get(0);\n // Initialize counter\n subcount1 = 0;\n subcount2 = 0;\n\n // Search if the phrase exists\n while(true){\n // Match, consecutive words (2/2) - EUREKA! //\n if (pp1+1 == pp2){\n // Save found match (docID and positional index of last\n // word)\n phrase.insert(p1.docID, pp2);\n // Increase counters and pos indices if list is not finished\n subcount1++;\n subcount2++;\n if (subcount1<ll1.size() && subcount2<ll2.size()){\n pp1 = ll1.get(subcount1);\n pp2 = ll2.get(subcount2);\n }\n // If list finished, break\n else\n break;\n }\n // Not match\n else if (pp1+1 < pp2){\n subcount1++;\n if (subcount1<ll1.size())\n pp1 = ll1.get(subcount1);\n // If list finished, break\n else\n break;\n }\n // Not match\n else{\n subcount2++;\n if (subcount2<ll2.size())\n pp2 = ll2.get(subcount2);\n else\n break;\n }\n }\n\n // Once we finished looking at the list of positional indices of one\n // posting, increase counters and go to next postings (if there are)\n count1++;\n count2++;\n if (count1<l1.size() && count2<l2.size()){\n p1 = l1.get(count1);\n p2 = l2.get(count2);\n }\n else{\n break;\n }\n }\n // docID not match, increase lowest counter\n else if (p1.docID < p2.docID){\n count1++;\n if (count1<l1.size()){\n p1 = l1.get(count1);\n }\n else{\n break;\n }\n }\n // docID not match, increase lowest counter\n else{\n count2++;\n if (count2<l2.size()){\n p2 = l2.get(count2);\n }\n else{\n break;\n }\n }\n }\n\n return phrase;\n }","@Override\n public boolean equals(Object o) {\n if(o == null){\n return false;\n }\n\n if (this == o) { return true; }\n if (getClass() != o.getClass()) { return false; }\n Query a_new = (Query) o;\n return this.requestedPosts== (a_new.getRequestedPosts()) && this.getQueryID() == a_new.getQueryID();\n }","private void queryListings(double left, double right, double top, double bottom) {\n ParseQuery<Listing> query = ParseQuery.getQuery(Listing.class);\n query.include(Listing.KEY_AUTHOR);\n query.whereGreaterThanOrEqualTo(Listing.KEY_LONGITUDE, left);\n query.whereLessThanOrEqualTo(Listing.KEY_LONGITUDE, right);\n query.whereGreaterThanOrEqualTo(Listing.KEY_LATITUDE, bottom);\n query.whereLessThanOrEqualTo(Listing.KEY_LATITUDE, top);\n query.findInBackground(new FindCallback<Listing>() {\n @Override\n public void done(List<Listing> listings, ParseException e) {\n // Check for errors\n if (e != null) {\n Log.e(TAG, \"Issue with getting listings\", e);\n return;\n }\n // Add a marker for each listing on screen\n for (Listing listing : listings) {\n LatLng coordinates = new LatLng(listing.getLatitude(), listing.getLongitude());\n Marker marker = thisMap.addMarker(new MarkerOptions().position(coordinates).title(listing.getCategory()));\n marker.setTag(listing);\n }\n }\n });\n }","public ArrayList<ArrayList> intersection (ArrayList<ArrayList> data, ArrayList<ArrayList> data2)\n {\n ArrayList<Document> docs = data.get(0);\n ArrayList<Double> relevance = data.get(1);\n ArrayList<Integer> occurrence = data.get(2);\n ArrayList<Integer> popularity = data.get(3);\n \n ArrayList<Document> docs2 = data2.get(0);\n ArrayList<Double> relevance2 = data2.get(1);\n ArrayList<Integer> occurrence2 = data2.get(2);\n ArrayList<Integer> popularity2 = data2.get(3);\n \n ArrayList<Document> docs3 = new ArrayList<>();\n ArrayList<Double> relevance3 = new ArrayList<>();\n ArrayList<Integer> occurrence3 = new ArrayList<>();\n ArrayList<Integer> popularity3 = new ArrayList<>();\n \n for(Document d: docs)\n {\n if(docs2.contains(d))\n {\n docs3.add(d);\n int docIndex = docs.indexOf(d);\n int docIndex2 = docs2.indexOf(d);\n double oldRel = (double) relevance.get(docIndex);\n int oldOcc = (int) occurrence.get(docIndex);\n relevance3.add(oldRel+relevance2.get(docIndex2));\n if(oldOcc > occurrence2.get(docIndex2))\n {\n occurrence3.add(occurrence2.get(docIndex2));\n }\n else\n {\n occurrence3.add(oldOcc);\n }\n popularity3.add(d.popularity);\n }\n \n }\n data = new ArrayList<ArrayList> ();\n data.add(docs3);\n data.add(relevance3);\n data.add(occurrence3);\n data.add(popularity3);\n \n return data;\n }","public void testQuery() throws Exception {\n DummyApprovalRequest req1 = new DummyApprovalRequest(reqadmin, null, caid, SecConst.EMPTY_ENDENTITYPROFILE, false);\n DummyApprovalRequest req2 = new DummyApprovalRequest(admin1, null, caid, SecConst.EMPTY_ENDENTITYPROFILE, false);\n DummyApprovalRequest req3 = new DummyApprovalRequest(admin2, null, 3, 2, false);\n\n approvalSessionRemote.addApprovalRequest(admin1, req1, gc);\n approvalSessionRemote.addApprovalRequest(admin1, req2, gc);\n approvalSessionRemote.addApprovalRequest(admin1, req3, gc);\n\n // Make som queries\n Query q1 = new Query(Query.TYPE_APPROVALQUERY);\n q1.add(ApprovalMatch.MATCH_WITH_APPROVALTYPE, BasicMatch.MATCH_TYPE_EQUALS, \"\" + req1.getApprovalType());\n\n List result = approvalSessionRemote.query(admin1, q1, 0, 3, \"cAId=\" + caid, \"(endEntityProfileId=\" + SecConst.EMPTY_ENDENTITYPROFILE + \")\");\n assertTrue(\"Result size \" + result.size(), result.size() >= 2 && result.size() <= 3);\n\n result = approvalSessionRemote.query(admin1, q1, 1, 3, \"cAId=\" + caid, \"(endEntityProfileId=\" + SecConst.EMPTY_ENDENTITYPROFILE + \")\");\n assertTrue(\"Result size \" + result.size(), result.size() >= 1 && result.size() <= 3);\n\n result = approvalSessionRemote.query(admin1, q1, 0, 1, \"cAId=\" + caid, \"(endEntityProfileId=\" + SecConst.EMPTY_ENDENTITYPROFILE + \")\");\n assertTrue(\"Result size \" + result.size(), result.size() == 1);\n\n Query q2 = new Query(Query.TYPE_APPROVALQUERY);\n q2.add(ApprovalMatch.MATCH_WITH_STATUS, BasicMatch.MATCH_TYPE_EQUALS, \"\" + ApprovalDataVO.STATUS_WAITINGFORAPPROVAL, Query.CONNECTOR_AND);\n q2.add(ApprovalMatch.MATCH_WITH_REQUESTADMINCERTSERIALNUMBER, BasicMatch.MATCH_TYPE_EQUALS, reqadmincert.getSerialNumber().toString(16));\n\n result = approvalSessionRemote.query(admin1, q1, 1, 3, \"cAId=\" + caid, \"(endEntityProfileId=\" + SecConst.EMPTY_ENDENTITYPROFILE + \")\");\n assertTrue(\"Result size \" + result.size(), result.size() >= 1 && result.size() <= 3);\n\n // Remove the requests\n int id1 = ((ApprovalDataVO) approvalSessionRemote.findApprovalDataVO(admin1, req1.generateApprovalId()).iterator().next()).getId();\n int id2 = ((ApprovalDataVO) approvalSessionRemote.findApprovalDataVO(admin1, req2.generateApprovalId()).iterator().next()).getId();\n int id3 = ((ApprovalDataVO) approvalSessionRemote.findApprovalDataVO(admin1, req3.generateApprovalId()).iterator().next()).getId();\n approvalSessionRemote.removeApprovalRequest(admin1, id1);\n approvalSessionRemote.removeApprovalRequest(admin1, id2);\n approvalSessionRemote.removeApprovalRequest(admin1, id3);\n }","public static List<String> query_intersect(List<String> queryWords) throws IOException {\n\t\tif (!initialized) initialize();\n\t\tList<PostingList> pls = new ArrayList<PostingList> ();\n\t\tfor (String queryWord : queryWords) {\n\t\t\tqueryWord = queryWord.toLowerCase();\n\t\t\tif (!termDict.containsKey(queryWord)) {\n\t\t\t\tpls.clear();\n\t\t\t\tbreak;\n\t\t\t}\n\t\t\tPostingList pl = readPosting(fc, termDict.get(queryWord));\n\t\t\tif (pl == null) {\n\t\t\t\tpls.clear();\n\t\t\t\tbreak;\n\t\t\t}\n\t\t\tpls.add(readPosting(fc, termDict.get(queryWord)));\n\t\t}\n\t\tCollections.sort(pls, new Comparator<PostingList>(){\n\t\t public int compare(PostingList p1, PostingList p2) {\n\t\t return p1.size() - p2.size(); // assumes you want biggest to smallest\n\t\t }\n\t\t});\n\t\tif (pls.size() == 0) {\n\t\t\treturn null;\n\t\t} else {\n\t\t\tList<Integer> current = pls.get(0).getList();\n\t\t\tfor (int i = 1; i < pls.size(); i++) {\n\t\t\t\tList<Integer> toBeAdd = pls.get(i).getList();\n\t\t\t\tcurrent = intersect(current, toBeAdd);\n\t\t\t}\n\t\t\tif (current.size() == 0) {\n\t\t\t\treturn null;\n\t\t\t} else {\n\t\t\t\tList<String> result = new ArrayList<String>();\n\t\t\t\tfor (int docId : current) {\n\t\t\t\t\tresult.add(docDict.get(docId));\n\t\t\t\t}\n\t\t\t\treturn result;\n\t\t\t}\n\t\t}\n\t}","private void positionIntersects(LinkedList<TermPositions> p1, LinkedList<TermPositions> p2, int k) {\n if (p1 != null && p2 != null) {\n int df1 = p1.size();\n int df2 = p2.size();\n while (!p1.isEmpty() && !p2.isEmpty()) {\n int tf1 = p1.peek().getPositionList().size();\n int tf2 = p1.peek().getPositionList().size();\n if (p1.peek().getDocId() == p2.peek().getDocId()) {\n LinkedList<Integer> pp1 = p1.peek().getPositionList();\n while (!pp1.isEmpty()) {\n for (Integer integer : p2.peek().getPositionList()) {\n if ((pp1.peek() - integer) < 0 && Math.abs(pp1.peek() - integer) <= (k + 1)) {\n double score = (1 + Math.log(tf1) * Math.log(N / df1)) + (1 + Math.log(tf2) * Math.log(N / df2));\n resultsCollector.add(new DocCollector(p1.peek().getDocId(), score));\n break;\n }\n }\n pp1.pop();\n }\n } else if (p1.peek().getDocId() < p2.peek().getDocId())\n p1.pop();\n else\n p2.pop();\n\n p1.pop();\n p2.pop();\n\n }\n\n }\n\n\n }","@Test\r\n\t\tpublic void testIntersection() {\n\t\t\ttestingSet = new IntegerSet(list1);\r\n\t\t\ttestingSet2= new IntegerSet(list2);\r\n\t\t\t// create 3rdset = to the intersection list \r\n\t\t\ttestingSet3= new IntegerSet(intersection);\r\n\t\t\t// create 4th set =to the intersection of set1 and set2\r\n\t\t\ttestingSet4= testingSet.intersection(testingSet, testingSet2);\r\n\t\t\t// sets 3 and set 4 should be equal \r\n\t\t\t// assertEquals for these parameters is a deprecated method \r\n\t\t\tassertArrayEquals(testingSet3.toArray(),testingSet4.toArray());\t \r\n\t\t}","public void queryTaskUnionSet2() {\r\n\t\t// task 1\r\n\t\tTask task1 = new Task();\r\n\t\ttask1.setName(\"DEFECTS\");\r\n\t\ttask1.setDisplayName(\"Defects\");\r\n\t\ttask1.setDescription(\"User story to address product defects\");\r\n\t\t\r\n\t\tTask d1 = new Task();\r\n\t\td1.setName(\"DEFECT 1\");\r\n\t\td1.setDisplayName(\"Defect 1\");\r\n\t\td1.setDescription(\"First defect\");\r\n\t\tTask d2 = new Task();\r\n\t\td2.setName(\"DEFECT 2\");\r\n\t\td2.setDisplayName(\"Defect 2\");\r\n\t\td2.setDescription(\"Second defect\");\r\n\t\tSet<Task> c = new HashSet<Task>();\r\n\t\tc.add(d1);\r\n\t\tc.add(d2);\r\n\t\ttask1.setTaskChildren(c);\r\n\t\ttask1 = (Task) aggregateService.create(task1, new Settings());\r\n\r\n\t\t\tSystem.out.println(\"Name: \" + task1.getName() + \", Id: \" + task1.getId());\r\n\r\n\t\t// task 2\r\n\t\tTask task2 = new Task();\r\n\t\ttask2.setName(\"FIX_DEFECTS\");\r\n\t\ttask2.setDisplayName(\"Fix defects\");\r\n\t\ttask2.setDescription(\"Task to track the defect fixing effort\");\r\n\t\ttask2 = (Task) aggregateService.create(task2, new Settings());\r\n\r\n\t\t// task 3\r\n\t\tTask task3 = new Task();\r\n\t\ttask3.setName(\"PRIORITIZE_DEFECTS\");\r\n\t\ttask3.setDisplayName(\"Prioritize defects\");\r\n\t\ttask3.setDescription(\"Based upon the effort required for the defects prioritize them\");\r\n\t\ttask3 = (Task) aggregateService.create(task3, new Settings());\r\n\r\n\t\ttask1 = (Task) aggregateService.read(task1, getSettings());\t\t\r\n\r\n\t\t// query the task object\r\n\t\tSettings settings = new Settings();\r\n\t\tsettings.setParam(\"name1\", \"DEFECTS\");\r\n\t\tsettings.setParam(\"name2\", \"PRIORITIZE_DEFECTS\");\r\n\t\tsettings.setParam(\"name3\", \"FIX_DEFECTS\");\r\n\t\tsettings.addFunction(FunctionHandler.NE, \"name\", \"name3\");\r\n\t\tsettings.addFunction(FunctionType.ASC, \"name\");\r\n\t\tsettings.setView(aggregateService.getView(\"TASKUNIONSET\"));\t\t\r\n\t\tList<?> toList = aggregateService.query(new Task(), settings);\r\n\r\n\t\tSystem.out.println(\"SIZE : \" + toList.size());\r\n\t\tfor(Object o: toList) {\r\n\t\t\tTask t = (Task) o;\r\n\t\t\tSystem.out.println(\"Name: \" + t.getName() + \", Id: \" + t.getId());\r\n\t\t}\r\n\t\tassert(toList.size() == 2);\r\n\r\n\t\tObject obj1 = toList.get(0);\r\n\t\tObject obj2 = toList.get(1);\r\n\r\n\t\tassert(Task.class.isAssignableFrom(obj1.getClass()));\r\n\t\tassert(Task.class.isAssignableFrom(obj2.getClass()));\r\n\t\t\r\n\t\tTask t1 = (Task) obj1;\r\n\t\tTask t2 = (Task) obj2;\r\n\r\n\t\tassert ((t1.getName().equals(\"DEFECTS\") && t2.getName().equals(\"PRIORITIZE_DEFECTS\")) ||\r\n\t\t\t(t2.getName().equals(\"DEFECTS\") && t1.getName().equals(\"PRIORITIZE_DEFECTS\")));\r\n\r\n\t\tTask d = t1.getName().equals(\"DEFECTS\") ? t1 : t2;\r\n\t\tassert (d.getTaskChildren() != null && d.getTaskChildren().size() == 2);\r\n\r\n//\t\tSystem.out.println(\"Task 1: \" + t1.getName() + \", Task 2: \" + t2.getName());\r\n//\t\tassert (t1.getName().equals(\"DEFECTS\") && t2.getName().equals(\"DEFECT 1\"));\r\n//\t\tassert(t1.getTaskChildren() != null && t1.getTaskChildren().size() == 2);\r\n\t}","protected void merge(Object in1, Object in2, Object out) {\n\t\tFlowSet inSet1 = (FlowSet) in1, inSet2 = (FlowSet) in2, outSet = (FlowSet) out;\n\n\t\tinSet1.intersection(inSet2, outSet);\n\t}","public void queryTaskUnionSet1() {\r\n\t\t// task 1\r\n\t\tTask task1 = new Task();\r\n\t\ttask1.setName(\"DEFECTS\");\r\n\t\ttask1.setDisplayName(\"Defects\");\r\n\t\ttask1.setDescription(\"User story to address product defects\");\r\n\t\ttask1 = (Task) aggregateService.create(task1, new Settings());\t\r\n\r\n\t\t// task 2\r\n\t\tTask task2 = new Task();\r\n\t\ttask2.setName(\"FIX_DEFECTS\");\r\n\t\ttask2.setDisplayName(\"Fix defects\");\r\n\t\ttask2.setDescription(\"Task to track the defect fixing effort\");\r\n\t\ttask2 = (Task) aggregateService.create(task2, new Settings());\r\n\r\n\t\t// task 3\r\n\t\tTask task3 = new Task();\r\n\t\ttask3.setName(\"PRIORITIZE_DEFECTS\");\r\n\t\ttask3.setDisplayName(\"Prioritize defects\");\r\n\t\ttask3.setDescription(\"Based upon the effort required for the defects prioritize them\");\r\n\t\ttask3 = (Task) aggregateService.create(task3, new Settings());\r\n\r\n\t\ttask1 = (Task) aggregateService.read(task1, getSettings());\t\t\r\n\r\n\t\t// query the task object\r\n\t\tSettings settings = new Settings();\r\n\t\tsettings.setParam(\"name1\", \"FIX_DEFECTS\");\r\n\t\tsettings.setParam(\"name2\", \"PRIORITIZE_DEFECTS\");\r\n\t\tsettings.setView(aggregateService.getView(\"TASKUNIONSET\"));\t\t\r\n\t\tList<?> toList = aggregateService.query(new Task(), settings);\r\n\r\n\t\tassert(toList.size() == 2);\r\n\r\n\t\tObject obj1 = toList.get(0);\r\n\t\tObject obj2 = toList.get(1);\r\n\r\n\t\tassert(Task.class.isAssignableFrom(obj1.getClass()));\r\n\t\tassert(Task.class.isAssignableFrom(obj2.getClass()));\r\n\t\t\r\n\t\tTask t1 = (Task) obj1;\r\n\t\tTask t2 = (Task) obj2;\t\t\r\n\t\t\r\n\t\tassert( (t1.getName().equals(\"FIX_DEFECTS\") && t2.getName().equals(\"PRIORITIZE_DEFECTS\")) ||\r\n\t\t\t\t(t2.getName().equals(\"FIX_DEFECTS\") && t1.getName().equals(\"PRIORITIZE_DEFECTS\")) );\r\n\t}","public PostingsList ranked_query(Query query, double w, double idf_threshold){\n long startTime = System.nanoTime();\n PostingsList result = new PostingsList();\n\n // Obtain union of terms above idf threshold if indexElimination is true\n // (Set idf_threshold to zero to disable this feature)\n Set<String> termsToConsider = this.queryTermsConsidered(query, idf_threshold);\n result = this.union_query(query, termsToConsider);\n //System.err.println(\"Size of result is \" + result.size());\n\n long estimatedTime = (System.nanoTime() - startTime)/1000000;\n System.err.println(\"* Union took: \" + estimatedTime);\n\n\n /*\n * 2) Iterate over PostingsEntries and build the solution\n */\n startTime = System.nanoTime();\n // Required when iterating over a PostingsList\n PostingsEntry postEnt = new PostingsEntry();\n // Number of documents in the collection\n double nDocs = this.docIDs.size();\n // Weight of a query vector coefficient\n double w_query_term;\n // Document tf-idf variables\n double termFrequency_doc, documentFrequency_doc, w_doc_term;\n\n for(String term : termsToConsider){\n // Obtain idf of the term\n documentFrequency_doc = Math.log(nDocs/new Double(this.idfMap.get(term)));\n\n // Obtain weight of the term\n w_query_term = query.weights.get(term);\n // Iterate over all documents containing the term and update the score(q,d)\n Iterator<PostingsEntry> it_d = result.iterator();\n while(it_d.hasNext()){\n postEnt = it_d.next();\n if (this.tfMap.get(postEnt.docID).containsKey(term)){\n termFrequency_doc = this.tfMap.get(postEnt.docID).get(term);\n w_doc_term = documentFrequency_doc*termFrequency_doc;\n postEnt.score += w_query_term*w_doc_term;\n }\n }\n }\n estimatedTime = (System.nanoTime() - startTime)/1000000;\n System.err.println(\"* Building solution took: \" + estimatedTime);\n\n /*\n * 3) Normalize the scores\n */\n startTime = System.nanoTime();\n Iterator<PostingsEntry> it = result.iterator();\n while(it.hasNext()){\n postEnt = it.next();\n postEnt.score /= (new Double(this.docLengths.get(\"\"+postEnt.docID)));//(Math.sqrt(postEnt.norm2));\n postEnt.score = w * postEnt.score + (1-w) * quality(postEnt.docID);\n }\n estimatedTime = (System.nanoTime() - startTime)/1000000;\n System.err.println(\"* Normalizing took: \" + estimatedTime);\n\n /*\n * 4) Sort the resulting solution\n */\n startTime = System.nanoTime();\n result.sort();\n estimatedTime = (System.nanoTime() - startTime)/1000000;\n System.err.println(\"* Sorting took: \" + estimatedTime);\n\n return result;\n }","private boolean isIntersectWithSource(List<Pair<Tuple,String>> list1, List<Pair<Tuple,String>> list2) {\n\t\tboolean intersect = false;\n\t\t\n\t\tfor (Pair<Tuple,String> tuple : list1) {\n\t\t\tif (list2.contains(tuple)) {\n\t\t\t\tintersect = true;\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\treturn intersect;\n\t}","public void mergeIn(QueryMetadata otherInstance) {\n for(QueryMetadataItem otherItem : otherInstance.items) {\n boolean alreadyExists = false;\n for(QueryMetadataItem item : items) {\n if(item.name.equals(otherItem.name)) {\n alreadyExists = true;\n }\n }\n if(!alreadyExists) {\n addItem(otherItem.name, otherItem.value);\n }\n }\n }","private Map mergeResults(Map first, Map second) {\n/* 216 */ Iterator verb_enum = second.keySet().iterator();\n/* 217 */ Map clonedHash = new HashMap(first);\n/* */ \n/* */ \n/* 220 */ while (verb_enum.hasNext()) {\n/* 221 */ String verb = verb_enum.next();\n/* 222 */ List cmdVector = (List)clonedHash.get(verb);\n/* 223 */ if (cmdVector == null) {\n/* 224 */ clonedHash.put(verb, second.get(verb));\n/* */ continue;\n/* */ } \n/* 227 */ List oldV = (List)second.get(verb);\n/* 228 */ cmdVector = new ArrayList(cmdVector);\n/* 229 */ cmdVector.addAll(oldV);\n/* 230 */ clonedHash.put(verb, cmdVector);\n/* */ } \n/* */ \n/* 233 */ return clonedHash;\n/* */ }","private void addQueries(String query){\n ArrayList <String> idsFullSet = new ArrayList <String>(searchIDs);\n while(idsFullSet.size() > 0){\n ArrayList <String> idsSmallSet = new ArrayList <String>(); \n if(debugMode) {\n System.out.println(\"\\t Pmids not used in query available : \" + idsFullSet.size());\n }\n idsSmallSet.addAll(idsFullSet.subList(0,Math.min(getSearchIdsLimit(), idsFullSet.size())));\n idsFullSet.removeAll(idsSmallSet);\n String idsConstrain =\"\";\n idsConstrain = idsConstrain(idsSmallSet);\n addQuery(query,idsConstrain);\n }\n }","@Test\n public void sharedFilterEnsuresUniqueResults() {\n Filter filter = new Filter(\"test-filter\");\n final Dataset dataset1 = new Dataset(\"TEST1\", \"sql\", filter);\n final Dataset dataset2 = new Dataset(\"TEST2\", \"sql2\", filter); // shared same filter\n\n List<String> entry1 = new ArrayList<>();\n entry1.add(\"001\");\n entry1.add(\"aaa\");\n\n List<String> entry2 = new ArrayList<>();\n entry2.add(\"002\");\n entry2.add(\"bbb\");\n\n List<String> entry3 = new ArrayList<>();\n entry3.add(\"003\");\n entry3.add(\"ccc\");\n\n List<String> entry4 = new ArrayList<>();\n entry4.add(\"004\");\n entry4.add(\"ddd\");\n\n List<List<String>> queryResults1 = new ArrayList<>();\n queryResults1.add(entry1);\n queryResults1.add(entry2);\n queryResults1.add(entry3);\n queryResults1.add(entry4);\n\n List<String> entry5 = new ArrayList<>();\n entry5.add(\"005\"); // different\n entry5.add(\"eee\");\n\n List<String> entry6 = new ArrayList<>();\n entry6.add(\"002\"); // same\n entry6.add(\"bbb\");\n\n List<String> entry7 = new ArrayList<>();\n entry7.add(\"007\"); // different\n entry7.add(\"fff\");\n\n List<String> entry8 = new ArrayList<>();\n entry8.add(\"004\"); // same\n entry8.add(\"ddd\");\n\n List<List<String>> queryResults2 = new ArrayList<>();\n queryResults2.add(entry5);\n queryResults2.add(entry6);\n queryResults2.add(entry7);\n queryResults2.add(entry8);\n\n // given\n dataset1.populateCache(queryResults1, 200L);\n dataset2.populateCache(queryResults2, 300L);\n\n // when\n final List<String> result1 = dataset1.getCachedResult();\n final List<String> result2 = dataset1.getCachedResult();\n final List<String> result3 = dataset1.getCachedResult();\n final List<String> result4 = dataset1.getCachedResult();\n final List<String> result5 = dataset2.getCachedResult();\n final List<String> result6 = dataset2.getCachedResult();\n\n // then\n assertEquals(\"Wrong result 1\", entry1, result1); // first datset is as-is\n assertEquals(\"Wrong result 2\", entry2, result2); // first datset is as-is\n assertEquals(\"Wrong result 3\", entry3, result3); // first datset is as-is\n assertEquals(\"Wrong result 4\", entry4, result4); // first datset is as-is\n assertEquals(\"Wrong result 3\", entry5, result5); // second datset, not filtered out\n assertEquals(\"Wrong result 3\", entry7, result6); // second dataset, entry6 is filtered out\n\n // and\n try {\n dataset1.getCachedResult();\n fail(\"Expected to run out of data\");\n\n } catch (IllegalStateException ex) {\n assertEquals(\"Wrong error\", \"No more data available for dataset: TEST1\", ex.getMessage());\n }\n\n try {\n // entry7 should be filtered out, resulting in no more data\n dataset2.getCachedResult();\n fail(\"Expected to run out of data\");\n\n } catch (IllegalStateException ex) {\n assertEquals(\"Wrong error\", \"No more data available for dataset: TEST2\", ex.getMessage());\n }\n\n // and\n assertEquals(\"Wrong cache size\", Optional.of(4), dataset1.getMetrics().getCacheSize());\n assertEquals(\"Wrong timing\", Optional.of(200L), dataset1.getMetrics().getTimingMilliseconds());\n assertEquals(\"Wrong cache requested\", Optional.of(5), dataset1.getMetrics().getCacheRequested());\n assertEquals(\"Wrong filtered out\", Optional.empty(), dataset1.getMetrics().getFilteredOut());\n\n // and\n assertEquals(\"Wrong cache size\", Optional.of(4), dataset2.getMetrics().getCacheSize());\n assertEquals(\"Wrong timing\", Optional.of(300L), dataset2.getMetrics().getTimingMilliseconds());\n assertEquals(\"Wrong cache requested\", Optional.of(3), dataset2.getMetrics().getCacheRequested());\n assertEquals(\"Wrong filtered out\", Optional.of(2), dataset2.getMetrics().getFilteredOut());\n }","public ArrayList<Posting> mergeTwoPostingList(ArrayList<Posting> a, ArrayList<Posting> b) { \r\n\t\tfor (Posting postingA : a) {\r\n\t\t\tint indexInB = b.indexOf(postingA);\r\n\t\t\tif (indexInB == -1)\r\n\t\t\t\tb.add(postingA);\r\n\t\t\telse\r\n\t\t\t\tb.get(indexInB).increaseTermFrequecyBy(postingA.getTermFrequency());\r\n\t\t}\r\n\t\treturn b;\r\n\t}","public void searchArea(Connection connection, String city, String state, int zip) throws SQLException {\n\n ResultSet rs = null;\n PreparedStatement pStmt = null;\n String sql1 = \"SELECT hotel_name, branch_id FROM Hotel_Address WHERE city = ?\";\n String sql2 = \"SELECT hotel_name, branch_id FROM Hotel_Address WHERE state = ?\";\n String sql3 = \"SELECT hotel_name, branch_id FROM Hotel_Address WHERE zip = ?\";\n\n // City and State combination:\n if (city != null && state != null){\n\n pStmt = connection.prepareStatement(sql1 + \" INTERSECT \" + sql2);\n pStmt.clearParameters();\n\n setCity(city);\n pStmt.setString(1, getCity());\n setState(state);\n pStmt.setString(2, getState());\n }\n\n // City and ZIP combination:\n else if (city != null){\n\n pStmt = connection.prepareStatement(sql1 + \" INTERSECT \" + sql3);\n pStmt.clearParameters();\n\n setCity(city);\n pStmt.setString(1, getCity());\n setZip(zip);\n pStmt.setInt(2, getZip());\n }\n\n // State and ZIP combination:\n else {\n\n pStmt = connection.prepareStatement(sql2 + \" INTERSECT \" + sql3);\n pStmt.clearParameters();\n\n setState(state);\n pStmt.setString(1, getState());\n setZip(zip);\n pStmt.setInt(2, getZip());\n }\n\n try {\n\n System.out.println(\" Hotels in area:\");\n System.out.println(\"+------------------------------------------------------------------------------+\");\n\n rs = pStmt.executeQuery();\n String result;\n\n while (rs.next()) {\n\n System.out.println(rs.getString(1) + \" \" + rs.getInt(2));\n }\n }\n catch (SQLException e) { throw e; }\n finally {\n pStmt.close();\n if(rs != null) { rs.close(); }\n }\n }","public ArrayList<ArrayList> union(ArrayList<ArrayList> data, ArrayList<ArrayList> data2)\n {\n if(data == null || data2 == null)\n {\n return null;\n }\n ArrayList<Document> docs = data.get(0);\n ArrayList<Double> relevance = data.get(1);\n ArrayList<Integer> occurrence = data.get(2);\n ArrayList<Integer> popularity = data.get(3);\n \n ArrayList<Document> docs2 = data2.get(0);\n ArrayList<Double> relevance2 = data2.get(1);\n ArrayList<Integer> occurrence2 = data2.get(2);\n ArrayList<Integer> popularity2 = data2.get(3);\n \n ArrayList<Document> docs3 = new ArrayList<>();\n ArrayList<Double> relevance3 = new ArrayList<>();\n ArrayList<Integer> occurrence3 = new ArrayList<>();\n ArrayList<Integer> popularity3 = new ArrayList<>();\n \n for(int i = 0; i < docs.size(); i++)\n {\n docs3.add(docs.get(i));\n relevance3.add(relevance.get(i));\n occurrence3.add(occurrence.get(i));\n popularity3.add(popularity.get(i));\n }\n \n for(Document d: docs2)\n {\n if(!docs3.contains(d))\n {\n docs3.add(d);\n int docIndex = docs2.indexOf(d);\n relevance3.add(relevance2.get(docIndex));\n occurrence3.add(occurrence2.get(docIndex));\n popularity3.add(d.popularity);\n }\n else\n {\n int docIndex = docs3.indexOf(d);\n int docIndex2 = docs2.indexOf(d);\n double oldRel = (double) relevance3.get(docIndex);\n int oldOcc = (int) occurrence3.get(docIndex);\n relevance3.set(docIndex, oldRel+relevance2.get(docIndex2));\n if(oldOcc > occurrence2.get(docIndex2))\n {\n occurrence3.set(docIndex, occurrence2.get(docIndex2));\n }\n } \n }\n ArrayList<ArrayList> data3 = new ArrayList();\n data3.add(docs3);\n data3.add(relevance3);\n data3.add(occurrence3);\n data3.add(popularity3);\n return data3; \n }","private Set<String> getIntersection( Set<String> a, Set<String> b ) {\n\t\tSet<String> intersection = new HashSet<String>(a);\n\t\tintersection.retainAll(b);\n\t\treturn intersection;\n\t}","@Override\n\tpublic IPredicate intersection(final IPredicate state1, final IPredicate state2) {\n\n\t\tfinal Set<HcPredicateSymbol> state1PredSymbols = new HashSet<>();\n\t\tstate1PredSymbols.addAll(((HCPredicate) state1).getHcPredicateSymbols());\n//\t\tassert state1PredSymbols.size() == 1 : \"what does this mean??\";\n\n//\t\tfinal Term conjoinedFormula = mSimplifier.getSimplifiedTerm(\n//\t\t\t\tSmtUtils.and(mBackendSmtSolverScript.getScript(), state1.getFormula(), state2.getFormula()));\n\t\tfinal IPredicate conjoinedPred = mPredicateFactory.and(state1, state2);\n\n\t\tif (mPredicateFactory.isDontCare(conjoinedPred)) {\n\t\t\treturn mPredicateFactory.newPredicate(state1PredSymbols, conjoinedPred.getFormula(),\n\t\t\t\tCollections.emptyList());\n//\t\t\treturn conjoinedPred;\n\t\t}\n\n\t\tfinal Term conjoinedFormula = new CommuhashNormalForm(mServices, mMgdScript.getScript())\n\t\t\t\t.transform(conjoinedPred.getFormula());\n\n//\t\tfinal Set<IPredicate> ps = new HashSet<>();\n//\t\tps.add(state1);\n//\t\tps.add(state2);\n\n\t\treturn mPredicateFactory.newPredicate(state1PredSymbols, conjoinedFormula,\n\t\t\t\tArrays.asList(state1.getFormula().getFreeVars()));\n\t}","ResponseEntity<Response> placesInCommon(String userId1, String listName1, String userId2, String listName2);","public static <T extends Comparable<? super T>>\n void intersection(SLL<T> list1, SLL<T> list2, SLL<T> result) {\n\n SLLNode<T> iterlist1 = list1.head;\n SLLNode<T> iterlist2 = list2.head;\n\n T itemlist1=null, itemlist2=null;\n\n // get first item in each list\n if ( iterlist1 != null && iterlist2 != null ) {\n itemlist1 = iterlist1.info;\n itemlist2 = iterlist2.info;\n }\n\n while ( itemlist1 != null && itemlist2 != null ) {\n int compareResult = itemlist1.compareTo(itemlist2);\n \n if ( compareResult == 0 ) {\n result.addToTail(itemlist1); //append to result list\n if( iterlist1.next != null ) {\n iterlist1 = iterlist1.next;\n itemlist1 = iterlist1.info;\n } else {\n itemlist1 = null;\n }\n \n if( iterlist2.next != null ) {\n iterlist2 = iterlist2.next;\n itemlist2 = iterlist2.info;\n } else {\n itemlist2 = null;\n } \n }\n else if ( compareResult < 0 ) { \n if( iterlist1.next != null ) {\n iterlist1 = iterlist1.next;\n itemlist1 = iterlist1.info;\n } else {\n itemlist1 = null;\n }\n }\n else {\n if( iterlist2.next != null ) {\n iterlist2 = iterlist2.next;\n itemlist2 = iterlist2.info;\n } else {\n itemlist2 = null;\n }\n }\n }\n }","private static Set<Item> multiSetIntersection(List<Set<Item>> setList) {\n Set<Item> interQrels = new HashSet<>(setList.get(0));\r\n \r\n for (int i = 1; i< setList.size();i++) {\r\n interQrels.retainAll(setList.get(i)); // intersection with two (and one)\r\n }\r\n\r\n return interQrels;\r\n }","private <T> ArrayList<T> intersection(ArrayList<T> list1, ArrayList<T> list2) {\n ArrayList<T> list = new ArrayList<T>();\n\n for (T t : list1) {\n if (list2.contains(t)) {\n list.add(t);\n }\n }\n\n return list;\n }","@SuppressWarnings({ \"rawtypes\", \"unchecked\" })\n\tprivate static List<Object> mergeResult(List<Object> list1, List<Object> list2) {\n\t\tList<Object> result = new ArrayList<Object>();\n\t\tfor (int i = 0; i < list1.size(); i++) {\n\t\t\tfor (int j = 0; j < list2.size(); j++) {\n\t\t\t\tif (Integer.parseInt(((Map) list1.get(i)).get(MongoDBConstants.DOCUMENT_ID).toString()) == Integer\n\t\t\t\t\t\t.parseInt(((Map) list2.get(j)).get(MongoDBConstants.DOCUMENT_ID).toString())) {\n\t\t\t\t\tMap data = new HashMap();\n\t\t\t\t\tint hour = (Integer.parseInt(((Map) list1.get(i)).get(MongoDBConstants.DOCUMENT_ID).toString()) + 8) % 24;\n\t\t\t\t\tdata.put(MongoDBConstants.DOCUMENT_ID, hour + \"\");\n\t\t\t\t\tdata.put(\"value\", Integer.parseInt(((Map) list1.get(i)).get(\"value\").toString())\n\t\t\t\t\t\t\t+ Integer.parseInt(((Map) list2.get(j)).get(\"value\").toString()));\n\t\t\t\t\tresult.add(data);\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t\treturn result;\n\t}","@Override\n public void processElement(ProcessContext c) {\n List<LdVariant> queryList = null;\n List<LdVariant> targetList = null;\n int inputListCount = 0;\n for (KV<Boolean, List<LdVariant>> vl : c.element().getValue()) {\n if (vl.getKey()) {\n queryList = vl.getValue();\n } else {\n targetList = vl.getValue();\n }\n inputListCount++;\n }\n\n if (inputListCount != 2 || queryList == null || targetList == null) {\n throw new IllegalArgumentException(\"There should be exactly two lists.\");\n }\n\n Iterator<LdVariant> targetIter = targetList.iterator();\n\n // Our working set of variants from the target shard that could be within window of variants\n // read in from the query shard.\n LinkedList<LdVariant> storedTarget = new LinkedList<>();\n\n for (LdVariant queryVar : queryList) {\n // Fill in storedTarget until we are past window from queryVar.\n while (targetIter.hasNext()\n && (storedTarget.isEmpty() || (queryVar.getInfo().getEnd() + window) > storedTarget\n .getLast().getInfo().getStart())) {\n storedTarget.add(targetIter.next());\n }\n\n ListIterator<LdVariant> storedTargetIter = storedTarget.listIterator(0);\n while (storedTargetIter.hasNext()) {\n LdVariant targetVar = storedTargetIter.next();\n\n if (queryVar.getInfo().compareTo(targetVar.getInfo()) != -1) {\n // Only do comparisons where query is before target. If query is past target then\n // we are done with target. Note: targetVar > queryVar implies targetVar start >= queryVar\n // start.\n storedTargetIter.remove();\n } else if (targetVar.getInfo().getStart() >= (queryVar.getInfo().getEnd() + window)) {\n // If the next query starts more than window from when target starts, we are done\n // with the rest of storedTarget for this query.\n break;\n } else {\n // If target starts >= query starts and target starts < window from query end, then they\n // must overlap.\n c.output(KV.of(queryVar, targetVar));\n }\n }\n }\n }","@Test\n public void testSqlExistsBasedJoin() {\n Query<Car> carsQuery = and(\n in(Car.FEATURES, \"sunroof\", \"convertible\"),\n existsIn(garages,\n Car.NAME,\n Garage.BRANDS_SERVICED,\n equal(Garage.LOCATION, \"Dublin\")\n )\n );\n\n Map<Car, Set<Garage>> results = new LinkedHashMap<Car, Set<Garage>>();\n for (Car car : cars.retrieve(carsQuery)) {\n Query<Garage> garagesWhichServiceThisCarInDublin\n = and(equal(Garage.BRANDS_SERVICED, car.name), equal(Garage.LOCATION, \"Dublin\"));\n for (Garage garage : garages.retrieve(garagesWhichServiceThisCarInDublin)) {\n Set<Garage> garagesWhichCanServiceThisCar = results.get(car);\n if (garagesWhichCanServiceThisCar == null) {\n garagesWhichCanServiceThisCar = new LinkedHashSet<Garage>();\n results.put(car, garagesWhichCanServiceThisCar);\n }\n garagesWhichCanServiceThisCar.add(garage);\n }\n }\n\n assertEquals(\"join results should contain 2 cars\", 2, results.size());\n Assert.assertTrue(\"join results should contain car1\", results.containsKey(car1));\n Assert.assertTrue(\"join results should contain car4\", results.containsKey(car4));\n\n assertEquals(\"join results for car1\", asSet(garage3, garage4), results.get(car1));\n assertEquals(\"join results for car4\", asSet(garage2), results.get(car4));\n }","public static void main(String[] args) {\n String[] data ={\"cars\",\"clothes\",\"jewelry\",\"women\"};\r\n List<String> list1 = Arrays.asList(data);\r\n \r\n ArrayList<String> list2 = new ArrayList<String>();\r\n list2.add(\"youtube\");\r\n list2.add(\"snapchat\");\r\n list2.add(\"instagram\");\r\n \r\n for(String x : list2)\r\n System.out.printf(\"%s \", x);\r\n \r\n Collections.addAll(list2, data);\r\n \r\n System.out.println();\r\n for(String x : list2)\r\n System.out.printf(\"%s \", x);\r\n System.out.println();\r\n \r\n System.out.println(Collections.frequency(list2, \"cars\"));\r\n \r\n boolean tof = Collections.disjoint(list1, list2);\r\n System.out.println(tof);\r\n \r\n if(tof)\r\n System.out.println(\"these list do not have anything in common\");\r\n else \r\n System.out.println(\"these list do have something in common!\");\r\n \r\n }","public static void main(String[] args) {\n\t\tint[] nums1 = {4,9,5};\r\n\t\tint[] nums2 = {9,4,9,8,4};\r\n\t\t//System.out.println(intersection(nums1, nums2));\r\n\t\tArrays.sort(nums1);\r\n\t\tArrays.sort(nums2);\r\n\t\tif (nums1.length>nums2.length) {\r\n\t\t\tint[] temp = nums2;\r\n\t\t\tnums2 = nums1;\r\n\t\t\tnums1 = temp;\r\n\t\t}\r\n\t\tHashSet<Integer> mSet1 = new HashSet<Integer>();\r\n\t\tHashSet<Integer> mSet2 = new HashSet<Integer>();\r\n\t\tfor (Integer i : nums2) {\r\n\t\t\tmSet1.add(i);\r\n\t\t}\r\n\t\tfor (Integer x: nums1) {\r\n\t\t\tif (mSet1.contains(x)) {\r\n\t\t\t\tmSet2.add(x);\r\n\t\t\t}\r\n\t\t}\r\n\t\tint[] r = new int[mSet2.size()];\r\n\t\tint index = 0;\r\n\t\tfor (Integer g: mSet2) {\r\n\t\t\tr[index] = g;\r\n\t\t\tindex++;\r\n\t\t}\r\n\t}","public PostingsList search( Query query, int queryType, int rankingType,\n int structureType ) {\n double idf_threshold = new Double(0);\n double index_elimination = new Double(0.008);\n // System.err.println(pageRank[docNumber.get(\"121\")]);\n\n if (query.size()>0){\n switch (queryType){\n case Index.INTERSECTION_QUERY:\n System.err.println(\"Intersection query\");\n return intersect(query);\n case Index.PHRASE_QUERY:\n System.err.println(\"Phrase query\");\n return phrase_query(query);\n case Index.RANKED_QUERY:\n System.err.println(\"Ranked query\");\n switch(rankingType){\n case Index.TF_IDF: return ranked_query(query, 1, idf_threshold);\n case Index.PAGERANK: return ranked_query(query, 0, idf_threshold);//ranked_query(query, 0, idf_threshold);//ranked_query2(query, 0);\n case Index.COMBINATION: return ranked_query(query, index_elimination, idf_threshold);\n }\n default:\n System.out.println(\"not valid query\");\n return null;\n }\n }\n else\n // Query was empty\n return null;\n }","public static void main(String[] args) {\n\n\t\tCollection<String> collection1 = new ArrayList<String>();\n\t\tcollection1.add(\"Toronto\");\n\t\tcollection1.add(\"Hamilton\");\n\t\tcollection1.add(\"London\");\n\t\tcollection1.add(\"Ottawa\");\n\t\tcollection1.add(\"Toronto\");\n\t\tSystem.out.println(\"A list of cities in c1 is \" + collection1);\n\t\tSystem.out.println(\" Is hamilton in c1? \" + collection1.contains(\"Hamilton\"));\n\t\tSystem.out.println(\"Size of collection c1 is \" + collection1.size());\n\t\tCollection<String> collection2 = new ArrayList<String>();\n\t\tcollection1.add(\"Vancouver\");\n\t\tcollection1.add(\"Delhi\");\n\t\tcollection1.add(\"chd\");\n\t\tcollection1.add(\"Toronto\");\n\t\tcollection1.addAll(collection2);\n\t\tSystem.out.println(\"combined list is : \" + collection1);\n//\t\tCollection<String> c1 = new ArrayList<String>(collection1);\n//\t\tc1.retainAll(collection2);\n//\t\tSystem.out.println(\"A list of cities in c1 is \" + c1);\n//\t\tc1.removeAll(collection2);\n//\t\tSystem.out.println(\"A list of cities in c1 is \" + c1);\n\t\t\n\t}","@Override\n public List<Auction> meetCriteria(List<Auction> auctions) \n {\n List<Auction> firstCriteriaItems = criteria1.meetCriteria(auctions);\n List<Auction> otherCriteriaItems = criteria2.meetCriteria(auctions);\n // if an item b is in Collection B but is not in Collection A,\n // add item b to collection A. This yields unique elements b and a\n // in the new collection C.\n for (Auction auction : otherCriteriaItems) \n {\n if(!firstCriteriaItems.contains(auction))\n {\n firstCriteriaItems.add(auction);\n }\n }\t\n return firstCriteriaItems;\n }","private static boolean intersect(\n\t\tDateTime start1, DateTime end1,\n\t\tDateTime start2, DateTime end2)\n\t{\n\t\tif (DateTime.op_LessThanOrEqual(end2, start1) || DateTime.op_LessThanOrEqual(end1, start2))\n\t\t\treturn false;\n\n\t\treturn true;\n\t}","abstract protected Object joinClause(Object o1, Object o2);","public static Set<Doc> and(Set<Doc> set1, Set<Doc> set2) {\r\n \t\t\r\n \t\tif((set1 == null) || (set2 == null)) {\r\n\t\t\tSystem.err.println(\"Doc.and() returning null!\");\r\n \t\t\treturn new TreeSet<Doc>();\r\n \t\t}\r\n \t\t//set1.retainAll(set2);\r\n \t\t//return set1;\r\n \t\t\r\n \t\tTreeSet<Doc> result = new TreeSet<Doc>();\r\n \t\tIterator<Doc> op1 = set1.iterator();\r\n \t\tIterator<Doc> op2 = set2.iterator();\r\n \t\t\r\n \t\tDoc current1 = getNext(op1);\r\n \t\tDoc current2 = getNext(op2);\r\n \r\n \t\twhile(current1!=null && current2!=null) {\r\n \t\t\t//If is the same document\r\n \t\t\tif(current1.getID() == current2.getID()) {\r\n \t\t\t\tresult.add(current1);\r\n \t\t\t\tcurrent1 = getNext(op1);\r\n \t\t\t\tcurrent2 = getNext(op2);\r\n \t\t\t}\r\n \t\t\t//If op2 is ahead of op1\r\n \t\t\telse if(current1.getID() < current2.getID()) \r\n \t\t\t\tcurrent1 = getNext(op1);\r\n \t\t\t//If op1 is ahead of op2\r\n \t\t\telse\r\n \t\t\t\tcurrent2 = getNext(op2);\r\n \t\t}\r\n \t\t\r\n \t\treturn result;\r\n \t}","@Override\n protected DataSet<GraphHead> computeNewGraphHeads() {\n return firstCollection.getGraphHeads()\n .union(secondCollection.getGraphHeads())\n .groupBy(new Id<GraphHead>())\n .reduceGroup(new GroupCountEquals<GraphHead>(2));\n }","public static void main(String[] args) {\n\t\tIntersection l5=new Intersection(5,null);\n\t\tIntersection l4=new Intersection(4,l5);\n\t\tIntersection l3=new Intersection(3,l4);\n\t\tIntersection l2=new Intersection(2,l3);\n\t\tIntersection l1=new Intersection(1,l2);\n\t\t\n\t\tIntersection m7=new Intersection(7,l3);\n\t\tIntersection m6=new Intersection(6,m7);\n\t\tint flag=0;\n\t\twhile(m6!=null && l1!=null){\n\t\t\tif(m6!=l1){\n\t\t\t\tm6=m6.next;\n\t\t\t\tl1=l1.next;\n\t\t\t}\n\t\t\telse{\n\t\t\t\tflag=1;\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\tif(flag==1){\n\t\t\tSystem.out.println(\"They Intersect!\");\n\t\t}\n\t\telse{\n\t\t\tSystem.out.println(\"They don't!\");\n\t\t}\n\t}","public static void main(String[] args) {\n\t\tLL l1 = new LL();\n\t\tLL l2 = new LL();\n\t\tl1.insert(15);\n\t\tl1.insert(25);\n\t\tl1.insert(35);\n\t\tl1.insert(45);\n\t\tl1.insert(55);\n\t\t\n\t\tl2.insert(10);\n\t\tl2.insert(17);\n\t\tl2.insert(35);\n\t\tl2.insert(47);\n\t\tl2.insert(11);\n\t \t\n\t\t\n//\t\tl1.print();\n//\t\tl2.print();\n\t\t\n\t\tSystem.out.println(getIntersection(l1.head,l2.head));\n\t\t\n\t}","public void testUsingQueriesFromQueryManger(){\n\t\tSet<String> names = testDataMap.keySet();\n\t\tUtils.prtObMess(this.getClass(), \"atm query\");\n\t\tDseInputQuery<BigDecimal> atmq = \n\t\t\t\tqm.getQuery(new AtmDiot());\n\t\tMap<String, ComplexQueryResult<BigDecimal>> bdResult = \n\t\t\t\tatmq.get(names, 1, TimeUnit.SECONDS);\n\t\tCollectionsStaticMethods.prtMapItems(bdResult);\n\n\t\tUtils.prtObMess(this.getClass(), \"vol query\");\n\t\tDseInputQuery<BigDecimal> volq = \n\t\t\t\tqm.getQuery(new VolDiotForTest());\n\t\tMap<String, ComplexQueryResult<BigDecimal>> dbResult = \n\t\t\t\tvolq.get(names, 1, TimeUnit.SECONDS);\n\t\tCollectionsStaticMethods.prtMapItems(dbResult);\n\t\n\t\tUtils.prtObMess(this.getClass(), \"integer query\");\n\t\tDseInputQuery<BigDecimal> strikeq = \n\t\t\t\tqm.getQuery(new StrikeDiotForTest());\n\t\tMap<String, ComplexQueryResult<BigDecimal>> strikeResult = \n\t\t\t\tstrikeq.get(names, 1, TimeUnit.SECONDS);\n\t\tCollectionsStaticMethods.prtMapItems(strikeResult);\n\t\n\t}","public ArrayList<Object> intersect(ArrayList<Object> list1, ArrayList<Object> list2)\r\n {\r\n ArrayList<Object> retList = new ArrayList<Object>();\r\n for(Object o : list1)\r\n if(list2.contains(o))\r\n retList.add(o);\r\n return retList;\r\n }","private void twoDateOccupancyQuery(String startDate, String endDate){\n List<String> emptyRooms = findEmptyRoomsInRange(startDate, endDate);\n List<String> fullyOccupiedRooms = findOccupiedRoomsInRange(startDate, endDate, emptyRooms);\n List<String> partiallyOccupiedRooms = \n (generateListOfAllRoomIDS().removeAll(emptyRooms)).removeAll(fullyOccupiedRooms);\n\n occupancyColumns = new Vector<String>();\n occupancyData = new Vector<Vector<String>>();\n occupancyColumns.addElement(\"RoomId\");\n occupancyColumns.addElement(\"Occupancy Status\");\n\n for(String room: emptyRooms) {\n Vector<String> row = new Vector<String>();\n row.addElement(room);\n row.addElement(\"Empty\");\n occupancyData.addElement(row);\n }\n for(String room: fullyOccupiedRooms) {\n Vector<String> row = new Vector<String>();\n row.addElement(room);\n row.addElement(\"Fully Occupied\");\n occupancyData.addElement(row);\n }\n for(String room: partiallyOccupiedRooms) {\n Vector<String> row = new Vector<String>();\n row.addElement(room);\n row.addElement(\"Partially Occupied\");\n occupancyData.addElement(row);\n }\n return;\n}","public static void main(String[] args) {\n List<Integer> list1 = new ArrayList<>();\n List<Integer> list2 = new ArrayList<>();\n list1.add(2);\n list1.add(3);\n list1.add(4);\n list2.add(1);\n list2.add(5);\n list2.add(6);\n merge(list1, list2).forEach(item -> System.out.print(item + \" \"));\n }","private boolean isIntersect(List<Tuple> list1, List<Tuple> list2) {\n\t\tboolean intersect = false;\n\t\tfor (Tuple tuple : list1) {\n\t\t\tif (list2.contains(tuple)) {\n\t\t\t\tintersect = true;\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\treturn intersect;\n\t}","@Test\n public void test1() {\n final List<String> listA = Arrays.asList(\"Fremont\", \"Dublin\", \"anamole\", \"San Jose\" , \"SFO\", \"Dublin\", \"San Jose\", \"paramount\", \"y\");\n final List<String> listB = Arrays.asList(\"Dublin\", \"san mateo\", \"los angeles\", \"san mateo\", \"fremont\", \"anamole\", \"x\", \"x\", \"Y\");\n final List<String> common = FindIntersection.findCommonLists(listA, listB);\n System.out.println(Arrays.toString(FindIntersection.findCommonLists(listA, listB).toArray()));\n\n }","boolean overlap(Reservation other);","@Test\n\tpublic void integrationTest2() throws Exception {\n\t\tHashSet<String> mistress = loadGrepResults(\"mistress\");\n\t\tHashSet<String> undocumented = loadGrepResults(\"undocumented\");\n\t\tHashSet<String> insane = loadGrepResults(\"insane\");\n\t\tHashSet<String> crazy = loadGrepResults(\"crazy\");\n\t\tHashSet<String> forced = loadGrepResults(\"!i+am+forced\");\n\t\t\n\t\tHashSet<String> grepFound = new HashSet<String>(mistress);\n\t\tgrepFound.retainAll(undocumented);\n\t\tHashSet<String> temp = new HashSet<String>(crazy);\n\t\ttemp.retainAll(forced);\n\t\tgrepFound.addAll(temp);\n\t\tgrepFound.addAll(insane);\n\t\t\n\t\tCollection<Page> index = queryTest.query(\"insane | crazy & !\\\"I am forced\\\" | mistress & undocumented\");\n\t\tHashSet<String> indexFound = new HashSet<String>();\n\n\t\tfor (Page p : index)\n\t\t\tindexFound.add(p.getURL().getPath().toLowerCase());\n\t\t\n\t\tassertEquals(indexFound, grepFound);\n\t}","public ArrayList<Integer> intersect(final List<Integer> a, final List<Integer> b) {\n\t ArrayList<Integer> res = new ArrayList<>();\n\t \n\t int i1 = 0, i2 = 0;\n\t while (i1 < a.size() && i2 < b.size()) {\n\t //System.out.println(i1 + \" \" + i2 + \" \" + a.get(i1) + \" \" + b.get(i2));\n\t if (a.get(i1).equals(b.get(i2))) {\n\t res.add(a.get(i1));\n\t i1++;\n\t i2++;\n\t } else if (a.get(i1) < b.get(i2)) {\n\t i1++;\n\t } else if (a.get(i1) > b.get(i2)) {\n\t i2++;\n\t }\n\t }\n\t \n\t return res;\n\t}","void findMatchings(boolean isProtein) {\n\n GraphDatabaseFactory dbFactory = new GraphDatabaseFactory();\n HashSet<String > searchSpaceList = new HashSet<>();\n GraphDatabaseService databaseService = dbFactory.newEmbeddedDatabase(graphFile);\n for (int id: queryGraphNodes.keySet()) {\n if(isProtein)\n searchSpaceList.add(queryGraphNodes.get(id).label);\n else\n searchSpaceList.add(String.valueOf(queryGraphNodes.get(id).labels.get(0)));\n }\n for(String x: searchSpaceList) {\n ResourceIterator<Node> xNodes;\n try(Transaction tx = databaseService.beginTx()) {\n xNodes = databaseService.findNodes(Label.label(x));\n tx.success();\n }\n\n while (xNodes.hasNext()) {\n Node node = xNodes.next();\n if (searchSpaceProtein.containsKey(x))\n searchSpaceProtein.get(x).add(node.getId());\n else {\n HashSet<Long> set = new HashSet<>();\n set.add(node.getId());\n searchSpaceProtein.put(x, set);\n }\n }\n\n }\n\n if(isProtein)\n search(0, databaseService, true);\n else\n search(0, databaseService, false);\n databaseService.shutdown();\n }","protected boolean query() {\r\n\t\tqueryStr = new String(processQueryTitle(queryBk.getTitle()) + processQueryAuthor(queryBk.getCreator())\r\n\t\t\t\t+ processQueryPublisher(queryBk.getPublisher()));\r\n\t\tSystem.out.println(queryStr);\r\n\t\t// if edition is 'lastest' (coded '0'), no query is performed; and\r\n\t\t// return false.\r\n\t\tif (queryBk.parseEdition() == 0) {\r\n\t\t\treturn false;\r\n\t\t} // end if\r\n\r\n\t\t/*\r\n\t\t * The following section adds edition info to the query string if edition no. is\r\n\t\t * greater than one. By cataloging practice, for the first edition, probably\r\n\t\t * there is NO input on the associated MARC field. Considering this, edition\r\n\t\t * query string to Primo is NOT added if querying for the first edition or no\r\n\t\t * edition is specified.\r\n\t\t */\r\n\t\tif (queryBk.parseEdition() > 1) {\r\n\t\t\tqueryStr += processQueryEdition(queryBk.parseEdition());\r\n\t\t} // end if\r\n\r\n\t\t/*\r\n\t\t * Querying the Primo X-service; and invoking the matching processes (all done\r\n\t\t * by remoteQuery()).\r\n\t\t */\r\n\t\tif (strHandle.hasSomething(queryBk.getPublisher())) {\r\n\t\t\tif (remoteQuery(queryStr)) {\r\n\t\t\t\tmatch = true;\r\n\t\t\t\tsetBookInfo();\r\n\t\t\t\tcheckAVA(queryBk.parseVolume());\r\n\t\t\t\treturn true;\r\n\t\t\t} else {\r\n\t\t\t\tmatch = false;\r\n\t\t\t} // end if\r\n\t\t} // end if\r\n\r\n\t\t/*\r\n\t\t * For various reasons, there are possibilities that the first query fails while\r\n\t\t * a match should be found. The follow work as remedy queries to ensure the\r\n\t\t * accuracy.\r\n\t\t */\r\n\r\n\t\tif (!match && strHandle.hasSomething(queryBk.getPublisher())) {\r\n\t\t\tqueryStr = new String(\r\n\t\t\t\t\tprocessQueryPublisher(queryBk.getPublisher()) + processQueryAuthor(queryBk.getCreator()));\r\n\t\t\tif (remoteQuery(queryStr)) {\r\n\t\t\t\tmatch = true;\r\n\t\t\t\tsetBookInfo();\r\n\t\t\t\tcheckAVA(queryBk.parseVolume());\r\n\t\t\t\treturn true;\r\n\t\t\t} else {\r\n\t\t\t\tmatch = false;\r\n\t\t\t} // end if\r\n\t\t} // end if\r\n\r\n\t\tif (!match) {\r\n\t\t\tqueryStr = new String(processQueryTitle(queryBk.getTitle()) + processQueryAuthor(queryBk.getCreator()));\r\n\t\t\tif (remoteQuery(queryStr)) {\r\n\t\t\t\tmatch = true;\r\n\t\t\t\tsetBookInfo();\r\n\t\t\t\tcheckAVA(queryBk.parseVolume());\r\n\t\t\t\treturn true;\r\n\t\t\t} else {\r\n\t\t\t\tmatch = false;\r\n\t\t\t} // end if\r\n\t\t} // end if\r\n\r\n\t\tif (!match) {\r\n\t\t\tqueryStr = new String(processQueryTitle(queryBk.getTitle()));\r\n\t\t\tif (remoteQuery(queryStr)) {\r\n\t\t\t\tmatch = true;\r\n\t\t\t\tsetBookInfo();\r\n\t\t\t\tcheckAVA(queryBk.parseVolume());\r\n\t\t\t\treturn true;\r\n\t\t\t} else {\r\n\t\t\t\tmatch = false;\r\n\t\t\t} // end if\r\n\t\t} // end if\r\n\r\n\t\tif (!match && strHandle.hasSomething(queryBk.getPublishYear())) {\r\n\t\t\tqueryStr = new String(\r\n\t\t\t\t\tprocessQueryAuthor(queryBk.getCreator()) + processQueryYear(queryBk.getPublishYear()));\r\n\r\n\t\t\tif (remoteQuery(queryStr)) {\r\n\t\t\t\tmatch = true;\r\n\t\t\t\tsetBookInfo();\r\n\t\t\t\tcheckAVA(queryBk.parseVolume());\r\n\t\t\t\treturn true;\r\n\t\t\t} else {\r\n\t\t\t\tmatch = false;\r\n\t\t\t} // end if\r\n\t\t} // end if\r\n\r\n\t\tif (!match) {\r\n\t\t\tqueryStr = new String(\r\n\t\t\t\t\tprocessQueryAuthor(queryBk.getCreator()) + processQueryTitleShort(queryBk.getTitle()));\r\n\t\t\tif (remoteQuery(queryStr)) {\r\n\t\t\t\tmatch = true;\r\n\t\t\t\tsetBookInfo();\r\n\t\t\t\tcheckAVA(queryBk.parseVolume());\r\n\t\t\t\treturn true;\r\n\t\t\t} else {\r\n\t\t\t\tmatch = false;\r\n\t\t\t} // end if\r\n\t\t} // end if\r\n\r\n\t\t// Additional query for Chinese titles\r\n\r\n\t\tif (!match && (CJKStringHandling.isCJKString(queryBk.getTitle())\r\n\t\t\t\t|| CJKStringHandling.isCJKString(queryBk.getCreator())\r\n\t\t\t\t|| CJKStringHandling.isCJKString(queryBk.getPublisher()))) {\r\n\r\n\t\t\tqueryStr = new String(processQueryTitle(queryBk.getTitle()));\r\n\t\t\tif (remoteQuery(queryStr)) {\r\n\t\t\t\tmatch = true;\r\n\t\t\t\tsetBookInfo();\r\n\t\t\t\tcheckAVA(queryBk.parseVolume());\r\n\t\t\t\treturn true;\r\n\t\t\t} else {\r\n\t\t\t\tmatch = false;\r\n\t\t\t} // end if\r\n\r\n\t\t\tif (!match && queryBk.parseEdition() != -1) {\r\n\t\t\t\tqueryStr = new String(\r\n\t\t\t\t\t\tprocessQueryTitle(queryBk.getTitle()) + processQueryEdition2(queryBk.parseEdition()));\r\n\t\t\t\tif (remoteQuery(queryStr)) {\r\n\t\t\t\t\tmatch = true;\r\n\t\t\t\t\tsetBookInfo();\r\n\t\t\t\t\tcheckAVA(queryBk.parseVolume());\r\n\t\t\t\t\treturn true;\r\n\t\t\t\t} else {\r\n\t\t\t\t\tmatch = false;\r\n\t\t\t\t} // end if\r\n\r\n\t\t\t\tif (!match && queryBk.parseEdition() != -1) {\r\n\t\t\t\t\tqueryStr = new String(\r\n\t\t\t\t\t\t\tprocessQueryTitle(queryBk.getTitle()) + processQueryEdition3(queryBk.parseEdition()));\r\n\t\t\t\t\tif (remoteQuery(queryStr)) {\r\n\t\t\t\t\t\tmatch = true;\r\n\t\t\t\t\t\tsetBookInfo();\r\n\t\t\t\t\t\tcheckAVA(queryBk.parseVolume());\r\n\t\t\t\t\t\treturn true;\r\n\t\t\t\t\t} else {\r\n\t\t\t\t\t\tmatch = false;\r\n\t\t\t\t\t} // end if\r\n\t\t\t\t} // end if\r\n\t\t\t} // end if\r\n\t\t} // end if\r\n\r\n\t\t// Additional check for ISO Document number in <search> <genernal> PNX\r\n\t\t// tag\r\n\t\tif (!match && !CJKStringHandling.isCJKString(queryBk.getTitle())) {\r\n\t\t\tqueryStr = new String(processQueryTitleISODoc(queryBk.getTitle()));\r\n\t\t\tif (remoteQuery(queryStr)) {\r\n\t\t\t\tmatch = true;\r\n\t\t\t\tsetBookInfo();\r\n\t\t\t\tcheckAVA(queryBk.parseVolume());\r\n\t\t\t\treturn true;\r\n\t\t\t} else {\r\n\t\t\t\tmatch = false;\r\n\t\t\t\terrMsg += \"Query: No record found on Primo.\" + Config.QUERY_SETTING;\r\n\t\t\t} // end if\r\n\t\t} // end if\r\n\t\treturn false;\r\n\t}","protected <Ty> HashSet<Ty> intersection(HashSet<Ty> setA, HashSet<Ty> setB) {\n HashSet<Ty> retSet = new HashSet<>();\n for (Ty t : setA) {\n if (setB.contains(t)) {\n retSet.add(t);\n }\n }\n return retSet;\n }","List<ProtocolPo> queryByUnion(ProtocolPo query);","protected abstract NativeSQLStatement createNativeIntersectsStatement(Geometry geom);","private void queryPosts() {\n ParseQuery<OutfitPost> query = ParseQuery.getQuery(OutfitPost.class);\n // only include data referred by user key\n query.include(OutfitPost.KEY_USER);\n query.whereEqualTo(OutfitPost.KEY_USER, ParseUser.getCurrentUser());\n // limit query to latest 20 items\n query.setLimit(20);\n // order posts by creation date (newest first)\n query.addDescendingOrder(OutfitPost.KEY_CREATED_KEY);\n // start an asynchronous call for posts\n query.findInBackground(new FindCallback<OutfitPost>() {\n @Override\n public void done(List<OutfitPost> posts, ParseException e) {\n // check for errors\n if (e != null) {\n Log.e(TAG, \"Issue with getting posts\", e);\n return;\n }\n // Save oldest post in query for loading more posts\n if (posts.size() > 0) {\n oldestPost = posts.get(posts.size() - 1).getCreatedAt();\n }\n // update adapter with posts list\n adapter.clear();\n adapter.addAll(posts);\n }\n });\n }","public void sensibleMatches1() \n { \n Map<String, Set<String>> clientMap = new HashMap<>();\n Set<String> interests = new HashSet<>();\n\n interests.add(\"Food\");\n interests.add(\"Wine\");\n interests.add(\"Tandems\");\n clientMap.put(\"Hal\", interests);\n\t \n interests = new HashSet<>();\n interests.add(\"Food\");\n interests.add(\"Walking\");\n interests.add(\"Welding\");\n clientMap.put(\"Gemma\", interests);\n\t \n interests = new HashSet<>();\n interests.add(\"Food\");\n interests.add(\"Cinema\");\n interests.add(\"Wine\");\n clientMap.put(\"Caroline\", interests);\n\n Set<String> halsInterests = clientMap.get(\"Hal\");\n String outputString;\n Set<String> eachClientInterests;\n Set<String> intersection ;\n\n Map<String, Set<String>> mapWithoutHal = new HashMap<>(clientMap);\n mapWithoutHal.remove(\"Hal\");\n for (String eachClient : mapWithoutHal.keySet()) \n {\n eachClientInterests = clientMap.get(eachClient);\n intersection = new HashSet<>(halsInterests);\n intersection.retainAll(eachClientInterests);\n outputString = \"Hal and \" + eachClient \n + \" have common interests: \"\n + intersection;\n System.out.println(outputString);\n }\n }","public void reflectRelationOnUnionQuery(ConditionQuery bqs, ConditionQuery uqs) {\n }","public void reflectRelationOnUnionQuery(ConditionQuery bqs, ConditionQuery uqs) {\n }","public void reflectRelationOnUnionQuery(ConditionQuery bqs, ConditionQuery uqs) {\n }","public Intersection(ListExpression expr1, ListExpression expr2) {\n this.expr1 = expr1;\n this.expr2 = expr2;\n }","@Test\n public void testIntersection2()\n {\n final int[] ints1 = {33, 100000};\n final int[] ints2 = {34, 100000};\n List<Integer> expected = Collections.singletonList(100000);\n\n ConciseSet set1 = new ConciseSet();\n for (int i : ints1) {\n set1.add(i);\n }\n ConciseSet set2 = new ConciseSet();\n for (int i : ints2) {\n set2.add(i);\n }\n\n verifyIntersection(expected, set1, set2);\n }","public void getIntersection(int[] A, int[] B, ArrayList<int[]> intersections) \n {\n if (A[0] >= B[0] && A[0] <= B[1]) \n {\n if (A[1] >= B[0] && A[1] <= B[1]) \n {\n // Take the entirety of A\n intersections.add(A);\n } \n else \n {\n // Take the start of A to end of B\n int[] intersection = new int[]{A[0], B[1]};\n intersections.add(intersection);\n }\n } \n else \n {\n if (A[1] >= B[0] && A[1] <= B[1]) \n {\n // Take start of B to end of A\n int[] intersection = new int[]{B[0], A[1]};\n intersections.add(intersection);\n } \n else \n {\n if (A[0] < B[0] && A[1] > B[1]) \n {\n // Take the entirety of B\n intersections.add(B);\n } \n else \n {\n // No intersection at all\n return;\n }\n }\n }\n }","private List<Object[]> executeDayQuery(\n List<Object> segments, List<Object> workplaces,\n String Eq1startTime, String Eq1endTime,\n String Eq2startTime, String Eq2endTime,\n String Eq3startTime, String Eq3endTime) {\n try {\n //Clear all tables\n //################# Declared Harness Data #################### \n Helper.startSession();\n\n String query_str_1 = \"(SELECT 'Matin' as shift,'%s' As start_time, '%s' as end_time, \"\n + \"bh.segment AS segment, \"\n + \"bh.workplace AS workplace, \"\n + \"bh.harness_part AS harness_part, \"\n + \"bh.std_time AS std_time, \"\n + \"COUNT(bh.harness_part) AS produced_qty, \"\n + \"SUM(bh.std_time) AS produced_hours \"\n + \"FROM base_harness bh, base_container bc \"\n + \"WHERE bc.id = bh.container_id \"\n + \"AND bh.create_time BETWEEN '%s' AND '%s' \"\n + \"AND bh.segment IN (:segments) \"\n + \"AND bh.workplace IN (:workplaces) \"\n + \"GROUP BY bh.segment, bh.workplace, bh.harness_part, bh.std_time)\";\n\n query_str_1 = String.format(query_str_1, Eq1startTime, Eq1endTime, Eq1startTime, Eq1endTime);\n\n String query_str_2 = \"(SELECT 'Soir' as shift,'%s' As start_time, '%s' as end_time, \"\n + \"bh.segment AS segment, \"\n + \"bh.workplace AS workplace, \"\n + \"bh.harness_part AS harness_part, \"\n + \"bh.std_time AS std_time, \"\n + \"COUNT(bh.harness_part) AS produced_qty, \"\n + \"SUM(bh.std_time) AS produced_hours \"\n + \"FROM base_harness bh, base_container bc \"\n + \"WHERE bc.id = bh.container_id \"\n + \"AND bh.create_time BETWEEN '%s' AND '%s' \"\n + \"AND bh.segment IN (:segments) \"\n + \"AND bh.workplace IN (:workplaces) \"\n + \"GROUP BY bh.segment, bh.workplace, bh.harness_part, bh.std_time)\";\n\n query_str_2 = String.format(query_str_2, Eq2startTime, Eq2endTime, Eq2startTime, Eq2endTime);\n\n String query_str_3 = \"(SELECT 'Nuit' as shift,'%s' As start_time, '%s' as end_time, \"\n + \"bh.segment AS segment, \"\n + \"bh.workplace AS workplace, \"\n + \"bh.harness_part AS harness_part, \"\n + \"bh.std_time AS std_time, \"\n + \"COUNT(bh.harness_part) AS produced_qty, \"\n + \"SUM(bh.std_time) AS produced_hours \"\n + \"FROM base_harness bh, base_container bc \"\n + \"WHERE bc.id = bh.container_id \"\n + \"AND bh.create_time BETWEEN '%s' AND '%s' \"\n + \"AND bh.segment IN (:segments) \"\n + \"AND bh.workplace IN (:workplaces)\"\n + \"GROUP BY bh.segment, bh.workplace, bh.harness_part, bh.std_time) \";\n\n query_str_3 = String.format(query_str_3, Eq3startTime, Eq3endTime, Eq3startTime, Eq3endTime);\n\n String query_str = \"SELECT * FROM (\"\n + query_str_1 + \" UNION \"\n + query_str_2 + \" UNION \"\n + query_str_3\n + \") results ORDER BY start_time ASC, segment ASC, workplace ASC, harness_part ASC\";\n\n SQLQuery query = Helper.sess.createSQLQuery(query_str);\n\n query.addScalar(\"shift\", StandardBasicTypes.STRING)\n .addScalar(\"start_time\", StandardBasicTypes.STRING)\n .addScalar(\"end_time\", StandardBasicTypes.STRING)\n .addScalar(\"segment\", StandardBasicTypes.STRING)\n .addScalar(\"workplace\", StandardBasicTypes.STRING)\n .addScalar(\"harness_part\", StandardBasicTypes.STRING)\n .addScalar(\"std_time\", StandardBasicTypes.DOUBLE)\n .addScalar(\"produced_qty\", StandardBasicTypes.INTEGER)\n .addScalar(\"produced_hours\", StandardBasicTypes.DOUBLE)\n .setParameterList(\"segments\", segments)\n .setParameterList(\"workplaces\", workplaces);\n\n this.dataResultList = query.list();\n\n Helper.sess.getTransaction().commit();\n\n return this.dataResultList;\n\n } catch (HibernateException e) {\n if (Helper.sess.getTransaction() != null) {\n Helper.sess.getTransaction().rollback();\n }\n }\n\n return this.dataResultList;\n }","public PostingsList phrase_query(Query query){\n\n LinkedList<PostingsList> listQueriedPostings = new LinkedList<PostingsList>();\n // List with postings corresponding to the queries\n for (int i = 0; i<query.size(); i++){\n // If any query has zero matches, return 0 results\n //if(!(new File(\"postings/t\"+hash(query.terms.get(i))+\".json\")).exists()){\n if (!this.index.containsKey(query.terms.get(i))){\n return null;\n }\n // Otherwise store postings in the list\n listQueriedPostings.add(this.getPostings(query.terms.get(i)));\n }\n\n PostingsList result = new PostingsList();\n result = listQueriedPostings.get(0);\n\n // In case only one word is queried\n if (listQueriedPostings.size() == 1){\n return result;\n }\n\n // Apply algorithm as many times as words in the query\n for(int i = 1; i < listQueriedPostings.size(); i++){\n result = phrase_query(result, listQueriedPostings.get(i));\n if (result.isEmpty()){\n return null;\n }\n }\n return result;\n }","private static boolean availabilityQuery(String roomid, String date1, String date2)\n {\n String query = \"SELECT status\"\n + \" FROM (\"\n + \" SELECT DISTINCT ro.RoomId, 'occupied' AS status\"\n + \" FROM myReservations re JOIN myRooms ro ON (re.Room = ro.RoomId)\"\n + \" WHERE (DATEDIFF(CheckIn, DATE(\" + date1 + \")) <= 0\"\n + \" AND DATEDIFF(CheckOut, DATE(\" + date2 + \")) > 0)\" \n + \" OR (DATEDIFF(CheckIn, DATE(\" + date1 + \")) > 0\" \n + \" AND DATEDIFF(CheckIn, DATE(\" + date2 + \")) <= 0)\" \n + \" OR (DATEDIFF(CheckOut, DATE(\" + date1 + \")) > 0\" \n + \" AND DATEDIFF(CheckOut, DATE(\" + date2 + \")) < 0)\"\n + \" UNION\"\n + \" SELECT DISTINCT RoomId, 'empty' AS status\"\n + \" FROM myRooms\"\n + \" WHERE RoomId NOT IN (\"\n + \" SELECT DISTINCT re.Room\"\n + \" FROM myReservations re JOIN myRooms ro ON (re.Room = ro.RoomId)\"\n + \" WHERE (DATEDIFF(CheckIn, DATE(\" + date1 + \")) <= 0\"\n + \" AND DATEDIFF(CheckOut, DATE(\" + date2 + \")) > 0)\"\n + \" OR (DATEDIFF(CheckIn, DATE(\" + date1 + \")) > 0\"\n + \" AND DATEDIFF(CheckIn, DATE(\" + date2 + \")) <= 0)\" \n + \" OR (DATEDIFF(CheckOut, DATE(\" + date1 + \")) > 0\" \n + \" AND DATEDIFF(CheckOut, DATE(\" + date2 + \")) < 0)\" \n + \" )) AS tb\"\n + \" WHERE RoomId = '\" + roomid + \"'\";\n\n PreparedStatement stmt = null;\n ResultSet rset = null;\n\n try\n {\n stmt = conn.prepareStatement(query);\n rset = stmt.executeQuery();\n rset.next();\n if(rset.getString(\"status\").equals(\"empty\"))\n return true;\n }\n catch (Exception ex){\n ex.printStackTrace();\n }\n finally {\n try {\n stmt.close();\n }\n catch (Exception ex) {\n ex.printStackTrace( ); \n } \t\n }\n \n return false;\n\n }","private void link(String sourceInstance, String targetInstance, Tuple<String, String> queries) {\n\t\t// Adapt queries to sample instances\n\t\tTuple<String,String> newQueries = queries;\n\t\tif(sourceInstance!=null && targetInstance!=null) {\n\t\t\t// if sourceInstance and targetInstance are not null, add the clauses:\n\t\t\t//\t\t\"WHERE source.id = sourceInstance\" to queries.getFirstElement()\n\t\t\t//\t\t\"WHERE target.id = targetInstance\" to queries.getSecondElement()\n\t\t}\n\t\texecuteSourceQuery(newQueries.getFirstElement(), newQueries.getSecondElement());\n\t}","private static <Item extends Comparable> List<Item> catenate(List<Item> q1, List<Item> q2) {\n List<Item> catenated = new ArrayList<>();\n for (Item item : q1) {\n catenated.add(item);\n }\n for (Item item: q2) {\n catenated.add(item);\n }\n return catenated;\n }","private ExampleSetBuilder performInnerJoin(ExampleSet leftExampleSet, ExampleSet rightExampleSet,\n\t\t\tList<AttributeSource> originalAttributeSources, List<Attribute> unionAttributeList,\n\t\t\tPair<Attribute[], Attribute[]> keyAttributes) throws ProcessStoppedException {\n\t\tExampleSetBuilder builder = ExampleSets.from(unionAttributeList);\n\n\t\tAttribute[] leftKeyAttributes = null;\n\t\tAttribute[] rightKeyAttributes = null;\n\t\tMap<DoubleArrayWrapper, List<Example>> rightKeyMapping = null;\n\t\tboolean useId = getParameterAsBoolean(PARAMETER_USE_ID);\n\n\t\tif (!useId) {\n\t\t\t// create key mapping for right example set\n\t\t\tleftKeyAttributes = keyAttributes.getFirst();\n\t\t\trightKeyAttributes = keyAttributes.getSecond();\n\t\t\trightKeyMapping = createKeyMapping(rightExampleSet, rightKeyAttributes, leftKeyAttributes);\n\t\t}\n\n\t\tint progressCounter = 0;\n\t\t// iterate over all example from left table and search for matching examples in right table:\n\t\tfor (Example leftExample : leftExampleSet) {\n\n\t\t\tList<Example> matchingRightExamples = getMatchingExamples(leftExampleSet, rightExampleSet, leftKeyAttributes,\n\t\t\t\t\trightKeyMapping, useId, leftExample);\n\n\t\t\tif (matchingRightExamples != null) {\n\t\t\t\tfor (Example rightExample : matchingRightExamples) {\n\t\t\t\t\taddCombinedOccurence(originalAttributeSources, unionAttributeList, builder, leftExample, rightExample);\n\t\t\t\t}\n\t\t\t}\n\n\t\t\t// trigger operator progress every 100 examples\n\t\t\t++progressCounter;\n\t\t\tif (progressCounter % 100 == 0) {\n\t\t\t\tgetProgress().step(100);\n\t\t\t\tprogressCounter = 0;\n\t\t\t}\n\t\t}\n\t\treturn builder;\n\t}","private Set<String> intersection(Set<String> s1, Set<String> s2) {\n Set<String> intersection = new HashSet<>(s1);\n intersection.retainAll(s2);\n return intersection;\n }","private ClusterCombination checkAndDoJoinMultiPearson(ClusterCombination CC1, ClusterCombination CC2) {\n boolean doJoin = true;\r\n ArrayList<Cluster> CCList = new ArrayList<>(CC1.getClusters().size()+1); //list of output clusters for new CC if join is succesfull\r\n\r\n ArrayList<Cluster> CC1Clusters = CC1.getClusters();\r\n ArrayList<Cluster> CC2Clusters = CC2.getClusters();\r\n\r\n ArrayList<Cluster> LHS1 = CC1.getLHS();\r\n ArrayList<Cluster> LHS2 = CC2.getLHS();\r\n\r\n ArrayList<Cluster> RHS1 = CC1.getRHS();\r\n ArrayList<Cluster> RHS2 = CC2.getRHS();\r\n\r\n for(int i =0; i<CC1Clusters.size()-1; i++) {\r\n Cluster C1 = CC1Clusters.get(i);\r\n Cluster C2 = CC2Clusters.get(i);\r\n\r\n boolean overlap = checkClusterOverlap(C1, C2); // check if there is some overlap\r\n\r\n\r\n\r\n if(!overlap){ //the cluster in this position does not overlap, we don't need to join\r\n doJoin=false;\r\n break;\r\n }else{ // there is overlap, add the intersection of C1 and C2\r\n if(C1.getNPoints() <= C2.getNPoints()){\r\n CCList.add(C1);\r\n }else{\r\n CCList.add(C2);\r\n }\r\n\r\n }\r\n\r\n\r\n }\r\n\r\n\r\n if(doJoin){ // each cluster in the candidate (except the last) does overlap\r\n // so, according to apriori, we join -> return the overlapping clusters + the last clusters of CC1 and CC2\r\n Cluster lastCC1 = CC1Clusters.get(CC1Clusters.size()-1);\r\n Cluster lastCC2 = CC2Clusters.get(CC2Clusters.size()-1);\r\n if(lastCC1.getClusterId() <= lastCC2.getClusterId()){ // make sure to respect ordering of clusters within a candidate by ID. otherwise this could be designated as a duplicate\r\n CCList.add(lastCC1); CCList.add(lastCC2);\r\n }else{\r\n CCList.add(lastCC2); CCList.add(lastCC1);\r\n }\r\n\r\n ArrayList<Cluster> newLHS = new ArrayList<>();\r\n ArrayList<Cluster> newRHS = new ArrayList<>();\r\n for(int i = 0; i<LHS1.size(); i++){\r\n newLHS.add(CCList.get(i));\r\n }\r\n for(int i = LHS1.size(); i<CCList.size(); i++){\r\n newRHS.add(CCList.get(i));\r\n }\r\n\r\n ClusterCombination newCC = new MultiPearsonClusterCombination(newLHS, newRHS);\r\n newCC.checkAndSetMaxSubsetLowerBound(Math.max(CC1.getLB(), CC1.getMaxLowerBoundSubset()));\r\n newCC.checkAndSetMaxSubsetLowerBound(Math.max(CC2.getLB(), CC2.getMaxLowerBoundSubset()));\r\n\r\n return newCC;\r\n\r\n }else{\r\n return null;\r\n }\r\n }","public boolean query(int a, int b) {\n\t\treturn find(a) == find(b);\n }","@Test\n\tpublic void orGrepTest() throws Exception {\n\t\t// | for 'insane' and 'mistress'\n\t\tHashSet<String> grep1 = loadGrepResults(\"mistress\");\n\t\tHashSet<String> grepFound = loadGrepResults(\"insane\");\n\t\tgrepFound.addAll(grep1);\n\n\t\tCollection<Page> index = queryTest.query(\"mistress | insane\");\n\t\tHashSet<String> indexFound = new HashSet<String>();\n\n\t\tfor (Page p : index)\n\t\t\tindexFound.add(p.getURL().getPath().toLowerCase());\n\n\t\tassertEquals(indexFound, grepFound);\n\n\t}","public static void intersection(ArrayList<String> x, ArrayList<String> y, ArrayList<String> z, JTextArea ta) {\n\t\t\n\t\t//This is the loop to add items from list 1 to results array, if the elements are present in both the lists\n\t\tfor (int i=0; i<x.size(); i++)\n\t\t{\n\t\t\tfor (int j=0; j<y.size(); j++)\n\t\t\t{\n\t\t\t\tif (x.get(i).equals(y.get(j))&&!z.contains(x.get(i)))\n\t\t\t\t{\n\t\t\t\t\tz.add(x.get(i));\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t\t\n\t\t\n\t\t//This is the loop to print all the items of the results array list\n\t\tta.setText(\"{ \");\n\t\tfor (int i=0; i<z.size(); i++)\n\t\t{\n\t\t\tta.append(z.get(i)+\" \");\n\t\t}\n\t\tta.append(\"}\");\n\t}","private boolean overlaps(ThingTimeTriple a, ThingTimeTriple b)\r\n/* 227: */ {\r\n/* 228:189 */ return (a.from < b.to) && (a.to > b.from);\r\n/* 229: */ }","@Override\n public int hashCode() {\n return Objects.hash(requestedPosts, this.getQueryID());\n }","public ArrayList<Integer> intersect(\n final List<Integer> A, final List<Integer> B) {\n ArrayList<Integer> res = new ArrayList<Integer>();\n int M = A.size();\n int N = B.size();\n if (M == 0 || N == 0) {\n return res;\n }\n int i = 0;\n int j = 0;\n while (i < M && j < N) {\n int a = A.get(i);\n int b = B.get(j);\n if (a == b) {\n res.add(a);\n i++;\n j++;\n } else if (a < b) {\n i++;\n } else {// a > b\n j++;\n }\n }\n return res;\n }","public PostingsList search( Query query, int queryType, int rankingType, int structureType ) {\r\n switch(queryType){\r\n case Index.INTERSECTION_QUERY : \r\n return searchIntersection( query, rankingType, structureType);\r\n\r\n case Index.PHRASE_QUERY :\r\n return searchPhrase( query, rankingType, structureType);\r\n default:\r\n break;\r\n }\r\n\r\n return null;\r\n }","public void sensibleMatches2() \n { \n Map<String, Set<String>> clientMap = new HashMap<>();\n Set<String> interests = new HashSet<>();\n\n interests.add(\"Food\");\n interests.add(\"Wine\");\n interests.add(\"Tandems\");\n clientMap.put(\"Hal\", interests);\n\t \n interests = new HashSet<>();\n interests.add(\"Food\");\n interests.add(\"Walking\");\n interests.add(\"Welding\");\n clientMap.put(\"Gemma\", interests);\n\n interests = new HashSet<>();\n interests.add(\"Food\");\n interests.add(\"Cinema\");\n interests.add(\"Wine\");\n clientMap.put(\"Caroline\", interests);\n\n Set<String> halsInterests = clientMap.get(\"Hal\");\n String outputString;\n Set<String> eachClientInterests;\n Set<String> intersection ;\n\n for (String eachClient : clientMap.keySet()) \n {\n if (!eachClient.equals(\"Hal\")) \n {\n eachClientInterests = clientMap.get(eachClient);\n intersection = new HashSet<>(halsInterests);\n intersection.retainAll(eachClientInterests);\n outputString = \"Hal and \" + eachClient \n + \" have common interests: \"\n + intersection;\n System.out.println(outputString);\n }\n }\n }","private Range<Token> intersect(Range<Token> serverRange, AbstractBounds<Token> requestedRange)\n {\n if (serverRange.contains(requestedRange.left) && serverRange.contains(requestedRange.right)) {\n //case 1: serverRange fully encompasses requestedRange\n return new Range<Token>(requestedRange.left, requestedRange.right, partitioner);\n } else if (requestedRange.contains(serverRange.left) && requestedRange.contains(serverRange.right)) {\n //case 2: serverRange is fully encompasses by requestedRange\n //serverRange is already the intersection\n return new Range<Token>(serverRange.left, serverRange.right);\n } else if (serverRange.contains(requestedRange.left) && requestedRange.contains(serverRange.right)) {\n //case 3: serverRange overlaps on the left: sR.left < rR.left < sR.right < rR.right\n return new Range<Token>(requestedRange.left, serverRange.right, partitioner);\n } else if (requestedRange.contains(serverRange.left) && serverRange.contains(requestedRange.right)) {\n //case 4: serverRange overlaps on the right rR.left < sR.left < rR.right < sR.right\n return new Range<Token>(serverRange.left, requestedRange.right, partitioner);\n } else if (!serverRange.contains(requestedRange.left) && !serverRange.contains(requestedRange.right) &&\n !requestedRange.contains(serverRange.left) && !requestedRange.contains(serverRange.right)) {\n //case 5: totally disjoint\n return null;\n } else {\n assert false : \"Failed intersecting serverRange = (\" + serverRange.left + \", \" + serverRange.right + \") and requestedRange = (\" + requestedRange.left + \", \" + requestedRange.right + \")\";\n return null;\n }\n }","public static List<StringMeeting> calendarMatching(\n List<StringMeeting> calendar1,\n StringMeeting dailyBounds1,\n List<StringMeeting> calendar2,\n StringMeeting dailyBounds2,\n int meetingDuration) {\n\n\n List<Meeting> updatedCaleandr1 = updateCalendar(calendar1, dailyBounds1);\n System.out.println(updatedCaleandr1);\n List<Meeting> updatedCaleandr2 = updateCalendar(calendar2, dailyBounds2);\n\n\n\n List<Meeting> mergedCalendar = mergeCalendars(updatedCaleandr1, updatedCaleandr2);\n mergedCalendar.forEach(k-> System.out.println(k.toString()));\n List<Meeting> flattencalendr = flattenCalenedars(mergedCalendar);\n// flattencalendr.forEach(k-> System.out.println(k.toString()));\n System.out.println();\n\n return getMatchingAvailabilities(flattencalendr, meetingDuration);\n }","public static void main(String[] args) {\n\t\t\r\n\t\tint arr1[] = {3,2,11,4,6,7};\r\n\t\tint arr2[] = {1,2,8,4,9,7};\r\n\t\t\r\n\t\tList<Integer> list1 = new ArrayList<Integer>();\r\n\t\t\r\n\t\tList<Integer> list2 = new ArrayList<Integer>();\r\n\t\t\r\n\t\tfor (int a : arr1) {\r\n\t\t\tlist1.add(a);\r\n\t\t}\r\n\t\tfor (int b : arr2) {\r\n\t\t\tlist2.add(b);\r\n\t\t}\r\n\t\t\r\n\t\tSystem.out.println(list1);\r\n System.out.println(list2);\r\n \r\n list1.retainAll(list2);\r\n System.out.println(\"The Intersection values : \" + list1);\r\n \r\n\t}","public static void main(String[] args) {\n\t\tInteger[] firstArray = {0,2,4,6,8};\n\t Integer[] secondArray = {1,3,10,4,7,8,9};\n\t \n\t intersectionUsingSet(firstArray, secondArray);\n\n\t System.out.println();\n\t \n\t // Array with duplicate elements in the array\n\t Integer[] firstArray1 = {0,2,2,4,6,6,8};\n\t Integer[] secondArray2 = {1,3,10,10,4,7,8,9};\n\t \n\t intersectionUsingSet(firstArray1, secondArray2);\n\t}","@Test\n\tpublic void andGrepTest() throws Exception {\n\t\t// & for 'undocumented' and 'mistress'\n\t\tHashSet<String> grepFound = loadGrepResults(\"undocumented\");\n\t\tHashSet<String> grep1 = loadGrepResults(\"mistress\");\n\t\tgrepFound.retainAll(grep1);\n\t\t\n\t\tCollection<Page> index = queryTest.query(\"mistress & undocumented\");\n\t\tHashSet<String> indexFound = new HashSet<String>();\n\n\t\tfor (Page p : index)\n\t\t\tindexFound.add(p.getURL().getPath().toLowerCase());\n\t\t\n\t\tassertEquals(indexFound, grepFound);\n\t}","public void matchesDemo() \n {\n Map<String, Set<String>> clientMap = new HashMap<>();\n Set<String> interests = new HashSet<>();\n\n interests.add(\"Food\");\n interests.add(\"Wine\");\n interests.add(\"Tandems\");\n clientMap.put(\"Hal\", interests);\n\t \n interests = new HashSet<>();\n interests.add(\"Food\");\n interests.add(\"Walking\");\n interests.add(\"Welding\");\n clientMap.put(\"Gemma\", interests);\n\t \n interests = new HashSet<>();\n interests.add(\"Food\");\n interests.add(\"Cinema\");\n interests.add(\"Wine\");\n clientMap.put(\"Caroline\", interests);\n\n Set<String> halsInterests = clientMap.get(\"Hal\");\n String outputString;\n Set<String> eachClientInterests;\n Set<String> intersection;\n\n for (String eachClient : clientMap.keySet()) \n {\n eachClientInterests = clientMap.get(eachClient);\n intersection = new HashSet<>(halsInterests);\n intersection.retainAll(eachClientInterests);\n outputString = \"Hal and \" + eachClient \n + \" have common interests: \"\n + intersection;\n System.out.println(outputString) ;\n }\n }","public ZYSet<ElementType> intersection(ZYSet<ElementType> otherSet){\n ZYSet<ElementType> result = new ZYArraySet<ElementType>();\n for(ElementType e :this){\n if(otherSet.contains(e)){\n result.add(e);\n }\n }\n return result;\n }","public void run(){\n\t\tif(searchHow==0){\n\t\t\tint isbnCount = 0;\n\t\t\tfor(int i=0; i<db.size(); i++){\n\t\t\t\t\tSearchRequest requestIsbn = new SearchRequest(db, searchForThis, isbnCount, db.size());\n\t\t\t\t\tdb.searchByISBN(requestIsbn);\n\t\t\t\t\tisbnCount = requestIsbn.foundPos;\n\t\t\t\t\tif (requestIsbn.foundPos >= 0) {\n\t\t\t\t\t\tisbnCount++;\n\t\t\t\t\t\tString formatThis = \"Matched ISBN at position: \" + requestIsbn.foundPos;\n\t\t\t\t\t\tSystem.out.printf(\"%-35s || Title: \"+db.getBook(requestIsbn.foundPos)+\"\\n\",formatThis);\n\t\t\t\t\t}\n\t\t\t\t\telse\n\t\t\t\t\t\ti=db.size();\n\t\t\t}\n\t\t}\n\t\tif(searchHow==1){\n\t\t\tint titleCount = 0;\n\t\t\tfor(int i=0; i<db.size(); i++){\n\t\t\t\t\tSearchRequest requestTitle = new SearchRequest(db, searchForThis, titleCount, db.size());\n\t\t\t\t\tdb.searchByTitle(requestTitle);\n\t\t\t\t\ttitleCount = requestTitle.foundPos;\n\t\t\t\t\tif (requestTitle.foundPos >= 0) {\n\t\t\t\t\t\ttitleCount++;\n\t\t\t\t\t\tString formatThis = \"Matched title at position: \" + requestTitle.foundPos;\n\t\t\t\t\t\tSystem.out.printf(\"%-35s || Title: \"+db.getBook(requestTitle.foundPos)+\"\\n\",formatThis);\n\t\t\t\t\t}\n\t\t\t\t\telse\n\t\t\t\t\t\ti=db.size();\n\t\t\t}\n\t\t}\n\t\tif(searchHow==2){\n\t\t\tint authorCount = 0;\n\t\t\tfor(int i=0; i<db.size(); i++){\n\t\t\t\t\tSearchRequest requestAuthor = new SearchRequest(db, searchForThis, authorCount, db.size());\n\t\t\t\t\tdb.searchByAuthor(requestAuthor);\n\t\t\t\t\tauthorCount = requestAuthor.foundPos;\n\t\t\t\t\tif (requestAuthor.foundPos >= 0) {\n\t\t\t\t\t\tauthorCount++;\n\t\t\t\t\t\tString formatThis = \"Matched author at position: \" + requestAuthor.foundPos;\n\t\t\t\t\t\tSystem.out.printf(\"%-35s || Title: \"+db.getBook(requestAuthor.foundPos)+\"\\n\",formatThis);\n\t\t\t\t\t}\n\t\t\t\t\telse\n\t\t\t\t\t\ti=db.size();\n\t\t\t}\n\t\t}\n\t\tif(searchHow==3){\n\t\t\tint pageCount = 0;\n\t\t\tfor(int i=0; i<db.size(); i++){\n\t\t\t\t\tSearchRequest requestPage = new SearchRequest(db, searchForThis, pageCount, db.size());\n\t\t\t\t\tdb.searchByNumPages(requestPage);\n\t\t\t\t\tpageCount = requestPage.foundPos;\n\t\t\t\t\tif (requestPage.foundPos >= 0) {\n\t\t\t\t\t\tpageCount++;\n\t\t\t\t\t\tString formatThis = \"Matched pages at position: \" + requestPage.foundPos;\n\t\t\t\t\t\tSystem.out.printf(\"%-35s || Title: \"+db.getBook(requestPage.foundPos)+\"\\n\",formatThis);\n\t\t\t\t\t}\n\t\t\t\t\telse\n\t\t\t\t\t\ti=db.size();\n\t\t\t}\n\t\t}\n\t\tif(searchHow==4){\n\t\t\tint yearCount = 0;\n\t\t\tfor(int i=0; i<db.size(); i++){\n\t\t\t\t\tSearchRequest requestYear = new SearchRequest(db, searchForThis, yearCount, db.size());\n\t\t\t\t\tdb.searchByYear(requestYear);\n\t\t\t\t\tyearCount = requestYear.foundPos;\n\t\t\t\t\tif (requestYear.foundPos >= 0) {\n\t\t\t\t\t\tyearCount++;\n\t\t\t\t\t\tString formatThis = \"Matched year at position: \" + requestYear.foundPos;\n\t\t\t\t\t\tSystem.out.printf(\"%-35s || Title: \"+db.getBook(requestYear.foundPos)+\"\\n\",formatThis);\n\t\t\t\t\t}\n\t\t\t\t\telse\n\t\t\t\t\t\ti=db.size();\n\t\t\t}\n\t\t}\n\t}","public interface SearchQuerySet extends QuerySet\n{\n\n // for AbstractSearch\n public static final int STAT_MODELS = 1;\n public static final int STAT_CLUSTERS = 2;\n public static final int STAT_GENOMES = 4;\n public static final int STAT_MODEL_CLUSTERS = 8;\n\n public String getStatsById(Collection data);\n public String getStatsByQuery(String query);\n public String getStatsById(Collection data,int stats);\n public String getStatsByQuery(String query,int stats);\n \n // for BlastSearch\n public String getBlastSearchQuery(Collection dbNames, Collection keys, KeyTypeUser.KeyType keyType);\n \n //for ClusterIDSearch\n public String getClusterIDSearchQuery(Collection input, int limit, int[] DBs, KeyTypeUser.KeyType keyType);\n \n // for ClusterNameSearch\n public String getClusterNameSearchQuery(Collection input, int limit, int[] DBs, KeyTypeUser.KeyType keyType);\n \n // for DescriptionSearch\n public String getDescriptionSearchQuery(Collection input, int limit, int[] DBs, KeyTypeUser.KeyType keyType);\n \n // for GoSearch \n public String getGoSearchQuery(Collection input, int limit, KeyTypeUser.KeyType keyType);\n \n // for GoTextSearch\n public String getGoTextSearchQuery(Collection input, int limit, KeyTypeUser.KeyType keyType);\n \n // for IdSearch\n public String getIdSearchQuery(Collection input, int limit, int[] DBs, KeyTypeUser.KeyType keyType);\n \n // for QueryCompSearch\n public String getQueryCompSearchQuery(String comp_id, String status, KeyTypeUser.KeyType keyType);\n \n // for QuerySearch\n public String getQuerySearchQuery(String queries_id, KeyTypeUser.KeyType keyType); \n \n // for SeqModelSearch\n public String getSeqModelSearchQuery(Collection model_ids, KeyTypeUser.KeyType keyType);\n \n // for UnknowclusterIdSearch\n public String getUnknownClusterIdSearchQuery(int cluster_id, KeyTypeUser.KeyType keyType);\n \n // for ProbeSetSearch\n public String getProbeSetSearchQuery(Collection input, int limit, KeyTypeUser.KeyType keyType);\n \n // for ProbeSetKeySearch\n public String getProbeSetKeySearchQuery(Collection input, int limit, KeyTypeUser.KeyType keyType);\n \n // for QueryTestSearch\n public String getQueryTestSearchQuery(String query_id, String version, String genome_id);\n \n // for QueryStatsSearch\n public String getQueryStatsSearchQuery(List query_ids,List DBs);\n \n // for PskClusterSearch\n public String getPskClusterSearchQuery(int cluster_id,KeyTypeUser.KeyType keyType);\n \n // for ClusterCorrSearch\n public String getClusterCorrSearchQuery(int cluster_id, int psk_id, KeyTypeUser.KeyType keyType);\n \n // for UnknownGenesSearch\n public String getUnknownGenesSearchQuery(Collection sources, KeyTypeUser.KeyType keyType);\n \n}","public static SiftKnnContainer mergetosizeofboth(SiftKnnContainer a, SiftKnnContainer b) {\n SiftKnnContainer ret = new SiftKnnContainer( a.getK() + b.getK() );\n ret.SetQueryPoint(a.getQueryPoint());\n\n knnPair[] knn = a.getknnPairArray();\n for (int i = 0; i < knn.length ; i++) {\n if (knn[i].distance != Integer.MAX_VALUE) {\n ret.addNoDuplicateIDs(knn[i].pointID, knn[i].distance);\n }\n }\n knn = b.getknnPairArray();\n for (int i = 0; i < knn.length ; i++) {\n if (knn[i].distance != Integer.MAX_VALUE) {\n ret.addNoDuplicateIDs(knn[i].pointID, knn[i].distance);\n }\n }\n return ret;\n }","public static final void computeSortedIntersection(ArrayList<MediaItem> firstList, final ArrayList<MediaItem> secondList,\n int maxSize, ArrayList<MediaItem> intersectionList, MediaItem[] hash) {\n int mask = hash.length - 1;\n int numItemsToHash = Math.min(secondList.size(), 2 * hash.length);\n for (int i = 0; i < numItemsToHash; ++i) {\n MediaItem item = secondList.get(i);\n if (item != null) {\n hash[item.hashCode() & mask] = item;\n }\n }\n\n // Build the intersection array.\n int firstListSize = firstList.size();\n for (int i = 0; i < firstListSize; ++i) {\n MediaItem firstListItem = firstList.get(i);\n if (firstListItem == null)\n continue;\n MediaItem hashItem = (hash != null) ? hash[firstListItem.hashCode() & mask] : null;\n if (hashItem != null\n && ((hashItem.mId != Shared.INVALID && hashItem.hashCode() == firstListItem.hashCode()) || contains(secondList, firstListItem))) {\n intersectionList.add(firstListItem);\n if (--maxSize == 0) {\n break;\n }\n }\n }\n\n // Clear the hash table.\n Arrays.fill(hash, null);\n }","private void findIntersection(Node head1, Node head2) {\n if (head1 == null || head2 == null) {\n System.out.println(\"No intersection found\");\n return;\n }\n Set<Node> set = new HashSet<Node>();\n boolean flag = false;\n\n for (Node temp = head1; temp != null; temp = temp.next)\n set.add(temp);\n for (Node temp = head2; temp != null; temp = temp.next)\n if (!set.add(temp)) {\n System.out.println(\"Intersection found at \" + temp.data);\n flag = true;\n break;\n }\n if (!flag) {\n System.out.println(\"No intersection found\");\n }\n }","public static <T extends Comparable<? super T>> \n void union(SLL<T> list1, SLL<T> list2,\n SLL<T> result) {\n \n SLLNode<T> iterlist1 = list1.head;\n SLLNode<T> iterlist2 = list2.head;\n \n T itemlist1=null, itemlist2=null;\n \n // get first item in each list\n if ( iterlist1 != null )\n itemlist1 = iterlist1.info;\n if( iterlist2 != null )\n itemlist2 = iterlist2.info;\n \n while ( itemlist1 != null || itemlist2 != null ) {\n\n int compareResult;\n if( itemlist1 == null ) {\n compareResult = 1;\n } else if ( itemlist2 == null ) {\n compareResult = -1;\n } else {\n compareResult = itemlist1.compareTo(itemlist2);\n }\n \n if ( compareResult == 0 ) {\n result.addToTail(itemlist1); //appending to result list \n if( iterlist1.next != null ) {\n iterlist1 = iterlist1.next;\n itemlist1 = iterlist1.info;\n } else {\n itemlist1 = null;\n }\n \n if( iterlist2.next != null ) {\n iterlist2 = iterlist2.next;\n itemlist2 = iterlist2.info;\n } else {\n itemlist2 = null;\n } \n }\n else if ( compareResult < 0 ) { \n result.addToTail(itemlist1); //appending to result list\n if( iterlist1.next != null ) {\n iterlist1 = iterlist1.next;\n itemlist1 = iterlist1.info;\n } else {\n itemlist1 = null;\n }\n }\n else {\n result.addToTail(itemlist2);\n if( iterlist2.next != null ) {\n iterlist2 = iterlist2.next;\n itemlist2 = iterlist2.info;\n } else {\n itemlist2 = null;\n }\n }\n } \n }","public void testRange() throws IOException, InvalidGeoException\r\n {\n LgteIndexSearcherWrapper searcher = new LgteIndexSearcherWrapper(path);\r\n\r\n //try find Jorge and Bruno documents last year\r\n // In this case the closest one will be in 2007\r\n String query = \"contents:(Jorge Bruno)\";\r\n\r\n LgteQuery lgteQueryResult1;\r\n LgteQuery lgteQueryResult1and2;\r\n try\r\n {\r\n lgteQueryResult1 = LgteQueryParser.parseQuery(query);\r\n lgteQueryResult1and2 = LgteQueryParser.parseQuery(query);\r\n\r\n MyCalendar c1Aux = new MyCalendar(2005,11,20,9,0,10);\r\n MyCalendar c2Aux = new MyCalendar(2007,1,12,20,45,15);\r\n long dif = c2Aux.getTimeInMillis() - c1Aux.getTimeInMillis();\r\n\r\n lgteQueryResult1.getQueryParams().setTimeMiliseconds(c1Aux.getTimeInMillis());\r\n lgteQueryResult1.getQueryParams().setRadiumMiliseconds(dif -1);\r\n lgteQueryResult1and2.getQueryParams().setTimeMiliseconds(c1Aux.getTimeInMillis());\r\n lgteQueryResult1and2.getQueryParams().setRadiumMiliseconds(dif+1);\r\n }\r\n catch (ParseException e)\r\n {\r\n fail(e.toString());\r\n return;\r\n }\r\n\r\n //Lets use aos Time Sorter to dont worry about distances and stuff like that, he will do the job\r\n TimeDistanceSortSource dsort1 = new TimeDistanceSortSource();\r\n LgteSort sort1 = new LgteSort(new SortField(\"foo\", dsort1));\r\n\r\n //LgteHits give you Documents and time with unecessary lines of boring code\r\n LgteHits lgteHits1;\r\n LgteHits lgteHits1and2;\r\n lgteHits1 = searcher.search(lgteQueryResult1, sort1);\r\n assertTrue(lgteHits1.length() == 1);\r\n\r\n lgteHits1and2 = searcher.search(lgteQueryResult1and2, sort1);\r\n assertTrue(lgteHits1and2.length() == 2);\r\n\r\n\r\n long time1_0 = lgteHits1.doc(0).getTime().getTime();\r\n long time1and2_0 = lgteHits1and2.doc(0).getTime().getTime();\r\n long time1and2_1 = lgteHits1and2.doc(1).getTime().getTime();\r\n assertTrue(time1_0 == new MyCalendar(2005,11,20,9,0,10).getTimeInMillis());\r\n assertTrue(time1and2_0 == new MyCalendar(2005,11,20,9,0,10).getTimeInMillis());\r\n assertTrue(time1and2_1 == new MyCalendar(2007,1,12,20,45,15).getTimeInMillis());\r\n\r\n\r\n searcher.close();\r\n }","protected void reflectRelationOnUnionQuery(ConditionQuery baseQueryAsSuper, ConditionQuery unionQueryAsSuper) {\r\n }","public ArrayList<String> combineDataOpsAndIntents(String p1, String p2) {\n\t\tArrayList<String> logics1 = QueryStream.getLogic(p1);\n\t\tArrayList<String> terms1 = QueryStream.getTerms(p1);\n\t\t//Get logic statements from p2\n\t\tArrayList<String> logics2 = QueryStream.getLogic(p2);\n\t\tArrayList<String> terms2 = QueryStream.getTerms(p2);\n\t\t\n\t\tArrayList<String> result_logics = new ArrayList<String>();\n\t\tArrayList<String> result_terms = new ArrayList<String>();\n\t\t\n\t\t//Iterate through logic for p1. If it matches anything in p2,\n\t\t// we add the terms from p1 and p2 together.\n\t\tfor(int i = 0; i < logics1.size(); ++i) {\n\t\t\t\n\t\t\tString result_term = \"\";\n\t\t\t//If any logic matches, we combine the corresponding terms together\n\t\t\tif(logics2.contains(logics1.get(i))) {\n\t\t\t\tresult_term = terms1.get(i) + \" \" + terms2.get(i);\n\t\t\t}\n\t\t\telse {\n\t\t\t\tresult_term = terms1.get(i);\n\t\t\t}\n\t\t\tresult_logics.add(logics1.get(i));\n\t\t\tresult_terms.add(result_term);\n\t\t}\n\t\t//Iterate through the logic for p2. If it includes any logic not\n\t\t// in the results, then add it in.\n\t\tfor(int i = 0; i < logics2.size(); ++i) {\n\t\t\t\n\t\t\tString result_term = \"\";\n\t\t\t//If any logic matches, we combine the corresponding terms together\n\t\t\tif(!result_logics.contains(logics2.get(i))) {\n\t\t\t\tresult_logics.add(logics2.get(i));\n\t\t\t\tresult_term = terms2.get(i);\n\t\t\t\tresult_terms.add(result_term);\n\t\t\t}\n\t\t}\n\t\t\n//\t\tfor(String l : result_logics) {\n//\t\t\tSystem.out.println(l);\n//\t\t}\n\t\t\n\t\t//Now we can create a new policy given the two strings\n\t\treturn produceDataOpsIntentsPolicy(result_logics, result_terms);\n\t}","public static void findIntersection(int[] ip1, int[] ip2) {\n int[] smaller, bigger;\n if (ip1.length <= ip2.length) {\n smaller = ip1;\n bigger = ip2;\n } else {\n smaller = ip2;\n bigger = ip1;\n }\n\n\n //O(n)\n for (int i = 0; i < smaller.length; ) {\n for (int j = 0; j < bigger.length; ) {\n\n if (smaller[i] == bigger[j]) {\n System.out.print(smaller[i]+\" \");\n i++;\n j++;\n } else if (smaller[i] < bigger[j]) {\n i++;\n } else {\n j++;\n }\n\n\n }\n }\n\n\n }","public void splitQuery(){\n for (int i=0;i<stemmed_query.size();i++){\n String stemmed_term = stemmed_query.get(i);\n for (int j=0;j<num_slave_client_threads;j++){\n if (stemmed_term.compareTo(ServerThread.start_terms[j]) >= 0 && stemmed_term.compareTo(ServerThread.end_terms[j]) <= 0){\n slave_queries.set(j, slave_queries.get(j)+\" \"+stemmed_term);\n break;\n }\n }\n }\n }","public int[] intersection(int[] nums1, int[] nums2) {\n \n HashSet<Integer> set = new HashSet<>();\n ArrayList<Integer> inter = new ArrayList<>();\n if(nums1.length > nums2.length)\n {\n for(int i = 0; i < nums1.length ;i ++)\n set.add(nums1[i]);\n\n for(int i = 0; i < nums2.length ;i ++)\n if(set.contains(nums2[i])&& !inter.contains(nums2[i]))\n inter.add(nums2[i]);\n }\n else {\n for(int i = 0; i < nums2.length ;i ++)\n set.add(nums2[i]);\n\n for(int i = 0; i < nums1.length ;i ++)\n if(set.contains(nums1[i]) && !inter.contains(nums1[i]))\n inter.add(nums1[i]);\n }\n\n int [] arr = new int[inter.size()];\n for(int i = 0; i < arr.length ;i ++)\n arr[i] = inter.get(i);\n return arr;\n\n }","private double intersection(HardClustering hard1, int comm1,\n HardClustering hard2, int comm2) {\n final TIntArrayList duplicate = new TIntArrayList(hard1.members(comm1));\n duplicate.retainAll(hard2.members(comm2));\n\n return duplicate.size();\n }","private MetaSparqlRequest createQueryMT2() {\n\t\treturn createQueryMT1();\n\t}"],"string":"[\n \"public PostingsList intersect(Query query){\\n\\n LinkedList<PostingsList> listQueriedPostings = new LinkedList<PostingsList>();\\n // List with postings corresponding to the queries\\n for (int i = 0; i<query.size(); i++){\\n // If any query has zero matches, return 0 results\\n //if(!(new File(\\\"postings/t\\\"+hash(query.terms.get(i))+\\\".json\\\")).exists()){\\n if (!this.index.containsKey(query.terms.get(i))){\\n return null;\\n }\\n // Otherwise store postings in the list\\n listQueriedPostings.add(this.getPostings(query.terms.get(i)));\\n }\\n\\n // Order the posting list by increasing document frequency\\n listQueriedPostings = sortByIncreasingFrequency(listQueriedPostings);\\n\\n PostingsList result = (PostingsList)listQueriedPostings.get(0);\\n\\n // In case only one word is queried\\n if (listQueriedPostings.size() == 1){\\n return result;\\n }\\n\\n // Apply algorithm as many times as words in the query\\n for(int i = 1; i < listQueriedPostings.size(); i++){\\n result = intersect(result, listQueriedPostings.get(i));\\n if (result.isEmpty()){\\n return null;\\n }\\n }\\n return result;\\n }\",\n \"public PostingsList phrase_query(PostingsList l1, PostingsList l2){\\n\\n PostingsList phrase = new PostingsList();\\n\\n // Counters to iterate docIDs\\n int count1 = 0;\\n int count2 = 0;\\n // Counters to iterate positional indices\\n int subcount1 = 0;\\n int subcount2 = 0;\\n\\n // First posting\\n PostingsEntry p1 = l1.get(0);\\n PostingsEntry p2 = l2.get(0);\\n\\n // List of positional indices (changes at each iteration)\\n LinkedList<Integer> ll1;\\n LinkedList<Integer> ll2;\\n\\n // Used to store positional index\\n int pp1;\\n int pp2;\\n\\n while(true){\\n // docID match (1/2) //\\n if (p1.docID == p2.docID){\\n // Obtain list of positional indices\\n ll1 = p1.positions;\\n ll2 = p2.positions;\\n // First positional indices\\n pp1 = ll1.get(0);\\n pp2 = ll2.get(0);\\n // Initialize counter\\n subcount1 = 0;\\n subcount2 = 0;\\n\\n // Search if the phrase exists\\n while(true){\\n // Match, consecutive words (2/2) - EUREKA! //\\n if (pp1+1 == pp2){\\n // Save found match (docID and positional index of last\\n // word)\\n phrase.insert(p1.docID, pp2);\\n // Increase counters and pos indices if list is not finished\\n subcount1++;\\n subcount2++;\\n if (subcount1<ll1.size() && subcount2<ll2.size()){\\n pp1 = ll1.get(subcount1);\\n pp2 = ll2.get(subcount2);\\n }\\n // If list finished, break\\n else\\n break;\\n }\\n // Not match\\n else if (pp1+1 < pp2){\\n subcount1++;\\n if (subcount1<ll1.size())\\n pp1 = ll1.get(subcount1);\\n // If list finished, break\\n else\\n break;\\n }\\n // Not match\\n else{\\n subcount2++;\\n if (subcount2<ll2.size())\\n pp2 = ll2.get(subcount2);\\n else\\n break;\\n }\\n }\\n\\n // Once we finished looking at the list of positional indices of one\\n // posting, increase counters and go to next postings (if there are)\\n count1++;\\n count2++;\\n if (count1<l1.size() && count2<l2.size()){\\n p1 = l1.get(count1);\\n p2 = l2.get(count2);\\n }\\n else{\\n break;\\n }\\n }\\n // docID not match, increase lowest counter\\n else if (p1.docID < p2.docID){\\n count1++;\\n if (count1<l1.size()){\\n p1 = l1.get(count1);\\n }\\n else{\\n break;\\n }\\n }\\n // docID not match, increase lowest counter\\n else{\\n count2++;\\n if (count2<l2.size()){\\n p2 = l2.get(count2);\\n }\\n else{\\n break;\\n }\\n }\\n }\\n\\n return phrase;\\n }\",\n \"@Override\\n public boolean equals(Object o) {\\n if(o == null){\\n return false;\\n }\\n\\n if (this == o) { return true; }\\n if (getClass() != o.getClass()) { return false; }\\n Query a_new = (Query) o;\\n return this.requestedPosts== (a_new.getRequestedPosts()) && this.getQueryID() == a_new.getQueryID();\\n }\",\n \"private void queryListings(double left, double right, double top, double bottom) {\\n ParseQuery<Listing> query = ParseQuery.getQuery(Listing.class);\\n query.include(Listing.KEY_AUTHOR);\\n query.whereGreaterThanOrEqualTo(Listing.KEY_LONGITUDE, left);\\n query.whereLessThanOrEqualTo(Listing.KEY_LONGITUDE, right);\\n query.whereGreaterThanOrEqualTo(Listing.KEY_LATITUDE, bottom);\\n query.whereLessThanOrEqualTo(Listing.KEY_LATITUDE, top);\\n query.findInBackground(new FindCallback<Listing>() {\\n @Override\\n public void done(List<Listing> listings, ParseException e) {\\n // Check for errors\\n if (e != null) {\\n Log.e(TAG, \\\"Issue with getting listings\\\", e);\\n return;\\n }\\n // Add a marker for each listing on screen\\n for (Listing listing : listings) {\\n LatLng coordinates = new LatLng(listing.getLatitude(), listing.getLongitude());\\n Marker marker = thisMap.addMarker(new MarkerOptions().position(coordinates).title(listing.getCategory()));\\n marker.setTag(listing);\\n }\\n }\\n });\\n }\",\n \"public ArrayList<ArrayList> intersection (ArrayList<ArrayList> data, ArrayList<ArrayList> data2)\\n {\\n ArrayList<Document> docs = data.get(0);\\n ArrayList<Double> relevance = data.get(1);\\n ArrayList<Integer> occurrence = data.get(2);\\n ArrayList<Integer> popularity = data.get(3);\\n \\n ArrayList<Document> docs2 = data2.get(0);\\n ArrayList<Double> relevance2 = data2.get(1);\\n ArrayList<Integer> occurrence2 = data2.get(2);\\n ArrayList<Integer> popularity2 = data2.get(3);\\n \\n ArrayList<Document> docs3 = new ArrayList<>();\\n ArrayList<Double> relevance3 = new ArrayList<>();\\n ArrayList<Integer> occurrence3 = new ArrayList<>();\\n ArrayList<Integer> popularity3 = new ArrayList<>();\\n \\n for(Document d: docs)\\n {\\n if(docs2.contains(d))\\n {\\n docs3.add(d);\\n int docIndex = docs.indexOf(d);\\n int docIndex2 = docs2.indexOf(d);\\n double oldRel = (double) relevance.get(docIndex);\\n int oldOcc = (int) occurrence.get(docIndex);\\n relevance3.add(oldRel+relevance2.get(docIndex2));\\n if(oldOcc > occurrence2.get(docIndex2))\\n {\\n occurrence3.add(occurrence2.get(docIndex2));\\n }\\n else\\n {\\n occurrence3.add(oldOcc);\\n }\\n popularity3.add(d.popularity);\\n }\\n \\n }\\n data = new ArrayList<ArrayList> ();\\n data.add(docs3);\\n data.add(relevance3);\\n data.add(occurrence3);\\n data.add(popularity3);\\n \\n return data;\\n }\",\n \"public void testQuery() throws Exception {\\n DummyApprovalRequest req1 = new DummyApprovalRequest(reqadmin, null, caid, SecConst.EMPTY_ENDENTITYPROFILE, false);\\n DummyApprovalRequest req2 = new DummyApprovalRequest(admin1, null, caid, SecConst.EMPTY_ENDENTITYPROFILE, false);\\n DummyApprovalRequest req3 = new DummyApprovalRequest(admin2, null, 3, 2, false);\\n\\n approvalSessionRemote.addApprovalRequest(admin1, req1, gc);\\n approvalSessionRemote.addApprovalRequest(admin1, req2, gc);\\n approvalSessionRemote.addApprovalRequest(admin1, req3, gc);\\n\\n // Make som queries\\n Query q1 = new Query(Query.TYPE_APPROVALQUERY);\\n q1.add(ApprovalMatch.MATCH_WITH_APPROVALTYPE, BasicMatch.MATCH_TYPE_EQUALS, \\\"\\\" + req1.getApprovalType());\\n\\n List result = approvalSessionRemote.query(admin1, q1, 0, 3, \\\"cAId=\\\" + caid, \\\"(endEntityProfileId=\\\" + SecConst.EMPTY_ENDENTITYPROFILE + \\\")\\\");\\n assertTrue(\\\"Result size \\\" + result.size(), result.size() >= 2 && result.size() <= 3);\\n\\n result = approvalSessionRemote.query(admin1, q1, 1, 3, \\\"cAId=\\\" + caid, \\\"(endEntityProfileId=\\\" + SecConst.EMPTY_ENDENTITYPROFILE + \\\")\\\");\\n assertTrue(\\\"Result size \\\" + result.size(), result.size() >= 1 && result.size() <= 3);\\n\\n result = approvalSessionRemote.query(admin1, q1, 0, 1, \\\"cAId=\\\" + caid, \\\"(endEntityProfileId=\\\" + SecConst.EMPTY_ENDENTITYPROFILE + \\\")\\\");\\n assertTrue(\\\"Result size \\\" + result.size(), result.size() == 1);\\n\\n Query q2 = new Query(Query.TYPE_APPROVALQUERY);\\n q2.add(ApprovalMatch.MATCH_WITH_STATUS, BasicMatch.MATCH_TYPE_EQUALS, \\\"\\\" + ApprovalDataVO.STATUS_WAITINGFORAPPROVAL, Query.CONNECTOR_AND);\\n q2.add(ApprovalMatch.MATCH_WITH_REQUESTADMINCERTSERIALNUMBER, BasicMatch.MATCH_TYPE_EQUALS, reqadmincert.getSerialNumber().toString(16));\\n\\n result = approvalSessionRemote.query(admin1, q1, 1, 3, \\\"cAId=\\\" + caid, \\\"(endEntityProfileId=\\\" + SecConst.EMPTY_ENDENTITYPROFILE + \\\")\\\");\\n assertTrue(\\\"Result size \\\" + result.size(), result.size() >= 1 && result.size() <= 3);\\n\\n // Remove the requests\\n int id1 = ((ApprovalDataVO) approvalSessionRemote.findApprovalDataVO(admin1, req1.generateApprovalId()).iterator().next()).getId();\\n int id2 = ((ApprovalDataVO) approvalSessionRemote.findApprovalDataVO(admin1, req2.generateApprovalId()).iterator().next()).getId();\\n int id3 = ((ApprovalDataVO) approvalSessionRemote.findApprovalDataVO(admin1, req3.generateApprovalId()).iterator().next()).getId();\\n approvalSessionRemote.removeApprovalRequest(admin1, id1);\\n approvalSessionRemote.removeApprovalRequest(admin1, id2);\\n approvalSessionRemote.removeApprovalRequest(admin1, id3);\\n }\",\n \"public static List<String> query_intersect(List<String> queryWords) throws IOException {\\n\\t\\tif (!initialized) initialize();\\n\\t\\tList<PostingList> pls = new ArrayList<PostingList> ();\\n\\t\\tfor (String queryWord : queryWords) {\\n\\t\\t\\tqueryWord = queryWord.toLowerCase();\\n\\t\\t\\tif (!termDict.containsKey(queryWord)) {\\n\\t\\t\\t\\tpls.clear();\\n\\t\\t\\t\\tbreak;\\n\\t\\t\\t}\\n\\t\\t\\tPostingList pl = readPosting(fc, termDict.get(queryWord));\\n\\t\\t\\tif (pl == null) {\\n\\t\\t\\t\\tpls.clear();\\n\\t\\t\\t\\tbreak;\\n\\t\\t\\t}\\n\\t\\t\\tpls.add(readPosting(fc, termDict.get(queryWord)));\\n\\t\\t}\\n\\t\\tCollections.sort(pls, new Comparator<PostingList>(){\\n\\t\\t public int compare(PostingList p1, PostingList p2) {\\n\\t\\t return p1.size() - p2.size(); // assumes you want biggest to smallest\\n\\t\\t }\\n\\t\\t});\\n\\t\\tif (pls.size() == 0) {\\n\\t\\t\\treturn null;\\n\\t\\t} else {\\n\\t\\t\\tList<Integer> current = pls.get(0).getList();\\n\\t\\t\\tfor (int i = 1; i < pls.size(); i++) {\\n\\t\\t\\t\\tList<Integer> toBeAdd = pls.get(i).getList();\\n\\t\\t\\t\\tcurrent = intersect(current, toBeAdd);\\n\\t\\t\\t}\\n\\t\\t\\tif (current.size() == 0) {\\n\\t\\t\\t\\treturn null;\\n\\t\\t\\t} else {\\n\\t\\t\\t\\tList<String> result = new ArrayList<String>();\\n\\t\\t\\t\\tfor (int docId : current) {\\n\\t\\t\\t\\t\\tresult.add(docDict.get(docId));\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\treturn result;\\n\\t\\t\\t}\\n\\t\\t}\\n\\t}\",\n \"private void positionIntersects(LinkedList<TermPositions> p1, LinkedList<TermPositions> p2, int k) {\\n if (p1 != null && p2 != null) {\\n int df1 = p1.size();\\n int df2 = p2.size();\\n while (!p1.isEmpty() && !p2.isEmpty()) {\\n int tf1 = p1.peek().getPositionList().size();\\n int tf2 = p1.peek().getPositionList().size();\\n if (p1.peek().getDocId() == p2.peek().getDocId()) {\\n LinkedList<Integer> pp1 = p1.peek().getPositionList();\\n while (!pp1.isEmpty()) {\\n for (Integer integer : p2.peek().getPositionList()) {\\n if ((pp1.peek() - integer) < 0 && Math.abs(pp1.peek() - integer) <= (k + 1)) {\\n double score = (1 + Math.log(tf1) * Math.log(N / df1)) + (1 + Math.log(tf2) * Math.log(N / df2));\\n resultsCollector.add(new DocCollector(p1.peek().getDocId(), score));\\n break;\\n }\\n }\\n pp1.pop();\\n }\\n } else if (p1.peek().getDocId() < p2.peek().getDocId())\\n p1.pop();\\n else\\n p2.pop();\\n\\n p1.pop();\\n p2.pop();\\n\\n }\\n\\n }\\n\\n\\n }\",\n \"@Test\\r\\n\\t\\tpublic void testIntersection() {\\n\\t\\t\\ttestingSet = new IntegerSet(list1);\\r\\n\\t\\t\\ttestingSet2= new IntegerSet(list2);\\r\\n\\t\\t\\t// create 3rdset = to the intersection list \\r\\n\\t\\t\\ttestingSet3= new IntegerSet(intersection);\\r\\n\\t\\t\\t// create 4th set =to the intersection of set1 and set2\\r\\n\\t\\t\\ttestingSet4= testingSet.intersection(testingSet, testingSet2);\\r\\n\\t\\t\\t// sets 3 and set 4 should be equal \\r\\n\\t\\t\\t// assertEquals for these parameters is a deprecated method \\r\\n\\t\\t\\tassertArrayEquals(testingSet3.toArray(),testingSet4.toArray());\\t \\r\\n\\t\\t}\",\n \"public void queryTaskUnionSet2() {\\r\\n\\t\\t// task 1\\r\\n\\t\\tTask task1 = new Task();\\r\\n\\t\\ttask1.setName(\\\"DEFECTS\\\");\\r\\n\\t\\ttask1.setDisplayName(\\\"Defects\\\");\\r\\n\\t\\ttask1.setDescription(\\\"User story to address product defects\\\");\\r\\n\\t\\t\\r\\n\\t\\tTask d1 = new Task();\\r\\n\\t\\td1.setName(\\\"DEFECT 1\\\");\\r\\n\\t\\td1.setDisplayName(\\\"Defect 1\\\");\\r\\n\\t\\td1.setDescription(\\\"First defect\\\");\\r\\n\\t\\tTask d2 = new Task();\\r\\n\\t\\td2.setName(\\\"DEFECT 2\\\");\\r\\n\\t\\td2.setDisplayName(\\\"Defect 2\\\");\\r\\n\\t\\td2.setDescription(\\\"Second defect\\\");\\r\\n\\t\\tSet<Task> c = new HashSet<Task>();\\r\\n\\t\\tc.add(d1);\\r\\n\\t\\tc.add(d2);\\r\\n\\t\\ttask1.setTaskChildren(c);\\r\\n\\t\\ttask1 = (Task) aggregateService.create(task1, new Settings());\\r\\n\\r\\n\\t\\t\\tSystem.out.println(\\\"Name: \\\" + task1.getName() + \\\", Id: \\\" + task1.getId());\\r\\n\\r\\n\\t\\t// task 2\\r\\n\\t\\tTask task2 = new Task();\\r\\n\\t\\ttask2.setName(\\\"FIX_DEFECTS\\\");\\r\\n\\t\\ttask2.setDisplayName(\\\"Fix defects\\\");\\r\\n\\t\\ttask2.setDescription(\\\"Task to track the defect fixing effort\\\");\\r\\n\\t\\ttask2 = (Task) aggregateService.create(task2, new Settings());\\r\\n\\r\\n\\t\\t// task 3\\r\\n\\t\\tTask task3 = new Task();\\r\\n\\t\\ttask3.setName(\\\"PRIORITIZE_DEFECTS\\\");\\r\\n\\t\\ttask3.setDisplayName(\\\"Prioritize defects\\\");\\r\\n\\t\\ttask3.setDescription(\\\"Based upon the effort required for the defects prioritize them\\\");\\r\\n\\t\\ttask3 = (Task) aggregateService.create(task3, new Settings());\\r\\n\\r\\n\\t\\ttask1 = (Task) aggregateService.read(task1, getSettings());\\t\\t\\r\\n\\r\\n\\t\\t// query the task object\\r\\n\\t\\tSettings settings = new Settings();\\r\\n\\t\\tsettings.setParam(\\\"name1\\\", \\\"DEFECTS\\\");\\r\\n\\t\\tsettings.setParam(\\\"name2\\\", \\\"PRIORITIZE_DEFECTS\\\");\\r\\n\\t\\tsettings.setParam(\\\"name3\\\", \\\"FIX_DEFECTS\\\");\\r\\n\\t\\tsettings.addFunction(FunctionHandler.NE, \\\"name\\\", \\\"name3\\\");\\r\\n\\t\\tsettings.addFunction(FunctionType.ASC, \\\"name\\\");\\r\\n\\t\\tsettings.setView(aggregateService.getView(\\\"TASKUNIONSET\\\"));\\t\\t\\r\\n\\t\\tList<?> toList = aggregateService.query(new Task(), settings);\\r\\n\\r\\n\\t\\tSystem.out.println(\\\"SIZE : \\\" + toList.size());\\r\\n\\t\\tfor(Object o: toList) {\\r\\n\\t\\t\\tTask t = (Task) o;\\r\\n\\t\\t\\tSystem.out.println(\\\"Name: \\\" + t.getName() + \\\", Id: \\\" + t.getId());\\r\\n\\t\\t}\\r\\n\\t\\tassert(toList.size() == 2);\\r\\n\\r\\n\\t\\tObject obj1 = toList.get(0);\\r\\n\\t\\tObject obj2 = toList.get(1);\\r\\n\\r\\n\\t\\tassert(Task.class.isAssignableFrom(obj1.getClass()));\\r\\n\\t\\tassert(Task.class.isAssignableFrom(obj2.getClass()));\\r\\n\\t\\t\\r\\n\\t\\tTask t1 = (Task) obj1;\\r\\n\\t\\tTask t2 = (Task) obj2;\\r\\n\\r\\n\\t\\tassert ((t1.getName().equals(\\\"DEFECTS\\\") && t2.getName().equals(\\\"PRIORITIZE_DEFECTS\\\")) ||\\r\\n\\t\\t\\t(t2.getName().equals(\\\"DEFECTS\\\") && t1.getName().equals(\\\"PRIORITIZE_DEFECTS\\\")));\\r\\n\\r\\n\\t\\tTask d = t1.getName().equals(\\\"DEFECTS\\\") ? t1 : t2;\\r\\n\\t\\tassert (d.getTaskChildren() != null && d.getTaskChildren().size() == 2);\\r\\n\\r\\n//\\t\\tSystem.out.println(\\\"Task 1: \\\" + t1.getName() + \\\", Task 2: \\\" + t2.getName());\\r\\n//\\t\\tassert (t1.getName().equals(\\\"DEFECTS\\\") && t2.getName().equals(\\\"DEFECT 1\\\"));\\r\\n//\\t\\tassert(t1.getTaskChildren() != null && t1.getTaskChildren().size() == 2);\\r\\n\\t}\",\n \"protected void merge(Object in1, Object in2, Object out) {\\n\\t\\tFlowSet inSet1 = (FlowSet) in1, inSet2 = (FlowSet) in2, outSet = (FlowSet) out;\\n\\n\\t\\tinSet1.intersection(inSet2, outSet);\\n\\t}\",\n \"public void queryTaskUnionSet1() {\\r\\n\\t\\t// task 1\\r\\n\\t\\tTask task1 = new Task();\\r\\n\\t\\ttask1.setName(\\\"DEFECTS\\\");\\r\\n\\t\\ttask1.setDisplayName(\\\"Defects\\\");\\r\\n\\t\\ttask1.setDescription(\\\"User story to address product defects\\\");\\r\\n\\t\\ttask1 = (Task) aggregateService.create(task1, new Settings());\\t\\r\\n\\r\\n\\t\\t// task 2\\r\\n\\t\\tTask task2 = new Task();\\r\\n\\t\\ttask2.setName(\\\"FIX_DEFECTS\\\");\\r\\n\\t\\ttask2.setDisplayName(\\\"Fix defects\\\");\\r\\n\\t\\ttask2.setDescription(\\\"Task to track the defect fixing effort\\\");\\r\\n\\t\\ttask2 = (Task) aggregateService.create(task2, new Settings());\\r\\n\\r\\n\\t\\t// task 3\\r\\n\\t\\tTask task3 = new Task();\\r\\n\\t\\ttask3.setName(\\\"PRIORITIZE_DEFECTS\\\");\\r\\n\\t\\ttask3.setDisplayName(\\\"Prioritize defects\\\");\\r\\n\\t\\ttask3.setDescription(\\\"Based upon the effort required for the defects prioritize them\\\");\\r\\n\\t\\ttask3 = (Task) aggregateService.create(task3, new Settings());\\r\\n\\r\\n\\t\\ttask1 = (Task) aggregateService.read(task1, getSettings());\\t\\t\\r\\n\\r\\n\\t\\t// query the task object\\r\\n\\t\\tSettings settings = new Settings();\\r\\n\\t\\tsettings.setParam(\\\"name1\\\", \\\"FIX_DEFECTS\\\");\\r\\n\\t\\tsettings.setParam(\\\"name2\\\", \\\"PRIORITIZE_DEFECTS\\\");\\r\\n\\t\\tsettings.setView(aggregateService.getView(\\\"TASKUNIONSET\\\"));\\t\\t\\r\\n\\t\\tList<?> toList = aggregateService.query(new Task(), settings);\\r\\n\\r\\n\\t\\tassert(toList.size() == 2);\\r\\n\\r\\n\\t\\tObject obj1 = toList.get(0);\\r\\n\\t\\tObject obj2 = toList.get(1);\\r\\n\\r\\n\\t\\tassert(Task.class.isAssignableFrom(obj1.getClass()));\\r\\n\\t\\tassert(Task.class.isAssignableFrom(obj2.getClass()));\\r\\n\\t\\t\\r\\n\\t\\tTask t1 = (Task) obj1;\\r\\n\\t\\tTask t2 = (Task) obj2;\\t\\t\\r\\n\\t\\t\\r\\n\\t\\tassert( (t1.getName().equals(\\\"FIX_DEFECTS\\\") && t2.getName().equals(\\\"PRIORITIZE_DEFECTS\\\")) ||\\r\\n\\t\\t\\t\\t(t2.getName().equals(\\\"FIX_DEFECTS\\\") && t1.getName().equals(\\\"PRIORITIZE_DEFECTS\\\")) );\\r\\n\\t}\",\n \"public PostingsList ranked_query(Query query, double w, double idf_threshold){\\n long startTime = System.nanoTime();\\n PostingsList result = new PostingsList();\\n\\n // Obtain union of terms above idf threshold if indexElimination is true\\n // (Set idf_threshold to zero to disable this feature)\\n Set<String> termsToConsider = this.queryTermsConsidered(query, idf_threshold);\\n result = this.union_query(query, termsToConsider);\\n //System.err.println(\\\"Size of result is \\\" + result.size());\\n\\n long estimatedTime = (System.nanoTime() - startTime)/1000000;\\n System.err.println(\\\"* Union took: \\\" + estimatedTime);\\n\\n\\n /*\\n * 2) Iterate over PostingsEntries and build the solution\\n */\\n startTime = System.nanoTime();\\n // Required when iterating over a PostingsList\\n PostingsEntry postEnt = new PostingsEntry();\\n // Number of documents in the collection\\n double nDocs = this.docIDs.size();\\n // Weight of a query vector coefficient\\n double w_query_term;\\n // Document tf-idf variables\\n double termFrequency_doc, documentFrequency_doc, w_doc_term;\\n\\n for(String term : termsToConsider){\\n // Obtain idf of the term\\n documentFrequency_doc = Math.log(nDocs/new Double(this.idfMap.get(term)));\\n\\n // Obtain weight of the term\\n w_query_term = query.weights.get(term);\\n // Iterate over all documents containing the term and update the score(q,d)\\n Iterator<PostingsEntry> it_d = result.iterator();\\n while(it_d.hasNext()){\\n postEnt = it_d.next();\\n if (this.tfMap.get(postEnt.docID).containsKey(term)){\\n termFrequency_doc = this.tfMap.get(postEnt.docID).get(term);\\n w_doc_term = documentFrequency_doc*termFrequency_doc;\\n postEnt.score += w_query_term*w_doc_term;\\n }\\n }\\n }\\n estimatedTime = (System.nanoTime() - startTime)/1000000;\\n System.err.println(\\\"* Building solution took: \\\" + estimatedTime);\\n\\n /*\\n * 3) Normalize the scores\\n */\\n startTime = System.nanoTime();\\n Iterator<PostingsEntry> it = result.iterator();\\n while(it.hasNext()){\\n postEnt = it.next();\\n postEnt.score /= (new Double(this.docLengths.get(\\\"\\\"+postEnt.docID)));//(Math.sqrt(postEnt.norm2));\\n postEnt.score = w * postEnt.score + (1-w) * quality(postEnt.docID);\\n }\\n estimatedTime = (System.nanoTime() - startTime)/1000000;\\n System.err.println(\\\"* Normalizing took: \\\" + estimatedTime);\\n\\n /*\\n * 4) Sort the resulting solution\\n */\\n startTime = System.nanoTime();\\n result.sort();\\n estimatedTime = (System.nanoTime() - startTime)/1000000;\\n System.err.println(\\\"* Sorting took: \\\" + estimatedTime);\\n\\n return result;\\n }\",\n \"private boolean isIntersectWithSource(List<Pair<Tuple,String>> list1, List<Pair<Tuple,String>> list2) {\\n\\t\\tboolean intersect = false;\\n\\t\\t\\n\\t\\tfor (Pair<Tuple,String> tuple : list1) {\\n\\t\\t\\tif (list2.contains(tuple)) {\\n\\t\\t\\t\\tintersect = true;\\n\\t\\t\\t\\tbreak;\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\treturn intersect;\\n\\t}\",\n \"public void mergeIn(QueryMetadata otherInstance) {\\n for(QueryMetadataItem otherItem : otherInstance.items) {\\n boolean alreadyExists = false;\\n for(QueryMetadataItem item : items) {\\n if(item.name.equals(otherItem.name)) {\\n alreadyExists = true;\\n }\\n }\\n if(!alreadyExists) {\\n addItem(otherItem.name, otherItem.value);\\n }\\n }\\n }\",\n \"private Map mergeResults(Map first, Map second) {\\n/* 216 */ Iterator verb_enum = second.keySet().iterator();\\n/* 217 */ Map clonedHash = new HashMap(first);\\n/* */ \\n/* */ \\n/* 220 */ while (verb_enum.hasNext()) {\\n/* 221 */ String verb = verb_enum.next();\\n/* 222 */ List cmdVector = (List)clonedHash.get(verb);\\n/* 223 */ if (cmdVector == null) {\\n/* 224 */ clonedHash.put(verb, second.get(verb));\\n/* */ continue;\\n/* */ } \\n/* 227 */ List oldV = (List)second.get(verb);\\n/* 228 */ cmdVector = new ArrayList(cmdVector);\\n/* 229 */ cmdVector.addAll(oldV);\\n/* 230 */ clonedHash.put(verb, cmdVector);\\n/* */ } \\n/* */ \\n/* 233 */ return clonedHash;\\n/* */ }\",\n \"private void addQueries(String query){\\n ArrayList <String> idsFullSet = new ArrayList <String>(searchIDs);\\n while(idsFullSet.size() > 0){\\n ArrayList <String> idsSmallSet = new ArrayList <String>(); \\n if(debugMode) {\\n System.out.println(\\\"\\\\t Pmids not used in query available : \\\" + idsFullSet.size());\\n }\\n idsSmallSet.addAll(idsFullSet.subList(0,Math.min(getSearchIdsLimit(), idsFullSet.size())));\\n idsFullSet.removeAll(idsSmallSet);\\n String idsConstrain =\\\"\\\";\\n idsConstrain = idsConstrain(idsSmallSet);\\n addQuery(query,idsConstrain);\\n }\\n }\",\n \"@Test\\n public void sharedFilterEnsuresUniqueResults() {\\n Filter filter = new Filter(\\\"test-filter\\\");\\n final Dataset dataset1 = new Dataset(\\\"TEST1\\\", \\\"sql\\\", filter);\\n final Dataset dataset2 = new Dataset(\\\"TEST2\\\", \\\"sql2\\\", filter); // shared same filter\\n\\n List<String> entry1 = new ArrayList<>();\\n entry1.add(\\\"001\\\");\\n entry1.add(\\\"aaa\\\");\\n\\n List<String> entry2 = new ArrayList<>();\\n entry2.add(\\\"002\\\");\\n entry2.add(\\\"bbb\\\");\\n\\n List<String> entry3 = new ArrayList<>();\\n entry3.add(\\\"003\\\");\\n entry3.add(\\\"ccc\\\");\\n\\n List<String> entry4 = new ArrayList<>();\\n entry4.add(\\\"004\\\");\\n entry4.add(\\\"ddd\\\");\\n\\n List<List<String>> queryResults1 = new ArrayList<>();\\n queryResults1.add(entry1);\\n queryResults1.add(entry2);\\n queryResults1.add(entry3);\\n queryResults1.add(entry4);\\n\\n List<String> entry5 = new ArrayList<>();\\n entry5.add(\\\"005\\\"); // different\\n entry5.add(\\\"eee\\\");\\n\\n List<String> entry6 = new ArrayList<>();\\n entry6.add(\\\"002\\\"); // same\\n entry6.add(\\\"bbb\\\");\\n\\n List<String> entry7 = new ArrayList<>();\\n entry7.add(\\\"007\\\"); // different\\n entry7.add(\\\"fff\\\");\\n\\n List<String> entry8 = new ArrayList<>();\\n entry8.add(\\\"004\\\"); // same\\n entry8.add(\\\"ddd\\\");\\n\\n List<List<String>> queryResults2 = new ArrayList<>();\\n queryResults2.add(entry5);\\n queryResults2.add(entry6);\\n queryResults2.add(entry7);\\n queryResults2.add(entry8);\\n\\n // given\\n dataset1.populateCache(queryResults1, 200L);\\n dataset2.populateCache(queryResults2, 300L);\\n\\n // when\\n final List<String> result1 = dataset1.getCachedResult();\\n final List<String> result2 = dataset1.getCachedResult();\\n final List<String> result3 = dataset1.getCachedResult();\\n final List<String> result4 = dataset1.getCachedResult();\\n final List<String> result5 = dataset2.getCachedResult();\\n final List<String> result6 = dataset2.getCachedResult();\\n\\n // then\\n assertEquals(\\\"Wrong result 1\\\", entry1, result1); // first datset is as-is\\n assertEquals(\\\"Wrong result 2\\\", entry2, result2); // first datset is as-is\\n assertEquals(\\\"Wrong result 3\\\", entry3, result3); // first datset is as-is\\n assertEquals(\\\"Wrong result 4\\\", entry4, result4); // first datset is as-is\\n assertEquals(\\\"Wrong result 3\\\", entry5, result5); // second datset, not filtered out\\n assertEquals(\\\"Wrong result 3\\\", entry7, result6); // second dataset, entry6 is filtered out\\n\\n // and\\n try {\\n dataset1.getCachedResult();\\n fail(\\\"Expected to run out of data\\\");\\n\\n } catch (IllegalStateException ex) {\\n assertEquals(\\\"Wrong error\\\", \\\"No more data available for dataset: TEST1\\\", ex.getMessage());\\n }\\n\\n try {\\n // entry7 should be filtered out, resulting in no more data\\n dataset2.getCachedResult();\\n fail(\\\"Expected to run out of data\\\");\\n\\n } catch (IllegalStateException ex) {\\n assertEquals(\\\"Wrong error\\\", \\\"No more data available for dataset: TEST2\\\", ex.getMessage());\\n }\\n\\n // and\\n assertEquals(\\\"Wrong cache size\\\", Optional.of(4), dataset1.getMetrics().getCacheSize());\\n assertEquals(\\\"Wrong timing\\\", Optional.of(200L), dataset1.getMetrics().getTimingMilliseconds());\\n assertEquals(\\\"Wrong cache requested\\\", Optional.of(5), dataset1.getMetrics().getCacheRequested());\\n assertEquals(\\\"Wrong filtered out\\\", Optional.empty(), dataset1.getMetrics().getFilteredOut());\\n\\n // and\\n assertEquals(\\\"Wrong cache size\\\", Optional.of(4), dataset2.getMetrics().getCacheSize());\\n assertEquals(\\\"Wrong timing\\\", Optional.of(300L), dataset2.getMetrics().getTimingMilliseconds());\\n assertEquals(\\\"Wrong cache requested\\\", Optional.of(3), dataset2.getMetrics().getCacheRequested());\\n assertEquals(\\\"Wrong filtered out\\\", Optional.of(2), dataset2.getMetrics().getFilteredOut());\\n }\",\n \"public ArrayList<Posting> mergeTwoPostingList(ArrayList<Posting> a, ArrayList<Posting> b) { \\r\\n\\t\\tfor (Posting postingA : a) {\\r\\n\\t\\t\\tint indexInB = b.indexOf(postingA);\\r\\n\\t\\t\\tif (indexInB == -1)\\r\\n\\t\\t\\t\\tb.add(postingA);\\r\\n\\t\\t\\telse\\r\\n\\t\\t\\t\\tb.get(indexInB).increaseTermFrequecyBy(postingA.getTermFrequency());\\r\\n\\t\\t}\\r\\n\\t\\treturn b;\\r\\n\\t}\",\n \"public void searchArea(Connection connection, String city, String state, int zip) throws SQLException {\\n\\n ResultSet rs = null;\\n PreparedStatement pStmt = null;\\n String sql1 = \\\"SELECT hotel_name, branch_id FROM Hotel_Address WHERE city = ?\\\";\\n String sql2 = \\\"SELECT hotel_name, branch_id FROM Hotel_Address WHERE state = ?\\\";\\n String sql3 = \\\"SELECT hotel_name, branch_id FROM Hotel_Address WHERE zip = ?\\\";\\n\\n // City and State combination:\\n if (city != null && state != null){\\n\\n pStmt = connection.prepareStatement(sql1 + \\\" INTERSECT \\\" + sql2);\\n pStmt.clearParameters();\\n\\n setCity(city);\\n pStmt.setString(1, getCity());\\n setState(state);\\n pStmt.setString(2, getState());\\n }\\n\\n // City and ZIP combination:\\n else if (city != null){\\n\\n pStmt = connection.prepareStatement(sql1 + \\\" INTERSECT \\\" + sql3);\\n pStmt.clearParameters();\\n\\n setCity(city);\\n pStmt.setString(1, getCity());\\n setZip(zip);\\n pStmt.setInt(2, getZip());\\n }\\n\\n // State and ZIP combination:\\n else {\\n\\n pStmt = connection.prepareStatement(sql2 + \\\" INTERSECT \\\" + sql3);\\n pStmt.clearParameters();\\n\\n setState(state);\\n pStmt.setString(1, getState());\\n setZip(zip);\\n pStmt.setInt(2, getZip());\\n }\\n\\n try {\\n\\n System.out.println(\\\" Hotels in area:\\\");\\n System.out.println(\\\"+------------------------------------------------------------------------------+\\\");\\n\\n rs = pStmt.executeQuery();\\n String result;\\n\\n while (rs.next()) {\\n\\n System.out.println(rs.getString(1) + \\\" \\\" + rs.getInt(2));\\n }\\n }\\n catch (SQLException e) { throw e; }\\n finally {\\n pStmt.close();\\n if(rs != null) { rs.close(); }\\n }\\n }\",\n \"public ArrayList<ArrayList> union(ArrayList<ArrayList> data, ArrayList<ArrayList> data2)\\n {\\n if(data == null || data2 == null)\\n {\\n return null;\\n }\\n ArrayList<Document> docs = data.get(0);\\n ArrayList<Double> relevance = data.get(1);\\n ArrayList<Integer> occurrence = data.get(2);\\n ArrayList<Integer> popularity = data.get(3);\\n \\n ArrayList<Document> docs2 = data2.get(0);\\n ArrayList<Double> relevance2 = data2.get(1);\\n ArrayList<Integer> occurrence2 = data2.get(2);\\n ArrayList<Integer> popularity2 = data2.get(3);\\n \\n ArrayList<Document> docs3 = new ArrayList<>();\\n ArrayList<Double> relevance3 = new ArrayList<>();\\n ArrayList<Integer> occurrence3 = new ArrayList<>();\\n ArrayList<Integer> popularity3 = new ArrayList<>();\\n \\n for(int i = 0; i < docs.size(); i++)\\n {\\n docs3.add(docs.get(i));\\n relevance3.add(relevance.get(i));\\n occurrence3.add(occurrence.get(i));\\n popularity3.add(popularity.get(i));\\n }\\n \\n for(Document d: docs2)\\n {\\n if(!docs3.contains(d))\\n {\\n docs3.add(d);\\n int docIndex = docs2.indexOf(d);\\n relevance3.add(relevance2.get(docIndex));\\n occurrence3.add(occurrence2.get(docIndex));\\n popularity3.add(d.popularity);\\n }\\n else\\n {\\n int docIndex = docs3.indexOf(d);\\n int docIndex2 = docs2.indexOf(d);\\n double oldRel = (double) relevance3.get(docIndex);\\n int oldOcc = (int) occurrence3.get(docIndex);\\n relevance3.set(docIndex, oldRel+relevance2.get(docIndex2));\\n if(oldOcc > occurrence2.get(docIndex2))\\n {\\n occurrence3.set(docIndex, occurrence2.get(docIndex2));\\n }\\n } \\n }\\n ArrayList<ArrayList> data3 = new ArrayList();\\n data3.add(docs3);\\n data3.add(relevance3);\\n data3.add(occurrence3);\\n data3.add(popularity3);\\n return data3; \\n }\",\n \"private Set<String> getIntersection( Set<String> a, Set<String> b ) {\\n\\t\\tSet<String> intersection = new HashSet<String>(a);\\n\\t\\tintersection.retainAll(b);\\n\\t\\treturn intersection;\\n\\t}\",\n \"@Override\\n\\tpublic IPredicate intersection(final IPredicate state1, final IPredicate state2) {\\n\\n\\t\\tfinal Set<HcPredicateSymbol> state1PredSymbols = new HashSet<>();\\n\\t\\tstate1PredSymbols.addAll(((HCPredicate) state1).getHcPredicateSymbols());\\n//\\t\\tassert state1PredSymbols.size() == 1 : \\\"what does this mean??\\\";\\n\\n//\\t\\tfinal Term conjoinedFormula = mSimplifier.getSimplifiedTerm(\\n//\\t\\t\\t\\tSmtUtils.and(mBackendSmtSolverScript.getScript(), state1.getFormula(), state2.getFormula()));\\n\\t\\tfinal IPredicate conjoinedPred = mPredicateFactory.and(state1, state2);\\n\\n\\t\\tif (mPredicateFactory.isDontCare(conjoinedPred)) {\\n\\t\\t\\treturn mPredicateFactory.newPredicate(state1PredSymbols, conjoinedPred.getFormula(),\\n\\t\\t\\t\\tCollections.emptyList());\\n//\\t\\t\\treturn conjoinedPred;\\n\\t\\t}\\n\\n\\t\\tfinal Term conjoinedFormula = new CommuhashNormalForm(mServices, mMgdScript.getScript())\\n\\t\\t\\t\\t.transform(conjoinedPred.getFormula());\\n\\n//\\t\\tfinal Set<IPredicate> ps = new HashSet<>();\\n//\\t\\tps.add(state1);\\n//\\t\\tps.add(state2);\\n\\n\\t\\treturn mPredicateFactory.newPredicate(state1PredSymbols, conjoinedFormula,\\n\\t\\t\\t\\tArrays.asList(state1.getFormula().getFreeVars()));\\n\\t}\",\n \"ResponseEntity<Response> placesInCommon(String userId1, String listName1, String userId2, String listName2);\",\n \"public static <T extends Comparable<? super T>>\\n void intersection(SLL<T> list1, SLL<T> list2, SLL<T> result) {\\n\\n SLLNode<T> iterlist1 = list1.head;\\n SLLNode<T> iterlist2 = list2.head;\\n\\n T itemlist1=null, itemlist2=null;\\n\\n // get first item in each list\\n if ( iterlist1 != null && iterlist2 != null ) {\\n itemlist1 = iterlist1.info;\\n itemlist2 = iterlist2.info;\\n }\\n\\n while ( itemlist1 != null && itemlist2 != null ) {\\n int compareResult = itemlist1.compareTo(itemlist2);\\n \\n if ( compareResult == 0 ) {\\n result.addToTail(itemlist1); //append to result list\\n if( iterlist1.next != null ) {\\n iterlist1 = iterlist1.next;\\n itemlist1 = iterlist1.info;\\n } else {\\n itemlist1 = null;\\n }\\n \\n if( iterlist2.next != null ) {\\n iterlist2 = iterlist2.next;\\n itemlist2 = iterlist2.info;\\n } else {\\n itemlist2 = null;\\n } \\n }\\n else if ( compareResult < 0 ) { \\n if( iterlist1.next != null ) {\\n iterlist1 = iterlist1.next;\\n itemlist1 = iterlist1.info;\\n } else {\\n itemlist1 = null;\\n }\\n }\\n else {\\n if( iterlist2.next != null ) {\\n iterlist2 = iterlist2.next;\\n itemlist2 = iterlist2.info;\\n } else {\\n itemlist2 = null;\\n }\\n }\\n }\\n }\",\n \"private static Set<Item> multiSetIntersection(List<Set<Item>> setList) {\\n Set<Item> interQrels = new HashSet<>(setList.get(0));\\r\\n \\r\\n for (int i = 1; i< setList.size();i++) {\\r\\n interQrels.retainAll(setList.get(i)); // intersection with two (and one)\\r\\n }\\r\\n\\r\\n return interQrels;\\r\\n }\",\n \"private <T> ArrayList<T> intersection(ArrayList<T> list1, ArrayList<T> list2) {\\n ArrayList<T> list = new ArrayList<T>();\\n\\n for (T t : list1) {\\n if (list2.contains(t)) {\\n list.add(t);\\n }\\n }\\n\\n return list;\\n }\",\n \"@SuppressWarnings({ \\\"rawtypes\\\", \\\"unchecked\\\" })\\n\\tprivate static List<Object> mergeResult(List<Object> list1, List<Object> list2) {\\n\\t\\tList<Object> result = new ArrayList<Object>();\\n\\t\\tfor (int i = 0; i < list1.size(); i++) {\\n\\t\\t\\tfor (int j = 0; j < list2.size(); j++) {\\n\\t\\t\\t\\tif (Integer.parseInt(((Map) list1.get(i)).get(MongoDBConstants.DOCUMENT_ID).toString()) == Integer\\n\\t\\t\\t\\t\\t\\t.parseInt(((Map) list2.get(j)).get(MongoDBConstants.DOCUMENT_ID).toString())) {\\n\\t\\t\\t\\t\\tMap data = new HashMap();\\n\\t\\t\\t\\t\\tint hour = (Integer.parseInt(((Map) list1.get(i)).get(MongoDBConstants.DOCUMENT_ID).toString()) + 8) % 24;\\n\\t\\t\\t\\t\\tdata.put(MongoDBConstants.DOCUMENT_ID, hour + \\\"\\\");\\n\\t\\t\\t\\t\\tdata.put(\\\"value\\\", Integer.parseInt(((Map) list1.get(i)).get(\\\"value\\\").toString())\\n\\t\\t\\t\\t\\t\\t\\t+ Integer.parseInt(((Map) list2.get(j)).get(\\\"value\\\").toString()));\\n\\t\\t\\t\\t\\tresult.add(data);\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\treturn result;\\n\\t}\",\n \"@Override\\n public void processElement(ProcessContext c) {\\n List<LdVariant> queryList = null;\\n List<LdVariant> targetList = null;\\n int inputListCount = 0;\\n for (KV<Boolean, List<LdVariant>> vl : c.element().getValue()) {\\n if (vl.getKey()) {\\n queryList = vl.getValue();\\n } else {\\n targetList = vl.getValue();\\n }\\n inputListCount++;\\n }\\n\\n if (inputListCount != 2 || queryList == null || targetList == null) {\\n throw new IllegalArgumentException(\\\"There should be exactly two lists.\\\");\\n }\\n\\n Iterator<LdVariant> targetIter = targetList.iterator();\\n\\n // Our working set of variants from the target shard that could be within window of variants\\n // read in from the query shard.\\n LinkedList<LdVariant> storedTarget = new LinkedList<>();\\n\\n for (LdVariant queryVar : queryList) {\\n // Fill in storedTarget until we are past window from queryVar.\\n while (targetIter.hasNext()\\n && (storedTarget.isEmpty() || (queryVar.getInfo().getEnd() + window) > storedTarget\\n .getLast().getInfo().getStart())) {\\n storedTarget.add(targetIter.next());\\n }\\n\\n ListIterator<LdVariant> storedTargetIter = storedTarget.listIterator(0);\\n while (storedTargetIter.hasNext()) {\\n LdVariant targetVar = storedTargetIter.next();\\n\\n if (queryVar.getInfo().compareTo(targetVar.getInfo()) != -1) {\\n // Only do comparisons where query is before target. If query is past target then\\n // we are done with target. Note: targetVar > queryVar implies targetVar start >= queryVar\\n // start.\\n storedTargetIter.remove();\\n } else if (targetVar.getInfo().getStart() >= (queryVar.getInfo().getEnd() + window)) {\\n // If the next query starts more than window from when target starts, we are done\\n // with the rest of storedTarget for this query.\\n break;\\n } else {\\n // If target starts >= query starts and target starts < window from query end, then they\\n // must overlap.\\n c.output(KV.of(queryVar, targetVar));\\n }\\n }\\n }\\n }\",\n \"@Test\\n public void testSqlExistsBasedJoin() {\\n Query<Car> carsQuery = and(\\n in(Car.FEATURES, \\\"sunroof\\\", \\\"convertible\\\"),\\n existsIn(garages,\\n Car.NAME,\\n Garage.BRANDS_SERVICED,\\n equal(Garage.LOCATION, \\\"Dublin\\\")\\n )\\n );\\n\\n Map<Car, Set<Garage>> results = new LinkedHashMap<Car, Set<Garage>>();\\n for (Car car : cars.retrieve(carsQuery)) {\\n Query<Garage> garagesWhichServiceThisCarInDublin\\n = and(equal(Garage.BRANDS_SERVICED, car.name), equal(Garage.LOCATION, \\\"Dublin\\\"));\\n for (Garage garage : garages.retrieve(garagesWhichServiceThisCarInDublin)) {\\n Set<Garage> garagesWhichCanServiceThisCar = results.get(car);\\n if (garagesWhichCanServiceThisCar == null) {\\n garagesWhichCanServiceThisCar = new LinkedHashSet<Garage>();\\n results.put(car, garagesWhichCanServiceThisCar);\\n }\\n garagesWhichCanServiceThisCar.add(garage);\\n }\\n }\\n\\n assertEquals(\\\"join results should contain 2 cars\\\", 2, results.size());\\n Assert.assertTrue(\\\"join results should contain car1\\\", results.containsKey(car1));\\n Assert.assertTrue(\\\"join results should contain car4\\\", results.containsKey(car4));\\n\\n assertEquals(\\\"join results for car1\\\", asSet(garage3, garage4), results.get(car1));\\n assertEquals(\\\"join results for car4\\\", asSet(garage2), results.get(car4));\\n }\",\n \"public static void main(String[] args) {\\n String[] data ={\\\"cars\\\",\\\"clothes\\\",\\\"jewelry\\\",\\\"women\\\"};\\r\\n List<String> list1 = Arrays.asList(data);\\r\\n \\r\\n ArrayList<String> list2 = new ArrayList<String>();\\r\\n list2.add(\\\"youtube\\\");\\r\\n list2.add(\\\"snapchat\\\");\\r\\n list2.add(\\\"instagram\\\");\\r\\n \\r\\n for(String x : list2)\\r\\n System.out.printf(\\\"%s \\\", x);\\r\\n \\r\\n Collections.addAll(list2, data);\\r\\n \\r\\n System.out.println();\\r\\n for(String x : list2)\\r\\n System.out.printf(\\\"%s \\\", x);\\r\\n System.out.println();\\r\\n \\r\\n System.out.println(Collections.frequency(list2, \\\"cars\\\"));\\r\\n \\r\\n boolean tof = Collections.disjoint(list1, list2);\\r\\n System.out.println(tof);\\r\\n \\r\\n if(tof)\\r\\n System.out.println(\\\"these list do not have anything in common\\\");\\r\\n else \\r\\n System.out.println(\\\"these list do have something in common!\\\");\\r\\n \\r\\n }\",\n \"public static void main(String[] args) {\\n\\t\\tint[] nums1 = {4,9,5};\\r\\n\\t\\tint[] nums2 = {9,4,9,8,4};\\r\\n\\t\\t//System.out.println(intersection(nums1, nums2));\\r\\n\\t\\tArrays.sort(nums1);\\r\\n\\t\\tArrays.sort(nums2);\\r\\n\\t\\tif (nums1.length>nums2.length) {\\r\\n\\t\\t\\tint[] temp = nums2;\\r\\n\\t\\t\\tnums2 = nums1;\\r\\n\\t\\t\\tnums1 = temp;\\r\\n\\t\\t}\\r\\n\\t\\tHashSet<Integer> mSet1 = new HashSet<Integer>();\\r\\n\\t\\tHashSet<Integer> mSet2 = new HashSet<Integer>();\\r\\n\\t\\tfor (Integer i : nums2) {\\r\\n\\t\\t\\tmSet1.add(i);\\r\\n\\t\\t}\\r\\n\\t\\tfor (Integer x: nums1) {\\r\\n\\t\\t\\tif (mSet1.contains(x)) {\\r\\n\\t\\t\\t\\tmSet2.add(x);\\r\\n\\t\\t\\t}\\r\\n\\t\\t}\\r\\n\\t\\tint[] r = new int[mSet2.size()];\\r\\n\\t\\tint index = 0;\\r\\n\\t\\tfor (Integer g: mSet2) {\\r\\n\\t\\t\\tr[index] = g;\\r\\n\\t\\t\\tindex++;\\r\\n\\t\\t}\\r\\n\\t}\",\n \"public PostingsList search( Query query, int queryType, int rankingType,\\n int structureType ) {\\n double idf_threshold = new Double(0);\\n double index_elimination = new Double(0.008);\\n // System.err.println(pageRank[docNumber.get(\\\"121\\\")]);\\n\\n if (query.size()>0){\\n switch (queryType){\\n case Index.INTERSECTION_QUERY:\\n System.err.println(\\\"Intersection query\\\");\\n return intersect(query);\\n case Index.PHRASE_QUERY:\\n System.err.println(\\\"Phrase query\\\");\\n return phrase_query(query);\\n case Index.RANKED_QUERY:\\n System.err.println(\\\"Ranked query\\\");\\n switch(rankingType){\\n case Index.TF_IDF: return ranked_query(query, 1, idf_threshold);\\n case Index.PAGERANK: return ranked_query(query, 0, idf_threshold);//ranked_query(query, 0, idf_threshold);//ranked_query2(query, 0);\\n case Index.COMBINATION: return ranked_query(query, index_elimination, idf_threshold);\\n }\\n default:\\n System.out.println(\\\"not valid query\\\");\\n return null;\\n }\\n }\\n else\\n // Query was empty\\n return null;\\n }\",\n \"public static void main(String[] args) {\\n\\n\\t\\tCollection<String> collection1 = new ArrayList<String>();\\n\\t\\tcollection1.add(\\\"Toronto\\\");\\n\\t\\tcollection1.add(\\\"Hamilton\\\");\\n\\t\\tcollection1.add(\\\"London\\\");\\n\\t\\tcollection1.add(\\\"Ottawa\\\");\\n\\t\\tcollection1.add(\\\"Toronto\\\");\\n\\t\\tSystem.out.println(\\\"A list of cities in c1 is \\\" + collection1);\\n\\t\\tSystem.out.println(\\\" Is hamilton in c1? \\\" + collection1.contains(\\\"Hamilton\\\"));\\n\\t\\tSystem.out.println(\\\"Size of collection c1 is \\\" + collection1.size());\\n\\t\\tCollection<String> collection2 = new ArrayList<String>();\\n\\t\\tcollection1.add(\\\"Vancouver\\\");\\n\\t\\tcollection1.add(\\\"Delhi\\\");\\n\\t\\tcollection1.add(\\\"chd\\\");\\n\\t\\tcollection1.add(\\\"Toronto\\\");\\n\\t\\tcollection1.addAll(collection2);\\n\\t\\tSystem.out.println(\\\"combined list is : \\\" + collection1);\\n//\\t\\tCollection<String> c1 = new ArrayList<String>(collection1);\\n//\\t\\tc1.retainAll(collection2);\\n//\\t\\tSystem.out.println(\\\"A list of cities in c1 is \\\" + c1);\\n//\\t\\tc1.removeAll(collection2);\\n//\\t\\tSystem.out.println(\\\"A list of cities in c1 is \\\" + c1);\\n\\t\\t\\n\\t}\",\n \"@Override\\n public List<Auction> meetCriteria(List<Auction> auctions) \\n {\\n List<Auction> firstCriteriaItems = criteria1.meetCriteria(auctions);\\n List<Auction> otherCriteriaItems = criteria2.meetCriteria(auctions);\\n // if an item b is in Collection B but is not in Collection A,\\n // add item b to collection A. This yields unique elements b and a\\n // in the new collection C.\\n for (Auction auction : otherCriteriaItems) \\n {\\n if(!firstCriteriaItems.contains(auction))\\n {\\n firstCriteriaItems.add(auction);\\n }\\n }\\t\\n return firstCriteriaItems;\\n }\",\n \"private static boolean intersect(\\n\\t\\tDateTime start1, DateTime end1,\\n\\t\\tDateTime start2, DateTime end2)\\n\\t{\\n\\t\\tif (DateTime.op_LessThanOrEqual(end2, start1) || DateTime.op_LessThanOrEqual(end1, start2))\\n\\t\\t\\treturn false;\\n\\n\\t\\treturn true;\\n\\t}\",\n \"abstract protected Object joinClause(Object o1, Object o2);\",\n \"public static Set<Doc> and(Set<Doc> set1, Set<Doc> set2) {\\r\\n \\t\\t\\r\\n \\t\\tif((set1 == null) || (set2 == null)) {\\r\\n\\t\\t\\tSystem.err.println(\\\"Doc.and() returning null!\\\");\\r\\n \\t\\t\\treturn new TreeSet<Doc>();\\r\\n \\t\\t}\\r\\n \\t\\t//set1.retainAll(set2);\\r\\n \\t\\t//return set1;\\r\\n \\t\\t\\r\\n \\t\\tTreeSet<Doc> result = new TreeSet<Doc>();\\r\\n \\t\\tIterator<Doc> op1 = set1.iterator();\\r\\n \\t\\tIterator<Doc> op2 = set2.iterator();\\r\\n \\t\\t\\r\\n \\t\\tDoc current1 = getNext(op1);\\r\\n \\t\\tDoc current2 = getNext(op2);\\r\\n \\r\\n \\t\\twhile(current1!=null && current2!=null) {\\r\\n \\t\\t\\t//If is the same document\\r\\n \\t\\t\\tif(current1.getID() == current2.getID()) {\\r\\n \\t\\t\\t\\tresult.add(current1);\\r\\n \\t\\t\\t\\tcurrent1 = getNext(op1);\\r\\n \\t\\t\\t\\tcurrent2 = getNext(op2);\\r\\n \\t\\t\\t}\\r\\n \\t\\t\\t//If op2 is ahead of op1\\r\\n \\t\\t\\telse if(current1.getID() < current2.getID()) \\r\\n \\t\\t\\t\\tcurrent1 = getNext(op1);\\r\\n \\t\\t\\t//If op1 is ahead of op2\\r\\n \\t\\t\\telse\\r\\n \\t\\t\\t\\tcurrent2 = getNext(op2);\\r\\n \\t\\t}\\r\\n \\t\\t\\r\\n \\t\\treturn result;\\r\\n \\t}\",\n \"@Override\\n protected DataSet<GraphHead> computeNewGraphHeads() {\\n return firstCollection.getGraphHeads()\\n .union(secondCollection.getGraphHeads())\\n .groupBy(new Id<GraphHead>())\\n .reduceGroup(new GroupCountEquals<GraphHead>(2));\\n }\",\n \"public static void main(String[] args) {\\n\\t\\tIntersection l5=new Intersection(5,null);\\n\\t\\tIntersection l4=new Intersection(4,l5);\\n\\t\\tIntersection l3=new Intersection(3,l4);\\n\\t\\tIntersection l2=new Intersection(2,l3);\\n\\t\\tIntersection l1=new Intersection(1,l2);\\n\\t\\t\\n\\t\\tIntersection m7=new Intersection(7,l3);\\n\\t\\tIntersection m6=new Intersection(6,m7);\\n\\t\\tint flag=0;\\n\\t\\twhile(m6!=null && l1!=null){\\n\\t\\t\\tif(m6!=l1){\\n\\t\\t\\t\\tm6=m6.next;\\n\\t\\t\\t\\tl1=l1.next;\\n\\t\\t\\t}\\n\\t\\t\\telse{\\n\\t\\t\\t\\tflag=1;\\n\\t\\t\\t\\tbreak;\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\tif(flag==1){\\n\\t\\t\\tSystem.out.println(\\\"They Intersect!\\\");\\n\\t\\t}\\n\\t\\telse{\\n\\t\\t\\tSystem.out.println(\\\"They don't!\\\");\\n\\t\\t}\\n\\t}\",\n \"public static void main(String[] args) {\\n\\t\\tLL l1 = new LL();\\n\\t\\tLL l2 = new LL();\\n\\t\\tl1.insert(15);\\n\\t\\tl1.insert(25);\\n\\t\\tl1.insert(35);\\n\\t\\tl1.insert(45);\\n\\t\\tl1.insert(55);\\n\\t\\t\\n\\t\\tl2.insert(10);\\n\\t\\tl2.insert(17);\\n\\t\\tl2.insert(35);\\n\\t\\tl2.insert(47);\\n\\t\\tl2.insert(11);\\n\\t \\t\\n\\t\\t\\n//\\t\\tl1.print();\\n//\\t\\tl2.print();\\n\\t\\t\\n\\t\\tSystem.out.println(getIntersection(l1.head,l2.head));\\n\\t\\t\\n\\t}\",\n \"public void testUsingQueriesFromQueryManger(){\\n\\t\\tSet<String> names = testDataMap.keySet();\\n\\t\\tUtils.prtObMess(this.getClass(), \\\"atm query\\\");\\n\\t\\tDseInputQuery<BigDecimal> atmq = \\n\\t\\t\\t\\tqm.getQuery(new AtmDiot());\\n\\t\\tMap<String, ComplexQueryResult<BigDecimal>> bdResult = \\n\\t\\t\\t\\tatmq.get(names, 1, TimeUnit.SECONDS);\\n\\t\\tCollectionsStaticMethods.prtMapItems(bdResult);\\n\\n\\t\\tUtils.prtObMess(this.getClass(), \\\"vol query\\\");\\n\\t\\tDseInputQuery<BigDecimal> volq = \\n\\t\\t\\t\\tqm.getQuery(new VolDiotForTest());\\n\\t\\tMap<String, ComplexQueryResult<BigDecimal>> dbResult = \\n\\t\\t\\t\\tvolq.get(names, 1, TimeUnit.SECONDS);\\n\\t\\tCollectionsStaticMethods.prtMapItems(dbResult);\\n\\t\\n\\t\\tUtils.prtObMess(this.getClass(), \\\"integer query\\\");\\n\\t\\tDseInputQuery<BigDecimal> strikeq = \\n\\t\\t\\t\\tqm.getQuery(new StrikeDiotForTest());\\n\\t\\tMap<String, ComplexQueryResult<BigDecimal>> strikeResult = \\n\\t\\t\\t\\tstrikeq.get(names, 1, TimeUnit.SECONDS);\\n\\t\\tCollectionsStaticMethods.prtMapItems(strikeResult);\\n\\t\\n\\t}\",\n \"public ArrayList<Object> intersect(ArrayList<Object> list1, ArrayList<Object> list2)\\r\\n {\\r\\n ArrayList<Object> retList = new ArrayList<Object>();\\r\\n for(Object o : list1)\\r\\n if(list2.contains(o))\\r\\n retList.add(o);\\r\\n return retList;\\r\\n }\",\n \"private void twoDateOccupancyQuery(String startDate, String endDate){\\n List<String> emptyRooms = findEmptyRoomsInRange(startDate, endDate);\\n List<String> fullyOccupiedRooms = findOccupiedRoomsInRange(startDate, endDate, emptyRooms);\\n List<String> partiallyOccupiedRooms = \\n (generateListOfAllRoomIDS().removeAll(emptyRooms)).removeAll(fullyOccupiedRooms);\\n\\n occupancyColumns = new Vector<String>();\\n occupancyData = new Vector<Vector<String>>();\\n occupancyColumns.addElement(\\\"RoomId\\\");\\n occupancyColumns.addElement(\\\"Occupancy Status\\\");\\n\\n for(String room: emptyRooms) {\\n Vector<String> row = new Vector<String>();\\n row.addElement(room);\\n row.addElement(\\\"Empty\\\");\\n occupancyData.addElement(row);\\n }\\n for(String room: fullyOccupiedRooms) {\\n Vector<String> row = new Vector<String>();\\n row.addElement(room);\\n row.addElement(\\\"Fully Occupied\\\");\\n occupancyData.addElement(row);\\n }\\n for(String room: partiallyOccupiedRooms) {\\n Vector<String> row = new Vector<String>();\\n row.addElement(room);\\n row.addElement(\\\"Partially Occupied\\\");\\n occupancyData.addElement(row);\\n }\\n return;\\n}\",\n \"public static void main(String[] args) {\\n List<Integer> list1 = new ArrayList<>();\\n List<Integer> list2 = new ArrayList<>();\\n list1.add(2);\\n list1.add(3);\\n list1.add(4);\\n list2.add(1);\\n list2.add(5);\\n list2.add(6);\\n merge(list1, list2).forEach(item -> System.out.print(item + \\\" \\\"));\\n }\",\n \"private boolean isIntersect(List<Tuple> list1, List<Tuple> list2) {\\n\\t\\tboolean intersect = false;\\n\\t\\tfor (Tuple tuple : list1) {\\n\\t\\t\\tif (list2.contains(tuple)) {\\n\\t\\t\\t\\tintersect = true;\\n\\t\\t\\t\\tbreak;\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\treturn intersect;\\n\\t}\",\n \"@Test\\n public void test1() {\\n final List<String> listA = Arrays.asList(\\\"Fremont\\\", \\\"Dublin\\\", \\\"anamole\\\", \\\"San Jose\\\" , \\\"SFO\\\", \\\"Dublin\\\", \\\"San Jose\\\", \\\"paramount\\\", \\\"y\\\");\\n final List<String> listB = Arrays.asList(\\\"Dublin\\\", \\\"san mateo\\\", \\\"los angeles\\\", \\\"san mateo\\\", \\\"fremont\\\", \\\"anamole\\\", \\\"x\\\", \\\"x\\\", \\\"Y\\\");\\n final List<String> common = FindIntersection.findCommonLists(listA, listB);\\n System.out.println(Arrays.toString(FindIntersection.findCommonLists(listA, listB).toArray()));\\n\\n }\",\n \"boolean overlap(Reservation other);\",\n \"@Test\\n\\tpublic void integrationTest2() throws Exception {\\n\\t\\tHashSet<String> mistress = loadGrepResults(\\\"mistress\\\");\\n\\t\\tHashSet<String> undocumented = loadGrepResults(\\\"undocumented\\\");\\n\\t\\tHashSet<String> insane = loadGrepResults(\\\"insane\\\");\\n\\t\\tHashSet<String> crazy = loadGrepResults(\\\"crazy\\\");\\n\\t\\tHashSet<String> forced = loadGrepResults(\\\"!i+am+forced\\\");\\n\\t\\t\\n\\t\\tHashSet<String> grepFound = new HashSet<String>(mistress);\\n\\t\\tgrepFound.retainAll(undocumented);\\n\\t\\tHashSet<String> temp = new HashSet<String>(crazy);\\n\\t\\ttemp.retainAll(forced);\\n\\t\\tgrepFound.addAll(temp);\\n\\t\\tgrepFound.addAll(insane);\\n\\t\\t\\n\\t\\tCollection<Page> index = queryTest.query(\\\"insane | crazy & !\\\\\\\"I am forced\\\\\\\" | mistress & undocumented\\\");\\n\\t\\tHashSet<String> indexFound = new HashSet<String>();\\n\\n\\t\\tfor (Page p : index)\\n\\t\\t\\tindexFound.add(p.getURL().getPath().toLowerCase());\\n\\t\\t\\n\\t\\tassertEquals(indexFound, grepFound);\\n\\t}\",\n \"public ArrayList<Integer> intersect(final List<Integer> a, final List<Integer> b) {\\n\\t ArrayList<Integer> res = new ArrayList<>();\\n\\t \\n\\t int i1 = 0, i2 = 0;\\n\\t while (i1 < a.size() && i2 < b.size()) {\\n\\t //System.out.println(i1 + \\\" \\\" + i2 + \\\" \\\" + a.get(i1) + \\\" \\\" + b.get(i2));\\n\\t if (a.get(i1).equals(b.get(i2))) {\\n\\t res.add(a.get(i1));\\n\\t i1++;\\n\\t i2++;\\n\\t } else if (a.get(i1) < b.get(i2)) {\\n\\t i1++;\\n\\t } else if (a.get(i1) > b.get(i2)) {\\n\\t i2++;\\n\\t }\\n\\t }\\n\\t \\n\\t return res;\\n\\t}\",\n \"void findMatchings(boolean isProtein) {\\n\\n GraphDatabaseFactory dbFactory = new GraphDatabaseFactory();\\n HashSet<String > searchSpaceList = new HashSet<>();\\n GraphDatabaseService databaseService = dbFactory.newEmbeddedDatabase(graphFile);\\n for (int id: queryGraphNodes.keySet()) {\\n if(isProtein)\\n searchSpaceList.add(queryGraphNodes.get(id).label);\\n else\\n searchSpaceList.add(String.valueOf(queryGraphNodes.get(id).labels.get(0)));\\n }\\n for(String x: searchSpaceList) {\\n ResourceIterator<Node> xNodes;\\n try(Transaction tx = databaseService.beginTx()) {\\n xNodes = databaseService.findNodes(Label.label(x));\\n tx.success();\\n }\\n\\n while (xNodes.hasNext()) {\\n Node node = xNodes.next();\\n if (searchSpaceProtein.containsKey(x))\\n searchSpaceProtein.get(x).add(node.getId());\\n else {\\n HashSet<Long> set = new HashSet<>();\\n set.add(node.getId());\\n searchSpaceProtein.put(x, set);\\n }\\n }\\n\\n }\\n\\n if(isProtein)\\n search(0, databaseService, true);\\n else\\n search(0, databaseService, false);\\n databaseService.shutdown();\\n }\",\n \"protected boolean query() {\\r\\n\\t\\tqueryStr = new String(processQueryTitle(queryBk.getTitle()) + processQueryAuthor(queryBk.getCreator())\\r\\n\\t\\t\\t\\t+ processQueryPublisher(queryBk.getPublisher()));\\r\\n\\t\\tSystem.out.println(queryStr);\\r\\n\\t\\t// if edition is 'lastest' (coded '0'), no query is performed; and\\r\\n\\t\\t// return false.\\r\\n\\t\\tif (queryBk.parseEdition() == 0) {\\r\\n\\t\\t\\treturn false;\\r\\n\\t\\t} // end if\\r\\n\\r\\n\\t\\t/*\\r\\n\\t\\t * The following section adds edition info to the query string if edition no. is\\r\\n\\t\\t * greater than one. By cataloging practice, for the first edition, probably\\r\\n\\t\\t * there is NO input on the associated MARC field. Considering this, edition\\r\\n\\t\\t * query string to Primo is NOT added if querying for the first edition or no\\r\\n\\t\\t * edition is specified.\\r\\n\\t\\t */\\r\\n\\t\\tif (queryBk.parseEdition() > 1) {\\r\\n\\t\\t\\tqueryStr += processQueryEdition(queryBk.parseEdition());\\r\\n\\t\\t} // end if\\r\\n\\r\\n\\t\\t/*\\r\\n\\t\\t * Querying the Primo X-service; and invoking the matching processes (all done\\r\\n\\t\\t * by remoteQuery()).\\r\\n\\t\\t */\\r\\n\\t\\tif (strHandle.hasSomething(queryBk.getPublisher())) {\\r\\n\\t\\t\\tif (remoteQuery(queryStr)) {\\r\\n\\t\\t\\t\\tmatch = true;\\r\\n\\t\\t\\t\\tsetBookInfo();\\r\\n\\t\\t\\t\\tcheckAVA(queryBk.parseVolume());\\r\\n\\t\\t\\t\\treturn true;\\r\\n\\t\\t\\t} else {\\r\\n\\t\\t\\t\\tmatch = false;\\r\\n\\t\\t\\t} // end if\\r\\n\\t\\t} // end if\\r\\n\\r\\n\\t\\t/*\\r\\n\\t\\t * For various reasons, there are possibilities that the first query fails while\\r\\n\\t\\t * a match should be found. The follow work as remedy queries to ensure the\\r\\n\\t\\t * accuracy.\\r\\n\\t\\t */\\r\\n\\r\\n\\t\\tif (!match && strHandle.hasSomething(queryBk.getPublisher())) {\\r\\n\\t\\t\\tqueryStr = new String(\\r\\n\\t\\t\\t\\t\\tprocessQueryPublisher(queryBk.getPublisher()) + processQueryAuthor(queryBk.getCreator()));\\r\\n\\t\\t\\tif (remoteQuery(queryStr)) {\\r\\n\\t\\t\\t\\tmatch = true;\\r\\n\\t\\t\\t\\tsetBookInfo();\\r\\n\\t\\t\\t\\tcheckAVA(queryBk.parseVolume());\\r\\n\\t\\t\\t\\treturn true;\\r\\n\\t\\t\\t} else {\\r\\n\\t\\t\\t\\tmatch = false;\\r\\n\\t\\t\\t} // end if\\r\\n\\t\\t} // end if\\r\\n\\r\\n\\t\\tif (!match) {\\r\\n\\t\\t\\tqueryStr = new String(processQueryTitle(queryBk.getTitle()) + processQueryAuthor(queryBk.getCreator()));\\r\\n\\t\\t\\tif (remoteQuery(queryStr)) {\\r\\n\\t\\t\\t\\tmatch = true;\\r\\n\\t\\t\\t\\tsetBookInfo();\\r\\n\\t\\t\\t\\tcheckAVA(queryBk.parseVolume());\\r\\n\\t\\t\\t\\treturn true;\\r\\n\\t\\t\\t} else {\\r\\n\\t\\t\\t\\tmatch = false;\\r\\n\\t\\t\\t} // end if\\r\\n\\t\\t} // end if\\r\\n\\r\\n\\t\\tif (!match) {\\r\\n\\t\\t\\tqueryStr = new String(processQueryTitle(queryBk.getTitle()));\\r\\n\\t\\t\\tif (remoteQuery(queryStr)) {\\r\\n\\t\\t\\t\\tmatch = true;\\r\\n\\t\\t\\t\\tsetBookInfo();\\r\\n\\t\\t\\t\\tcheckAVA(queryBk.parseVolume());\\r\\n\\t\\t\\t\\treturn true;\\r\\n\\t\\t\\t} else {\\r\\n\\t\\t\\t\\tmatch = false;\\r\\n\\t\\t\\t} // end if\\r\\n\\t\\t} // end if\\r\\n\\r\\n\\t\\tif (!match && strHandle.hasSomething(queryBk.getPublishYear())) {\\r\\n\\t\\t\\tqueryStr = new String(\\r\\n\\t\\t\\t\\t\\tprocessQueryAuthor(queryBk.getCreator()) + processQueryYear(queryBk.getPublishYear()));\\r\\n\\r\\n\\t\\t\\tif (remoteQuery(queryStr)) {\\r\\n\\t\\t\\t\\tmatch = true;\\r\\n\\t\\t\\t\\tsetBookInfo();\\r\\n\\t\\t\\t\\tcheckAVA(queryBk.parseVolume());\\r\\n\\t\\t\\t\\treturn true;\\r\\n\\t\\t\\t} else {\\r\\n\\t\\t\\t\\tmatch = false;\\r\\n\\t\\t\\t} // end if\\r\\n\\t\\t} // end if\\r\\n\\r\\n\\t\\tif (!match) {\\r\\n\\t\\t\\tqueryStr = new String(\\r\\n\\t\\t\\t\\t\\tprocessQueryAuthor(queryBk.getCreator()) + processQueryTitleShort(queryBk.getTitle()));\\r\\n\\t\\t\\tif (remoteQuery(queryStr)) {\\r\\n\\t\\t\\t\\tmatch = true;\\r\\n\\t\\t\\t\\tsetBookInfo();\\r\\n\\t\\t\\t\\tcheckAVA(queryBk.parseVolume());\\r\\n\\t\\t\\t\\treturn true;\\r\\n\\t\\t\\t} else {\\r\\n\\t\\t\\t\\tmatch = false;\\r\\n\\t\\t\\t} // end if\\r\\n\\t\\t} // end if\\r\\n\\r\\n\\t\\t// Additional query for Chinese titles\\r\\n\\r\\n\\t\\tif (!match && (CJKStringHandling.isCJKString(queryBk.getTitle())\\r\\n\\t\\t\\t\\t|| CJKStringHandling.isCJKString(queryBk.getCreator())\\r\\n\\t\\t\\t\\t|| CJKStringHandling.isCJKString(queryBk.getPublisher()))) {\\r\\n\\r\\n\\t\\t\\tqueryStr = new String(processQueryTitle(queryBk.getTitle()));\\r\\n\\t\\t\\tif (remoteQuery(queryStr)) {\\r\\n\\t\\t\\t\\tmatch = true;\\r\\n\\t\\t\\t\\tsetBookInfo();\\r\\n\\t\\t\\t\\tcheckAVA(queryBk.parseVolume());\\r\\n\\t\\t\\t\\treturn true;\\r\\n\\t\\t\\t} else {\\r\\n\\t\\t\\t\\tmatch = false;\\r\\n\\t\\t\\t} // end if\\r\\n\\r\\n\\t\\t\\tif (!match && queryBk.parseEdition() != -1) {\\r\\n\\t\\t\\t\\tqueryStr = new String(\\r\\n\\t\\t\\t\\t\\t\\tprocessQueryTitle(queryBk.getTitle()) + processQueryEdition2(queryBk.parseEdition()));\\r\\n\\t\\t\\t\\tif (remoteQuery(queryStr)) {\\r\\n\\t\\t\\t\\t\\tmatch = true;\\r\\n\\t\\t\\t\\t\\tsetBookInfo();\\r\\n\\t\\t\\t\\t\\tcheckAVA(queryBk.parseVolume());\\r\\n\\t\\t\\t\\t\\treturn true;\\r\\n\\t\\t\\t\\t} else {\\r\\n\\t\\t\\t\\t\\tmatch = false;\\r\\n\\t\\t\\t\\t} // end if\\r\\n\\r\\n\\t\\t\\t\\tif (!match && queryBk.parseEdition() != -1) {\\r\\n\\t\\t\\t\\t\\tqueryStr = new String(\\r\\n\\t\\t\\t\\t\\t\\t\\tprocessQueryTitle(queryBk.getTitle()) + processQueryEdition3(queryBk.parseEdition()));\\r\\n\\t\\t\\t\\t\\tif (remoteQuery(queryStr)) {\\r\\n\\t\\t\\t\\t\\t\\tmatch = true;\\r\\n\\t\\t\\t\\t\\t\\tsetBookInfo();\\r\\n\\t\\t\\t\\t\\t\\tcheckAVA(queryBk.parseVolume());\\r\\n\\t\\t\\t\\t\\t\\treturn true;\\r\\n\\t\\t\\t\\t\\t} else {\\r\\n\\t\\t\\t\\t\\t\\tmatch = false;\\r\\n\\t\\t\\t\\t\\t} // end if\\r\\n\\t\\t\\t\\t} // end if\\r\\n\\t\\t\\t} // end if\\r\\n\\t\\t} // end if\\r\\n\\r\\n\\t\\t// Additional check for ISO Document number in <search> <genernal> PNX\\r\\n\\t\\t// tag\\r\\n\\t\\tif (!match && !CJKStringHandling.isCJKString(queryBk.getTitle())) {\\r\\n\\t\\t\\tqueryStr = new String(processQueryTitleISODoc(queryBk.getTitle()));\\r\\n\\t\\t\\tif (remoteQuery(queryStr)) {\\r\\n\\t\\t\\t\\tmatch = true;\\r\\n\\t\\t\\t\\tsetBookInfo();\\r\\n\\t\\t\\t\\tcheckAVA(queryBk.parseVolume());\\r\\n\\t\\t\\t\\treturn true;\\r\\n\\t\\t\\t} else {\\r\\n\\t\\t\\t\\tmatch = false;\\r\\n\\t\\t\\t\\terrMsg += \\\"Query: No record found on Primo.\\\" + Config.QUERY_SETTING;\\r\\n\\t\\t\\t} // end if\\r\\n\\t\\t} // end if\\r\\n\\t\\treturn false;\\r\\n\\t}\",\n \"protected <Ty> HashSet<Ty> intersection(HashSet<Ty> setA, HashSet<Ty> setB) {\\n HashSet<Ty> retSet = new HashSet<>();\\n for (Ty t : setA) {\\n if (setB.contains(t)) {\\n retSet.add(t);\\n }\\n }\\n return retSet;\\n }\",\n \"List<ProtocolPo> queryByUnion(ProtocolPo query);\",\n \"protected abstract NativeSQLStatement createNativeIntersectsStatement(Geometry geom);\",\n \"private void queryPosts() {\\n ParseQuery<OutfitPost> query = ParseQuery.getQuery(OutfitPost.class);\\n // only include data referred by user key\\n query.include(OutfitPost.KEY_USER);\\n query.whereEqualTo(OutfitPost.KEY_USER, ParseUser.getCurrentUser());\\n // limit query to latest 20 items\\n query.setLimit(20);\\n // order posts by creation date (newest first)\\n query.addDescendingOrder(OutfitPost.KEY_CREATED_KEY);\\n // start an asynchronous call for posts\\n query.findInBackground(new FindCallback<OutfitPost>() {\\n @Override\\n public void done(List<OutfitPost> posts, ParseException e) {\\n // check for errors\\n if (e != null) {\\n Log.e(TAG, \\\"Issue with getting posts\\\", e);\\n return;\\n }\\n // Save oldest post in query for loading more posts\\n if (posts.size() > 0) {\\n oldestPost = posts.get(posts.size() - 1).getCreatedAt();\\n }\\n // update adapter with posts list\\n adapter.clear();\\n adapter.addAll(posts);\\n }\\n });\\n }\",\n \"public void sensibleMatches1() \\n { \\n Map<String, Set<String>> clientMap = new HashMap<>();\\n Set<String> interests = new HashSet<>();\\n\\n interests.add(\\\"Food\\\");\\n interests.add(\\\"Wine\\\");\\n interests.add(\\\"Tandems\\\");\\n clientMap.put(\\\"Hal\\\", interests);\\n\\t \\n interests = new HashSet<>();\\n interests.add(\\\"Food\\\");\\n interests.add(\\\"Walking\\\");\\n interests.add(\\\"Welding\\\");\\n clientMap.put(\\\"Gemma\\\", interests);\\n\\t \\n interests = new HashSet<>();\\n interests.add(\\\"Food\\\");\\n interests.add(\\\"Cinema\\\");\\n interests.add(\\\"Wine\\\");\\n clientMap.put(\\\"Caroline\\\", interests);\\n\\n Set<String> halsInterests = clientMap.get(\\\"Hal\\\");\\n String outputString;\\n Set<String> eachClientInterests;\\n Set<String> intersection ;\\n\\n Map<String, Set<String>> mapWithoutHal = new HashMap<>(clientMap);\\n mapWithoutHal.remove(\\\"Hal\\\");\\n for (String eachClient : mapWithoutHal.keySet()) \\n {\\n eachClientInterests = clientMap.get(eachClient);\\n intersection = new HashSet<>(halsInterests);\\n intersection.retainAll(eachClientInterests);\\n outputString = \\\"Hal and \\\" + eachClient \\n + \\\" have common interests: \\\"\\n + intersection;\\n System.out.println(outputString);\\n }\\n }\",\n \"public void reflectRelationOnUnionQuery(ConditionQuery bqs, ConditionQuery uqs) {\\n }\",\n \"public void reflectRelationOnUnionQuery(ConditionQuery bqs, ConditionQuery uqs) {\\n }\",\n \"public void reflectRelationOnUnionQuery(ConditionQuery bqs, ConditionQuery uqs) {\\n }\",\n \"public Intersection(ListExpression expr1, ListExpression expr2) {\\n this.expr1 = expr1;\\n this.expr2 = expr2;\\n }\",\n \"@Test\\n public void testIntersection2()\\n {\\n final int[] ints1 = {33, 100000};\\n final int[] ints2 = {34, 100000};\\n List<Integer> expected = Collections.singletonList(100000);\\n\\n ConciseSet set1 = new ConciseSet();\\n for (int i : ints1) {\\n set1.add(i);\\n }\\n ConciseSet set2 = new ConciseSet();\\n for (int i : ints2) {\\n set2.add(i);\\n }\\n\\n verifyIntersection(expected, set1, set2);\\n }\",\n \"public void getIntersection(int[] A, int[] B, ArrayList<int[]> intersections) \\n {\\n if (A[0] >= B[0] && A[0] <= B[1]) \\n {\\n if (A[1] >= B[0] && A[1] <= B[1]) \\n {\\n // Take the entirety of A\\n intersections.add(A);\\n } \\n else \\n {\\n // Take the start of A to end of B\\n int[] intersection = new int[]{A[0], B[1]};\\n intersections.add(intersection);\\n }\\n } \\n else \\n {\\n if (A[1] >= B[0] && A[1] <= B[1]) \\n {\\n // Take start of B to end of A\\n int[] intersection = new int[]{B[0], A[1]};\\n intersections.add(intersection);\\n } \\n else \\n {\\n if (A[0] < B[0] && A[1] > B[1]) \\n {\\n // Take the entirety of B\\n intersections.add(B);\\n } \\n else \\n {\\n // No intersection at all\\n return;\\n }\\n }\\n }\\n }\",\n \"private List<Object[]> executeDayQuery(\\n List<Object> segments, List<Object> workplaces,\\n String Eq1startTime, String Eq1endTime,\\n String Eq2startTime, String Eq2endTime,\\n String Eq3startTime, String Eq3endTime) {\\n try {\\n //Clear all tables\\n //################# Declared Harness Data #################### \\n Helper.startSession();\\n\\n String query_str_1 = \\\"(SELECT 'Matin' as shift,'%s' As start_time, '%s' as end_time, \\\"\\n + \\\"bh.segment AS segment, \\\"\\n + \\\"bh.workplace AS workplace, \\\"\\n + \\\"bh.harness_part AS harness_part, \\\"\\n + \\\"bh.std_time AS std_time, \\\"\\n + \\\"COUNT(bh.harness_part) AS produced_qty, \\\"\\n + \\\"SUM(bh.std_time) AS produced_hours \\\"\\n + \\\"FROM base_harness bh, base_container bc \\\"\\n + \\\"WHERE bc.id = bh.container_id \\\"\\n + \\\"AND bh.create_time BETWEEN '%s' AND '%s' \\\"\\n + \\\"AND bh.segment IN (:segments) \\\"\\n + \\\"AND bh.workplace IN (:workplaces) \\\"\\n + \\\"GROUP BY bh.segment, bh.workplace, bh.harness_part, bh.std_time)\\\";\\n\\n query_str_1 = String.format(query_str_1, Eq1startTime, Eq1endTime, Eq1startTime, Eq1endTime);\\n\\n String query_str_2 = \\\"(SELECT 'Soir' as shift,'%s' As start_time, '%s' as end_time, \\\"\\n + \\\"bh.segment AS segment, \\\"\\n + \\\"bh.workplace AS workplace, \\\"\\n + \\\"bh.harness_part AS harness_part, \\\"\\n + \\\"bh.std_time AS std_time, \\\"\\n + \\\"COUNT(bh.harness_part) AS produced_qty, \\\"\\n + \\\"SUM(bh.std_time) AS produced_hours \\\"\\n + \\\"FROM base_harness bh, base_container bc \\\"\\n + \\\"WHERE bc.id = bh.container_id \\\"\\n + \\\"AND bh.create_time BETWEEN '%s' AND '%s' \\\"\\n + \\\"AND bh.segment IN (:segments) \\\"\\n + \\\"AND bh.workplace IN (:workplaces) \\\"\\n + \\\"GROUP BY bh.segment, bh.workplace, bh.harness_part, bh.std_time)\\\";\\n\\n query_str_2 = String.format(query_str_2, Eq2startTime, Eq2endTime, Eq2startTime, Eq2endTime);\\n\\n String query_str_3 = \\\"(SELECT 'Nuit' as shift,'%s' As start_time, '%s' as end_time, \\\"\\n + \\\"bh.segment AS segment, \\\"\\n + \\\"bh.workplace AS workplace, \\\"\\n + \\\"bh.harness_part AS harness_part, \\\"\\n + \\\"bh.std_time AS std_time, \\\"\\n + \\\"COUNT(bh.harness_part) AS produced_qty, \\\"\\n + \\\"SUM(bh.std_time) AS produced_hours \\\"\\n + \\\"FROM base_harness bh, base_container bc \\\"\\n + \\\"WHERE bc.id = bh.container_id \\\"\\n + \\\"AND bh.create_time BETWEEN '%s' AND '%s' \\\"\\n + \\\"AND bh.segment IN (:segments) \\\"\\n + \\\"AND bh.workplace IN (:workplaces)\\\"\\n + \\\"GROUP BY bh.segment, bh.workplace, bh.harness_part, bh.std_time) \\\";\\n\\n query_str_3 = String.format(query_str_3, Eq3startTime, Eq3endTime, Eq3startTime, Eq3endTime);\\n\\n String query_str = \\\"SELECT * FROM (\\\"\\n + query_str_1 + \\\" UNION \\\"\\n + query_str_2 + \\\" UNION \\\"\\n + query_str_3\\n + \\\") results ORDER BY start_time ASC, segment ASC, workplace ASC, harness_part ASC\\\";\\n\\n SQLQuery query = Helper.sess.createSQLQuery(query_str);\\n\\n query.addScalar(\\\"shift\\\", StandardBasicTypes.STRING)\\n .addScalar(\\\"start_time\\\", StandardBasicTypes.STRING)\\n .addScalar(\\\"end_time\\\", StandardBasicTypes.STRING)\\n .addScalar(\\\"segment\\\", StandardBasicTypes.STRING)\\n .addScalar(\\\"workplace\\\", StandardBasicTypes.STRING)\\n .addScalar(\\\"harness_part\\\", StandardBasicTypes.STRING)\\n .addScalar(\\\"std_time\\\", StandardBasicTypes.DOUBLE)\\n .addScalar(\\\"produced_qty\\\", StandardBasicTypes.INTEGER)\\n .addScalar(\\\"produced_hours\\\", StandardBasicTypes.DOUBLE)\\n .setParameterList(\\\"segments\\\", segments)\\n .setParameterList(\\\"workplaces\\\", workplaces);\\n\\n this.dataResultList = query.list();\\n\\n Helper.sess.getTransaction().commit();\\n\\n return this.dataResultList;\\n\\n } catch (HibernateException e) {\\n if (Helper.sess.getTransaction() != null) {\\n Helper.sess.getTransaction().rollback();\\n }\\n }\\n\\n return this.dataResultList;\\n }\",\n \"public PostingsList phrase_query(Query query){\\n\\n LinkedList<PostingsList> listQueriedPostings = new LinkedList<PostingsList>();\\n // List with postings corresponding to the queries\\n for (int i = 0; i<query.size(); i++){\\n // If any query has zero matches, return 0 results\\n //if(!(new File(\\\"postings/t\\\"+hash(query.terms.get(i))+\\\".json\\\")).exists()){\\n if (!this.index.containsKey(query.terms.get(i))){\\n return null;\\n }\\n // Otherwise store postings in the list\\n listQueriedPostings.add(this.getPostings(query.terms.get(i)));\\n }\\n\\n PostingsList result = new PostingsList();\\n result = listQueriedPostings.get(0);\\n\\n // In case only one word is queried\\n if (listQueriedPostings.size() == 1){\\n return result;\\n }\\n\\n // Apply algorithm as many times as words in the query\\n for(int i = 1; i < listQueriedPostings.size(); i++){\\n result = phrase_query(result, listQueriedPostings.get(i));\\n if (result.isEmpty()){\\n return null;\\n }\\n }\\n return result;\\n }\",\n \"private static boolean availabilityQuery(String roomid, String date1, String date2)\\n {\\n String query = \\\"SELECT status\\\"\\n + \\\" FROM (\\\"\\n + \\\" SELECT DISTINCT ro.RoomId, 'occupied' AS status\\\"\\n + \\\" FROM myReservations re JOIN myRooms ro ON (re.Room = ro.RoomId)\\\"\\n + \\\" WHERE (DATEDIFF(CheckIn, DATE(\\\" + date1 + \\\")) <= 0\\\"\\n + \\\" AND DATEDIFF(CheckOut, DATE(\\\" + date2 + \\\")) > 0)\\\" \\n + \\\" OR (DATEDIFF(CheckIn, DATE(\\\" + date1 + \\\")) > 0\\\" \\n + \\\" AND DATEDIFF(CheckIn, DATE(\\\" + date2 + \\\")) <= 0)\\\" \\n + \\\" OR (DATEDIFF(CheckOut, DATE(\\\" + date1 + \\\")) > 0\\\" \\n + \\\" AND DATEDIFF(CheckOut, DATE(\\\" + date2 + \\\")) < 0)\\\"\\n + \\\" UNION\\\"\\n + \\\" SELECT DISTINCT RoomId, 'empty' AS status\\\"\\n + \\\" FROM myRooms\\\"\\n + \\\" WHERE RoomId NOT IN (\\\"\\n + \\\" SELECT DISTINCT re.Room\\\"\\n + \\\" FROM myReservations re JOIN myRooms ro ON (re.Room = ro.RoomId)\\\"\\n + \\\" WHERE (DATEDIFF(CheckIn, DATE(\\\" + date1 + \\\")) <= 0\\\"\\n + \\\" AND DATEDIFF(CheckOut, DATE(\\\" + date2 + \\\")) > 0)\\\"\\n + \\\" OR (DATEDIFF(CheckIn, DATE(\\\" + date1 + \\\")) > 0\\\"\\n + \\\" AND DATEDIFF(CheckIn, DATE(\\\" + date2 + \\\")) <= 0)\\\" \\n + \\\" OR (DATEDIFF(CheckOut, DATE(\\\" + date1 + \\\")) > 0\\\" \\n + \\\" AND DATEDIFF(CheckOut, DATE(\\\" + date2 + \\\")) < 0)\\\" \\n + \\\" )) AS tb\\\"\\n + \\\" WHERE RoomId = '\\\" + roomid + \\\"'\\\";\\n\\n PreparedStatement stmt = null;\\n ResultSet rset = null;\\n\\n try\\n {\\n stmt = conn.prepareStatement(query);\\n rset = stmt.executeQuery();\\n rset.next();\\n if(rset.getString(\\\"status\\\").equals(\\\"empty\\\"))\\n return true;\\n }\\n catch (Exception ex){\\n ex.printStackTrace();\\n }\\n finally {\\n try {\\n stmt.close();\\n }\\n catch (Exception ex) {\\n ex.printStackTrace( ); \\n } \\t\\n }\\n \\n return false;\\n\\n }\",\n \"private void link(String sourceInstance, String targetInstance, Tuple<String, String> queries) {\\n\\t\\t// Adapt queries to sample instances\\n\\t\\tTuple<String,String> newQueries = queries;\\n\\t\\tif(sourceInstance!=null && targetInstance!=null) {\\n\\t\\t\\t// if sourceInstance and targetInstance are not null, add the clauses:\\n\\t\\t\\t//\\t\\t\\\"WHERE source.id = sourceInstance\\\" to queries.getFirstElement()\\n\\t\\t\\t//\\t\\t\\\"WHERE target.id = targetInstance\\\" to queries.getSecondElement()\\n\\t\\t}\\n\\t\\texecuteSourceQuery(newQueries.getFirstElement(), newQueries.getSecondElement());\\n\\t}\",\n \"private static <Item extends Comparable> List<Item> catenate(List<Item> q1, List<Item> q2) {\\n List<Item> catenated = new ArrayList<>();\\n for (Item item : q1) {\\n catenated.add(item);\\n }\\n for (Item item: q2) {\\n catenated.add(item);\\n }\\n return catenated;\\n }\",\n \"private ExampleSetBuilder performInnerJoin(ExampleSet leftExampleSet, ExampleSet rightExampleSet,\\n\\t\\t\\tList<AttributeSource> originalAttributeSources, List<Attribute> unionAttributeList,\\n\\t\\t\\tPair<Attribute[], Attribute[]> keyAttributes) throws ProcessStoppedException {\\n\\t\\tExampleSetBuilder builder = ExampleSets.from(unionAttributeList);\\n\\n\\t\\tAttribute[] leftKeyAttributes = null;\\n\\t\\tAttribute[] rightKeyAttributes = null;\\n\\t\\tMap<DoubleArrayWrapper, List<Example>> rightKeyMapping = null;\\n\\t\\tboolean useId = getParameterAsBoolean(PARAMETER_USE_ID);\\n\\n\\t\\tif (!useId) {\\n\\t\\t\\t// create key mapping for right example set\\n\\t\\t\\tleftKeyAttributes = keyAttributes.getFirst();\\n\\t\\t\\trightKeyAttributes = keyAttributes.getSecond();\\n\\t\\t\\trightKeyMapping = createKeyMapping(rightExampleSet, rightKeyAttributes, leftKeyAttributes);\\n\\t\\t}\\n\\n\\t\\tint progressCounter = 0;\\n\\t\\t// iterate over all example from left table and search for matching examples in right table:\\n\\t\\tfor (Example leftExample : leftExampleSet) {\\n\\n\\t\\t\\tList<Example> matchingRightExamples = getMatchingExamples(leftExampleSet, rightExampleSet, leftKeyAttributes,\\n\\t\\t\\t\\t\\trightKeyMapping, useId, leftExample);\\n\\n\\t\\t\\tif (matchingRightExamples != null) {\\n\\t\\t\\t\\tfor (Example rightExample : matchingRightExamples) {\\n\\t\\t\\t\\t\\taddCombinedOccurence(originalAttributeSources, unionAttributeList, builder, leftExample, rightExample);\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\n\\t\\t\\t// trigger operator progress every 100 examples\\n\\t\\t\\t++progressCounter;\\n\\t\\t\\tif (progressCounter % 100 == 0) {\\n\\t\\t\\t\\tgetProgress().step(100);\\n\\t\\t\\t\\tprogressCounter = 0;\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\treturn builder;\\n\\t}\",\n \"private Set<String> intersection(Set<String> s1, Set<String> s2) {\\n Set<String> intersection = new HashSet<>(s1);\\n intersection.retainAll(s2);\\n return intersection;\\n }\",\n \"private ClusterCombination checkAndDoJoinMultiPearson(ClusterCombination CC1, ClusterCombination CC2) {\\n boolean doJoin = true;\\r\\n ArrayList<Cluster> CCList = new ArrayList<>(CC1.getClusters().size()+1); //list of output clusters for new CC if join is succesfull\\r\\n\\r\\n ArrayList<Cluster> CC1Clusters = CC1.getClusters();\\r\\n ArrayList<Cluster> CC2Clusters = CC2.getClusters();\\r\\n\\r\\n ArrayList<Cluster> LHS1 = CC1.getLHS();\\r\\n ArrayList<Cluster> LHS2 = CC2.getLHS();\\r\\n\\r\\n ArrayList<Cluster> RHS1 = CC1.getRHS();\\r\\n ArrayList<Cluster> RHS2 = CC2.getRHS();\\r\\n\\r\\n for(int i =0; i<CC1Clusters.size()-1; i++) {\\r\\n Cluster C1 = CC1Clusters.get(i);\\r\\n Cluster C2 = CC2Clusters.get(i);\\r\\n\\r\\n boolean overlap = checkClusterOverlap(C1, C2); // check if there is some overlap\\r\\n\\r\\n\\r\\n\\r\\n if(!overlap){ //the cluster in this position does not overlap, we don't need to join\\r\\n doJoin=false;\\r\\n break;\\r\\n }else{ // there is overlap, add the intersection of C1 and C2\\r\\n if(C1.getNPoints() <= C2.getNPoints()){\\r\\n CCList.add(C1);\\r\\n }else{\\r\\n CCList.add(C2);\\r\\n }\\r\\n\\r\\n }\\r\\n\\r\\n\\r\\n }\\r\\n\\r\\n\\r\\n if(doJoin){ // each cluster in the candidate (except the last) does overlap\\r\\n // so, according to apriori, we join -> return the overlapping clusters + the last clusters of CC1 and CC2\\r\\n Cluster lastCC1 = CC1Clusters.get(CC1Clusters.size()-1);\\r\\n Cluster lastCC2 = CC2Clusters.get(CC2Clusters.size()-1);\\r\\n if(lastCC1.getClusterId() <= lastCC2.getClusterId()){ // make sure to respect ordering of clusters within a candidate by ID. otherwise this could be designated as a duplicate\\r\\n CCList.add(lastCC1); CCList.add(lastCC2);\\r\\n }else{\\r\\n CCList.add(lastCC2); CCList.add(lastCC1);\\r\\n }\\r\\n\\r\\n ArrayList<Cluster> newLHS = new ArrayList<>();\\r\\n ArrayList<Cluster> newRHS = new ArrayList<>();\\r\\n for(int i = 0; i<LHS1.size(); i++){\\r\\n newLHS.add(CCList.get(i));\\r\\n }\\r\\n for(int i = LHS1.size(); i<CCList.size(); i++){\\r\\n newRHS.add(CCList.get(i));\\r\\n }\\r\\n\\r\\n ClusterCombination newCC = new MultiPearsonClusterCombination(newLHS, newRHS);\\r\\n newCC.checkAndSetMaxSubsetLowerBound(Math.max(CC1.getLB(), CC1.getMaxLowerBoundSubset()));\\r\\n newCC.checkAndSetMaxSubsetLowerBound(Math.max(CC2.getLB(), CC2.getMaxLowerBoundSubset()));\\r\\n\\r\\n return newCC;\\r\\n\\r\\n }else{\\r\\n return null;\\r\\n }\\r\\n }\",\n \"public boolean query(int a, int b) {\\n\\t\\treturn find(a) == find(b);\\n }\",\n \"@Test\\n\\tpublic void orGrepTest() throws Exception {\\n\\t\\t// | for 'insane' and 'mistress'\\n\\t\\tHashSet<String> grep1 = loadGrepResults(\\\"mistress\\\");\\n\\t\\tHashSet<String> grepFound = loadGrepResults(\\\"insane\\\");\\n\\t\\tgrepFound.addAll(grep1);\\n\\n\\t\\tCollection<Page> index = queryTest.query(\\\"mistress | insane\\\");\\n\\t\\tHashSet<String> indexFound = new HashSet<String>();\\n\\n\\t\\tfor (Page p : index)\\n\\t\\t\\tindexFound.add(p.getURL().getPath().toLowerCase());\\n\\n\\t\\tassertEquals(indexFound, grepFound);\\n\\n\\t}\",\n \"public static void intersection(ArrayList<String> x, ArrayList<String> y, ArrayList<String> z, JTextArea ta) {\\n\\t\\t\\n\\t\\t//This is the loop to add items from list 1 to results array, if the elements are present in both the lists\\n\\t\\tfor (int i=0; i<x.size(); i++)\\n\\t\\t{\\n\\t\\t\\tfor (int j=0; j<y.size(); j++)\\n\\t\\t\\t{\\n\\t\\t\\t\\tif (x.get(i).equals(y.get(j))&&!z.contains(x.get(i)))\\n\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\tz.add(x.get(i));\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\t\\n\\t\\t\\n\\t\\t//This is the loop to print all the items of the results array list\\n\\t\\tta.setText(\\\"{ \\\");\\n\\t\\tfor (int i=0; i<z.size(); i++)\\n\\t\\t{\\n\\t\\t\\tta.append(z.get(i)+\\\" \\\");\\n\\t\\t}\\n\\t\\tta.append(\\\"}\\\");\\n\\t}\",\n \"private boolean overlaps(ThingTimeTriple a, ThingTimeTriple b)\\r\\n/* 227: */ {\\r\\n/* 228:189 */ return (a.from < b.to) && (a.to > b.from);\\r\\n/* 229: */ }\",\n \"@Override\\n public int hashCode() {\\n return Objects.hash(requestedPosts, this.getQueryID());\\n }\",\n \"public ArrayList<Integer> intersect(\\n final List<Integer> A, final List<Integer> B) {\\n ArrayList<Integer> res = new ArrayList<Integer>();\\n int M = A.size();\\n int N = B.size();\\n if (M == 0 || N == 0) {\\n return res;\\n }\\n int i = 0;\\n int j = 0;\\n while (i < M && j < N) {\\n int a = A.get(i);\\n int b = B.get(j);\\n if (a == b) {\\n res.add(a);\\n i++;\\n j++;\\n } else if (a < b) {\\n i++;\\n } else {// a > b\\n j++;\\n }\\n }\\n return res;\\n }\",\n \"public PostingsList search( Query query, int queryType, int rankingType, int structureType ) {\\r\\n switch(queryType){\\r\\n case Index.INTERSECTION_QUERY : \\r\\n return searchIntersection( query, rankingType, structureType);\\r\\n\\r\\n case Index.PHRASE_QUERY :\\r\\n return searchPhrase( query, rankingType, structureType);\\r\\n default:\\r\\n break;\\r\\n }\\r\\n\\r\\n return null;\\r\\n }\",\n \"public void sensibleMatches2() \\n { \\n Map<String, Set<String>> clientMap = new HashMap<>();\\n Set<String> interests = new HashSet<>();\\n\\n interests.add(\\\"Food\\\");\\n interests.add(\\\"Wine\\\");\\n interests.add(\\\"Tandems\\\");\\n clientMap.put(\\\"Hal\\\", interests);\\n\\t \\n interests = new HashSet<>();\\n interests.add(\\\"Food\\\");\\n interests.add(\\\"Walking\\\");\\n interests.add(\\\"Welding\\\");\\n clientMap.put(\\\"Gemma\\\", interests);\\n\\n interests = new HashSet<>();\\n interests.add(\\\"Food\\\");\\n interests.add(\\\"Cinema\\\");\\n interests.add(\\\"Wine\\\");\\n clientMap.put(\\\"Caroline\\\", interests);\\n\\n Set<String> halsInterests = clientMap.get(\\\"Hal\\\");\\n String outputString;\\n Set<String> eachClientInterests;\\n Set<String> intersection ;\\n\\n for (String eachClient : clientMap.keySet()) \\n {\\n if (!eachClient.equals(\\\"Hal\\\")) \\n {\\n eachClientInterests = clientMap.get(eachClient);\\n intersection = new HashSet<>(halsInterests);\\n intersection.retainAll(eachClientInterests);\\n outputString = \\\"Hal and \\\" + eachClient \\n + \\\" have common interests: \\\"\\n + intersection;\\n System.out.println(outputString);\\n }\\n }\\n }\",\n \"private Range<Token> intersect(Range<Token> serverRange, AbstractBounds<Token> requestedRange)\\n {\\n if (serverRange.contains(requestedRange.left) && serverRange.contains(requestedRange.right)) {\\n //case 1: serverRange fully encompasses requestedRange\\n return new Range<Token>(requestedRange.left, requestedRange.right, partitioner);\\n } else if (requestedRange.contains(serverRange.left) && requestedRange.contains(serverRange.right)) {\\n //case 2: serverRange is fully encompasses by requestedRange\\n //serverRange is already the intersection\\n return new Range<Token>(serverRange.left, serverRange.right);\\n } else if (serverRange.contains(requestedRange.left) && requestedRange.contains(serverRange.right)) {\\n //case 3: serverRange overlaps on the left: sR.left < rR.left < sR.right < rR.right\\n return new Range<Token>(requestedRange.left, serverRange.right, partitioner);\\n } else if (requestedRange.contains(serverRange.left) && serverRange.contains(requestedRange.right)) {\\n //case 4: serverRange overlaps on the right rR.left < sR.left < rR.right < sR.right\\n return new Range<Token>(serverRange.left, requestedRange.right, partitioner);\\n } else if (!serverRange.contains(requestedRange.left) && !serverRange.contains(requestedRange.right) &&\\n !requestedRange.contains(serverRange.left) && !requestedRange.contains(serverRange.right)) {\\n //case 5: totally disjoint\\n return null;\\n } else {\\n assert false : \\\"Failed intersecting serverRange = (\\\" + serverRange.left + \\\", \\\" + serverRange.right + \\\") and requestedRange = (\\\" + requestedRange.left + \\\", \\\" + requestedRange.right + \\\")\\\";\\n return null;\\n }\\n }\",\n \"public static List<StringMeeting> calendarMatching(\\n List<StringMeeting> calendar1,\\n StringMeeting dailyBounds1,\\n List<StringMeeting> calendar2,\\n StringMeeting dailyBounds2,\\n int meetingDuration) {\\n\\n\\n List<Meeting> updatedCaleandr1 = updateCalendar(calendar1, dailyBounds1);\\n System.out.println(updatedCaleandr1);\\n List<Meeting> updatedCaleandr2 = updateCalendar(calendar2, dailyBounds2);\\n\\n\\n\\n List<Meeting> mergedCalendar = mergeCalendars(updatedCaleandr1, updatedCaleandr2);\\n mergedCalendar.forEach(k-> System.out.println(k.toString()));\\n List<Meeting> flattencalendr = flattenCalenedars(mergedCalendar);\\n// flattencalendr.forEach(k-> System.out.println(k.toString()));\\n System.out.println();\\n\\n return getMatchingAvailabilities(flattencalendr, meetingDuration);\\n }\",\n \"public static void main(String[] args) {\\n\\t\\t\\r\\n\\t\\tint arr1[] = {3,2,11,4,6,7};\\r\\n\\t\\tint arr2[] = {1,2,8,4,9,7};\\r\\n\\t\\t\\r\\n\\t\\tList<Integer> list1 = new ArrayList<Integer>();\\r\\n\\t\\t\\r\\n\\t\\tList<Integer> list2 = new ArrayList<Integer>();\\r\\n\\t\\t\\r\\n\\t\\tfor (int a : arr1) {\\r\\n\\t\\t\\tlist1.add(a);\\r\\n\\t\\t}\\r\\n\\t\\tfor (int b : arr2) {\\r\\n\\t\\t\\tlist2.add(b);\\r\\n\\t\\t}\\r\\n\\t\\t\\r\\n\\t\\tSystem.out.println(list1);\\r\\n System.out.println(list2);\\r\\n \\r\\n list1.retainAll(list2);\\r\\n System.out.println(\\\"The Intersection values : \\\" + list1);\\r\\n \\r\\n\\t}\",\n \"public static void main(String[] args) {\\n\\t\\tInteger[] firstArray = {0,2,4,6,8};\\n\\t Integer[] secondArray = {1,3,10,4,7,8,9};\\n\\t \\n\\t intersectionUsingSet(firstArray, secondArray);\\n\\n\\t System.out.println();\\n\\t \\n\\t // Array with duplicate elements in the array\\n\\t Integer[] firstArray1 = {0,2,2,4,6,6,8};\\n\\t Integer[] secondArray2 = {1,3,10,10,4,7,8,9};\\n\\t \\n\\t intersectionUsingSet(firstArray1, secondArray2);\\n\\t}\",\n \"@Test\\n\\tpublic void andGrepTest() throws Exception {\\n\\t\\t// & for 'undocumented' and 'mistress'\\n\\t\\tHashSet<String> grepFound = loadGrepResults(\\\"undocumented\\\");\\n\\t\\tHashSet<String> grep1 = loadGrepResults(\\\"mistress\\\");\\n\\t\\tgrepFound.retainAll(grep1);\\n\\t\\t\\n\\t\\tCollection<Page> index = queryTest.query(\\\"mistress & undocumented\\\");\\n\\t\\tHashSet<String> indexFound = new HashSet<String>();\\n\\n\\t\\tfor (Page p : index)\\n\\t\\t\\tindexFound.add(p.getURL().getPath().toLowerCase());\\n\\t\\t\\n\\t\\tassertEquals(indexFound, grepFound);\\n\\t}\",\n \"public void matchesDemo() \\n {\\n Map<String, Set<String>> clientMap = new HashMap<>();\\n Set<String> interests = new HashSet<>();\\n\\n interests.add(\\\"Food\\\");\\n interests.add(\\\"Wine\\\");\\n interests.add(\\\"Tandems\\\");\\n clientMap.put(\\\"Hal\\\", interests);\\n\\t \\n interests = new HashSet<>();\\n interests.add(\\\"Food\\\");\\n interests.add(\\\"Walking\\\");\\n interests.add(\\\"Welding\\\");\\n clientMap.put(\\\"Gemma\\\", interests);\\n\\t \\n interests = new HashSet<>();\\n interests.add(\\\"Food\\\");\\n interests.add(\\\"Cinema\\\");\\n interests.add(\\\"Wine\\\");\\n clientMap.put(\\\"Caroline\\\", interests);\\n\\n Set<String> halsInterests = clientMap.get(\\\"Hal\\\");\\n String outputString;\\n Set<String> eachClientInterests;\\n Set<String> intersection;\\n\\n for (String eachClient : clientMap.keySet()) \\n {\\n eachClientInterests = clientMap.get(eachClient);\\n intersection = new HashSet<>(halsInterests);\\n intersection.retainAll(eachClientInterests);\\n outputString = \\\"Hal and \\\" + eachClient \\n + \\\" have common interests: \\\"\\n + intersection;\\n System.out.println(outputString) ;\\n }\\n }\",\n \"public ZYSet<ElementType> intersection(ZYSet<ElementType> otherSet){\\n ZYSet<ElementType> result = new ZYArraySet<ElementType>();\\n for(ElementType e :this){\\n if(otherSet.contains(e)){\\n result.add(e);\\n }\\n }\\n return result;\\n }\",\n \"public void run(){\\n\\t\\tif(searchHow==0){\\n\\t\\t\\tint isbnCount = 0;\\n\\t\\t\\tfor(int i=0; i<db.size(); i++){\\n\\t\\t\\t\\t\\tSearchRequest requestIsbn = new SearchRequest(db, searchForThis, isbnCount, db.size());\\n\\t\\t\\t\\t\\tdb.searchByISBN(requestIsbn);\\n\\t\\t\\t\\t\\tisbnCount = requestIsbn.foundPos;\\n\\t\\t\\t\\t\\tif (requestIsbn.foundPos >= 0) {\\n\\t\\t\\t\\t\\t\\tisbnCount++;\\n\\t\\t\\t\\t\\t\\tString formatThis = \\\"Matched ISBN at position: \\\" + requestIsbn.foundPos;\\n\\t\\t\\t\\t\\t\\tSystem.out.printf(\\\"%-35s || Title: \\\"+db.getBook(requestIsbn.foundPos)+\\\"\\\\n\\\",formatThis);\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\telse\\n\\t\\t\\t\\t\\t\\ti=db.size();\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\tif(searchHow==1){\\n\\t\\t\\tint titleCount = 0;\\n\\t\\t\\tfor(int i=0; i<db.size(); i++){\\n\\t\\t\\t\\t\\tSearchRequest requestTitle = new SearchRequest(db, searchForThis, titleCount, db.size());\\n\\t\\t\\t\\t\\tdb.searchByTitle(requestTitle);\\n\\t\\t\\t\\t\\ttitleCount = requestTitle.foundPos;\\n\\t\\t\\t\\t\\tif (requestTitle.foundPos >= 0) {\\n\\t\\t\\t\\t\\t\\ttitleCount++;\\n\\t\\t\\t\\t\\t\\tString formatThis = \\\"Matched title at position: \\\" + requestTitle.foundPos;\\n\\t\\t\\t\\t\\t\\tSystem.out.printf(\\\"%-35s || Title: \\\"+db.getBook(requestTitle.foundPos)+\\\"\\\\n\\\",formatThis);\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\telse\\n\\t\\t\\t\\t\\t\\ti=db.size();\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\tif(searchHow==2){\\n\\t\\t\\tint authorCount = 0;\\n\\t\\t\\tfor(int i=0; i<db.size(); i++){\\n\\t\\t\\t\\t\\tSearchRequest requestAuthor = new SearchRequest(db, searchForThis, authorCount, db.size());\\n\\t\\t\\t\\t\\tdb.searchByAuthor(requestAuthor);\\n\\t\\t\\t\\t\\tauthorCount = requestAuthor.foundPos;\\n\\t\\t\\t\\t\\tif (requestAuthor.foundPos >= 0) {\\n\\t\\t\\t\\t\\t\\tauthorCount++;\\n\\t\\t\\t\\t\\t\\tString formatThis = \\\"Matched author at position: \\\" + requestAuthor.foundPos;\\n\\t\\t\\t\\t\\t\\tSystem.out.printf(\\\"%-35s || Title: \\\"+db.getBook(requestAuthor.foundPos)+\\\"\\\\n\\\",formatThis);\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\telse\\n\\t\\t\\t\\t\\t\\ti=db.size();\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\tif(searchHow==3){\\n\\t\\t\\tint pageCount = 0;\\n\\t\\t\\tfor(int i=0; i<db.size(); i++){\\n\\t\\t\\t\\t\\tSearchRequest requestPage = new SearchRequest(db, searchForThis, pageCount, db.size());\\n\\t\\t\\t\\t\\tdb.searchByNumPages(requestPage);\\n\\t\\t\\t\\t\\tpageCount = requestPage.foundPos;\\n\\t\\t\\t\\t\\tif (requestPage.foundPos >= 0) {\\n\\t\\t\\t\\t\\t\\tpageCount++;\\n\\t\\t\\t\\t\\t\\tString formatThis = \\\"Matched pages at position: \\\" + requestPage.foundPos;\\n\\t\\t\\t\\t\\t\\tSystem.out.printf(\\\"%-35s || Title: \\\"+db.getBook(requestPage.foundPos)+\\\"\\\\n\\\",formatThis);\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\telse\\n\\t\\t\\t\\t\\t\\ti=db.size();\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\tif(searchHow==4){\\n\\t\\t\\tint yearCount = 0;\\n\\t\\t\\tfor(int i=0; i<db.size(); i++){\\n\\t\\t\\t\\t\\tSearchRequest requestYear = new SearchRequest(db, searchForThis, yearCount, db.size());\\n\\t\\t\\t\\t\\tdb.searchByYear(requestYear);\\n\\t\\t\\t\\t\\tyearCount = requestYear.foundPos;\\n\\t\\t\\t\\t\\tif (requestYear.foundPos >= 0) {\\n\\t\\t\\t\\t\\t\\tyearCount++;\\n\\t\\t\\t\\t\\t\\tString formatThis = \\\"Matched year at position: \\\" + requestYear.foundPos;\\n\\t\\t\\t\\t\\t\\tSystem.out.printf(\\\"%-35s || Title: \\\"+db.getBook(requestYear.foundPos)+\\\"\\\\n\\\",formatThis);\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\telse\\n\\t\\t\\t\\t\\t\\ti=db.size();\\n\\t\\t\\t}\\n\\t\\t}\\n\\t}\",\n \"public interface SearchQuerySet extends QuerySet\\n{\\n\\n // for AbstractSearch\\n public static final int STAT_MODELS = 1;\\n public static final int STAT_CLUSTERS = 2;\\n public static final int STAT_GENOMES = 4;\\n public static final int STAT_MODEL_CLUSTERS = 8;\\n\\n public String getStatsById(Collection data);\\n public String getStatsByQuery(String query);\\n public String getStatsById(Collection data,int stats);\\n public String getStatsByQuery(String query,int stats);\\n \\n // for BlastSearch\\n public String getBlastSearchQuery(Collection dbNames, Collection keys, KeyTypeUser.KeyType keyType);\\n \\n //for ClusterIDSearch\\n public String getClusterIDSearchQuery(Collection input, int limit, int[] DBs, KeyTypeUser.KeyType keyType);\\n \\n // for ClusterNameSearch\\n public String getClusterNameSearchQuery(Collection input, int limit, int[] DBs, KeyTypeUser.KeyType keyType);\\n \\n // for DescriptionSearch\\n public String getDescriptionSearchQuery(Collection input, int limit, int[] DBs, KeyTypeUser.KeyType keyType);\\n \\n // for GoSearch \\n public String getGoSearchQuery(Collection input, int limit, KeyTypeUser.KeyType keyType);\\n \\n // for GoTextSearch\\n public String getGoTextSearchQuery(Collection input, int limit, KeyTypeUser.KeyType keyType);\\n \\n // for IdSearch\\n public String getIdSearchQuery(Collection input, int limit, int[] DBs, KeyTypeUser.KeyType keyType);\\n \\n // for QueryCompSearch\\n public String getQueryCompSearchQuery(String comp_id, String status, KeyTypeUser.KeyType keyType);\\n \\n // for QuerySearch\\n public String getQuerySearchQuery(String queries_id, KeyTypeUser.KeyType keyType); \\n \\n // for SeqModelSearch\\n public String getSeqModelSearchQuery(Collection model_ids, KeyTypeUser.KeyType keyType);\\n \\n // for UnknowclusterIdSearch\\n public String getUnknownClusterIdSearchQuery(int cluster_id, KeyTypeUser.KeyType keyType);\\n \\n // for ProbeSetSearch\\n public String getProbeSetSearchQuery(Collection input, int limit, KeyTypeUser.KeyType keyType);\\n \\n // for ProbeSetKeySearch\\n public String getProbeSetKeySearchQuery(Collection input, int limit, KeyTypeUser.KeyType keyType);\\n \\n // for QueryTestSearch\\n public String getQueryTestSearchQuery(String query_id, String version, String genome_id);\\n \\n // for QueryStatsSearch\\n public String getQueryStatsSearchQuery(List query_ids,List DBs);\\n \\n // for PskClusterSearch\\n public String getPskClusterSearchQuery(int cluster_id,KeyTypeUser.KeyType keyType);\\n \\n // for ClusterCorrSearch\\n public String getClusterCorrSearchQuery(int cluster_id, int psk_id, KeyTypeUser.KeyType keyType);\\n \\n // for UnknownGenesSearch\\n public String getUnknownGenesSearchQuery(Collection sources, KeyTypeUser.KeyType keyType);\\n \\n}\",\n \"public static SiftKnnContainer mergetosizeofboth(SiftKnnContainer a, SiftKnnContainer b) {\\n SiftKnnContainer ret = new SiftKnnContainer( a.getK() + b.getK() );\\n ret.SetQueryPoint(a.getQueryPoint());\\n\\n knnPair[] knn = a.getknnPairArray();\\n for (int i = 0; i < knn.length ; i++) {\\n if (knn[i].distance != Integer.MAX_VALUE) {\\n ret.addNoDuplicateIDs(knn[i].pointID, knn[i].distance);\\n }\\n }\\n knn = b.getknnPairArray();\\n for (int i = 0; i < knn.length ; i++) {\\n if (knn[i].distance != Integer.MAX_VALUE) {\\n ret.addNoDuplicateIDs(knn[i].pointID, knn[i].distance);\\n }\\n }\\n return ret;\\n }\",\n \"public static final void computeSortedIntersection(ArrayList<MediaItem> firstList, final ArrayList<MediaItem> secondList,\\n int maxSize, ArrayList<MediaItem> intersectionList, MediaItem[] hash) {\\n int mask = hash.length - 1;\\n int numItemsToHash = Math.min(secondList.size(), 2 * hash.length);\\n for (int i = 0; i < numItemsToHash; ++i) {\\n MediaItem item = secondList.get(i);\\n if (item != null) {\\n hash[item.hashCode() & mask] = item;\\n }\\n }\\n\\n // Build the intersection array.\\n int firstListSize = firstList.size();\\n for (int i = 0; i < firstListSize; ++i) {\\n MediaItem firstListItem = firstList.get(i);\\n if (firstListItem == null)\\n continue;\\n MediaItem hashItem = (hash != null) ? hash[firstListItem.hashCode() & mask] : null;\\n if (hashItem != null\\n && ((hashItem.mId != Shared.INVALID && hashItem.hashCode() == firstListItem.hashCode()) || contains(secondList, firstListItem))) {\\n intersectionList.add(firstListItem);\\n if (--maxSize == 0) {\\n break;\\n }\\n }\\n }\\n\\n // Clear the hash table.\\n Arrays.fill(hash, null);\\n }\",\n \"private void findIntersection(Node head1, Node head2) {\\n if (head1 == null || head2 == null) {\\n System.out.println(\\\"No intersection found\\\");\\n return;\\n }\\n Set<Node> set = new HashSet<Node>();\\n boolean flag = false;\\n\\n for (Node temp = head1; temp != null; temp = temp.next)\\n set.add(temp);\\n for (Node temp = head2; temp != null; temp = temp.next)\\n if (!set.add(temp)) {\\n System.out.println(\\\"Intersection found at \\\" + temp.data);\\n flag = true;\\n break;\\n }\\n if (!flag) {\\n System.out.println(\\\"No intersection found\\\");\\n }\\n }\",\n \"public static <T extends Comparable<? super T>> \\n void union(SLL<T> list1, SLL<T> list2,\\n SLL<T> result) {\\n \\n SLLNode<T> iterlist1 = list1.head;\\n SLLNode<T> iterlist2 = list2.head;\\n \\n T itemlist1=null, itemlist2=null;\\n \\n // get first item in each list\\n if ( iterlist1 != null )\\n itemlist1 = iterlist1.info;\\n if( iterlist2 != null )\\n itemlist2 = iterlist2.info;\\n \\n while ( itemlist1 != null || itemlist2 != null ) {\\n\\n int compareResult;\\n if( itemlist1 == null ) {\\n compareResult = 1;\\n } else if ( itemlist2 == null ) {\\n compareResult = -1;\\n } else {\\n compareResult = itemlist1.compareTo(itemlist2);\\n }\\n \\n if ( compareResult == 0 ) {\\n result.addToTail(itemlist1); //appending to result list \\n if( iterlist1.next != null ) {\\n iterlist1 = iterlist1.next;\\n itemlist1 = iterlist1.info;\\n } else {\\n itemlist1 = null;\\n }\\n \\n if( iterlist2.next != null ) {\\n iterlist2 = iterlist2.next;\\n itemlist2 = iterlist2.info;\\n } else {\\n itemlist2 = null;\\n } \\n }\\n else if ( compareResult < 0 ) { \\n result.addToTail(itemlist1); //appending to result list\\n if( iterlist1.next != null ) {\\n iterlist1 = iterlist1.next;\\n itemlist1 = iterlist1.info;\\n } else {\\n itemlist1 = null;\\n }\\n }\\n else {\\n result.addToTail(itemlist2);\\n if( iterlist2.next != null ) {\\n iterlist2 = iterlist2.next;\\n itemlist2 = iterlist2.info;\\n } else {\\n itemlist2 = null;\\n }\\n }\\n } \\n }\",\n \"public void testRange() throws IOException, InvalidGeoException\\r\\n {\\n LgteIndexSearcherWrapper searcher = new LgteIndexSearcherWrapper(path);\\r\\n\\r\\n //try find Jorge and Bruno documents last year\\r\\n // In this case the closest one will be in 2007\\r\\n String query = \\\"contents:(Jorge Bruno)\\\";\\r\\n\\r\\n LgteQuery lgteQueryResult1;\\r\\n LgteQuery lgteQueryResult1and2;\\r\\n try\\r\\n {\\r\\n lgteQueryResult1 = LgteQueryParser.parseQuery(query);\\r\\n lgteQueryResult1and2 = LgteQueryParser.parseQuery(query);\\r\\n\\r\\n MyCalendar c1Aux = new MyCalendar(2005,11,20,9,0,10);\\r\\n MyCalendar c2Aux = new MyCalendar(2007,1,12,20,45,15);\\r\\n long dif = c2Aux.getTimeInMillis() - c1Aux.getTimeInMillis();\\r\\n\\r\\n lgteQueryResult1.getQueryParams().setTimeMiliseconds(c1Aux.getTimeInMillis());\\r\\n lgteQueryResult1.getQueryParams().setRadiumMiliseconds(dif -1);\\r\\n lgteQueryResult1and2.getQueryParams().setTimeMiliseconds(c1Aux.getTimeInMillis());\\r\\n lgteQueryResult1and2.getQueryParams().setRadiumMiliseconds(dif+1);\\r\\n }\\r\\n catch (ParseException e)\\r\\n {\\r\\n fail(e.toString());\\r\\n return;\\r\\n }\\r\\n\\r\\n //Lets use aos Time Sorter to dont worry about distances and stuff like that, he will do the job\\r\\n TimeDistanceSortSource dsort1 = new TimeDistanceSortSource();\\r\\n LgteSort sort1 = new LgteSort(new SortField(\\\"foo\\\", dsort1));\\r\\n\\r\\n //LgteHits give you Documents and time with unecessary lines of boring code\\r\\n LgteHits lgteHits1;\\r\\n LgteHits lgteHits1and2;\\r\\n lgteHits1 = searcher.search(lgteQueryResult1, sort1);\\r\\n assertTrue(lgteHits1.length() == 1);\\r\\n\\r\\n lgteHits1and2 = searcher.search(lgteQueryResult1and2, sort1);\\r\\n assertTrue(lgteHits1and2.length() == 2);\\r\\n\\r\\n\\r\\n long time1_0 = lgteHits1.doc(0).getTime().getTime();\\r\\n long time1and2_0 = lgteHits1and2.doc(0).getTime().getTime();\\r\\n long time1and2_1 = lgteHits1and2.doc(1).getTime().getTime();\\r\\n assertTrue(time1_0 == new MyCalendar(2005,11,20,9,0,10).getTimeInMillis());\\r\\n assertTrue(time1and2_0 == new MyCalendar(2005,11,20,9,0,10).getTimeInMillis());\\r\\n assertTrue(time1and2_1 == new MyCalendar(2007,1,12,20,45,15).getTimeInMillis());\\r\\n\\r\\n\\r\\n searcher.close();\\r\\n }\",\n \"protected void reflectRelationOnUnionQuery(ConditionQuery baseQueryAsSuper, ConditionQuery unionQueryAsSuper) {\\r\\n }\",\n \"public ArrayList<String> combineDataOpsAndIntents(String p1, String p2) {\\n\\t\\tArrayList<String> logics1 = QueryStream.getLogic(p1);\\n\\t\\tArrayList<String> terms1 = QueryStream.getTerms(p1);\\n\\t\\t//Get logic statements from p2\\n\\t\\tArrayList<String> logics2 = QueryStream.getLogic(p2);\\n\\t\\tArrayList<String> terms2 = QueryStream.getTerms(p2);\\n\\t\\t\\n\\t\\tArrayList<String> result_logics = new ArrayList<String>();\\n\\t\\tArrayList<String> result_terms = new ArrayList<String>();\\n\\t\\t\\n\\t\\t//Iterate through logic for p1. If it matches anything in p2,\\n\\t\\t// we add the terms from p1 and p2 together.\\n\\t\\tfor(int i = 0; i < logics1.size(); ++i) {\\n\\t\\t\\t\\n\\t\\t\\tString result_term = \\\"\\\";\\n\\t\\t\\t//If any logic matches, we combine the corresponding terms together\\n\\t\\t\\tif(logics2.contains(logics1.get(i))) {\\n\\t\\t\\t\\tresult_term = terms1.get(i) + \\\" \\\" + terms2.get(i);\\n\\t\\t\\t}\\n\\t\\t\\telse {\\n\\t\\t\\t\\tresult_term = terms1.get(i);\\n\\t\\t\\t}\\n\\t\\t\\tresult_logics.add(logics1.get(i));\\n\\t\\t\\tresult_terms.add(result_term);\\n\\t\\t}\\n\\t\\t//Iterate through the logic for p2. If it includes any logic not\\n\\t\\t// in the results, then add it in.\\n\\t\\tfor(int i = 0; i < logics2.size(); ++i) {\\n\\t\\t\\t\\n\\t\\t\\tString result_term = \\\"\\\";\\n\\t\\t\\t//If any logic matches, we combine the corresponding terms together\\n\\t\\t\\tif(!result_logics.contains(logics2.get(i))) {\\n\\t\\t\\t\\tresult_logics.add(logics2.get(i));\\n\\t\\t\\t\\tresult_term = terms2.get(i);\\n\\t\\t\\t\\tresult_terms.add(result_term);\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\t\\n//\\t\\tfor(String l : result_logics) {\\n//\\t\\t\\tSystem.out.println(l);\\n//\\t\\t}\\n\\t\\t\\n\\t\\t//Now we can create a new policy given the two strings\\n\\t\\treturn produceDataOpsIntentsPolicy(result_logics, result_terms);\\n\\t}\",\n \"public static void findIntersection(int[] ip1, int[] ip2) {\\n int[] smaller, bigger;\\n if (ip1.length <= ip2.length) {\\n smaller = ip1;\\n bigger = ip2;\\n } else {\\n smaller = ip2;\\n bigger = ip1;\\n }\\n\\n\\n //O(n)\\n for (int i = 0; i < smaller.length; ) {\\n for (int j = 0; j < bigger.length; ) {\\n\\n if (smaller[i] == bigger[j]) {\\n System.out.print(smaller[i]+\\\" \\\");\\n i++;\\n j++;\\n } else if (smaller[i] < bigger[j]) {\\n i++;\\n } else {\\n j++;\\n }\\n\\n\\n }\\n }\\n\\n\\n }\",\n \"public void splitQuery(){\\n for (int i=0;i<stemmed_query.size();i++){\\n String stemmed_term = stemmed_query.get(i);\\n for (int j=0;j<num_slave_client_threads;j++){\\n if (stemmed_term.compareTo(ServerThread.start_terms[j]) >= 0 && stemmed_term.compareTo(ServerThread.end_terms[j]) <= 0){\\n slave_queries.set(j, slave_queries.get(j)+\\\" \\\"+stemmed_term);\\n break;\\n }\\n }\\n }\\n }\",\n \"public int[] intersection(int[] nums1, int[] nums2) {\\n \\n HashSet<Integer> set = new HashSet<>();\\n ArrayList<Integer> inter = new ArrayList<>();\\n if(nums1.length > nums2.length)\\n {\\n for(int i = 0; i < nums1.length ;i ++)\\n set.add(nums1[i]);\\n\\n for(int i = 0; i < nums2.length ;i ++)\\n if(set.contains(nums2[i])&& !inter.contains(nums2[i]))\\n inter.add(nums2[i]);\\n }\\n else {\\n for(int i = 0; i < nums2.length ;i ++)\\n set.add(nums2[i]);\\n\\n for(int i = 0; i < nums1.length ;i ++)\\n if(set.contains(nums1[i]) && !inter.contains(nums1[i]))\\n inter.add(nums1[i]);\\n }\\n\\n int [] arr = new int[inter.size()];\\n for(int i = 0; i < arr.length ;i ++)\\n arr[i] = inter.get(i);\\n return arr;\\n\\n }\",\n \"private double intersection(HardClustering hard1, int comm1,\\n HardClustering hard2, int comm2) {\\n final TIntArrayList duplicate = new TIntArrayList(hard1.members(comm1));\\n duplicate.retainAll(hard2.members(comm2));\\n\\n return duplicate.size();\\n }\",\n \"private MetaSparqlRequest createQueryMT2() {\\n\\t\\treturn createQueryMT1();\\n\\t}\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.69769245","0.6333911","0.5428158","0.5357878","0.530351","0.5271801","0.51897854","0.51882815","0.51229084","0.50980556","0.5068206","0.50642776","0.506333","0.5041754","0.502724","0.5019483","0.5001322","0.49797273","0.49742696","0.4948692","0.49297482","0.49296632","0.49152625","0.4902071","0.48992515","0.4899249","0.48972848","0.4883559","0.4882021","0.4875533","0.48731148","0.48700714","0.48564497","0.4843899","0.48435736","0.48327523","0.4831181","0.48270538","0.48237234","0.48167416","0.4814523","0.48048198","0.47797883","0.47787896","0.47694135","0.47526503","0.47478363","0.4747363","0.47392878","0.47233588","0.47124588","0.47023365","0.4699569","0.46981785","0.4698125","0.46893966","0.4688012","0.46839514","0.46839514","0.46839514","0.46827263","0.467099","0.4662867","0.46601397","0.46526662","0.4639742","0.463964","0.46331403","0.46272334","0.46251887","0.46240312","0.46211112","0.46203515","0.46168703","0.46087405","0.46031943","0.45942703","0.4590699","0.45890477","0.4579803","0.45760468","0.45689905","0.45682594","0.45636377","0.4560762","0.4559033","0.4556336","0.45493516","0.45457223","0.4544857","0.45397946","0.45373127","0.45368826","0.45359004","0.4534447","0.45327792","0.45292738","0.45257157","0.45240524","0.4520284"],"string":"[\n \"0.69769245\",\n \"0.6333911\",\n \"0.5428158\",\n \"0.5357878\",\n \"0.530351\",\n \"0.5271801\",\n \"0.51897854\",\n \"0.51882815\",\n \"0.51229084\",\n \"0.50980556\",\n \"0.5068206\",\n \"0.50642776\",\n \"0.506333\",\n \"0.5041754\",\n \"0.502724\",\n \"0.5019483\",\n \"0.5001322\",\n \"0.49797273\",\n \"0.49742696\",\n \"0.4948692\",\n \"0.49297482\",\n \"0.49296632\",\n \"0.49152625\",\n \"0.4902071\",\n \"0.48992515\",\n \"0.4899249\",\n \"0.48972848\",\n \"0.4883559\",\n \"0.4882021\",\n \"0.4875533\",\n \"0.48731148\",\n \"0.48700714\",\n \"0.48564497\",\n \"0.4843899\",\n \"0.48435736\",\n \"0.48327523\",\n \"0.4831181\",\n \"0.48270538\",\n \"0.48237234\",\n \"0.48167416\",\n \"0.4814523\",\n \"0.48048198\",\n \"0.47797883\",\n \"0.47787896\",\n \"0.47694135\",\n \"0.47526503\",\n \"0.47478363\",\n \"0.4747363\",\n \"0.47392878\",\n \"0.47233588\",\n \"0.47124588\",\n \"0.47023365\",\n \"0.4699569\",\n \"0.46981785\",\n \"0.4698125\",\n \"0.46893966\",\n \"0.4688012\",\n \"0.46839514\",\n \"0.46839514\",\n \"0.46839514\",\n \"0.46827263\",\n \"0.467099\",\n \"0.4662867\",\n \"0.46601397\",\n \"0.46526662\",\n \"0.4639742\",\n \"0.463964\",\n \"0.46331403\",\n \"0.46272334\",\n \"0.46251887\",\n \"0.46240312\",\n \"0.46211112\",\n \"0.46203515\",\n \"0.46168703\",\n \"0.46087405\",\n \"0.46031943\",\n \"0.45942703\",\n \"0.4590699\",\n \"0.45890477\",\n \"0.4579803\",\n \"0.45760468\",\n \"0.45689905\",\n \"0.45682594\",\n \"0.45636377\",\n \"0.4560762\",\n \"0.4559033\",\n \"0.4556336\",\n \"0.45493516\",\n \"0.45457223\",\n \"0.4544857\",\n \"0.45397946\",\n \"0.45373127\",\n \"0.45368826\",\n \"0.45359004\",\n \"0.4534447\",\n \"0.45327792\",\n \"0.45292738\",\n \"0.45257157\",\n \"0.45240524\",\n \"0.4520284\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.6708024"},"document_rank":{"kind":"string","value":"1"}}},{"rowIdx":13894,"cells":{"query":{"kind":"string","value":"[NEW] Sorts a set of postings list according to the document frequency"},"document":{"kind":"string","value":"public LinkedList<PostingsList> sortByIncreasingFrequency(LinkedList<PostingsList> l){\n Collections.sort(l, new Comparator<PostingsList>(){\n @Override\n public int compare(PostingsList p1, PostingsList p2){\n if(p1.size() < p2.size()){\n return -1;\n }\n if(p1.size() > p2.size()){\n return 1;\n }\n return 0;\n }\n });\n return l;\n }"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["public void sort() {\n documents.sort();\n }","public void sortDocumentsByDocnos() {\n order = new int[mDocSet.length];\n mDocSet_tmp = new double[mDocSet.length];\n accumulated_scores_tmp = new float[mDocSet.length];\n\n for (int i = 0; i < order.length; i++) {\n order[i] = i;\n mDocSet_tmp[i] = mDocSet[i];\n accumulated_scores_tmp[i] = accumulated_scores[i];\n }\n\n ivory.smrf.model.constrained.ConstraintModel.Quicksort(mDocSet_tmp, order, 0, order.length - 1);\n\n for (int i = 0; i < order.length; i++) {\n mDocSet[i] = (int) mDocSet_tmp[i];\n accumulated_scores[i] = accumulated_scores_tmp[order[i]];\n }\n }","private void buildPostingList(){\n boolean isEndOfList = false;\n// boolean moveToNextDoc = false;\n ArrayList<Integer> tempList = new ArrayList<>(); // tempList to hold doc wise posting List\n\n while(!isEndOfList){\n boolean skipDoc = false;\n int doc = children.get(0).nextCandidate();\n if(doc == -1) {\n // End of list. No more windows to collect. Exit.\n isEndOfList = true; break;\n }\n int distance = super.getDiskReader().getRetrievedDocToLengthMap().get(doc);\n // Check if doc exists in all other children.\n // If it exists, skip to that Document.\n for(QueryNode child : children){\n /* skipToDoc skips the pointer in child node to the current doc.\n */\n if(!child.skipToDoc(doc)) {\n skipDoc = true;\n break;\n }\n\n }\n if(!skipDoc) {\n /* From here, all nodes have the document. Proceed to calculating number of windows in doc */\n\n tempList.clear();\n tempList.add(doc); //\n tempList.add(0); // doc term frequency. We will update this later.\n int fkid = 0; // doc term frequency tracker\n// int i = startTermIndex+1;\n int minPosIndex = 0; // holds the index of the node which has current minimum Pos\n int minPos = children.get(minPosIndex).nextPos(); // initialize min Pos.\n boolean isEndOfDoc = false;\n while(!isEndOfDoc) {\n if(minPos == -1) break; // End of document. Move to next doc\n for (int i = 0; i < children.size(); i++) {\n int pos = children.get(i).nextPos();\n if(pos == -1){\n isEndOfDoc = true;\n break;\n }\n if (pos < minPos) {\n minPos = pos;\n minPosIndex = i;\n }\n }\n if(isEndOfDoc) break;\n /* Check for window size against min pos */\n for (int i = 0; i < children.size(); i++) {\n int pos = children.get(i).nextPos();\n\n if (pos - minPos < distance) {\n // Valid candidate so far.\n // check if last term.\n if (i == children.size() - 1) {\n tempList.add(children.get(minPosIndex).nextPos());\n fkid++;\n // update all the child node pointers to next position. No double dipping\n for(QueryNode child : children)\n child.updatePos();\n\n\n }\n\n } else {\n // Candidate failed.\n // update minimum position to next pos and repeat process\n children.get(minPosIndex).updatePos();\n minPos = children.get(minPosIndex).nextPos();\n break;\n\n }\n }\n\n }\n\n\n /* The document has been consumed. If the temp List size is > 2, we have collected windows.\n Add them to the posting list.\n */\n if (tempList.size() > 2) {\n tempList.set(1, fkid);\n cqi += fkid;\n postingList.addAll(new ArrayList<>(tempList));\n }\n }\n// if(moveToNextDoc) continue;\n children.get(0).updateToNextDoc();\n }\n }","public List<DictionaryData> frequencyOrderedList() {\n List<DictionaryData> wordlist = alphabeticalList();\r\n\r\n //using insertion sort\r\n int j;\r\n DictionaryData k;\r\n for (int i = 1; i < wordlist.size(); i++) {\r\n j = i;\r\n\r\n while (j > 0 && compare_dictdata(wordlist.get(j), wordlist.get(j - 1))) {\r\n k = wordlist.get(j);\r\n wordlist.set(j, wordlist.get(j - 1));\r\n wordlist.set(j - 1, k);\r\n j--;\r\n\r\n }\r\n //i++;\r\n }\r\n return wordlist;\r\n }","public PostingList(int df, int N)\n {\n documentFrequency = df;\n totalNoOfDocuments = N;\n }","public void sortCount() {\n\t\tfor(Entry<String, TreeMap<String, Integer>> entry:map.entrySet()){\r\n\t\t\tTreeMap<String, Integer> tmap = entry.getValue();\r\n\t\t\tList<Entry<String, Integer>> sorttmap = MapSort.sortMapByIntegerValue(tmap);\r\n\t\t\t int flag=0;\r\n for(Entry<String, Integer> word:sorttmap){ \r\n \tflag++;\r\n \tkeyword.add(word.getKey());\r\n// System.out.println(mapping.getKey()+\":\"+mapping.getValue()); \r\n \tif(flag==5)\r\n \t\tbreak;\r\n } \r\n\t\t}\r\n\t\r\n\t}","public static WordFrq[] sort(WordFrq b[]){\n WordFrq temp;\n int i=0;\n while (i < 3) {\n for (i = 1; i < 3; i++) {\n if (b[i-1].count > b[i].count) {\n temp = b[i];\n b[i] = b[i-1];\n b[i-1] = temp;\n break;\n }\n }\n }\n\n\n return b;\n\n\n\n\n\n }","private static void sortSlidesByNumberTags() {\n\t\tCollections.sort(slideList, new Comparator<Slide>() {\n\t\t\tpublic int compare(Slide s1, Slide s2) {\n\n\t\t\t\tInteger sS1 = s1.getTagList().size();\n\t\t\t\tInteger sS2 = s2.getTagList().size();\n\n\t\t\t\tint sComp = sS1.compareTo(sS2);\n\n\t\t\t\treturn -1 * sComp;\n\t\t\t}\n\t\t});\n\t}","public void sortWordTokens (String [] list, int count){\n \n String[] sortedWordsCopy = new String[count];\n \n \n //Makes a copy of list and stores it in sortedWordsCopy\n for (int i = 0; i < count; i++)\n sortedWordsCopy[i] = list[i];\n \n //Sorts sortedWordsCopy which is a copy of list\n Arrays.sort(sortedWordsCopy);\n \n //Copies the sorted list back out to list\n for (int i = 0; i < count; i++)\n list[i] = sortedWordsCopy[i];\n \n }","public void sortGivenArray_popularity() { \n int i, j, k; \n for(i = movieList.size()/2; i > 0; i /= 2) {\n for(j = i; j < movieList.size(); j++) {\n Movie key = movieList.get(j);\n for(k = j; k >= i; k -= i) {\n if(key.rents > movieList.get(k-i).rents) {\n movieList.set(k, movieList.get(k-i));\n } else {\n break; \n }\n }\n movieList.set(k, key);\n }\n } \n }","private static void sortPhotosByNumberTags() {\n\t\tCollections.sort(photoList, new Comparator<Photo>() {\n\t\t\tpublic int compare(Photo p1, Photo p2) {\n\n\t\t\t\tInteger s1 = p1.getTagList().size();\n\t\t\t\tInteger s2 = p2.getTagList().size();\n\n\t\t\t\tint sComp = s1.compareTo(s2);\n\n\t\t\t\treturn -1 * sComp;\n\t\t\t}\n\t\t});\n\t}","private void sortMedApts(List<MedicationAppointment> medApts2) {\n \t}","public void sortByQnNum() {\r\n\t\tfor (int j = 0; j < displayingList.size() - 1; j++) {\r\n\t\t\tfor (int i = 0; i < displayingList.size() - j - 1; i++) {\r\n\t\t\t\tif (displayingList.get(i).getQnNum() > displayingList.get(i + 1).getQnNum()) {\r\n\t\t\t\t\tswapPosition(displayingList, i, i + 1);\r\n\t\t\t\t}\r\n\t\t\t}\r\n\t\t}\r\n\t}","public static PriorityQueue<WordCount> sortWords(HashMap<String, Integer> counts){\n\t\tPriorityQueue<WordCount> words = new PriorityQueue<WordCount>(99999, new wordCountComparator());\n\t\tWordCount wc = null;\n\t\tfor(Map.Entry<String, Integer> entry : counts.entrySet()){\n\t\t\twc = new WordCount(entry.getKey(), entry.getValue());\n\t\t\twords.add(wc);\n\t\t}\n\t\treturn words;\n\t}","private static void sortNoun() throws Exception{\r\n\t\tBufferedReader[] brArray = new BufferedReader[ actionNumber ];\r\n\t\tBufferedWriter[] bwArray = new BufferedWriter[ actionNumber ];\r\n\t\tString line = null;\r\n\t\tfor(int i = 0; i < actionNameArray.length; ++i){\r\n\t\t\tSystem.out.println(\"sorting for \" + actionNameArray[ i ]);\r\n\t\t\tbrArray[ i ] = new BufferedReader( new FileReader(TFIDF_URL + actionNameArray[ i ] + \".tfidf\"));\r\n\t\t\tHashMap<String, Double> nounTFIDFMap = new HashMap<String, Double>();\r\n\t\t\tint k = 0;\r\n\t\t\t// 1. Read tfidf data\r\n\t\t\twhile((line = brArray[ i ].readLine())!=null){\r\n\t\t\t\tnounTFIDFMap.put(nounList.get(k), Double.parseDouble(line));\r\n\t\t\t\tk++;\r\n\t\t\t}\r\n\t\t\tbrArray[ i ].close();\r\n\t\t\t// 2. Rank according to tfidf\r\n\t\t\tValueComparator bvc = new ValueComparator(nounTFIDFMap);\r\n\t\t\tTreeMap<String, Double> sortedMap = new TreeMap<String, Double>(bvc);\r\n\t\t\tsortedMap.putAll(nounTFIDFMap);\r\n\t\t\t\r\n\t\t\t// 3. Write to disk\r\n\t\t\tbwArray[ i ] = new BufferedWriter(new FileWriter( SORTED_URL + actionNameArray[ i ] + \".sorted\"));\r\n\t\t\tfor(String nounKey : sortedMap.keySet()){\r\n\t\t\t\tbwArray[ i ].append(nounKey + \"\\t\" + nounTFIDFMap.get(nounKey) + \"\\n\");\r\n\t\t\t}\r\n\t\t\tbwArray[ i ].close();\r\n\t\t}\r\n\t}","static void sortByFreq(int arr[], int n){\n Map<Integer, Integer> map = new HashMap<>(); \n List<Integer> outputArray = new ArrayList<>(); \n \n // Assign elements and their count in the list and map \n for (int current : arr) { \n int count = map.getOrDefault(current, 0); \n map.put(current, count + 1); \n outputArray.add(current); \n } \n \n // Compare the map by value \n SortComparator comp = new SortComparator(map); \n \n // Sort the map using Collections CLass \n Collections.sort(outputArray, comp); \n \n // Final Output \n for (Integer i : outputArray) { \n System.out.print(i + \" \"); \n }\n }","private List<Article> orderArticles(List<Article> things){\n\t\t Comparator<Article> comparatorPrizes = new Comparator<Article>() {\n\t public int compare(Article x, Article y) {\n\t return (int) (x.getPrize() - y.getPrize());\n\t }\n\t };\n\t Collections.sort(things,comparatorPrizes); \n\t Collections.reverse(things);\n\t return things;\n\t }","public void sortByTagCount() {\r\n this.addSortField(\"\", \"*\", SORT_DESCENDING, \"count\");\r\n }","public void sort() {\n\t\tArrays.sort(contactList, 0, contactCounter);\n\t}","public static void sortByPlaceCount(List<Apartment> apartments) {\n Collections.sort(apartments, SORT_BY_PLACE_COUNT);\n }","public String frequencySort(String s) {\n\n\t\t// prepare a frequency map\n\t\tMap<Character, Integer> m = new HashMap<Character, Integer>();\n\t\tfor (char c : s.toCharArray())\n\t\t\tm.put(c, m.getOrDefault(c, 0) + 1);\n\n\t\tPriorityQueue<CKEntry1> pq = new PriorityQueue<>();\n\t\tfor (Entry<Character, Integer> e : m.entrySet()) {\n\t\t\tpq.add(new CKEntry1(e.getKey(), e.getValue()));\n\t\t}\n\t\t\n\t\t// prepare the output now\n\t\tStringBuilder sb = new StringBuilder();\n\t\twhile(!pq.isEmpty()) {\n\t\t\tCKEntry1 temp = pq.poll();\n\t\t\tchar[] tempC = new char[temp.count];\n\t\t\tArrays.fill(tempC, temp.c); // repeat c count' times\n\t\t\tsb.append(tempC);\n\t\t}\n\t\t\n\t\treturn sb.toString();\n\n\t}","protected HashMap<String,Double> rank(ArrayList<String> queryPostingLines, ArrayList<String> query){\n HashMap<String,HashMap<String,Integer>> queryWordsTFPerDoc = computeTFForQueryWords(queryPostingLines);\n ArrayList<String> retrievedDocuments = new ArrayList<>(queryWordsTFPerDoc.keySet());\n HashMap<String,Double> rankedDocs = new HashMap<>();\n\n for(String doc : retrievedDocuments){\n HashMap<String,Integer> docTFs = queryWordsTFPerDoc.get(doc);\n double rank = 0.3*rankByBM25(query,doc,docTFs) + 0.7*rankByPosition(query,doc,queryPostingLines);// - rankByCosSim(query,doc,docTFs);\n rankedDocs.put(doc,rank);\n }\n rankedDocs = sortByValue(rankedDocs);\n ArrayList<String> docsAfterSort = new ArrayList<>(rankedDocs.keySet());\n HashMap<String,Double> docsToRetrieve = new HashMap<>();\n int i=0;\n for(String doc: docsAfterSort){\n docsToRetrieve.put(documentDetails.get(doc)[0],rankedDocs.get(doc));\n i++;\n if(i == 50)\n break;\n }\n return docsToRetrieve;\n }","private static void SortHash(HashMap<String,ArrayList<input>> hashMap,Distribution list)\n\t{\n\t\tCollections.sort(list.First, new Comparator<input>() {\n\t\t public int compare(input one, input other) {\n\t\t \tif(one.sum>other.sum)\n\t\t \t{\n\t\t \t\treturn 1;\n\t\t \t}\n\t\t \telse\n\t\t \t{\n\t\t \t\treturn -1;\n\t\t \t}\n\t\t }\n\t\t}); \n\t\tCollections.sort(list.Second, new Comparator<input>() {\n\t\t public int compare(input one, input other) {\n\t\t \tif(one.sum>other.sum)\n\t\t \t{\n\t\t \t\treturn 1;\n\t\t \t}\n\t\t \telse\n\t\t \t{\n\t\t \t\treturn -1;\n\t\t \t}\n\t\t }\n\t\t}); \n\t\tCollections.sort(list.Third, new Comparator<input>() {\n\t\t public int compare(input one, input other) {\n\t\t \tif(one.sum>other.sum)\n\t\t \t{\n\t\t \t\treturn 1;\n\t\t \t}\n\t\t \telse\n\t\t \t{\n\t\t \t\treturn -1;\n\t\t \t}\n\t\t }\n\t\t}); \n\t\tCollections.sort(list.Fourth, new Comparator<input>() {\n\t\t public int compare(input one, input other) {\n\t\t \tif(one.sum>other.sum)\n\t\t \t{\n\t\t \t\treturn 1;\n\t\t \t}\n\t\t \telse\n\t\t \t{\n\t\t \t\treturn -1;\n\t\t \t}\n\t\t }\n\t\t}); \n\t\tCollections.sort(list.Fifth, new Comparator<input>() {\n\t\t public int compare(input one, input other) {\n\t\t \tif(one.sum>other.sum)\n\t\t \t{\n\t\t \t\treturn 1;\n\t\t \t}\n\t\t \telse\n\t\t \t{\n\t\t \t\treturn -1;\n\t\t \t}\n\t\t }\n\t\t}); \n\t\tCollections.reverse(list.First);\n\t\tCollections.reverse(list.Second);\n\t\tCollections.reverse(list.Third);\n\t\tCollections.reverse(list.Fourth);\n\t\tCollections.reverse(list.Fifth);\n\t\tputInHashMap(hashMap,list);\n\t}","protected void sort() {\n\n\t\tCollections.sort(this.myRRList);\n\t}","public static void main(String[] args) {\n\r\n\t\tint arr[]={2, 3, 2, 4, 5, 12, 2, 3, 3, 3, 12};\r\n\t\tMap<Integer,Data> map = new HashMap<>();\r\n\t\tfor(int a :arr)\r\n\t\t{\r\n\t\t\tif(map.containsKey(a))\r\n\t\t\t{\r\n\t\t\t\tmap.get(a).incrementFrequency();\r\n\t\t\t}\r\n\t\t\telse\r\n\t\t\t{\r\n\t\t\t\tmap.put(a, new Data(a));\r\n\t\t\t}\r\n\t\t}\r\n\t\t\r\n\t\t\r\n\t\t\r\n\t\tSet<Data> sortedData = new TreeSet<>(map.values());\r\n\t\tList<Integer> result = new ArrayList<>();\r\n\t\tfor(Data d : sortedData)\r\n\t\t{\r\n\t\t\tfor(int i=0;i<d.frequency;i++)\r\n\t\t\t\tresult.add(d.number);\r\n\t\t}\r\n\t\tSystem.out.println(result);\r\n\t}","public void sortAppointments() {\n reminders = sort(reminders);\n followup = sort(followup);\n }","public static void rankFiles(Hashtable<?, Integer> fname, int numberOfOccurrences) \r\n\t{\n\t\tArrayList<Map.Entry<?, Integer>> arrayList = new ArrayList(fname.entrySet());\r\n\r\n\t\tCollections.sort(arrayList, new Comparator<Map.Entry<?, Integer>>() \r\n\t\t{\r\n\t\t\tpublic int compare(Map.Entry<?, Integer> obj1, Map.Entry<?, Integer> obj2) \r\n\t\t\t{\r\n\t\t\t\treturn obj1.getValue().compareTo(obj2.getValue());\r\n\t\t\t}\r\n\t\t});\r\n\r\n\t\tCollections.reverse(arrayList);\r\n\r\n\t\tif (numberOfOccurrences > 0) \r\n\t\t{\r\n\t\t\tSystem.out.println(\"\\n------Top 10 search results-----\\n\");\r\n\r\n\t\t\tint my_number = 10;\r\n\t\t\tint j = 1;\r\n\t\t\twhile (arrayList.size() > j && my_number > 0) \r\n\t\t\t{\r\n\t\t\t\tSystem.out.println(\"(\" + j + \") \" + arrayList.get(j) + \" times \");\r\n\t\t\t\tj++;\r\n\t\t\t\tmy_number--;\r\n\t\t\t}\r\n\t\t} \r\n\t}","public String[] topHotWords( int count ){\r\n //If the number put in the arguments is greater than the number of distinct hotwords\r\n //in the document, limit it to distinctCount\r\n if (count > distinctCount()){\r\n count = distinctCount();\r\n }\r\n //Creating the array that will hold all the hotwords in order of number of appearances \r\n String[] topWord = new String[words.size()];\r\n //This is the subset of the array above that will return the amount specified by the count argument\r\n String[] output = new String[count];\r\n //Fills the array with blank strings\r\n Arrays.fill(topWord, \"\");\r\n //Iterator for moving through topWord for assignment\r\n int iterator = 0;\r\n //Loop through every hotword in words and puts those words in topWord\r\n for(String key: words.keySet()){\r\n topWord[iterator] = key;\r\n iterator++;\r\n }\r\n //Sorts the words in topword\r\n for(int i = 0; i < words.size(); i++){\r\n for(int j = words.size()-1; j > 0; j-- ){\r\n \r\n if(count(topWord[j]) > count(topWord[i])){\r\n String temp = topWord[i];\r\n topWord[i] = topWord[j];\r\n topWord[j] = temp;\r\n }\r\n \r\n }\r\n }\r\n //Does a secondary check to be certain all words are in proper appearance number order\r\n for(int i = words.size()-1; i >0; i--){\r\n if(count(topWord[i]) > count(topWord[i-1])){\r\n String temp = topWord[i];\r\n topWord[i] = topWord[i-1];\r\n topWord[i-1] = temp;\r\n }\r\n }\r\n //Orders the words with the same number of appearances by order of appearance in the document\r\n for (int i = 0; i < words.size(); i++){\r\n for(int j = i+1; j < words.size(); j++){\r\n if (count(topWord[i]) == count(topWord[j])){\r\n if (consec.indexOf(topWord[j]) < consec.indexOf(topWord[i])){\r\n String temp = topWord[i];\r\n topWord[i] = topWord[j];\r\n topWord[j] = temp;\r\n }\r\n }\r\n }\r\n }\r\n //Gets the subset requested for return\r\n for (int i = 0; i < count; i++){\r\n output[i] = topWord[i];\r\n }\r\n return output;\r\n\t}","public void getWordFrequency(ArrayList<String> out_words, ArrayList<Integer> out_counts) {\n //... Put in ArrayList so sort entries by frequency\n ArrayList<Map.Entry<String, MutableInteger>> entries =\n new ArrayList<Map.Entry<String, MutableInteger>>(wordFrequency.entrySet());\n Collections.sort(entries, new ComparatorFrequency());\n\n //... Add word and frequency to parallel output ArrayLists.\n for (Map.Entry<String, MutableInteger> ent : entries) {\n out_words.add(ent.getKey());\n out_counts.add(ent.getValue().getValue());\n }\n }","@Override\n public void sort() {\n\n List<Doctor> unsortedDocs = this.doctors;\n\n Collections.sort(unsortedDocs, new Comparator<Doctor>() {\n @Override\n public int compare(Doctor a, Doctor b) {\n //Compare first name for doctors and re-arrange list\n return a.getFirstName().compareTo(b.getFirstName());\n }\n });\n \n this.doctors = unsortedDocs;\n\n }","private List<List<Record>> sortRecordsBy(List<Record> unsortedRecords, RankingType rankingType) {\n Comparator<Long> comparator = rankingType.isDescending()\n ? Comparator.reverseOrder()\n : Comparator.naturalOrder();\n SortedMap<Long, List<Record>> scoreGroups = new TreeMap<>(comparator);\n for (Record record : unsortedRecords) {\n Long score = rankingType.getScoreFunction().apply(record);\n if (scoreGroups.containsKey(score)) {\n scoreGroups.get(score).add(record);\n } else {\n scoreGroups.put(score, new LinkedList<>());\n scoreGroups.get(score).add(record);\n }\n }\n\n return new ArrayList<>(scoreGroups.values());\n }","Results sortResults(FilterSpecifier.ListBy listBy, SortSpecifier sortspec) throws SearchServiceException;","void documentFrequncy(Set<String> features,\n int index,\n int troush\n ) {\n for (String str : features) {\n switch (index) {\n case 1:\n for (int i = 0; i < count1; i++) {\n if (economydocument[i].contains(str)) {\n e++;\n }\n }\n if (e > troush) {\n documntfrequencyeco.put(str, e);\n }\n e = 0;\n break;\n case 2:\n for (int i = 0; i < count2; i++) {\n if (educationdocument[i].contains(str)) {\n e++;\n }\n }\n if (e > troush) {\n documntfrequencyedu.put(str, e);\n }\n e = 0;\n break;\n case 3:\n for (int i = 0; i < count3; i++) {\n if (sportdocument[i].contains(str)) {\n e++;\n }\n }\n if (e > troush) {\n documntfrequencyspo.put(str, e);\n }\n e = 0;\n break;\n case 4:\n for (int i = 0; i < count4; i++) {\n if (culturedocument[i].contains(str)) {\n e++;\n }\n }\n if (e > troush) {\n documntfrequencycul.put(str, e);\n }\n e = 0;\n break;\n case 5:\n for (int i = 0; i < count5; i++) {\n if (accedentdocument[i].contains(str)) {\n e++;\n }\n }\n if (e > troush) {\n documntfrequencyaccid.put(str, e);\n }\n e = 0;\n break;\n case 6:\n for (int i = 0; i < count6; i++) {\n if (environmntaldocument[i].contains(str)) {\n e++;\n }\n }\n if (e > troush) {\n documntfrequencyenv.put(str, e);\n }\n e = 0;\n break;\n case 7:\n for (int i = 0; i < count7; i++) {\n if (foreign_affairdocument[i].contains(str)) {\n e++;\n }\n }\n if (e > troush) {\n documntfrequencydep.put(str, e);\n }\n e = 0;\n break;\n case 8:\n for (int i = 0; i < count8; i++) {\n if (law_justicedocument[i].contains(str)) {\n e++;\n }\n }\n if (e > troush) {\n documntfrequencylaw.put(str, e);\n }\n e = 0;\n break;\n case 9:\n for (int i = 0; i < count9; i++) {\n if (agriculture[i].contains(str)) {\n e++;\n }\n }\n if (e > troush) {\n documntfrequencyagri.put(str, e);\n }\n e = 0;\n break;\n case 10:\n for (int i = 0; i < count10; i++) {\n if (politicsdocument[i].contains(str)) {\n e++;\n }\n }\n if (e > troush) {\n documntfrequencypoltics.put(str, e);\n }\n e = 0;\n break;\n// case 11:\n//\n// for (int i = 0; i < count11; i++) {\n// if (social_affairsdocument[i].contains(str)) {\n// e++;\n// }\n// }\n// if (e > troush) {\n// documntfrequencysocial.put(str, e);\n// }\n// e = 0;\n// break;\n case 11:\n for (int i = 0; i < count12; i++) {\n if (science_technologydocument[i].contains(str)) {\n e++;\n }\n }\n\n if (e > troush) {\n documntfrequencysci.put(str, e);\n }\n e = 0;\n break;\n case 12:\n for (int i = 0; i < count13; i++) {\n if (healthdocument[i].contains(str)) {\n e++;\n }\n }\n if (e > troush) {\n documntfrequencyhel.put(str, e);\n }\n e = 0;\n break;\n case 13:\n for (int i = 0; i < count14; i++) {\n if (army[i].contains(str)) {\n e++;\n }\n }\n\n if (e > troush) {\n documntfrequencyarmy.put(str, e);\n }\n e = 0;\n break;\n default:\n break;\n }\n\n }\n }","public void sortKnowledgeBase()\n {\n int i;\n Random random;\n String aPredicate;\n StringTokenizer tokenizer;\n //------------\n random = new Random();\n i = 0;\n while (i < knowledgeBase.size())\n {\n aPredicate = knowledgeBase.get(i).commitments.get(0).predicate;\n tokenizer = new StringTokenizer(aPredicate,\"(), \");\n if(tokenizer.nextToken().equals(\"secuencia\"))\n knowledgeBase.get(i).priority = random.nextInt(100);\n //end if\n else\n knowledgeBase.get(i).priority = random.nextInt(10000);\n //end else\n i = i + 1;\n }//end while\n Collections.sort(knowledgeBase);\n }","public static void DocumentFrequencies() throws FileNotFoundException {\n for (Entry<String, List<Integer>> entry : dictionary.entrySet()) {\n List<Integer> termfrequency = new ArrayList<>();\n\n termfrequency = entry.getValue();\t// getting each word's termfrequency list\n int i = 0;\n termfrequency.add(0); \t\t\t//maintaining documentfrequency at the 57th index\n Integer documentFrequency = termfrequency.get(totaldocument+1);\n while(i<56) { //iterate 0 to 55 all speeches term frequency\n if(termfrequency.get(i)>0) {\t\t//increment document frequency of that word if termfrequency is greater than 0.0\n documentFrequency++;\t\t\t//increment document frequency\n }\n i++;\t\t//increment index\n }\n termfrequency.set(57, documentFrequency);\t//re-set the documentfrequency and save the current maintained document frequency from 0 to calculated value\n dictionary.put(entry.getKey(), termfrequency);\t\t// place the incremented final value of that word back to the same list in dictionary hashmap\n }\n //save();\n }","private static String frequencySort(String s) {\n if (s == null || s.isEmpty()) { return s; }\n\n int[] freq = new int[256];\n for (char c : s.toCharArray()) {\n freq[c]++;\n }\n\n PriorityQueue<Pair<Character, Integer>> pq = new PriorityQueue<>((a, b) -> b.getValue() - a.getValue());\n for (int i = 0; i < freq.length; i++) {\n if (freq[i] == 0) { continue; }\n Pair<Character, Integer> pair = new Pair<>((char) (i), freq[i]);\n pq.offer(pair);\n }\n\n StringBuilder sb = new StringBuilder();\n while (!pq.isEmpty()) {\n Pair<Character, Integer> pair = pq.poll();\n for (int i = 0; i < pair.getValue(); i++) {\n sb.append(pair.getKey());\n }\n }\n return sb.toString();\n }","public void sortByTopic() {\r\n\t\tfor (int i = 1; i < displayingList.size(); i++) {\r\n\t\t\tQuestion temp = displayingList.get(i);\r\n\t\t\tfor (int j = i - 1; j >= 0; j--) {\r\n\t\t\t\tif (String.CASE_INSENSITIVE_ORDER.compare(temp.getTopic(), displayingList.get(j).getTopic()) < 0) {\r\n\t\t\t\t\tdisplayingList.set(j + 1, displayingList.get(j));\r\n\t\t\t\t} else {\r\n\t\t\t\t\tdisplayingList.set(j + 1, temp);\r\n\t\t\t\t\tbreak;\r\n\t\t\t\t}\r\n\t\t\t\tdisplayingList.set(j, temp);\r\n\t\t\t}\r\n\t\t}\r\n\t}","private void sort() {\n ScoreComparator comparator = new ScoreComparator();\n Collections.sort(scores, comparator);\n }","private void updateDocPostingList(int docId){\n int i = getIndexForDocument(docId);\n if(i==-1){\n // document does not exist in posting list. Error out.\n System.err.println(\"Document not in List\");\n updateDocPostingList(this.postingList.get(0));\n }\n int size = this.postingList.get(i+1);\n this.docPostingList = new int[size];\n int k = 0;\n for(int j = i+2; j<size+i+2;j++)\n this.docPostingList[k++] = this.postingList.get(j);\n this.pos = 0;\n\n }","private List<? extends Publication> sortPublicationsAfterTitle(Collection<? extends Publication> publicationList) {\n\n return publicationList.stream().sorted(Comparator.comparing(Publication::getTitle)).collect(Collectors.toList());\n }","void comparatorSort() {\n Collections.sort(vendor, Vendor.sizeVendor); // calling collection sort method and passing list and comparator variables\r\n for (HDTV item : vendor) { //looping arraylist\r\n System.out.println(\"Brand: \" + item.brandname + \" Size: \" + item.size);\r\n }\r\n }","private void sort() {\n Collections.sort(mEntries, new Comparator<BarEntry>() {\n @Override\n public int compare(BarEntry o1, BarEntry o2) {\n return o1.getX() > o2.getX() ? 1 : o1.getX() < o2.getX() ? -1 : 0;\n }\n });\n }","public HashMap<Integer, Integer> readFreqPosting(IndexReader indexReader, String fieldName, String term) throws IOException {\n\n\t\tHashMap<Integer, Integer> listOfFreqSortedByDocID = new HashMap<>();\n\t\tSystem.out.printf( \"%-10s%-15s%-6s\\n\", \"DOCID\", \"URL\", \"FREQ\" );//Reads the posting list of the term in a specific index field. You need to encode the term into a BytesRef object, which is the internal representation of a term used by Lucene.\n\t\tPostingsEnum posting = MultiFields.getTermDocsEnum( indexReader, fieldName, new BytesRef( term ), PostingsEnum.FREQS );\n\n\t\tif ( posting != null ) { // if the term does not appear in any document, the posting object may be null\n\t\t\tint docid;\n\t\t\twhile ( ( docid = posting.nextDoc() ) != PostingsEnum.NO_MORE_DOCS ) {//Each time you call posting.nextDoc(), it moves the cursor of the posting list to the next position and returns the docid of the current entry (document). Note that this is an internal Lucene docid. It returns PostingsEnum.NO_MORE_DOCS if you have reached the end of the posting list.\n\t\t\t\tString url = getDocno( indexReader, \"url\", docid );\n\t\t\t\tint freq = posting.freq(); // get the frequency of the term in the current document\n\t\t\t\tlistOfFreqSortedByDocID.put(docid, freq);\n\t\t\t\tSystem.out.printf( \"%-10d%-15s%-6d\\n\", docid, url, freq );\n\t\t\t}\n\t\t}\n\n\t\treturn listOfFreqSortedByDocID;\n\t}","public static void main(String args[]){\r\n\t\t\r\n\t\t\r\n\t\tint arr[] = {2,5,2,8,5,6,8,8};\r\n\t\t\r\n\t\tMap<Integer, Integer> freqMap = new LinkedHashMap<Integer,Integer>();\r\n\t\t\r\n\t\tfor(int i = 0; i< arr.length;i++){\r\n\t\t\tif(freqMap.containsKey(arr[i])){\r\n\t\t\t\tint count = freqMap.get(arr[i]);\r\n\t\t\t\tfreqMap.put(arr[i],count + 1);\r\n\t\t\t}else{\r\n\t\t\t\tfreqMap.put(arr[i], 1);\r\n\t\t\t}\r\n\t\t}\r\n\t\t//2-2,5-2,6-1,8-3\r\n\t\t\r\n\t\tMap<Integer,ArrayList<Integer>> sortedList = new TreeMap<Integer, ArrayList<Integer>>(new Comparator<Integer>(){\r\n\r\n\t\t\t@Override\r\n\t\t\tpublic int compare(Integer arg0, Integer arg1) {\r\n\t\t\t\t// TODO Auto-generated method stub\r\n\t\t\t\treturn arg1.compareTo(arg0);\r\n\t\t\t}\r\n\t\t\t\r\n\t\t});\r\n\t\t\r\n\t\tfor(Entry<Integer, Integer> entry : freqMap.entrySet()){\r\n\t\t\tint key = entry.getKey();\r\n\t\t\tint val = entry.getValue();\r\n\t\t\tif(sortedList.containsKey(val)){\r\n\t\t\t\tArrayList<Integer> list = sortedList.get(val);\r\n\t\t\t\tfor(int j = 0; j<val ; j++)\r\n\t\t\t\t\tlist.add(key);\r\n\t\t\t}else{\r\n\t\t\t\tArrayList<Integer> list = new ArrayList<Integer>();\r\n\t\t\t\tfor(int j = 0; j<val ; j++)\r\n\t\t\t\t\tlist.add(key);\r\n\t\t\t\tsortedList.put(val, list);\r\n\t\t\t}\r\n\t\t\t\r\n\t\t}\r\n\t\t\r\n\t\tSystem.out.println(sortedList.values());\r\n\t\t\r\n\t\t\r\n\t\t\r\n\t\t\r\n\t}","public static String Sorts(Map<Integer,Double> docsInfo) {\n Map<Integer, Double> sorted = docsInfo.entrySet().stream().sorted(Map.Entry.comparingByValue()).collect(Collectors.toMap(e -> e.getKey(), e -> e.getValue(), (e1, e2) -> e2,\n LinkedHashMap::new));\n String ans = \"\";\n sorted = docsInfo\n .entrySet()\n .stream()\n .sorted(Collections.reverseOrder(Map.Entry.comparingByValue()))\n .collect(\n Collectors.toMap(Map.Entry::getKey, Map.Entry::getValue, (e1, e2) -> e2,\n LinkedHashMap::new));\n for(Map.Entry<Integer, Double> en : sorted.entrySet()) {\n ans = ans + (\"doc.Id ---> \" + en.getKey() +\"\\n\");\n }\n GUI.count = String.valueOf(sorted.size());\n return ans;\n }","public CountryList sortByCount() {\n\t\tCountryList sorted = new CountryList();\n\t\tfor (int i = 0; i < this.nextAvailable; i++)\n\t\t\tsorted.binInsert(new Country(this.countries.get(i)));\n\t\tsorted.totalCount = this.totalCount;\n\t\treturn sorted;\n\t}","SortComparator(Map<Integer, Integer> tFreqMap) { \n this.freqMap = tFreqMap; \n }","public static List<String> sortUniqueWords(HashMap<String, Integer> tracker, List<String> allWords) {\n List<Integer> frequency = new ArrayList<>(tracker.values());\n frequency.sort(Collections.reverseOrder());\n List<String> result = new ArrayList<>();\n\n while(!tracker.isEmpty()){\n for (String key : allWords) {\n if(frequency.size()!= 0 && frequency.get(0) == tracker.get(key)){\n frequency.remove(0);\n\n result.add(key + \" \" + tracker.get(key));\n tracker.remove(key);\n }\n\n }\n }\n return result;\n\n\n }","private List<StringCountDto> getSortedStatistics() {\n return STRING_STATISTICS.entrySet()\n .stream()\n .sorted(Map.Entry.<String, CounterInfo>comparingByValue().reversed())\n .map(entry -> new StringCountDto(entry.getKey(), entry.getValue().getCount()))\n .collect(Collectors.toList());\n }","public static void main(String[] args) {\n String s = \"9988777yyhhgfvvvvvvddsseeeeww3344\";\n System.out.println(frequencySort(s));\n }","private static HashMap<String,Integer> sortByEditDistance(String keyword, PreSearch ps) {\r\n\t\tHashMap<String, Integer> indexDistance = new HashMap<String,Integer>();\r\n\t\tIterator<Entry<String,HashSet<Integer>>> iterator = ps.index.entrySet().iterator();\r\n\t\twhile(iterator.hasNext()) \r\n\t\t{ \t\t\t\r\n\t\t\tMap.Entry<String, HashSet<Integer>> me = (Map.Entry<String, HashSet<Integer>>)iterator.next();\r\n\t\t\tString word = me.getKey().toString();\t\t\t\r\n\t\t\tint distance = Sequences.editDistance(word, keyword);\r\n\t\t\tif(distance<3 && distance!=0) {\r\n\t\t\t\tindexDistance.put(word, distance);\t\t\t\t\r\n\t\t\t}\r\n\t\t}\r\n\t\t\r\n\t\tHashMap<String,Integer> sortedDistance = SortResultsByRank.sortValues(indexDistance);\r\n\t\treturn sortedDistance;\r\n\t}","public static void getHotItems(int k) throws IOException {\r\n\t\twlist = new ArrayList();\r\n\t\twlist.clear();\r\n\t\tBufferedReader input = new BufferedReader(new FileReader(\r\n\t\t\t\t\"frequency.txt\"));\r\n\t\tString buff = input.readLine();\r\n\t\t// \"sssss#xxx\\n\"\r\n\t\twhile (buff != null) {\r\n\t\t\tString str[] = buff.split(\"#\");\r\n\t\t\tWord w = new Word(str[0]);\r\n\t\t\tw.setfreq(Integer.parseInt(str[1]));\r\n\t\t\twlist.add(w);\r\n\t\t\tbuff = input.readLine();\r\n\t\t}\r\n\t\tinput.close();\r\n\t\tsort(k);\r\n\t\tfor (int i = 0; i < k; i++) {\r\n\t\t\tSystem.out.print(wlist.get(i).getval() + \"|\");\r\n\t\t}\r\n\t}","public void sortElements(){\n\t\tgetInput();\n\t\tPeople[] all = countAndSort(people, 0, people.length-1);\n\t\t//PrintArray(all);\n\t\tSystem.out.println(InversionCount);\n\t}","public static void main(String[] args) {\n\n\t\tList<String> list = Arrays.asList(\"I\", \"Love\", \"Word\", \"I\", \"Love\");\n\t\tMap<String, Long> map = list.stream()\n\t\t\t\t.collect(Collectors.groupingBy(Function.identity(), Collectors.counting()));\n\t\t//map.entrySet().stream().sorted(Comparator.(Entry.comparingByValue()).thenComparing(Entry.comparingByKey()))\n\t\t// I - 2, \"Word\" -1, \"Love\"- 2\n\t\t\n\t}","private static void performSort(TestApp testApp) {\n testApp.testPartition();\n\n /*\n Date end = new Date();\n System.out.println(\"Sort ended @ \" + end.getTime());\n System.out.println(\"Total time = \" + (end.getTime() - start.getTime())/1000.0 + \" seconds...\");\n */\n }","public void sortMarkers() {\n\t\tCollections.sort(getMarkerSet().getMarkers(),\r\n\t\t\t\tnew MarkerTimeComparator());\r\n\t\t// log.debug(\"[sortMarkers]after: \" + getMarkerSet().getMarkers());\r\n\r\n\t}","private void printingSearchResults() {\n HashMap<Integer, Double> resultsMap = new HashMap<>();\n for (DocCollector collector : resultsCollector) {\n if (resultsMap.containsKey(collector.getDocId())) {\n double score = resultsMap.get(collector.getDocId()) + collector.getTermScore();\n resultsMap.put(collector.getDocId(), score);\n } else {\n resultsMap.put(collector.getDocId(), collector.getTermScore());\n }\n }\n List<Map.Entry<Integer, Double>> list = new LinkedList<>(resultsMap.entrySet());\n Collections.sort(list, new Comparator<Map.Entry<Integer, Double>>() {\n public int compare(Map.Entry<Integer, Double> o1,\n Map.Entry<Integer, Double> o2) {\n return (o2.getValue()).compareTo(o1.getValue());\n }\n });\n if (list.isEmpty())\n System.out.println(\"no match\");\n else {\n DecimalFormat df = new DecimalFormat(\".##\");\n for (Map.Entry<Integer, Double> each : list)\n System.out.println(\"docId: \" + each.getKey() + \" score: \" + df.format(each.getValue()));\n }\n\n }","private static void sortingArrayList() {\n Collections.sort(allMapData, new Comparator<MapDataModel>() {\n public int compare(MapDataModel d1, MapDataModel d2) {\n return valueOf(d1.getDateTime().compareTo(d2.getDateTime()));\n }\n });\n }","public void sort() {\r\n // sort the process variables\r\n Arrays.sort(pvValues, categoryComparator);\r\n fireTableDataChanged();\r\n }","private void sortDate()\n {\n for(int i = 0; i < movieList.size(); i++){\n for(int j = 1; j < movieList.size() - i; j++)\n {\n Movie a = movieList.get(j-1);\n Movie b = movieList.get(j);\n int result = a.getReleaseDate().compareTo(b.getReleaseDate());\n if( result < 0)\n {\n movieList.set(j-1, b);\n movieList.set(j, a);\n }\n else if(result == 0)\n {\n result = a.getTitle().compareTo(b.getTitle());\n if(result > 0)\n {\n movieList.set(j-1, b);\n movieList.set(j, a);\n }\n }\n }\n }\n }","private void sortByDate(List<Entry> entries) {\n\t\t\n\t\tCollections.sort(entries, new Comparator<Entry>() {\n\t\t\tpublic int compare(Entry o1, Entry o2) {\n\t\t\t if (o1.getTimestamp() == null || o2.getTimestamp() == null)\n\t\t\t return 0;\n\t\t\t return o1.getTimestamp().compareTo(o2.getTimestamp());\n\t\t\t }\n\t\t\t});\n\t}","public void sort()\n {\n\tstrack.sort((Node n1, Node n2) ->\n\t{\n\t if (n1.getCost() < n2.getCost()) return -1;\n\t if (n1.getCost() > n2.getCost()) return 1;\n\t return 0;\n\t});\n }","public Map<String, Integer> getWordFrequencies(SortOrder sortBy) {\n ArrayList<Map.Entry<String, MutableInteger>> entries =\n new ArrayList<Map.Entry<String, MutableInteger>>(wordFrequency.entrySet());\n if (sortBy == SortOrder.ALPHABETICALLY_ASCENDING) {\n Collections.sort(entries, SORT_ALPHABETICALLY_ASCENDING);\n } else {\n Collections.sort(entries, SORT_BY_FREQUENCY_DESCENDING);\n }\n \n Map<String, Integer> wordFrequencies = new HashMap<String, Integer>();\n ValueComparator bvc = new ValueComparator(wordFrequencies);\n TreeMap<String, Integer> sorted_map = new TreeMap(bvc);\n \n for (Map.Entry<String, MutableInteger> entry : entries) {\n wordFrequencies.put(entry.getKey(), entry.getValue().getInteger());\n }\n \n sorted_map.putAll(wordFrequencies);\n\n return sorted_map;\n }","public void listSort() {\n\t\tCollections.sort(cd);\n\t}","private static void sort(MongoCollection mongoCollection) {\n mongoCollection.find().sort(eq(\"name\", 1)).forEach(new Block<Document>() {\n public void apply(Document document) {\n System.out.println(document.toJson());\n }\n });\n }","void sort();","void sort();","public static void pageRankmain() {\n\t\t\t\n\t\t\tstopWordStore();\n\t\t\t//File[] file_read= dir.listFiles();\n\t\t\t//textProcessor(file_read);// Will be called from LinkCrawler\n\t\t\t//queryProcess();\n\t\t\t//System.out.println(\"docsave \"+ docsave);\n\t\t\t/*for ( Map.Entry<String, ArrayList<String>> entry : docsave.entrySet()) {\n\t\t\t String key = entry.getKey();\n\t\t\t List<String> values = entry.getValue();\n\t\t\t System.out.print(\"Key = \" + key);\n\t\t\t System.out.println(\" , Values = \"+ values);\n\t\t\t}*/\n\t\t\t//########## RESPOINSIBLE FOR CREATING INVERTED INDEX OF TERMS ##########\n\t\t\tfor(int i=0;i<vocabulary.size();i++) {\n\t\t\t\tint count=1;\n\t\t\t\tMap<String, Integer> nestMap = new HashMap<String, Integer>();\n\t\t\t\tfor ( Map.Entry<String, ArrayList<String>> entry : docsave.entrySet()) {\n\t\t\t\t String keyMain = entry.getKey();\n\t\t\t\t List<String> values = entry.getValue();\n\t\t\t\t if(values.contains(vocabulary.get(i)))\n\t\t\t\t \t{\n\t\t\t\t \tentryDf.put(vocabulary.get(i), count);//entryDf stores documents frequency of vocabulary word \\\\it increase the count value for specific key\n\t\t\t\t \tcount++;\n\t\t\t\t \t}\n\t\t\t\t \n\t\t\t\t nestMap.put(keyMain, Collections.frequency(values,vocabulary.get(i)));\n\t\t\t \t\n\t\t\t \t//System.out.println(\"VOC \"+ vocabulary.get(i)+ \" KeyMain \" +keyMain+ \" \"+ Collections.frequency(values,vocabulary.get(i)));\n\t\t\t\t\t}\n\t\t\t\t\ttfList.put(vocabulary.get(i), nestMap);\n\t\t\t}\n\t\t\t//########## RESPOINSIBLE FOR CREATING A MAP \"storeIdf\" TO STORE IDF VALUES OF TERMS ##########\n\t\t\tfor ( Map.Entry<String, Integer> endf : entryDf.entrySet()) {\n\t\t\t\tString keydf = endf.getKey();\n\t\t\t\tint valdf = endf.getValue();\n\t\t\t\t//System.out.print(\"Key = \" + \"'\"+keydf+ \"'\");\n\t\t\t //System.out.print(\" , Values = \"+ valdf);\n\t\t\t double Hudai = (double) (docsave.size())/valdf;\n\t\t\t //System.out.println(\"docsave size \"+docsave.size()+ \" valdf \"+ valdf + \" Hudai \"+ Hudai+ \" log Value1 \"+ Math.log(Hudai)+ \" log Value2 \"+ Math.log(2));\n\t\t\t double idf= Math.log(Hudai)/Math.log(2);\n\t\t\t storeIdf.put(keydf, idf);\n\t\t\t //System.out.print(\" idf-> \"+ idf);\n\t\t\t //System.out.println();\n\t\t\t} \n\t\t\t\n\t\t\t//############ Just for Printing ##########NO WORK HERE########\n\t\t\tfor (Map.Entry<String, Map<String, Integer>> tokTf : tfList.entrySet()) {\n\t\t\t\tString keyTf = tokTf.getKey();\n\t\t\t\tMap<String, Integer> valTF = tokTf.getValue();\n\t\t\t\tSystem.out.println(\"Inverted Indexing by Key Word = \" + \"'\"+keyTf+ \"'\");\n\t\t\t\tfor (Map.Entry<String, Integer> nesTf : valTF.entrySet()) {\n\t\t\t\t\tString keyTF = nesTf.getKey();\n\t\t\t\t\tInteger valTf = nesTf.getValue();\n\t\t\t\t\tSystem.out.print(\" Document Consists This Key Word = \" + \"'\"+ keyTF+ \"'\");\n\t\t\t\t\tSystem.out.println(\" , Term Frequencies in This Doc = \"+ valTf);\n\t\t\t\t} \n\t\t\t}\n\t\t\t//########### FOR CALCULATING DOCUMENT LENTH #############//\n\t\t\tfor ( Map.Entry<String, ArrayList<String>> entry_new : docsave.entrySet()) // Iterating Number of Documents\n\t\t\t{\n\t\t\t\tString keyMain_new = entry_new.getKey();\n\t\t\t\t//int countStop=0;\n\t\t\t\tdouble sum=0;\n\t\t\t\t for(Map.Entry<String, Map<String, Integer>> tokTf_new : tfList.entrySet()) // Iterating through the vocabulary\n\t\t\t\t { \n\t\t\t\t\t Map<String, Integer> valTF_new = tokTf_new.getValue();\n\t\t\t\t\t for (Map.Entry<String, Integer> nesTf_new : valTF_new.entrySet()) // Iterating Through the Documents\n\t\t\t\t\t {\n\t\t\t\t\t\t if(keyMain_new.equals(nesTf_new.getKey())) // Only doc name EQUAL with docsave name can enter here\n\t\t\t\t\t\t {\n\t\t\t\t\t\t\t double val = nesTf_new.getValue()* (Double) storeIdf.get(tokTf_new.getKey());\n\t\t\t\t\t\t\t sum = sum+ Math.pow(val, 2);\n\t\t\t\t\t\t }\n\t\t\t\t\t }\n\t\t\t\t\t \n\t\t\t\t\t //countStop++;\n\t\t\t\t }\n\t\t\t\t docLength.put(keyMain_new, Math.sqrt(sum));\n\t\t\t\t sum=0;\n\t\t\t}\n\t\t\t\n\t\t\t\n\t\t\tSystem.out.println(\"Document Length \"+ docLength);\n\t\t\t//System.out.println(\"tfList \"+tfList);\n\t\t\t\n\t\t\t //########### FOR CALCULATING QUERY LENTH #############///\n\t\t\t\tdouble qrySum=0;\n\t\t\t\t for(String qryTerm: queryList) // Iterating through the vocabulary\n\t\t\t\t {\n\t\t\t\t\t//entryQf.put(qryTerm, Collections.frequency(queryList,qryTerm));// VUl ase\n\t\t\t\t\t \n\t\t\t\t\t\t if(storeIdf.get(qryTerm) != null) \n\t\t\t\t\t\t {\n\t\t\t\t\t\t\t entryQf.put(qryTerm, Collections.frequency(queryList,qryTerm));\n\t\t\t\t\t\t\t double val = entryQf.get(qryTerm)* (Double) storeIdf.get(qryTerm);\n\t\t\t\t\t\t\t qrySum = qrySum+ Math.pow(val, 2);\n\t\t\t\t\t\t }\n\t\t\t\t\t System.out.println(qryTerm+\" \"+entryQf.get(qryTerm)+ \" \"+ (Double) storeIdf.get(qryTerm));\n\t\t\t\t }\n\t\t\t\t qrySum=Math.sqrt(qrySum);\n\t\t\t\t System.out.println(\"qrySum \" + qrySum);\n\t\t\t\t \n\t\t\t\t//########### FOR CALCULATING COSINE SIMILARITY #############///\n\t\t\t\t for ( Map.Entry<String, ArrayList<String>> entry_dotP : docsave.entrySet()) // Iterating Number of Documents\n\t\t\t\t\t{\n\t\t\t\t\t\tdouble sumProduct=0;\n\t\t\t\t\t\tdouble productTfIdf=0;\n\t\t\t\t\t\tString keyMain_new = entry_dotP.getKey(); //Geting Doc Name\n\t\t\t\t\t\t for(Map.Entry<String, Integer> qryTermItr : entryQf.entrySet()) // Iterating through the vocabulary\n\t\t\t\t\t\t {\n\t\t\t\t\t\t\t \n\t\t\t\t\t\t\t Map<String, Integer> matchTerm = tfList.get(qryTermItr.getKey()); // Getting a map of doc Names by a Query Term as value of tfList\n\n\t\t\t\t\t\t\t\t if(matchTerm.containsKey(keyMain_new)) // Only doc name EQUAL with docsave name can enter here\n\t\t\t\t\t\t\t\t {\n\t\t\t\t\t\t\t\t\t //System.out.println(\"Test \"+ matchTerm.get(keyMain_new) +\" keyMain_new \" + keyMain_new);\n\t\t\t\t\t\t\t\t\t double docTfIdf= matchTerm.get(keyMain_new) * storeIdf.get(qryTermItr.getKey());\n\t\t\t\t\t\t\t\t\t double qryTfIdf= qryTermItr.getValue() * storeIdf.get(qryTermItr.getKey());\n\t\t\t\t\t\t\t\t\t productTfIdf = docTfIdf * qryTfIdf;\n\t\t\t\t\t\t\t\t }\n\t\t\t\t\t\t\t \n\t\t\t\t\t\t\t sumProduct= sumProduct+productTfIdf;\n\t\t\t\t\t\t\t //System.out.println(\"productTfIdf \"+productTfIdf+\" sumProduct \"+ sumProduct);\n\t\t\t\t\t\t\t productTfIdf=0;\n\t\t\t\t\t\t }\n\t\t\t\t\t\t cosineProd.put(entry_dotP.getKey(), sumProduct/(docLength.get(entry_dotP.getKey())*qrySum));\n\t\t\t\t\t\t sumProduct=0;\n\t\t\t\t\t\t //System.out.println(entry_dotP.getKey()+ \" \" + docLength.get(entry_dotP.getKey()));\n\t\t\t\t\t}\n\t\t\t\t System.out.println(\"cosineProd \"+ cosineProd);\n\t\t\t\t \n\t\t\t\t System.out.println(\"Number of Top Pages you want to see\");\n\t\t\t\t int topRank = Integer.parseInt(scan.nextLine());\n\t\t\t\t Map<String, Double> result = cosineProd.entrySet().stream()\n\t\t\t .sorted(Map.Entry.comparingByValue(Comparator.reverseOrder())).limit(topRank)\n\t\t\t .collect(Collectors.toMap(Map.Entry::getKey, Map.Entry::getValue,\n\t\t\t (oldValue, newValue) -> oldValue, LinkedHashMap::new));\n\n\t\t\t\t scan.close();\n\t\t\t //Alternative way\n\t\t\t //Map<String, Double> result2 = new LinkedHashMap<>();\n\t\t\t //cosineProd.entrySet().stream().sorted(Map.Entry.<String, Double>comparingByValue().reversed()).limit(2).forEachOrdered(x -> result2.put(x.getKey(), x.getValue()));\n\n\t\t\t System.out.println(\"Sorted...\");\n\t\t\t System.out.println(result);\n\t\t\t //System.out.println(result2);\n\t}","public void sort() {\r\n\t\tCollections.sort(parts);\r\n\t}","public ArrayList<String> top5search(String kw1, String kw2) {\n\t\t/** COMPLETE THIS METHOD **/\n\t\tArrayList<String> results = new ArrayList<String>();\n\t\tArrayList<Occurrence> ocArr1 = new ArrayList<Occurrence>();\n\t\tArrayList<Occurrence> ocArr2 = new ArrayList<Occurrence>();\n\t\tArrayList<Occurrence> combined = new ArrayList<Occurrence>();\n\t\t\n\t\tif (keywordsIndex.containsKey(kw1))\n\t\t\tocArr1 = keywordsIndex.get(kw1);\n\t\t\n\t\tif (keywordsIndex.containsKey(kw2))\n\t\t\tocArr2 = keywordsIndex.get(kw2);\n\t\t\n\t\tcombined.addAll(ocArr1);\n\t\tcombined.addAll(ocArr2);\n\t\t\n\t\tif (!(ocArr1.isEmpty()) && !(ocArr2.isEmpty()))\n\t\t{\n\t\t\t// Sort with preference for ocArr1\n\t\t\tfor (int x = 0; x < combined.size()-1; x++)\n\t\t\t{\n\t\t\t\tfor (int y = 1; y < combined.size()-x; y++)\n\t\t\t\t{\n\t\t\t\t\tif (combined.get(y-1).frequency < combined.get(y).frequency)\n\t\t\t\t\t{\n\t\t\t\t\t\tOccurrence temp = combined.get(y-1);\n\t\t\t\t\t\tcombined.set(y-1, combined.get(y));\n\t\t\t\t\t\tcombined.set(y, temp);\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\n\t\t\t// Remove duplicates\n\t\t\tfor (int x = 0; x < combined.size()-1; x++)\n\t\t\t{\n\t\t\t\tfor (int y = x + 1; y < combined.size(); y++)\n\t\t\t\t{\n\t\t\t\t\tif (combined.get(x).document == combined.get(y).document)\n\t\t\t\t\t\tcombined.remove(y);\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\n\t\t// Top 5\n\t\twhile (combined.size() > 5)\n\t\t\tcombined.remove(combined.size()-1);\n\t\t\n\t\t//System.out.println(combined);\n\t\t\n\t\tfor (Occurrence oc : combined)\n\t\t\tresults.add(oc.document);\n\n\t\treturn results;\n\t\n\t\t\n\t\t// following line is a placeholder to make the program compile\n\t\t// you should modify it as needed when you write your code\n\t\n\t}","public PostingsList ranked_query(Query query, double w, double idf_threshold){\n long startTime = System.nanoTime();\n PostingsList result = new PostingsList();\n\n // Obtain union of terms above idf threshold if indexElimination is true\n // (Set idf_threshold to zero to disable this feature)\n Set<String> termsToConsider = this.queryTermsConsidered(query, idf_threshold);\n result = this.union_query(query, termsToConsider);\n //System.err.println(\"Size of result is \" + result.size());\n\n long estimatedTime = (System.nanoTime() - startTime)/1000000;\n System.err.println(\"* Union took: \" + estimatedTime);\n\n\n /*\n * 2) Iterate over PostingsEntries and build the solution\n */\n startTime = System.nanoTime();\n // Required when iterating over a PostingsList\n PostingsEntry postEnt = new PostingsEntry();\n // Number of documents in the collection\n double nDocs = this.docIDs.size();\n // Weight of a query vector coefficient\n double w_query_term;\n // Document tf-idf variables\n double termFrequency_doc, documentFrequency_doc, w_doc_term;\n\n for(String term : termsToConsider){\n // Obtain idf of the term\n documentFrequency_doc = Math.log(nDocs/new Double(this.idfMap.get(term)));\n\n // Obtain weight of the term\n w_query_term = query.weights.get(term);\n // Iterate over all documents containing the term and update the score(q,d)\n Iterator<PostingsEntry> it_d = result.iterator();\n while(it_d.hasNext()){\n postEnt = it_d.next();\n if (this.tfMap.get(postEnt.docID).containsKey(term)){\n termFrequency_doc = this.tfMap.get(postEnt.docID).get(term);\n w_doc_term = documentFrequency_doc*termFrequency_doc;\n postEnt.score += w_query_term*w_doc_term;\n }\n }\n }\n estimatedTime = (System.nanoTime() - startTime)/1000000;\n System.err.println(\"* Building solution took: \" + estimatedTime);\n\n /*\n * 3) Normalize the scores\n */\n startTime = System.nanoTime();\n Iterator<PostingsEntry> it = result.iterator();\n while(it.hasNext()){\n postEnt = it.next();\n postEnt.score /= (new Double(this.docLengths.get(\"\"+postEnt.docID)));//(Math.sqrt(postEnt.norm2));\n postEnt.score = w * postEnt.score + (1-w) * quality(postEnt.docID);\n }\n estimatedTime = (System.nanoTime() - startTime)/1000000;\n System.err.println(\"* Normalizing took: \" + estimatedTime);\n\n /*\n * 4) Sort the resulting solution\n */\n startTime = System.nanoTime();\n result.sort();\n estimatedTime = (System.nanoTime() - startTime)/1000000;\n System.err.println(\"* Sorting took: \" + estimatedTime);\n\n return result;\n }","private static ArrayList<Quest> sortAfterTimestamp(ArrayList<Quest> questListToSort) {\n\t\tfor (int i = 0; i < questListToSort.size() - 1; i++) {\n\t\t\tint index = i;\n\t\t\tfor (int j = i + 1; j < questListToSort.size(); j++) {\n\t\t\t\tif (questListToSort.get(j).getTimestamp() > questListToSort.get(index).getTimestamp()) {\n\t\t\t\t\tindex = j;\n\t\t\t\t}\n\t\t\t}\n\t\t\tCollections.swap(questListToSort, index, i);\n\t\t}\n\t\treturn questListToSort;\n\t}","private void sortRating()\n {\n for(int i = 0; i < movieList.size(); i++){\n for(int j = 1; j < movieList.size() - i; j++)\n {\n Movie a = movieList.get(j-1);\n Movie b = movieList.get(j);\n int result = a.getRating().compareTo(b.getRating());\n if(result < 0)\n {\n movieList.set(j-1, b);\n movieList.set(j, a);\n }\n else if(result == 0)\n {\n result = a.getTitle().compareTo(b.getTitle());\n if(result > 0)\n {\n movieList.set(j-1, b);\n movieList.set(j, a);\n }\n }\n }\n }\n }","public List<String> getSortedResults() {\r\n\t\tList<String> subset;\r\n\t\tif (filter == null) {\r\n\t\t\tsubset = allWords;\r\n\t\t} else {\r\n\t\t\tsubset = getFilteredWords();\r\n\t\t}\r\n\t\tsortResults(subset);\r\n\t\tint wordCount = Math.min(subset.size(), wordLimit);\r\n\t\tArrayList<String> result = new ArrayList<String>(wordCount);\t\r\n\t\tresult.addAll(subset.subList(0, wordCount));\r\n\t\treturn result;\r\n\t}","public void sortMatches();","public static ArrayList<JsonNode> sortData(ArrayList<JsonNode> wordList) {\n Collections.sort( wordList, new Comparator<JsonNode>() {\n @Override\n public int compare(JsonNode a, JsonNode b) {\n int valA = Integer.parseInt(a.get(\"weight\").asText());\n int valB = Integer.parseInt(b.get(\"weight\").asText());\n return valB - valA; //Sort in order of largest to smallest\n }\n });\n\n return wordList;\n }","private void sortByKeys(LazyMap<ProcessorDistributionKey, Collection<Geometry>> keyToGeoms,\n Collection<? extends Geometry> sortGeoms, Collection<Geometry> unprocessed)\n {\n final ProcessorDistributionKey hull = new ProcessorDistributionKey();\n for (final Geometry geom : sortGeoms)\n {\n sortByKeys(keyToGeoms, geom, unprocessed, hull);\n }\n }","private static void printTable(int numberOfDocs) {\n \n Gson gs = new Gson();\n String json = gs.toJson(wor);\n // System.out.println(json);\n \n List<String> queryWords = new ArrayList();\n //to test it for other query word you can change the following two words\n //queryWords.add(\"carpet\");\n //queryWords.add(\"hous\");\n queryWords.add(\"the\");\n queryWords.add(\"crystallin\");\n queryWords.add(\"len\");\n queryWords.add(\"vertebr\");\n queryWords.add(\"includ\");\n \n \n FrequencySummary frequencySummary = new FrequencySummary();\n frequencySummary.getSummary(json,docName, queryWords);\n \n System.exit(0);\n \n Hashtable<Integer,Integer> g = new Hashtable<>();\n \n /* wor.entrySet().forEach((wordToDocument) -> {\n String currentWord = wordToDocument.getKey();\n Map<String, Integer> documentToWordCount = wordToDocument.getValue();\n freq.set(0);\n df.set(0);\n documentToWordCount.entrySet().forEach((documentToFrequency) -> {\n String document = documentToFrequency.getKey();\n Integer wordCount = documentToFrequency.getValue();\n freq.addAndGet(wordCount);\n System.out.println(\"Word \" + currentWord + \" found \" + wordCount +\n \" times in document \" + document);\n \n if(g.getOrDefault(currentWord.hashCode(), null)==null){\n g.put(currentWord.hashCode(),1);\n \n }else {\n System.out.println(\"Hello\");\n \n int i = g.get(currentWord.hashCode());\n System.out.println(\"i \"+i);\n g.put(currentWord.hashCode(), i++);\n }\n // System.out.println(currentWord+\" \"+ g.get(currentWord.hashCode()));\n // g.put(currentWord.hashCode(), g.getOrDefault(currentWord.hashCode(), 0)+wordCount);\n \n });\n // System.out.println(freq.doubleValue());\n \n // System.out.println(\"IDF for this word: \"+Math.log10( (double)(counter/freq.doubleValue())));\n });\n // System.out.println(g.get(\"plai\".hashCode()));\n //System.out.println(\"IDF for this word: \"+Math.log10( (double)(counter/(double)g.get(\"plai\".hashCode()))));\n */\n }","static void countSort(List<List<String>> arr) {\n StringBuilder rs = new StringBuilder(\"\");\n int len = arr.size();\n StringBuilder[] sList = new StringBuilder[100];\n for (int i = 0; i < 100; i++) {\n sList[i] = new StringBuilder(\"\");\n }\n for (int i = 0; i < len; i++) {\n int n = Integer.parseInt(arr.get(i).get(0));\n if (i < len / 2) {\n sList[n].append(\"- \");\n } else {\n sList[n].append(arr.get(i).get(1) + \" \");\n }\n }\n for (StringBuilder ls : sList) {\n rs.append(ls);\n }\n System.out.println(rs.toString());\n }","public void createSummary(){\n\n for(int j=0;j<=noOfParagraphs;j++){\n int primary_set = paragraphs.get(j).sentences.size()/5;\n\n //Sort based on score (importance)\n Collections.sort(paragraphs.get(j).sentences,new SentenceComparator());\n for(int i=0;i<=primary_set;i++){\n contentSummary.add(paragraphs.get(j).sentences.get(i));\n }\n }\n\n //To ensure proper ordering\n Collections.sort(contentSummary,new SentenceComparatorForSummary());\n printSummary();\n }","public void sort() {\n }","public void sort() {\n\t\t\tfor (int j = nowLength - 1; j > 1; j--) {\n\t\t\t\tfor (int i = 0; i < j; i++) {\n\t\t\t\t\tif (ray[i] > ray[i+1]) {\n\t\t\t\t\t\tint tmp = ray [i];\n\t\t\t\t\t\tray[i] = ray[i+1];\n\t\t\t\t\t\tray[i+1] = tmp;\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t\tprint();\n\t\t\t}\n\t}","private static void RankedQueryMode(DiskIndexWriter diskWriter, DiskPositionalIndex disk_posIndex) throws IOException, ClassNotFoundException, InstantiationException, IllegalAccessException {\n\n if (query.equals(\"q\")) {\n\n System.exit(0);\n }\n\n List<String> word = new ArrayList();\n String[] query_array = query.split(\"\\\\s+\");\n TokenProcessor processor = new NewTokenProcessor();\n\n for (int i = 0; i < query_array.length; i++) {\n word.add(processor.processToken(query_array[i]).get(0));\n }\n\n StrategyFactory sf = new StrategyFactory();\n StrategyInterface strategy = sf.execute(rankedOption);\n\n //maps postings to accumulator value\n HashMap<Integer, Doc_accum> postingMap = new HashMap<Integer, Doc_accum>();\n\n PriorityQueue<Doc_accum> queue = new PriorityQueue<>(Collections.reverseOrder());\n\n List<Posting> postings = new ArrayList<>();\n List<Doc_accum> results = new ArrayList<>();\n\n for (String term : word) {\n\n postings = disk_posIndex.getPosting_noPos(term);\n for (Posting p : postings) { //for each document in the postings list\n double t_fd = p.getT_fd();\n double d_ft = p.getD_ft();\n double w_qt = strategy.calculate_wqt(N, d_ft);\n double accum = 0;\n double w_dt = strategy.get_wdt(t_fd, disk_posIndex, p.getDocumentId());\n\n //pairs (Ranked_posting, accumulator factor)\n if (postingMap.containsKey(p.getDocumentId())) {\n accum = postingMap.get(p.getDocumentId()).getAccumulator();\n accum += (w_qt * w_dt);\n postingMap.replace(p.getDocumentId(), new Doc_accum(p, accum)); //replaces old accum value\n\n } else {\n accum += (w_qt * w_dt);\n postingMap.put(p.getDocumentId(), new Doc_accum(p, accum));\n }\n }\n\n }\n\n for (Integer p : postingMap.keySet()) {\n Doc_accum doc_temp = postingMap.get(p);\n double accum = doc_temp.getAccumulator(); //gets accum associated with doc\n\n if (accum > 0) {\n //search for each p's Ld factor in docWeights.bin\n double l_d = strategy.calculate_Ld(disk_posIndex, doc_temp.getPosting().getDocumentId());\n\n accum /= l_d;\n doc_temp.setAccumulator(accum);\n }\n\n queue.add(postingMap.get(p));\n\n }\n\n //returns top K=10 results \n int topK = 50;\n\n while ((results.size() < topK) && queue.size() > 0) {\n\n results.add(queue.poll()); //gets the posting acc pair and returns only posting\n\n }\n\n display_RankedResults(results);\n\n }","public Iterator rankOrdering(Iterator pages)\n\t{\n\t\t//Iterator allWebNode = ind.retrievePages(keyword);\n\t\tIterator allWebNode = pages;\n\t\tif(allWebNode.hasNext()){\n\t\t\tWebNode wb = (WebNode) allWebNode.next();\n\t\t\tint score = wb.getInDegree() * wb.getWordFreq(keyword);\n\t\t\twb.keywordScore = score;\n\t\t\taL.add(wb); \n\t\t}\n\t\t\n\t\twhile (allWebNode.hasNext()) {\n\t\t\tWebNode nwb = (WebNode) allWebNode.next();\n\t\t\tint nscore = nwb.getInDegree() * nwb.getWordFreq(keyword);\n\t\t\tnwb.keywordScore = nscore;\n\t\t\tint i = 0; \n\t\t\twhile(i<aL.size()){\n\t\t\t\tif (nwb.keywordScore < ((WebNode) aL.get(i)).keywordScore)\n\t\t\t \ti++;\n\t\t\t else\n\t\t\t \taL.add(i,nwb);\n\t\t\t} \n\t\t}\n\t\t\n\t\treturn aL.iterator();\n\t}","public void sortManlist(){\r\n\t\tCollections.sort(Manlist, new MySort());\r\n\t}","static void sortByFreq(int arr[], int n)\r\n {\n int[] hash = new int[61];\r\n for (int x : arr) {\r\n hash[x]++;\r\n }\r\n HashMap<Integer, ArrayList<Integer>> valueHash = new HashMap<Integer, ArrayList<Integer>>();\r\n \r\n for (int i = 0; i<hash.length; i++) {\r\n int x = hash[i];\r\n if (x != 0) {\r\n if (valueHash.containsKey(x)) {\r\n valueHash.get(x).add(i);\r\n } else {\r\n ArrayList<Integer> list = new ArrayList<>();\r\n list.add(i);\r\n valueHash.put(x, list);\r\n }\r\n }\r\n }\r\n Set<Integer> keys = valueHash.keySet();\r\n List<Integer> list = new ArrayList<Integer>(keys); \r\n Collections.sort(list, new Comparator<Integer>()\r\n\t\t{\r\n\t\t\t@Override\r\n\t\t\tpublic int compare(Integer o1, Integer o2)\r\n\t\t\t{\r\n\t\t\t\tif (o1 > o2) return -1;\r\n\t\t\t\t\r\n\t\t\t\treturn 1;\r\n\t\t\t}\r\n\t\t});\r\n StringBuffer buff = new StringBuffer();\r\n for (int x : list) {\r\n \tArrayList<Integer> numList = valueHash.get(x);\r\n \tCollections.sort(numList);\r\n \tfor (int num : numList) {\r\n \t\tint y = x;\r\n \t\twhile (y > 0) {\r\n \t\t\tbuff.append(num + \" \");\r\n \t\t\ty--;\r\n \t\t}\r\n \t}\r\n }\r\n System.out.print(buff);\r\n }","private static void sortingMemo() {\n\t\t\n\t}","private List<Article> sortTopics(Article queryTopic, List<Article>relatedTopics) throws Exception {\n for (Article art:relatedTopics) \n art.setWeight(_comparer.getRelatedness(art, queryTopic)) ;\n\n //Now that the weight attribute is set, sorting will be in descending order of weight.\n //If weight was not set, it would be in ascending order of id. \n Collections.sort(relatedTopics) ;\n return relatedTopics ;\n }","public void sort() {\n compares = 0;\n shuttlesort((int[]) indexes.clone(), indexes, 0, indexes.length);\n }","private static List<MoneyLoss> sortLosses(Collection<MoneyLoss> unsortedLosses)\n {\n //Sort budget items first on frequency and then alphabetically\n ArrayList<MoneyLoss> oneTimeItems = new ArrayList<MoneyLoss>();\n ArrayList<MoneyLoss> dailyItems = new ArrayList<MoneyLoss>();\n ArrayList<MoneyLoss> weeklyItems = new ArrayList<MoneyLoss>();\n ArrayList<MoneyLoss> biweeklyItems = new ArrayList<MoneyLoss>();\n ArrayList<MoneyLoss> monthlyItems = new ArrayList<MoneyLoss>();\n ArrayList<MoneyLoss> yearlyItems = new ArrayList<MoneyLoss>();\n\n for (MoneyLoss loss : unsortedLosses)\n {\n switch (loss.lossFrequency())\n {\n case oneTime:\n {\n oneTimeItems.add(loss);\n break;\n }\n case daily:\n {\n dailyItems.add(loss);\n break;\n }\n case weekly:\n {\n weeklyItems.add(loss);\n break;\n }\n case biWeekly:\n {\n biweeklyItems.add(loss);\n break;\n }\n case monthly:\n {\n monthlyItems.add(loss);\n break;\n }\n case yearly:\n {\n yearlyItems.add(loss);\n break;\n }\n }\n }\n\n Comparator<MoneyLoss> comparator = new Comparator<MoneyLoss>() {\n @Override\n public int compare(MoneyLoss lhs, MoneyLoss rhs) {\n return lhs.expenseDescription().compareTo(rhs.expenseDescription());\n }\n };\n\n Collections.sort(oneTimeItems, comparator);\n Collections.sort(dailyItems, comparator);\n Collections.sort(weeklyItems, comparator);\n Collections.sort(biweeklyItems, comparator);\n Collections.sort(monthlyItems, comparator);\n Collections.sort(yearlyItems, comparator);\n\n ArrayList<MoneyLoss> sortedItems = new ArrayList<MoneyLoss>();\n BadBudgetApplication.appendItems(sortedItems, oneTimeItems);\n BadBudgetApplication.appendItems(sortedItems, dailyItems);\n BadBudgetApplication.appendItems(sortedItems, weeklyItems);\n BadBudgetApplication.appendItems(sortedItems, biweeklyItems);\n BadBudgetApplication.appendItems(sortedItems, monthlyItems);\n BadBudgetApplication.appendItems(sortedItems, yearlyItems);\n\n return sortedItems;\n }","public void sortTree(TreeNode root){\r\n\t\tArrayList<TreeNode> newChildrenlist = new ArrayList<TreeNode>();\r\n\t\tIterator<TreeNode> it = root.children();\r\n\t\tTreeNode child;\r\n\t\tint i, j, l, freq;\r\n\t\twhile(it.hasNext()){\r\n\t\t\tchild = it.next();\r\n\t\t\tfreq = child.getFrequency();\r\n\t\t\tif(newChildrenlist.size() == 0){\r\n\t\t\t\tnewChildrenlist.add(child);\r\n\t\t\t}\t\t\t\r\n\t\t\telse if(newChildrenlist.get(0).getFrequency() <= freq){\r\n\t\t\t\tnewChildrenlist.add(0, child);\r\n\t\t\t}\r\n\t\t\telse if(newChildrenlist.get(newChildrenlist.size()-1).getFrequency()\r\n\t\t\t\t\t>= freq){\r\n\t\t\t\tnewChildrenlist.add(child);\r\n\t\t\t}\r\n\t\t\telse{\r\n\t\t\t\ti = 0;\r\n\t\t\t\tj = newChildrenlist.size() - 1;\r\n\t\t\t\twhile(i < j){\r\n\t\t\t\t\tl = (i+j)/2;\r\n\t\t\t\t\tif(freq == newChildrenlist.get(l).getFrequency()){\r\n\t\t\t\t\t\tnewChildrenlist.add(l, child);\r\n\t\t\t\t\t\treturn;\r\n\t\t\t\t\t}\r\n\t\t\t\t\tif(freq < newChildrenlist.get(l).getFrequency()){\r\n\t\t\t\t\t\ti = Math.max(l, i+1);\r\n\t\t\t\t\t}else{\r\n\t\t\t\t\t\tj = Math.min(l, j-1);\r\n\t\t\t\t\t}\r\n\t\t\t\t}\r\n\t\t\t\tif(newChildrenlist.get(i).getFrequency() > freq){\r\n\t\t\t\t\tnewChildrenlist.add(i+1, child);\r\n\t\t\t\t}else{\r\n\t\t\t\t\tnewChildrenlist.add(i, child);\r\n\t\t\t\t}\r\n\t\t\t}\r\n\t\t}\r\n\r\n\t\troot.setChildren(newChildrenlist);\r\n\t\tit = root.children();\r\n\t\twhile(it.hasNext()){\r\n\t\t\tchild = it.next();\r\n\t\t\tsortTree(child);\r\n\t\t}\r\n\t}","public TreeMap<GenericDocument, LinkedList<Posting>> getDocumentBasedIndex(Collection collection) { \r\n\t\tTreeMap<GenericDocument, LinkedList<Posting>> result = new TreeMap<GenericDocument, LinkedList<Posting>>();\r\n\t\t\r\n\t\tfor(java.util.Collection<Posting> bag : map.values()) {\r\n\t\t\tfor (Posting posting : bag) {\r\n\t\t\t\tGenericDocument doc = collection.findArticle(posting.getDocumentID());\r\n\t\t\t\tif (doc != null) {\r\n\t\t\t\t\tif (result.containsKey(doc))\r\n\t\t\t\t\t\tresult.get(doc).add(posting);\r\n\t\t\t\t\telse {\r\n\t\t\t\t\t\tLinkedList<Posting> list = new LinkedList<Posting>();\r\n\t\t\t\t\t\tlist.add(posting);\r\n\t\t\t\t\t\tresult.put(doc, list);\r\n\t\t\t\t\t}\r\n\t\t\t\t}\r\n\t\t\t}\r\n\t\t\t\t \r\n\t\t}\r\n\t\t \r\n\t\tSystem.out.println(\"Document based indexing complete.\");\r\n\t\treturn result;\r\n\t}","@Override\r\n\tpublic void addSort() {\n\t\t\r\n\t}","private List<Score> order(List<Score> s)\n {\n Collections.sort(s, new Comparator<Score>()\n {\n\n @Override\n public int compare(Score o1, Score o2) {\n // TODO Auto-generated method stub\n\n return o1.getSentId() - o2.getSentId();\n }\n });\n return s;\n }","public void ArtistAndSource() throws IOException{\r\n List<String> ArrangersAndTheirSongs=new ArrayList<>();\r\n HashMap <String,Integer> SongCountMap= new HashMap<>();\r\n String allsongs=\"\";\r\n String sourcesong=\"\";\r\n for(int id: ArrangersMap.keySet()){\r\n String ArrangerName=ArrangersMap.get(id);\r\n for(String song:ArrangerLinesList){\r\n String perform[];\r\n perform=song.split(\"/\");\r\n int arrangeid=Integer.parseInt(perform[1]);\r\n if(id==arrangeid){\r\n int songid= Integer.parseInt(perform[0]);\r\n String songname=test.getsongName(songid);\r\n sourcesong=test.SongToSource(songname);\r\n allsongs+=sourcesong+\",\";\r\n if (SongCountMap.get(sourcesong) !=null){ \r\n SongCountMap.put(sourcesong, SongCountMap.get(sourcesong)+1);\r\n }\r\n else{\r\n SongCountMap.put(sourcesong, 1);\r\n }\r\n } \r\n }\r\n for(String song:SongCountMap.keySet()){\r\n //System.out.println(song);\r\n }\r\n HashMap <String,Integer> SortedMap= sortByValues(SongCountMap);\r\n SongCountMap.clear();\r\n String allsongs2=\"\";\r\n for(String song:SortedMap.keySet()){\r\n //System.out.println(\"Number\"+SortedMap.get(song)+\"The song is\"+song);\r\n allsongs2+=\"#occurences:\"+SortedMap.get(song)+\"The song is\"+song+\"\\n\";\r\n //System.out.println(\"Number of times:\"+SortedMap.get(song)+\"The song is\"+song);\r\n }\r\n //System.out.println(allsongs2);\r\n // ArrangersAndTheirSongs.add(\"The Arrangers Name is:\"+ArrangerName+ \" Their songs are:\"+allsongs);\r\n ArrangersAndTheirSongs.add(\"The Arrangers Name is:\"+ArrangerName+ \" Their songs are: \"\r\n + \"\"+allsongs2);\r\n allsongs=\"\";\r\n SortedMap.clear();\r\n allsongs2=\"\";\r\n }\r\n //method is broken\r\n writeListToTextFile(\"d:\\\\documents\\\\textfiles\\\\ArrangersAndTheirSources.txt\",ArrangersAndTheirSongs);\r\n System.out.println(\"The size of the list is:\"+ArrangersAndTheirSongs.size());\r\n System.out.println(\"Artist and Their Source Complete\");\r\n }","private void sort() {\n setFiles(getFileStreamFromView());\n }","@Override\n \tpublic void sort() {\n \t\tArrays.sort(data);\n \t}","public HashMap<String, Integer> getOrder(){\n\t\t\n\t\tHashMap<String, Integer> hm2 = getHashMap();\n\t\n\t\tArrayList fq = new ArrayList<>();\n\t\t\n\t\tHashMap<String, Integer> top10 = new HashMap<String, Integer>();\n\t\t\n\t\tfor(String key : hm2.keySet()){\n\t\t\t\n\t\t\tfq.add(hm2.get(key));\n\t\t}\n\t\t// use Collection to get the order of frequency\n\t\tCollections.sort(fq);\n \tCollections.reverse(fq);\n \t\n \tfor(int i = 0; i<11; i++){\n \t\t\n \t\tfor(String key : hm2.keySet()){\n \t\t// make sure the word not equals to balck space\n \t\tif(hm2.get(key) == fq.get(i) && !key.equals(\"\") ){\n \t\t\t\n \t\t top10.put(key, hm2.get(key));\n \t\t\t\t\n \t\t}\n \t}\t\n\t}\n\t\treturn top10;\n\t}","public static void main(String[] args) {\n\n List<String> animals = new ArrayList <String>();\n\n animals.add(\"Elephatn\");\n animals.add(\"snake\");\n animals.add(\"Lion\");\n animals.add(\"Mongoose\");\n animals.add(\"Cat\");\n\n\n\n// Collections.sort(animals, new StringLengthComparator());\n// Collections.sort(animals, new AlphabeticalComparator());\n Collections.sort(animals, new ReverseAlphabeticalComparator());\n for(String animal:animals){\n System.out.println(animal);\n }\n\n//////////////Sorting Numbers ///////////\n List<Integer> numbers = new ArrayList <Integer>();\n\n numbers.add(54);\n numbers.add(1);\n numbers.add(36);\n numbers.add(73);\n numbers.add(9);\n\n Collections.sort(numbers, new Comparator <Integer>() {\n @Override\n public int compare(Integer num1, Integer num2) {\n return num1.compareTo(num2);\n }\n });\n\n for(Integer number: numbers){\n System.out.println(number);\n }\n\n\n///////////////Sorting Arbitrary objects////////\n\n\n List<Person> people = new ArrayList <Person>();\n\n people.add(new Person(1,\"Joe\"));\n people.add(new Person(5,\"Harry\"));\n people.add(new Person(2,\"Hermoine\"));\n people.add(new Person(4,\"Muffet\"));\n\n// Sort in order of ID\n Collections.sort(people, new Comparator <Person>() {\n @Override\n public int compare(Person p1, Person p2) {\n\n if(p1.getId()>p2.getId()){\n return 1;\n }else if(p1.getId()<p2.getId()){\n return -1;\n }\n return 0;\n\n }\n });\n\n\n // Sort in order of Name\n Collections.sort(people, new Comparator <Person>() {\n @Override\n public int compare(Person p1, Person p2) {\n\n return p1.getName().compareTo(p2.getName());\n\n\n }\n });\n\n for(Person person: people){\n System.out.println(person);\n\n }\n\n }","public void sort()\n\t{\n\t\tfor(int i=0;i<bowlers.size()-1;i++)\n\t\t{\n\t\t\tfor(int j=i+1;j<bowlers.size();j++)\n\t\t\t{\n\t\t\t\tif(bowlers.get(i).getBall()<bowlers.get(j).getBall())\n\t\t\t\t{\n\t\t\t\t\tBowler bowler=bowlers.get(i);\n\t\t\t\t\tbowlers.set(i,bowlers.get(j));\n\t\t\t\t\tbowlers.set(j,bowler);\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t\tfor(int i=0;i<bowlers.size();i++)\n\t\t{\n\t\tSystem.out.println(bowlers.get(i).getBall());\n\t\t}\n\t}"],"string":"[\n \"public void sort() {\\n documents.sort();\\n }\",\n \"public void sortDocumentsByDocnos() {\\n order = new int[mDocSet.length];\\n mDocSet_tmp = new double[mDocSet.length];\\n accumulated_scores_tmp = new float[mDocSet.length];\\n\\n for (int i = 0; i < order.length; i++) {\\n order[i] = i;\\n mDocSet_tmp[i] = mDocSet[i];\\n accumulated_scores_tmp[i] = accumulated_scores[i];\\n }\\n\\n ivory.smrf.model.constrained.ConstraintModel.Quicksort(mDocSet_tmp, order, 0, order.length - 1);\\n\\n for (int i = 0; i < order.length; i++) {\\n mDocSet[i] = (int) mDocSet_tmp[i];\\n accumulated_scores[i] = accumulated_scores_tmp[order[i]];\\n }\\n }\",\n \"private void buildPostingList(){\\n boolean isEndOfList = false;\\n// boolean moveToNextDoc = false;\\n ArrayList<Integer> tempList = new ArrayList<>(); // tempList to hold doc wise posting List\\n\\n while(!isEndOfList){\\n boolean skipDoc = false;\\n int doc = children.get(0).nextCandidate();\\n if(doc == -1) {\\n // End of list. No more windows to collect. Exit.\\n isEndOfList = true; break;\\n }\\n int distance = super.getDiskReader().getRetrievedDocToLengthMap().get(doc);\\n // Check if doc exists in all other children.\\n // If it exists, skip to that Document.\\n for(QueryNode child : children){\\n /* skipToDoc skips the pointer in child node to the current doc.\\n */\\n if(!child.skipToDoc(doc)) {\\n skipDoc = true;\\n break;\\n }\\n\\n }\\n if(!skipDoc) {\\n /* From here, all nodes have the document. Proceed to calculating number of windows in doc */\\n\\n tempList.clear();\\n tempList.add(doc); //\\n tempList.add(0); // doc term frequency. We will update this later.\\n int fkid = 0; // doc term frequency tracker\\n// int i = startTermIndex+1;\\n int minPosIndex = 0; // holds the index of the node which has current minimum Pos\\n int minPos = children.get(minPosIndex).nextPos(); // initialize min Pos.\\n boolean isEndOfDoc = false;\\n while(!isEndOfDoc) {\\n if(minPos == -1) break; // End of document. Move to next doc\\n for (int i = 0; i < children.size(); i++) {\\n int pos = children.get(i).nextPos();\\n if(pos == -1){\\n isEndOfDoc = true;\\n break;\\n }\\n if (pos < minPos) {\\n minPos = pos;\\n minPosIndex = i;\\n }\\n }\\n if(isEndOfDoc) break;\\n /* Check for window size against min pos */\\n for (int i = 0; i < children.size(); i++) {\\n int pos = children.get(i).nextPos();\\n\\n if (pos - minPos < distance) {\\n // Valid candidate so far.\\n // check if last term.\\n if (i == children.size() - 1) {\\n tempList.add(children.get(minPosIndex).nextPos());\\n fkid++;\\n // update all the child node pointers to next position. No double dipping\\n for(QueryNode child : children)\\n child.updatePos();\\n\\n\\n }\\n\\n } else {\\n // Candidate failed.\\n // update minimum position to next pos and repeat process\\n children.get(minPosIndex).updatePos();\\n minPos = children.get(minPosIndex).nextPos();\\n break;\\n\\n }\\n }\\n\\n }\\n\\n\\n /* The document has been consumed. If the temp List size is > 2, we have collected windows.\\n Add them to the posting list.\\n */\\n if (tempList.size() > 2) {\\n tempList.set(1, fkid);\\n cqi += fkid;\\n postingList.addAll(new ArrayList<>(tempList));\\n }\\n }\\n// if(moveToNextDoc) continue;\\n children.get(0).updateToNextDoc();\\n }\\n }\",\n \"public List<DictionaryData> frequencyOrderedList() {\\n List<DictionaryData> wordlist = alphabeticalList();\\r\\n\\r\\n //using insertion sort\\r\\n int j;\\r\\n DictionaryData k;\\r\\n for (int i = 1; i < wordlist.size(); i++) {\\r\\n j = i;\\r\\n\\r\\n while (j > 0 && compare_dictdata(wordlist.get(j), wordlist.get(j - 1))) {\\r\\n k = wordlist.get(j);\\r\\n wordlist.set(j, wordlist.get(j - 1));\\r\\n wordlist.set(j - 1, k);\\r\\n j--;\\r\\n\\r\\n }\\r\\n //i++;\\r\\n }\\r\\n return wordlist;\\r\\n }\",\n \"public PostingList(int df, int N)\\n {\\n documentFrequency = df;\\n totalNoOfDocuments = N;\\n }\",\n \"public void sortCount() {\\n\\t\\tfor(Entry<String, TreeMap<String, Integer>> entry:map.entrySet()){\\r\\n\\t\\t\\tTreeMap<String, Integer> tmap = entry.getValue();\\r\\n\\t\\t\\tList<Entry<String, Integer>> sorttmap = MapSort.sortMapByIntegerValue(tmap);\\r\\n\\t\\t\\t int flag=0;\\r\\n for(Entry<String, Integer> word:sorttmap){ \\r\\n \\tflag++;\\r\\n \\tkeyword.add(word.getKey());\\r\\n// System.out.println(mapping.getKey()+\\\":\\\"+mapping.getValue()); \\r\\n \\tif(flag==5)\\r\\n \\t\\tbreak;\\r\\n } \\r\\n\\t\\t}\\r\\n\\t\\r\\n\\t}\",\n \"public static WordFrq[] sort(WordFrq b[]){\\n WordFrq temp;\\n int i=0;\\n while (i < 3) {\\n for (i = 1; i < 3; i++) {\\n if (b[i-1].count > b[i].count) {\\n temp = b[i];\\n b[i] = b[i-1];\\n b[i-1] = temp;\\n break;\\n }\\n }\\n }\\n\\n\\n return b;\\n\\n\\n\\n\\n\\n }\",\n \"private static void sortSlidesByNumberTags() {\\n\\t\\tCollections.sort(slideList, new Comparator<Slide>() {\\n\\t\\t\\tpublic int compare(Slide s1, Slide s2) {\\n\\n\\t\\t\\t\\tInteger sS1 = s1.getTagList().size();\\n\\t\\t\\t\\tInteger sS2 = s2.getTagList().size();\\n\\n\\t\\t\\t\\tint sComp = sS1.compareTo(sS2);\\n\\n\\t\\t\\t\\treturn -1 * sComp;\\n\\t\\t\\t}\\n\\t\\t});\\n\\t}\",\n \"public void sortWordTokens (String [] list, int count){\\n \\n String[] sortedWordsCopy = new String[count];\\n \\n \\n //Makes a copy of list and stores it in sortedWordsCopy\\n for (int i = 0; i < count; i++)\\n sortedWordsCopy[i] = list[i];\\n \\n //Sorts sortedWordsCopy which is a copy of list\\n Arrays.sort(sortedWordsCopy);\\n \\n //Copies the sorted list back out to list\\n for (int i = 0; i < count; i++)\\n list[i] = sortedWordsCopy[i];\\n \\n }\",\n \"public void sortGivenArray_popularity() { \\n int i, j, k; \\n for(i = movieList.size()/2; i > 0; i /= 2) {\\n for(j = i; j < movieList.size(); j++) {\\n Movie key = movieList.get(j);\\n for(k = j; k >= i; k -= i) {\\n if(key.rents > movieList.get(k-i).rents) {\\n movieList.set(k, movieList.get(k-i));\\n } else {\\n break; \\n }\\n }\\n movieList.set(k, key);\\n }\\n } \\n }\",\n \"private static void sortPhotosByNumberTags() {\\n\\t\\tCollections.sort(photoList, new Comparator<Photo>() {\\n\\t\\t\\tpublic int compare(Photo p1, Photo p2) {\\n\\n\\t\\t\\t\\tInteger s1 = p1.getTagList().size();\\n\\t\\t\\t\\tInteger s2 = p2.getTagList().size();\\n\\n\\t\\t\\t\\tint sComp = s1.compareTo(s2);\\n\\n\\t\\t\\t\\treturn -1 * sComp;\\n\\t\\t\\t}\\n\\t\\t});\\n\\t}\",\n \"private void sortMedApts(List<MedicationAppointment> medApts2) {\\n \\t}\",\n \"public void sortByQnNum() {\\r\\n\\t\\tfor (int j = 0; j < displayingList.size() - 1; j++) {\\r\\n\\t\\t\\tfor (int i = 0; i < displayingList.size() - j - 1; i++) {\\r\\n\\t\\t\\t\\tif (displayingList.get(i).getQnNum() > displayingList.get(i + 1).getQnNum()) {\\r\\n\\t\\t\\t\\t\\tswapPosition(displayingList, i, i + 1);\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t}\\r\\n\\t\\t}\\r\\n\\t}\",\n \"public static PriorityQueue<WordCount> sortWords(HashMap<String, Integer> counts){\\n\\t\\tPriorityQueue<WordCount> words = new PriorityQueue<WordCount>(99999, new wordCountComparator());\\n\\t\\tWordCount wc = null;\\n\\t\\tfor(Map.Entry<String, Integer> entry : counts.entrySet()){\\n\\t\\t\\twc = new WordCount(entry.getKey(), entry.getValue());\\n\\t\\t\\twords.add(wc);\\n\\t\\t}\\n\\t\\treturn words;\\n\\t}\",\n \"private static void sortNoun() throws Exception{\\r\\n\\t\\tBufferedReader[] brArray = new BufferedReader[ actionNumber ];\\r\\n\\t\\tBufferedWriter[] bwArray = new BufferedWriter[ actionNumber ];\\r\\n\\t\\tString line = null;\\r\\n\\t\\tfor(int i = 0; i < actionNameArray.length; ++i){\\r\\n\\t\\t\\tSystem.out.println(\\\"sorting for \\\" + actionNameArray[ i ]);\\r\\n\\t\\t\\tbrArray[ i ] = new BufferedReader( new FileReader(TFIDF_URL + actionNameArray[ i ] + \\\".tfidf\\\"));\\r\\n\\t\\t\\tHashMap<String, Double> nounTFIDFMap = new HashMap<String, Double>();\\r\\n\\t\\t\\tint k = 0;\\r\\n\\t\\t\\t// 1. Read tfidf data\\r\\n\\t\\t\\twhile((line = brArray[ i ].readLine())!=null){\\r\\n\\t\\t\\t\\tnounTFIDFMap.put(nounList.get(k), Double.parseDouble(line));\\r\\n\\t\\t\\t\\tk++;\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\tbrArray[ i ].close();\\r\\n\\t\\t\\t// 2. Rank according to tfidf\\r\\n\\t\\t\\tValueComparator bvc = new ValueComparator(nounTFIDFMap);\\r\\n\\t\\t\\tTreeMap<String, Double> sortedMap = new TreeMap<String, Double>(bvc);\\r\\n\\t\\t\\tsortedMap.putAll(nounTFIDFMap);\\r\\n\\t\\t\\t\\r\\n\\t\\t\\t// 3. Write to disk\\r\\n\\t\\t\\tbwArray[ i ] = new BufferedWriter(new FileWriter( SORTED_URL + actionNameArray[ i ] + \\\".sorted\\\"));\\r\\n\\t\\t\\tfor(String nounKey : sortedMap.keySet()){\\r\\n\\t\\t\\t\\tbwArray[ i ].append(nounKey + \\\"\\\\t\\\" + nounTFIDFMap.get(nounKey) + \\\"\\\\n\\\");\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\tbwArray[ i ].close();\\r\\n\\t\\t}\\r\\n\\t}\",\n \"static void sortByFreq(int arr[], int n){\\n Map<Integer, Integer> map = new HashMap<>(); \\n List<Integer> outputArray = new ArrayList<>(); \\n \\n // Assign elements and their count in the list and map \\n for (int current : arr) { \\n int count = map.getOrDefault(current, 0); \\n map.put(current, count + 1); \\n outputArray.add(current); \\n } \\n \\n // Compare the map by value \\n SortComparator comp = new SortComparator(map); \\n \\n // Sort the map using Collections CLass \\n Collections.sort(outputArray, comp); \\n \\n // Final Output \\n for (Integer i : outputArray) { \\n System.out.print(i + \\\" \\\"); \\n }\\n }\",\n \"private List<Article> orderArticles(List<Article> things){\\n\\t\\t Comparator<Article> comparatorPrizes = new Comparator<Article>() {\\n\\t public int compare(Article x, Article y) {\\n\\t return (int) (x.getPrize() - y.getPrize());\\n\\t }\\n\\t };\\n\\t Collections.sort(things,comparatorPrizes); \\n\\t Collections.reverse(things);\\n\\t return things;\\n\\t }\",\n \"public void sortByTagCount() {\\r\\n this.addSortField(\\\"\\\", \\\"*\\\", SORT_DESCENDING, \\\"count\\\");\\r\\n }\",\n \"public void sort() {\\n\\t\\tArrays.sort(contactList, 0, contactCounter);\\n\\t}\",\n \"public static void sortByPlaceCount(List<Apartment> apartments) {\\n Collections.sort(apartments, SORT_BY_PLACE_COUNT);\\n }\",\n \"public String frequencySort(String s) {\\n\\n\\t\\t// prepare a frequency map\\n\\t\\tMap<Character, Integer> m = new HashMap<Character, Integer>();\\n\\t\\tfor (char c : s.toCharArray())\\n\\t\\t\\tm.put(c, m.getOrDefault(c, 0) + 1);\\n\\n\\t\\tPriorityQueue<CKEntry1> pq = new PriorityQueue<>();\\n\\t\\tfor (Entry<Character, Integer> e : m.entrySet()) {\\n\\t\\t\\tpq.add(new CKEntry1(e.getKey(), e.getValue()));\\n\\t\\t}\\n\\t\\t\\n\\t\\t// prepare the output now\\n\\t\\tStringBuilder sb = new StringBuilder();\\n\\t\\twhile(!pq.isEmpty()) {\\n\\t\\t\\tCKEntry1 temp = pq.poll();\\n\\t\\t\\tchar[] tempC = new char[temp.count];\\n\\t\\t\\tArrays.fill(tempC, temp.c); // repeat c count' times\\n\\t\\t\\tsb.append(tempC);\\n\\t\\t}\\n\\t\\t\\n\\t\\treturn sb.toString();\\n\\n\\t}\",\n \"protected HashMap<String,Double> rank(ArrayList<String> queryPostingLines, ArrayList<String> query){\\n HashMap<String,HashMap<String,Integer>> queryWordsTFPerDoc = computeTFForQueryWords(queryPostingLines);\\n ArrayList<String> retrievedDocuments = new ArrayList<>(queryWordsTFPerDoc.keySet());\\n HashMap<String,Double> rankedDocs = new HashMap<>();\\n\\n for(String doc : retrievedDocuments){\\n HashMap<String,Integer> docTFs = queryWordsTFPerDoc.get(doc);\\n double rank = 0.3*rankByBM25(query,doc,docTFs) + 0.7*rankByPosition(query,doc,queryPostingLines);// - rankByCosSim(query,doc,docTFs);\\n rankedDocs.put(doc,rank);\\n }\\n rankedDocs = sortByValue(rankedDocs);\\n ArrayList<String> docsAfterSort = new ArrayList<>(rankedDocs.keySet());\\n HashMap<String,Double> docsToRetrieve = new HashMap<>();\\n int i=0;\\n for(String doc: docsAfterSort){\\n docsToRetrieve.put(documentDetails.get(doc)[0],rankedDocs.get(doc));\\n i++;\\n if(i == 50)\\n break;\\n }\\n return docsToRetrieve;\\n }\",\n \"private static void SortHash(HashMap<String,ArrayList<input>> hashMap,Distribution list)\\n\\t{\\n\\t\\tCollections.sort(list.First, new Comparator<input>() {\\n\\t\\t public int compare(input one, input other) {\\n\\t\\t \\tif(one.sum>other.sum)\\n\\t\\t \\t{\\n\\t\\t \\t\\treturn 1;\\n\\t\\t \\t}\\n\\t\\t \\telse\\n\\t\\t \\t{\\n\\t\\t \\t\\treturn -1;\\n\\t\\t \\t}\\n\\t\\t }\\n\\t\\t}); \\n\\t\\tCollections.sort(list.Second, new Comparator<input>() {\\n\\t\\t public int compare(input one, input other) {\\n\\t\\t \\tif(one.sum>other.sum)\\n\\t\\t \\t{\\n\\t\\t \\t\\treturn 1;\\n\\t\\t \\t}\\n\\t\\t \\telse\\n\\t\\t \\t{\\n\\t\\t \\t\\treturn -1;\\n\\t\\t \\t}\\n\\t\\t }\\n\\t\\t}); \\n\\t\\tCollections.sort(list.Third, new Comparator<input>() {\\n\\t\\t public int compare(input one, input other) {\\n\\t\\t \\tif(one.sum>other.sum)\\n\\t\\t \\t{\\n\\t\\t \\t\\treturn 1;\\n\\t\\t \\t}\\n\\t\\t \\telse\\n\\t\\t \\t{\\n\\t\\t \\t\\treturn -1;\\n\\t\\t \\t}\\n\\t\\t }\\n\\t\\t}); \\n\\t\\tCollections.sort(list.Fourth, new Comparator<input>() {\\n\\t\\t public int compare(input one, input other) {\\n\\t\\t \\tif(one.sum>other.sum)\\n\\t\\t \\t{\\n\\t\\t \\t\\treturn 1;\\n\\t\\t \\t}\\n\\t\\t \\telse\\n\\t\\t \\t{\\n\\t\\t \\t\\treturn -1;\\n\\t\\t \\t}\\n\\t\\t }\\n\\t\\t}); \\n\\t\\tCollections.sort(list.Fifth, new Comparator<input>() {\\n\\t\\t public int compare(input one, input other) {\\n\\t\\t \\tif(one.sum>other.sum)\\n\\t\\t \\t{\\n\\t\\t \\t\\treturn 1;\\n\\t\\t \\t}\\n\\t\\t \\telse\\n\\t\\t \\t{\\n\\t\\t \\t\\treturn -1;\\n\\t\\t \\t}\\n\\t\\t }\\n\\t\\t}); \\n\\t\\tCollections.reverse(list.First);\\n\\t\\tCollections.reverse(list.Second);\\n\\t\\tCollections.reverse(list.Third);\\n\\t\\tCollections.reverse(list.Fourth);\\n\\t\\tCollections.reverse(list.Fifth);\\n\\t\\tputInHashMap(hashMap,list);\\n\\t}\",\n \"protected void sort() {\\n\\n\\t\\tCollections.sort(this.myRRList);\\n\\t}\",\n \"public static void main(String[] args) {\\n\\r\\n\\t\\tint arr[]={2, 3, 2, 4, 5, 12, 2, 3, 3, 3, 12};\\r\\n\\t\\tMap<Integer,Data> map = new HashMap<>();\\r\\n\\t\\tfor(int a :arr)\\r\\n\\t\\t{\\r\\n\\t\\t\\tif(map.containsKey(a))\\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\tmap.get(a).incrementFrequency();\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\telse\\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\tmap.put(a, new Data(a));\\r\\n\\t\\t\\t}\\r\\n\\t\\t}\\r\\n\\t\\t\\r\\n\\t\\t\\r\\n\\t\\t\\r\\n\\t\\tSet<Data> sortedData = new TreeSet<>(map.values());\\r\\n\\t\\tList<Integer> result = new ArrayList<>();\\r\\n\\t\\tfor(Data d : sortedData)\\r\\n\\t\\t{\\r\\n\\t\\t\\tfor(int i=0;i<d.frequency;i++)\\r\\n\\t\\t\\t\\tresult.add(d.number);\\r\\n\\t\\t}\\r\\n\\t\\tSystem.out.println(result);\\r\\n\\t}\",\n \"public void sortAppointments() {\\n reminders = sort(reminders);\\n followup = sort(followup);\\n }\",\n \"public static void rankFiles(Hashtable<?, Integer> fname, int numberOfOccurrences) \\r\\n\\t{\\n\\t\\tArrayList<Map.Entry<?, Integer>> arrayList = new ArrayList(fname.entrySet());\\r\\n\\r\\n\\t\\tCollections.sort(arrayList, new Comparator<Map.Entry<?, Integer>>() \\r\\n\\t\\t{\\r\\n\\t\\t\\tpublic int compare(Map.Entry<?, Integer> obj1, Map.Entry<?, Integer> obj2) \\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\treturn obj1.getValue().compareTo(obj2.getValue());\\r\\n\\t\\t\\t}\\r\\n\\t\\t});\\r\\n\\r\\n\\t\\tCollections.reverse(arrayList);\\r\\n\\r\\n\\t\\tif (numberOfOccurrences > 0) \\r\\n\\t\\t{\\r\\n\\t\\t\\tSystem.out.println(\\\"\\\\n------Top 10 search results-----\\\\n\\\");\\r\\n\\r\\n\\t\\t\\tint my_number = 10;\\r\\n\\t\\t\\tint j = 1;\\r\\n\\t\\t\\twhile (arrayList.size() > j && my_number > 0) \\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\tSystem.out.println(\\\"(\\\" + j + \\\") \\\" + arrayList.get(j) + \\\" times \\\");\\r\\n\\t\\t\\t\\tj++;\\r\\n\\t\\t\\t\\tmy_number--;\\r\\n\\t\\t\\t}\\r\\n\\t\\t} \\r\\n\\t}\",\n \"public String[] topHotWords( int count ){\\r\\n //If the number put in the arguments is greater than the number of distinct hotwords\\r\\n //in the document, limit it to distinctCount\\r\\n if (count > distinctCount()){\\r\\n count = distinctCount();\\r\\n }\\r\\n //Creating the array that will hold all the hotwords in order of number of appearances \\r\\n String[] topWord = new String[words.size()];\\r\\n //This is the subset of the array above that will return the amount specified by the count argument\\r\\n String[] output = new String[count];\\r\\n //Fills the array with blank strings\\r\\n Arrays.fill(topWord, \\\"\\\");\\r\\n //Iterator for moving through topWord for assignment\\r\\n int iterator = 0;\\r\\n //Loop through every hotword in words and puts those words in topWord\\r\\n for(String key: words.keySet()){\\r\\n topWord[iterator] = key;\\r\\n iterator++;\\r\\n }\\r\\n //Sorts the words in topword\\r\\n for(int i = 0; i < words.size(); i++){\\r\\n for(int j = words.size()-1; j > 0; j-- ){\\r\\n \\r\\n if(count(topWord[j]) > count(topWord[i])){\\r\\n String temp = topWord[i];\\r\\n topWord[i] = topWord[j];\\r\\n topWord[j] = temp;\\r\\n }\\r\\n \\r\\n }\\r\\n }\\r\\n //Does a secondary check to be certain all words are in proper appearance number order\\r\\n for(int i = words.size()-1; i >0; i--){\\r\\n if(count(topWord[i]) > count(topWord[i-1])){\\r\\n String temp = topWord[i];\\r\\n topWord[i] = topWord[i-1];\\r\\n topWord[i-1] = temp;\\r\\n }\\r\\n }\\r\\n //Orders the words with the same number of appearances by order of appearance in the document\\r\\n for (int i = 0; i < words.size(); i++){\\r\\n for(int j = i+1; j < words.size(); j++){\\r\\n if (count(topWord[i]) == count(topWord[j])){\\r\\n if (consec.indexOf(topWord[j]) < consec.indexOf(topWord[i])){\\r\\n String temp = topWord[i];\\r\\n topWord[i] = topWord[j];\\r\\n topWord[j] = temp;\\r\\n }\\r\\n }\\r\\n }\\r\\n }\\r\\n //Gets the subset requested for return\\r\\n for (int i = 0; i < count; i++){\\r\\n output[i] = topWord[i];\\r\\n }\\r\\n return output;\\r\\n\\t}\",\n \"public void getWordFrequency(ArrayList<String> out_words, ArrayList<Integer> out_counts) {\\n //... Put in ArrayList so sort entries by frequency\\n ArrayList<Map.Entry<String, MutableInteger>> entries =\\n new ArrayList<Map.Entry<String, MutableInteger>>(wordFrequency.entrySet());\\n Collections.sort(entries, new ComparatorFrequency());\\n\\n //... Add word and frequency to parallel output ArrayLists.\\n for (Map.Entry<String, MutableInteger> ent : entries) {\\n out_words.add(ent.getKey());\\n out_counts.add(ent.getValue().getValue());\\n }\\n }\",\n \"@Override\\n public void sort() {\\n\\n List<Doctor> unsortedDocs = this.doctors;\\n\\n Collections.sort(unsortedDocs, new Comparator<Doctor>() {\\n @Override\\n public int compare(Doctor a, Doctor b) {\\n //Compare first name for doctors and re-arrange list\\n return a.getFirstName().compareTo(b.getFirstName());\\n }\\n });\\n \\n this.doctors = unsortedDocs;\\n\\n }\",\n \"private List<List<Record>> sortRecordsBy(List<Record> unsortedRecords, RankingType rankingType) {\\n Comparator<Long> comparator = rankingType.isDescending()\\n ? Comparator.reverseOrder()\\n : Comparator.naturalOrder();\\n SortedMap<Long, List<Record>> scoreGroups = new TreeMap<>(comparator);\\n for (Record record : unsortedRecords) {\\n Long score = rankingType.getScoreFunction().apply(record);\\n if (scoreGroups.containsKey(score)) {\\n scoreGroups.get(score).add(record);\\n } else {\\n scoreGroups.put(score, new LinkedList<>());\\n scoreGroups.get(score).add(record);\\n }\\n }\\n\\n return new ArrayList<>(scoreGroups.values());\\n }\",\n \"Results sortResults(FilterSpecifier.ListBy listBy, SortSpecifier sortspec) throws SearchServiceException;\",\n \"void documentFrequncy(Set<String> features,\\n int index,\\n int troush\\n ) {\\n for (String str : features) {\\n switch (index) {\\n case 1:\\n for (int i = 0; i < count1; i++) {\\n if (economydocument[i].contains(str)) {\\n e++;\\n }\\n }\\n if (e > troush) {\\n documntfrequencyeco.put(str, e);\\n }\\n e = 0;\\n break;\\n case 2:\\n for (int i = 0; i < count2; i++) {\\n if (educationdocument[i].contains(str)) {\\n e++;\\n }\\n }\\n if (e > troush) {\\n documntfrequencyedu.put(str, e);\\n }\\n e = 0;\\n break;\\n case 3:\\n for (int i = 0; i < count3; i++) {\\n if (sportdocument[i].contains(str)) {\\n e++;\\n }\\n }\\n if (e > troush) {\\n documntfrequencyspo.put(str, e);\\n }\\n e = 0;\\n break;\\n case 4:\\n for (int i = 0; i < count4; i++) {\\n if (culturedocument[i].contains(str)) {\\n e++;\\n }\\n }\\n if (e > troush) {\\n documntfrequencycul.put(str, e);\\n }\\n e = 0;\\n break;\\n case 5:\\n for (int i = 0; i < count5; i++) {\\n if (accedentdocument[i].contains(str)) {\\n e++;\\n }\\n }\\n if (e > troush) {\\n documntfrequencyaccid.put(str, e);\\n }\\n e = 0;\\n break;\\n case 6:\\n for (int i = 0; i < count6; i++) {\\n if (environmntaldocument[i].contains(str)) {\\n e++;\\n }\\n }\\n if (e > troush) {\\n documntfrequencyenv.put(str, e);\\n }\\n e = 0;\\n break;\\n case 7:\\n for (int i = 0; i < count7; i++) {\\n if (foreign_affairdocument[i].contains(str)) {\\n e++;\\n }\\n }\\n if (e > troush) {\\n documntfrequencydep.put(str, e);\\n }\\n e = 0;\\n break;\\n case 8:\\n for (int i = 0; i < count8; i++) {\\n if (law_justicedocument[i].contains(str)) {\\n e++;\\n }\\n }\\n if (e > troush) {\\n documntfrequencylaw.put(str, e);\\n }\\n e = 0;\\n break;\\n case 9:\\n for (int i = 0; i < count9; i++) {\\n if (agriculture[i].contains(str)) {\\n e++;\\n }\\n }\\n if (e > troush) {\\n documntfrequencyagri.put(str, e);\\n }\\n e = 0;\\n break;\\n case 10:\\n for (int i = 0; i < count10; i++) {\\n if (politicsdocument[i].contains(str)) {\\n e++;\\n }\\n }\\n if (e > troush) {\\n documntfrequencypoltics.put(str, e);\\n }\\n e = 0;\\n break;\\n// case 11:\\n//\\n// for (int i = 0; i < count11; i++) {\\n// if (social_affairsdocument[i].contains(str)) {\\n// e++;\\n// }\\n// }\\n// if (e > troush) {\\n// documntfrequencysocial.put(str, e);\\n// }\\n// e = 0;\\n// break;\\n case 11:\\n for (int i = 0; i < count12; i++) {\\n if (science_technologydocument[i].contains(str)) {\\n e++;\\n }\\n }\\n\\n if (e > troush) {\\n documntfrequencysci.put(str, e);\\n }\\n e = 0;\\n break;\\n case 12:\\n for (int i = 0; i < count13; i++) {\\n if (healthdocument[i].contains(str)) {\\n e++;\\n }\\n }\\n if (e > troush) {\\n documntfrequencyhel.put(str, e);\\n }\\n e = 0;\\n break;\\n case 13:\\n for (int i = 0; i < count14; i++) {\\n if (army[i].contains(str)) {\\n e++;\\n }\\n }\\n\\n if (e > troush) {\\n documntfrequencyarmy.put(str, e);\\n }\\n e = 0;\\n break;\\n default:\\n break;\\n }\\n\\n }\\n }\",\n \"public void sortKnowledgeBase()\\n {\\n int i;\\n Random random;\\n String aPredicate;\\n StringTokenizer tokenizer;\\n //------------\\n random = new Random();\\n i = 0;\\n while (i < knowledgeBase.size())\\n {\\n aPredicate = knowledgeBase.get(i).commitments.get(0).predicate;\\n tokenizer = new StringTokenizer(aPredicate,\\\"(), \\\");\\n if(tokenizer.nextToken().equals(\\\"secuencia\\\"))\\n knowledgeBase.get(i).priority = random.nextInt(100);\\n //end if\\n else\\n knowledgeBase.get(i).priority = random.nextInt(10000);\\n //end else\\n i = i + 1;\\n }//end while\\n Collections.sort(knowledgeBase);\\n }\",\n \"public static void DocumentFrequencies() throws FileNotFoundException {\\n for (Entry<String, List<Integer>> entry : dictionary.entrySet()) {\\n List<Integer> termfrequency = new ArrayList<>();\\n\\n termfrequency = entry.getValue();\\t// getting each word's termfrequency list\\n int i = 0;\\n termfrequency.add(0); \\t\\t\\t//maintaining documentfrequency at the 57th index\\n Integer documentFrequency = termfrequency.get(totaldocument+1);\\n while(i<56) { //iterate 0 to 55 all speeches term frequency\\n if(termfrequency.get(i)>0) {\\t\\t//increment document frequency of that word if termfrequency is greater than 0.0\\n documentFrequency++;\\t\\t\\t//increment document frequency\\n }\\n i++;\\t\\t//increment index\\n }\\n termfrequency.set(57, documentFrequency);\\t//re-set the documentfrequency and save the current maintained document frequency from 0 to calculated value\\n dictionary.put(entry.getKey(), termfrequency);\\t\\t// place the incremented final value of that word back to the same list in dictionary hashmap\\n }\\n //save();\\n }\",\n \"private static String frequencySort(String s) {\\n if (s == null || s.isEmpty()) { return s; }\\n\\n int[] freq = new int[256];\\n for (char c : s.toCharArray()) {\\n freq[c]++;\\n }\\n\\n PriorityQueue<Pair<Character, Integer>> pq = new PriorityQueue<>((a, b) -> b.getValue() - a.getValue());\\n for (int i = 0; i < freq.length; i++) {\\n if (freq[i] == 0) { continue; }\\n Pair<Character, Integer> pair = new Pair<>((char) (i), freq[i]);\\n pq.offer(pair);\\n }\\n\\n StringBuilder sb = new StringBuilder();\\n while (!pq.isEmpty()) {\\n Pair<Character, Integer> pair = pq.poll();\\n for (int i = 0; i < pair.getValue(); i++) {\\n sb.append(pair.getKey());\\n }\\n }\\n return sb.toString();\\n }\",\n \"public void sortByTopic() {\\r\\n\\t\\tfor (int i = 1; i < displayingList.size(); i++) {\\r\\n\\t\\t\\tQuestion temp = displayingList.get(i);\\r\\n\\t\\t\\tfor (int j = i - 1; j >= 0; j--) {\\r\\n\\t\\t\\t\\tif (String.CASE_INSENSITIVE_ORDER.compare(temp.getTopic(), displayingList.get(j).getTopic()) < 0) {\\r\\n\\t\\t\\t\\t\\tdisplayingList.set(j + 1, displayingList.get(j));\\r\\n\\t\\t\\t\\t} else {\\r\\n\\t\\t\\t\\t\\tdisplayingList.set(j + 1, temp);\\r\\n\\t\\t\\t\\t\\tbreak;\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\tdisplayingList.set(j, temp);\\r\\n\\t\\t\\t}\\r\\n\\t\\t}\\r\\n\\t}\",\n \"private void sort() {\\n ScoreComparator comparator = new ScoreComparator();\\n Collections.sort(scores, comparator);\\n }\",\n \"private void updateDocPostingList(int docId){\\n int i = getIndexForDocument(docId);\\n if(i==-1){\\n // document does not exist in posting list. Error out.\\n System.err.println(\\\"Document not in List\\\");\\n updateDocPostingList(this.postingList.get(0));\\n }\\n int size = this.postingList.get(i+1);\\n this.docPostingList = new int[size];\\n int k = 0;\\n for(int j = i+2; j<size+i+2;j++)\\n this.docPostingList[k++] = this.postingList.get(j);\\n this.pos = 0;\\n\\n }\",\n \"private List<? extends Publication> sortPublicationsAfterTitle(Collection<? extends Publication> publicationList) {\\n\\n return publicationList.stream().sorted(Comparator.comparing(Publication::getTitle)).collect(Collectors.toList());\\n }\",\n \"void comparatorSort() {\\n Collections.sort(vendor, Vendor.sizeVendor); // calling collection sort method and passing list and comparator variables\\r\\n for (HDTV item : vendor) { //looping arraylist\\r\\n System.out.println(\\\"Brand: \\\" + item.brandname + \\\" Size: \\\" + item.size);\\r\\n }\\r\\n }\",\n \"private void sort() {\\n Collections.sort(mEntries, new Comparator<BarEntry>() {\\n @Override\\n public int compare(BarEntry o1, BarEntry o2) {\\n return o1.getX() > o2.getX() ? 1 : o1.getX() < o2.getX() ? -1 : 0;\\n }\\n });\\n }\",\n \"public HashMap<Integer, Integer> readFreqPosting(IndexReader indexReader, String fieldName, String term) throws IOException {\\n\\n\\t\\tHashMap<Integer, Integer> listOfFreqSortedByDocID = new HashMap<>();\\n\\t\\tSystem.out.printf( \\\"%-10s%-15s%-6s\\\\n\\\", \\\"DOCID\\\", \\\"URL\\\", \\\"FREQ\\\" );//Reads the posting list of the term in a specific index field. You need to encode the term into a BytesRef object, which is the internal representation of a term used by Lucene.\\n\\t\\tPostingsEnum posting = MultiFields.getTermDocsEnum( indexReader, fieldName, new BytesRef( term ), PostingsEnum.FREQS );\\n\\n\\t\\tif ( posting != null ) { // if the term does not appear in any document, the posting object may be null\\n\\t\\t\\tint docid;\\n\\t\\t\\twhile ( ( docid = posting.nextDoc() ) != PostingsEnum.NO_MORE_DOCS ) {//Each time you call posting.nextDoc(), it moves the cursor of the posting list to the next position and returns the docid of the current entry (document). Note that this is an internal Lucene docid. It returns PostingsEnum.NO_MORE_DOCS if you have reached the end of the posting list.\\n\\t\\t\\t\\tString url = getDocno( indexReader, \\\"url\\\", docid );\\n\\t\\t\\t\\tint freq = posting.freq(); // get the frequency of the term in the current document\\n\\t\\t\\t\\tlistOfFreqSortedByDocID.put(docid, freq);\\n\\t\\t\\t\\tSystem.out.printf( \\\"%-10d%-15s%-6d\\\\n\\\", docid, url, freq );\\n\\t\\t\\t}\\n\\t\\t}\\n\\n\\t\\treturn listOfFreqSortedByDocID;\\n\\t}\",\n \"public static void main(String args[]){\\r\\n\\t\\t\\r\\n\\t\\t\\r\\n\\t\\tint arr[] = {2,5,2,8,5,6,8,8};\\r\\n\\t\\t\\r\\n\\t\\tMap<Integer, Integer> freqMap = new LinkedHashMap<Integer,Integer>();\\r\\n\\t\\t\\r\\n\\t\\tfor(int i = 0; i< arr.length;i++){\\r\\n\\t\\t\\tif(freqMap.containsKey(arr[i])){\\r\\n\\t\\t\\t\\tint count = freqMap.get(arr[i]);\\r\\n\\t\\t\\t\\tfreqMap.put(arr[i],count + 1);\\r\\n\\t\\t\\t}else{\\r\\n\\t\\t\\t\\tfreqMap.put(arr[i], 1);\\r\\n\\t\\t\\t}\\r\\n\\t\\t}\\r\\n\\t\\t//2-2,5-2,6-1,8-3\\r\\n\\t\\t\\r\\n\\t\\tMap<Integer,ArrayList<Integer>> sortedList = new TreeMap<Integer, ArrayList<Integer>>(new Comparator<Integer>(){\\r\\n\\r\\n\\t\\t\\t@Override\\r\\n\\t\\t\\tpublic int compare(Integer arg0, Integer arg1) {\\r\\n\\t\\t\\t\\t// TODO Auto-generated method stub\\r\\n\\t\\t\\t\\treturn arg1.compareTo(arg0);\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\t\\r\\n\\t\\t});\\r\\n\\t\\t\\r\\n\\t\\tfor(Entry<Integer, Integer> entry : freqMap.entrySet()){\\r\\n\\t\\t\\tint key = entry.getKey();\\r\\n\\t\\t\\tint val = entry.getValue();\\r\\n\\t\\t\\tif(sortedList.containsKey(val)){\\r\\n\\t\\t\\t\\tArrayList<Integer> list = sortedList.get(val);\\r\\n\\t\\t\\t\\tfor(int j = 0; j<val ; j++)\\r\\n\\t\\t\\t\\t\\tlist.add(key);\\r\\n\\t\\t\\t}else{\\r\\n\\t\\t\\t\\tArrayList<Integer> list = new ArrayList<Integer>();\\r\\n\\t\\t\\t\\tfor(int j = 0; j<val ; j++)\\r\\n\\t\\t\\t\\t\\tlist.add(key);\\r\\n\\t\\t\\t\\tsortedList.put(val, list);\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\t\\r\\n\\t\\t}\\r\\n\\t\\t\\r\\n\\t\\tSystem.out.println(sortedList.values());\\r\\n\\t\\t\\r\\n\\t\\t\\r\\n\\t\\t\\r\\n\\t\\t\\r\\n\\t}\",\n \"public static String Sorts(Map<Integer,Double> docsInfo) {\\n Map<Integer, Double> sorted = docsInfo.entrySet().stream().sorted(Map.Entry.comparingByValue()).collect(Collectors.toMap(e -> e.getKey(), e -> e.getValue(), (e1, e2) -> e2,\\n LinkedHashMap::new));\\n String ans = \\\"\\\";\\n sorted = docsInfo\\n .entrySet()\\n .stream()\\n .sorted(Collections.reverseOrder(Map.Entry.comparingByValue()))\\n .collect(\\n Collectors.toMap(Map.Entry::getKey, Map.Entry::getValue, (e1, e2) -> e2,\\n LinkedHashMap::new));\\n for(Map.Entry<Integer, Double> en : sorted.entrySet()) {\\n ans = ans + (\\\"doc.Id ---> \\\" + en.getKey() +\\\"\\\\n\\\");\\n }\\n GUI.count = String.valueOf(sorted.size());\\n return ans;\\n }\",\n \"public CountryList sortByCount() {\\n\\t\\tCountryList sorted = new CountryList();\\n\\t\\tfor (int i = 0; i < this.nextAvailable; i++)\\n\\t\\t\\tsorted.binInsert(new Country(this.countries.get(i)));\\n\\t\\tsorted.totalCount = this.totalCount;\\n\\t\\treturn sorted;\\n\\t}\",\n \"SortComparator(Map<Integer, Integer> tFreqMap) { \\n this.freqMap = tFreqMap; \\n }\",\n \"public static List<String> sortUniqueWords(HashMap<String, Integer> tracker, List<String> allWords) {\\n List<Integer> frequency = new ArrayList<>(tracker.values());\\n frequency.sort(Collections.reverseOrder());\\n List<String> result = new ArrayList<>();\\n\\n while(!tracker.isEmpty()){\\n for (String key : allWords) {\\n if(frequency.size()!= 0 && frequency.get(0) == tracker.get(key)){\\n frequency.remove(0);\\n\\n result.add(key + \\\" \\\" + tracker.get(key));\\n tracker.remove(key);\\n }\\n\\n }\\n }\\n return result;\\n\\n\\n }\",\n \"private List<StringCountDto> getSortedStatistics() {\\n return STRING_STATISTICS.entrySet()\\n .stream()\\n .sorted(Map.Entry.<String, CounterInfo>comparingByValue().reversed())\\n .map(entry -> new StringCountDto(entry.getKey(), entry.getValue().getCount()))\\n .collect(Collectors.toList());\\n }\",\n \"public static void main(String[] args) {\\n String s = \\\"9988777yyhhgfvvvvvvddsseeeeww3344\\\";\\n System.out.println(frequencySort(s));\\n }\",\n \"private static HashMap<String,Integer> sortByEditDistance(String keyword, PreSearch ps) {\\r\\n\\t\\tHashMap<String, Integer> indexDistance = new HashMap<String,Integer>();\\r\\n\\t\\tIterator<Entry<String,HashSet<Integer>>> iterator = ps.index.entrySet().iterator();\\r\\n\\t\\twhile(iterator.hasNext()) \\r\\n\\t\\t{ \\t\\t\\t\\r\\n\\t\\t\\tMap.Entry<String, HashSet<Integer>> me = (Map.Entry<String, HashSet<Integer>>)iterator.next();\\r\\n\\t\\t\\tString word = me.getKey().toString();\\t\\t\\t\\r\\n\\t\\t\\tint distance = Sequences.editDistance(word, keyword);\\r\\n\\t\\t\\tif(distance<3 && distance!=0) {\\r\\n\\t\\t\\t\\tindexDistance.put(word, distance);\\t\\t\\t\\t\\r\\n\\t\\t\\t}\\r\\n\\t\\t}\\r\\n\\t\\t\\r\\n\\t\\tHashMap<String,Integer> sortedDistance = SortResultsByRank.sortValues(indexDistance);\\r\\n\\t\\treturn sortedDistance;\\r\\n\\t}\",\n \"public static void getHotItems(int k) throws IOException {\\r\\n\\t\\twlist = new ArrayList();\\r\\n\\t\\twlist.clear();\\r\\n\\t\\tBufferedReader input = new BufferedReader(new FileReader(\\r\\n\\t\\t\\t\\t\\\"frequency.txt\\\"));\\r\\n\\t\\tString buff = input.readLine();\\r\\n\\t\\t// \\\"sssss#xxx\\\\n\\\"\\r\\n\\t\\twhile (buff != null) {\\r\\n\\t\\t\\tString str[] = buff.split(\\\"#\\\");\\r\\n\\t\\t\\tWord w = new Word(str[0]);\\r\\n\\t\\t\\tw.setfreq(Integer.parseInt(str[1]));\\r\\n\\t\\t\\twlist.add(w);\\r\\n\\t\\t\\tbuff = input.readLine();\\r\\n\\t\\t}\\r\\n\\t\\tinput.close();\\r\\n\\t\\tsort(k);\\r\\n\\t\\tfor (int i = 0; i < k; i++) {\\r\\n\\t\\t\\tSystem.out.print(wlist.get(i).getval() + \\\"|\\\");\\r\\n\\t\\t}\\r\\n\\t}\",\n \"public void sortElements(){\\n\\t\\tgetInput();\\n\\t\\tPeople[] all = countAndSort(people, 0, people.length-1);\\n\\t\\t//PrintArray(all);\\n\\t\\tSystem.out.println(InversionCount);\\n\\t}\",\n \"public static void main(String[] args) {\\n\\n\\t\\tList<String> list = Arrays.asList(\\\"I\\\", \\\"Love\\\", \\\"Word\\\", \\\"I\\\", \\\"Love\\\");\\n\\t\\tMap<String, Long> map = list.stream()\\n\\t\\t\\t\\t.collect(Collectors.groupingBy(Function.identity(), Collectors.counting()));\\n\\t\\t//map.entrySet().stream().sorted(Comparator.(Entry.comparingByValue()).thenComparing(Entry.comparingByKey()))\\n\\t\\t// I - 2, \\\"Word\\\" -1, \\\"Love\\\"- 2\\n\\t\\t\\n\\t}\",\n \"private static void performSort(TestApp testApp) {\\n testApp.testPartition();\\n\\n /*\\n Date end = new Date();\\n System.out.println(\\\"Sort ended @ \\\" + end.getTime());\\n System.out.println(\\\"Total time = \\\" + (end.getTime() - start.getTime())/1000.0 + \\\" seconds...\\\");\\n */\\n }\",\n \"public void sortMarkers() {\\n\\t\\tCollections.sort(getMarkerSet().getMarkers(),\\r\\n\\t\\t\\t\\tnew MarkerTimeComparator());\\r\\n\\t\\t// log.debug(\\\"[sortMarkers]after: \\\" + getMarkerSet().getMarkers());\\r\\n\\r\\n\\t}\",\n \"private void printingSearchResults() {\\n HashMap<Integer, Double> resultsMap = new HashMap<>();\\n for (DocCollector collector : resultsCollector) {\\n if (resultsMap.containsKey(collector.getDocId())) {\\n double score = resultsMap.get(collector.getDocId()) + collector.getTermScore();\\n resultsMap.put(collector.getDocId(), score);\\n } else {\\n resultsMap.put(collector.getDocId(), collector.getTermScore());\\n }\\n }\\n List<Map.Entry<Integer, Double>> list = new LinkedList<>(resultsMap.entrySet());\\n Collections.sort(list, new Comparator<Map.Entry<Integer, Double>>() {\\n public int compare(Map.Entry<Integer, Double> o1,\\n Map.Entry<Integer, Double> o2) {\\n return (o2.getValue()).compareTo(o1.getValue());\\n }\\n });\\n if (list.isEmpty())\\n System.out.println(\\\"no match\\\");\\n else {\\n DecimalFormat df = new DecimalFormat(\\\".##\\\");\\n for (Map.Entry<Integer, Double> each : list)\\n System.out.println(\\\"docId: \\\" + each.getKey() + \\\" score: \\\" + df.format(each.getValue()));\\n }\\n\\n }\",\n \"private static void sortingArrayList() {\\n Collections.sort(allMapData, new Comparator<MapDataModel>() {\\n public int compare(MapDataModel d1, MapDataModel d2) {\\n return valueOf(d1.getDateTime().compareTo(d2.getDateTime()));\\n }\\n });\\n }\",\n \"public void sort() {\\r\\n // sort the process variables\\r\\n Arrays.sort(pvValues, categoryComparator);\\r\\n fireTableDataChanged();\\r\\n }\",\n \"private void sortDate()\\n {\\n for(int i = 0; i < movieList.size(); i++){\\n for(int j = 1; j < movieList.size() - i; j++)\\n {\\n Movie a = movieList.get(j-1);\\n Movie b = movieList.get(j);\\n int result = a.getReleaseDate().compareTo(b.getReleaseDate());\\n if( result < 0)\\n {\\n movieList.set(j-1, b);\\n movieList.set(j, a);\\n }\\n else if(result == 0)\\n {\\n result = a.getTitle().compareTo(b.getTitle());\\n if(result > 0)\\n {\\n movieList.set(j-1, b);\\n movieList.set(j, a);\\n }\\n }\\n }\\n }\\n }\",\n \"private void sortByDate(List<Entry> entries) {\\n\\t\\t\\n\\t\\tCollections.sort(entries, new Comparator<Entry>() {\\n\\t\\t\\tpublic int compare(Entry o1, Entry o2) {\\n\\t\\t\\t if (o1.getTimestamp() == null || o2.getTimestamp() == null)\\n\\t\\t\\t return 0;\\n\\t\\t\\t return o1.getTimestamp().compareTo(o2.getTimestamp());\\n\\t\\t\\t }\\n\\t\\t\\t});\\n\\t}\",\n \"public void sort()\\n {\\n\\tstrack.sort((Node n1, Node n2) ->\\n\\t{\\n\\t if (n1.getCost() < n2.getCost()) return -1;\\n\\t if (n1.getCost() > n2.getCost()) return 1;\\n\\t return 0;\\n\\t});\\n }\",\n \"public Map<String, Integer> getWordFrequencies(SortOrder sortBy) {\\n ArrayList<Map.Entry<String, MutableInteger>> entries =\\n new ArrayList<Map.Entry<String, MutableInteger>>(wordFrequency.entrySet());\\n if (sortBy == SortOrder.ALPHABETICALLY_ASCENDING) {\\n Collections.sort(entries, SORT_ALPHABETICALLY_ASCENDING);\\n } else {\\n Collections.sort(entries, SORT_BY_FREQUENCY_DESCENDING);\\n }\\n \\n Map<String, Integer> wordFrequencies = new HashMap<String, Integer>();\\n ValueComparator bvc = new ValueComparator(wordFrequencies);\\n TreeMap<String, Integer> sorted_map = new TreeMap(bvc);\\n \\n for (Map.Entry<String, MutableInteger> entry : entries) {\\n wordFrequencies.put(entry.getKey(), entry.getValue().getInteger());\\n }\\n \\n sorted_map.putAll(wordFrequencies);\\n\\n return sorted_map;\\n }\",\n \"public void listSort() {\\n\\t\\tCollections.sort(cd);\\n\\t}\",\n \"private static void sort(MongoCollection mongoCollection) {\\n mongoCollection.find().sort(eq(\\\"name\\\", 1)).forEach(new Block<Document>() {\\n public void apply(Document document) {\\n System.out.println(document.toJson());\\n }\\n });\\n }\",\n \"void sort();\",\n \"void sort();\",\n \"public static void pageRankmain() {\\n\\t\\t\\t\\n\\t\\t\\tstopWordStore();\\n\\t\\t\\t//File[] file_read= dir.listFiles();\\n\\t\\t\\t//textProcessor(file_read);// Will be called from LinkCrawler\\n\\t\\t\\t//queryProcess();\\n\\t\\t\\t//System.out.println(\\\"docsave \\\"+ docsave);\\n\\t\\t\\t/*for ( Map.Entry<String, ArrayList<String>> entry : docsave.entrySet()) {\\n\\t\\t\\t String key = entry.getKey();\\n\\t\\t\\t List<String> values = entry.getValue();\\n\\t\\t\\t System.out.print(\\\"Key = \\\" + key);\\n\\t\\t\\t System.out.println(\\\" , Values = \\\"+ values);\\n\\t\\t\\t}*/\\n\\t\\t\\t//########## RESPOINSIBLE FOR CREATING INVERTED INDEX OF TERMS ##########\\n\\t\\t\\tfor(int i=0;i<vocabulary.size();i++) {\\n\\t\\t\\t\\tint count=1;\\n\\t\\t\\t\\tMap<String, Integer> nestMap = new HashMap<String, Integer>();\\n\\t\\t\\t\\tfor ( Map.Entry<String, ArrayList<String>> entry : docsave.entrySet()) {\\n\\t\\t\\t\\t String keyMain = entry.getKey();\\n\\t\\t\\t\\t List<String> values = entry.getValue();\\n\\t\\t\\t\\t if(values.contains(vocabulary.get(i)))\\n\\t\\t\\t\\t \\t{\\n\\t\\t\\t\\t \\tentryDf.put(vocabulary.get(i), count);//entryDf stores documents frequency of vocabulary word \\\\\\\\it increase the count value for specific key\\n\\t\\t\\t\\t \\tcount++;\\n\\t\\t\\t\\t \\t}\\n\\t\\t\\t\\t \\n\\t\\t\\t\\t nestMap.put(keyMain, Collections.frequency(values,vocabulary.get(i)));\\n\\t\\t\\t \\t\\n\\t\\t\\t \\t//System.out.println(\\\"VOC \\\"+ vocabulary.get(i)+ \\\" KeyMain \\\" +keyMain+ \\\" \\\"+ Collections.frequency(values,vocabulary.get(i)));\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\ttfList.put(vocabulary.get(i), nestMap);\\n\\t\\t\\t}\\n\\t\\t\\t//########## RESPOINSIBLE FOR CREATING A MAP \\\"storeIdf\\\" TO STORE IDF VALUES OF TERMS ##########\\n\\t\\t\\tfor ( Map.Entry<String, Integer> endf : entryDf.entrySet()) {\\n\\t\\t\\t\\tString keydf = endf.getKey();\\n\\t\\t\\t\\tint valdf = endf.getValue();\\n\\t\\t\\t\\t//System.out.print(\\\"Key = \\\" + \\\"'\\\"+keydf+ \\\"'\\\");\\n\\t\\t\\t //System.out.print(\\\" , Values = \\\"+ valdf);\\n\\t\\t\\t double Hudai = (double) (docsave.size())/valdf;\\n\\t\\t\\t //System.out.println(\\\"docsave size \\\"+docsave.size()+ \\\" valdf \\\"+ valdf + \\\" Hudai \\\"+ Hudai+ \\\" log Value1 \\\"+ Math.log(Hudai)+ \\\" log Value2 \\\"+ Math.log(2));\\n\\t\\t\\t double idf= Math.log(Hudai)/Math.log(2);\\n\\t\\t\\t storeIdf.put(keydf, idf);\\n\\t\\t\\t //System.out.print(\\\" idf-> \\\"+ idf);\\n\\t\\t\\t //System.out.println();\\n\\t\\t\\t} \\n\\t\\t\\t\\n\\t\\t\\t//############ Just for Printing ##########NO WORK HERE########\\n\\t\\t\\tfor (Map.Entry<String, Map<String, Integer>> tokTf : tfList.entrySet()) {\\n\\t\\t\\t\\tString keyTf = tokTf.getKey();\\n\\t\\t\\t\\tMap<String, Integer> valTF = tokTf.getValue();\\n\\t\\t\\t\\tSystem.out.println(\\\"Inverted Indexing by Key Word = \\\" + \\\"'\\\"+keyTf+ \\\"'\\\");\\n\\t\\t\\t\\tfor (Map.Entry<String, Integer> nesTf : valTF.entrySet()) {\\n\\t\\t\\t\\t\\tString keyTF = nesTf.getKey();\\n\\t\\t\\t\\t\\tInteger valTf = nesTf.getValue();\\n\\t\\t\\t\\t\\tSystem.out.print(\\\" Document Consists This Key Word = \\\" + \\\"'\\\"+ keyTF+ \\\"'\\\");\\n\\t\\t\\t\\t\\tSystem.out.println(\\\" , Term Frequencies in This Doc = \\\"+ valTf);\\n\\t\\t\\t\\t} \\n\\t\\t\\t}\\n\\t\\t\\t//########### FOR CALCULATING DOCUMENT LENTH #############//\\n\\t\\t\\tfor ( Map.Entry<String, ArrayList<String>> entry_new : docsave.entrySet()) // Iterating Number of Documents\\n\\t\\t\\t{\\n\\t\\t\\t\\tString keyMain_new = entry_new.getKey();\\n\\t\\t\\t\\t//int countStop=0;\\n\\t\\t\\t\\tdouble sum=0;\\n\\t\\t\\t\\t for(Map.Entry<String, Map<String, Integer>> tokTf_new : tfList.entrySet()) // Iterating through the vocabulary\\n\\t\\t\\t\\t { \\n\\t\\t\\t\\t\\t Map<String, Integer> valTF_new = tokTf_new.getValue();\\n\\t\\t\\t\\t\\t for (Map.Entry<String, Integer> nesTf_new : valTF_new.entrySet()) // Iterating Through the Documents\\n\\t\\t\\t\\t\\t {\\n\\t\\t\\t\\t\\t\\t if(keyMain_new.equals(nesTf_new.getKey())) // Only doc name EQUAL with docsave name can enter here\\n\\t\\t\\t\\t\\t\\t {\\n\\t\\t\\t\\t\\t\\t\\t double val = nesTf_new.getValue()* (Double) storeIdf.get(tokTf_new.getKey());\\n\\t\\t\\t\\t\\t\\t\\t sum = sum+ Math.pow(val, 2);\\n\\t\\t\\t\\t\\t\\t }\\n\\t\\t\\t\\t\\t }\\n\\t\\t\\t\\t\\t \\n\\t\\t\\t\\t\\t //countStop++;\\n\\t\\t\\t\\t }\\n\\t\\t\\t\\t docLength.put(keyMain_new, Math.sqrt(sum));\\n\\t\\t\\t\\t sum=0;\\n\\t\\t\\t}\\n\\t\\t\\t\\n\\t\\t\\t\\n\\t\\t\\tSystem.out.println(\\\"Document Length \\\"+ docLength);\\n\\t\\t\\t//System.out.println(\\\"tfList \\\"+tfList);\\n\\t\\t\\t\\n\\t\\t\\t //########### FOR CALCULATING QUERY LENTH #############///\\n\\t\\t\\t\\tdouble qrySum=0;\\n\\t\\t\\t\\t for(String qryTerm: queryList) // Iterating through the vocabulary\\n\\t\\t\\t\\t {\\n\\t\\t\\t\\t\\t//entryQf.put(qryTerm, Collections.frequency(queryList,qryTerm));// VUl ase\\n\\t\\t\\t\\t\\t \\n\\t\\t\\t\\t\\t\\t if(storeIdf.get(qryTerm) != null) \\n\\t\\t\\t\\t\\t\\t {\\n\\t\\t\\t\\t\\t\\t\\t entryQf.put(qryTerm, Collections.frequency(queryList,qryTerm));\\n\\t\\t\\t\\t\\t\\t\\t double val = entryQf.get(qryTerm)* (Double) storeIdf.get(qryTerm);\\n\\t\\t\\t\\t\\t\\t\\t qrySum = qrySum+ Math.pow(val, 2);\\n\\t\\t\\t\\t\\t\\t }\\n\\t\\t\\t\\t\\t System.out.println(qryTerm+\\\" \\\"+entryQf.get(qryTerm)+ \\\" \\\"+ (Double) storeIdf.get(qryTerm));\\n\\t\\t\\t\\t }\\n\\t\\t\\t\\t qrySum=Math.sqrt(qrySum);\\n\\t\\t\\t\\t System.out.println(\\\"qrySum \\\" + qrySum);\\n\\t\\t\\t\\t \\n\\t\\t\\t\\t//########### FOR CALCULATING COSINE SIMILARITY #############///\\n\\t\\t\\t\\t for ( Map.Entry<String, ArrayList<String>> entry_dotP : docsave.entrySet()) // Iterating Number of Documents\\n\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\tdouble sumProduct=0;\\n\\t\\t\\t\\t\\t\\tdouble productTfIdf=0;\\n\\t\\t\\t\\t\\t\\tString keyMain_new = entry_dotP.getKey(); //Geting Doc Name\\n\\t\\t\\t\\t\\t\\t for(Map.Entry<String, Integer> qryTermItr : entryQf.entrySet()) // Iterating through the vocabulary\\n\\t\\t\\t\\t\\t\\t {\\n\\t\\t\\t\\t\\t\\t\\t \\n\\t\\t\\t\\t\\t\\t\\t Map<String, Integer> matchTerm = tfList.get(qryTermItr.getKey()); // Getting a map of doc Names by a Query Term as value of tfList\\n\\n\\t\\t\\t\\t\\t\\t\\t\\t if(matchTerm.containsKey(keyMain_new)) // Only doc name EQUAL with docsave name can enter here\\n\\t\\t\\t\\t\\t\\t\\t\\t {\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t //System.out.println(\\\"Test \\\"+ matchTerm.get(keyMain_new) +\\\" keyMain_new \\\" + keyMain_new);\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t double docTfIdf= matchTerm.get(keyMain_new) * storeIdf.get(qryTermItr.getKey());\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t double qryTfIdf= qryTermItr.getValue() * storeIdf.get(qryTermItr.getKey());\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t productTfIdf = docTfIdf * qryTfIdf;\\n\\t\\t\\t\\t\\t\\t\\t\\t }\\n\\t\\t\\t\\t\\t\\t\\t \\n\\t\\t\\t\\t\\t\\t\\t sumProduct= sumProduct+productTfIdf;\\n\\t\\t\\t\\t\\t\\t\\t //System.out.println(\\\"productTfIdf \\\"+productTfIdf+\\\" sumProduct \\\"+ sumProduct);\\n\\t\\t\\t\\t\\t\\t\\t productTfIdf=0;\\n\\t\\t\\t\\t\\t\\t }\\n\\t\\t\\t\\t\\t\\t cosineProd.put(entry_dotP.getKey(), sumProduct/(docLength.get(entry_dotP.getKey())*qrySum));\\n\\t\\t\\t\\t\\t\\t sumProduct=0;\\n\\t\\t\\t\\t\\t\\t //System.out.println(entry_dotP.getKey()+ \\\" \\\" + docLength.get(entry_dotP.getKey()));\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t System.out.println(\\\"cosineProd \\\"+ cosineProd);\\n\\t\\t\\t\\t \\n\\t\\t\\t\\t System.out.println(\\\"Number of Top Pages you want to see\\\");\\n\\t\\t\\t\\t int topRank = Integer.parseInt(scan.nextLine());\\n\\t\\t\\t\\t Map<String, Double> result = cosineProd.entrySet().stream()\\n\\t\\t\\t .sorted(Map.Entry.comparingByValue(Comparator.reverseOrder())).limit(topRank)\\n\\t\\t\\t .collect(Collectors.toMap(Map.Entry::getKey, Map.Entry::getValue,\\n\\t\\t\\t (oldValue, newValue) -> oldValue, LinkedHashMap::new));\\n\\n\\t\\t\\t\\t scan.close();\\n\\t\\t\\t //Alternative way\\n\\t\\t\\t //Map<String, Double> result2 = new LinkedHashMap<>();\\n\\t\\t\\t //cosineProd.entrySet().stream().sorted(Map.Entry.<String, Double>comparingByValue().reversed()).limit(2).forEachOrdered(x -> result2.put(x.getKey(), x.getValue()));\\n\\n\\t\\t\\t System.out.println(\\\"Sorted...\\\");\\n\\t\\t\\t System.out.println(result);\\n\\t\\t\\t //System.out.println(result2);\\n\\t}\",\n \"public void sort() {\\r\\n\\t\\tCollections.sort(parts);\\r\\n\\t}\",\n \"public ArrayList<String> top5search(String kw1, String kw2) {\\n\\t\\t/** COMPLETE THIS METHOD **/\\n\\t\\tArrayList<String> results = new ArrayList<String>();\\n\\t\\tArrayList<Occurrence> ocArr1 = new ArrayList<Occurrence>();\\n\\t\\tArrayList<Occurrence> ocArr2 = new ArrayList<Occurrence>();\\n\\t\\tArrayList<Occurrence> combined = new ArrayList<Occurrence>();\\n\\t\\t\\n\\t\\tif (keywordsIndex.containsKey(kw1))\\n\\t\\t\\tocArr1 = keywordsIndex.get(kw1);\\n\\t\\t\\n\\t\\tif (keywordsIndex.containsKey(kw2))\\n\\t\\t\\tocArr2 = keywordsIndex.get(kw2);\\n\\t\\t\\n\\t\\tcombined.addAll(ocArr1);\\n\\t\\tcombined.addAll(ocArr2);\\n\\t\\t\\n\\t\\tif (!(ocArr1.isEmpty()) && !(ocArr2.isEmpty()))\\n\\t\\t{\\n\\t\\t\\t// Sort with preference for ocArr1\\n\\t\\t\\tfor (int x = 0; x < combined.size()-1; x++)\\n\\t\\t\\t{\\n\\t\\t\\t\\tfor (int y = 1; y < combined.size()-x; y++)\\n\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\tif (combined.get(y-1).frequency < combined.get(y).frequency)\\n\\t\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\t\\tOccurrence temp = combined.get(y-1);\\n\\t\\t\\t\\t\\t\\tcombined.set(y-1, combined.get(y));\\n\\t\\t\\t\\t\\t\\tcombined.set(y, temp);\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\n\\t\\t\\t// Remove duplicates\\n\\t\\t\\tfor (int x = 0; x < combined.size()-1; x++)\\n\\t\\t\\t{\\n\\t\\t\\t\\tfor (int y = x + 1; y < combined.size(); y++)\\n\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\tif (combined.get(x).document == combined.get(y).document)\\n\\t\\t\\t\\t\\t\\tcombined.remove(y);\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t}\\n\\n\\t\\t// Top 5\\n\\t\\twhile (combined.size() > 5)\\n\\t\\t\\tcombined.remove(combined.size()-1);\\n\\t\\t\\n\\t\\t//System.out.println(combined);\\n\\t\\t\\n\\t\\tfor (Occurrence oc : combined)\\n\\t\\t\\tresults.add(oc.document);\\n\\n\\t\\treturn results;\\n\\t\\n\\t\\t\\n\\t\\t// following line is a placeholder to make the program compile\\n\\t\\t// you should modify it as needed when you write your code\\n\\t\\n\\t}\",\n \"public PostingsList ranked_query(Query query, double w, double idf_threshold){\\n long startTime = System.nanoTime();\\n PostingsList result = new PostingsList();\\n\\n // Obtain union of terms above idf threshold if indexElimination is true\\n // (Set idf_threshold to zero to disable this feature)\\n Set<String> termsToConsider = this.queryTermsConsidered(query, idf_threshold);\\n result = this.union_query(query, termsToConsider);\\n //System.err.println(\\\"Size of result is \\\" + result.size());\\n\\n long estimatedTime = (System.nanoTime() - startTime)/1000000;\\n System.err.println(\\\"* Union took: \\\" + estimatedTime);\\n\\n\\n /*\\n * 2) Iterate over PostingsEntries and build the solution\\n */\\n startTime = System.nanoTime();\\n // Required when iterating over a PostingsList\\n PostingsEntry postEnt = new PostingsEntry();\\n // Number of documents in the collection\\n double nDocs = this.docIDs.size();\\n // Weight of a query vector coefficient\\n double w_query_term;\\n // Document tf-idf variables\\n double termFrequency_doc, documentFrequency_doc, w_doc_term;\\n\\n for(String term : termsToConsider){\\n // Obtain idf of the term\\n documentFrequency_doc = Math.log(nDocs/new Double(this.idfMap.get(term)));\\n\\n // Obtain weight of the term\\n w_query_term = query.weights.get(term);\\n // Iterate over all documents containing the term and update the score(q,d)\\n Iterator<PostingsEntry> it_d = result.iterator();\\n while(it_d.hasNext()){\\n postEnt = it_d.next();\\n if (this.tfMap.get(postEnt.docID).containsKey(term)){\\n termFrequency_doc = this.tfMap.get(postEnt.docID).get(term);\\n w_doc_term = documentFrequency_doc*termFrequency_doc;\\n postEnt.score += w_query_term*w_doc_term;\\n }\\n }\\n }\\n estimatedTime = (System.nanoTime() - startTime)/1000000;\\n System.err.println(\\\"* Building solution took: \\\" + estimatedTime);\\n\\n /*\\n * 3) Normalize the scores\\n */\\n startTime = System.nanoTime();\\n Iterator<PostingsEntry> it = result.iterator();\\n while(it.hasNext()){\\n postEnt = it.next();\\n postEnt.score /= (new Double(this.docLengths.get(\\\"\\\"+postEnt.docID)));//(Math.sqrt(postEnt.norm2));\\n postEnt.score = w * postEnt.score + (1-w) * quality(postEnt.docID);\\n }\\n estimatedTime = (System.nanoTime() - startTime)/1000000;\\n System.err.println(\\\"* Normalizing took: \\\" + estimatedTime);\\n\\n /*\\n * 4) Sort the resulting solution\\n */\\n startTime = System.nanoTime();\\n result.sort();\\n estimatedTime = (System.nanoTime() - startTime)/1000000;\\n System.err.println(\\\"* Sorting took: \\\" + estimatedTime);\\n\\n return result;\\n }\",\n \"private static ArrayList<Quest> sortAfterTimestamp(ArrayList<Quest> questListToSort) {\\n\\t\\tfor (int i = 0; i < questListToSort.size() - 1; i++) {\\n\\t\\t\\tint index = i;\\n\\t\\t\\tfor (int j = i + 1; j < questListToSort.size(); j++) {\\n\\t\\t\\t\\tif (questListToSort.get(j).getTimestamp() > questListToSort.get(index).getTimestamp()) {\\n\\t\\t\\t\\t\\tindex = j;\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t\\tCollections.swap(questListToSort, index, i);\\n\\t\\t}\\n\\t\\treturn questListToSort;\\n\\t}\",\n \"private void sortRating()\\n {\\n for(int i = 0; i < movieList.size(); i++){\\n for(int j = 1; j < movieList.size() - i; j++)\\n {\\n Movie a = movieList.get(j-1);\\n Movie b = movieList.get(j);\\n int result = a.getRating().compareTo(b.getRating());\\n if(result < 0)\\n {\\n movieList.set(j-1, b);\\n movieList.set(j, a);\\n }\\n else if(result == 0)\\n {\\n result = a.getTitle().compareTo(b.getTitle());\\n if(result > 0)\\n {\\n movieList.set(j-1, b);\\n movieList.set(j, a);\\n }\\n }\\n }\\n }\\n }\",\n \"public List<String> getSortedResults() {\\r\\n\\t\\tList<String> subset;\\r\\n\\t\\tif (filter == null) {\\r\\n\\t\\t\\tsubset = allWords;\\r\\n\\t\\t} else {\\r\\n\\t\\t\\tsubset = getFilteredWords();\\r\\n\\t\\t}\\r\\n\\t\\tsortResults(subset);\\r\\n\\t\\tint wordCount = Math.min(subset.size(), wordLimit);\\r\\n\\t\\tArrayList<String> result = new ArrayList<String>(wordCount);\\t\\r\\n\\t\\tresult.addAll(subset.subList(0, wordCount));\\r\\n\\t\\treturn result;\\r\\n\\t}\",\n \"public void sortMatches();\",\n \"public static ArrayList<JsonNode> sortData(ArrayList<JsonNode> wordList) {\\n Collections.sort( wordList, new Comparator<JsonNode>() {\\n @Override\\n public int compare(JsonNode a, JsonNode b) {\\n int valA = Integer.parseInt(a.get(\\\"weight\\\").asText());\\n int valB = Integer.parseInt(b.get(\\\"weight\\\").asText());\\n return valB - valA; //Sort in order of largest to smallest\\n }\\n });\\n\\n return wordList;\\n }\",\n \"private void sortByKeys(LazyMap<ProcessorDistributionKey, Collection<Geometry>> keyToGeoms,\\n Collection<? extends Geometry> sortGeoms, Collection<Geometry> unprocessed)\\n {\\n final ProcessorDistributionKey hull = new ProcessorDistributionKey();\\n for (final Geometry geom : sortGeoms)\\n {\\n sortByKeys(keyToGeoms, geom, unprocessed, hull);\\n }\\n }\",\n \"private static void printTable(int numberOfDocs) {\\n \\n Gson gs = new Gson();\\n String json = gs.toJson(wor);\\n // System.out.println(json);\\n \\n List<String> queryWords = new ArrayList();\\n //to test it for other query word you can change the following two words\\n //queryWords.add(\\\"carpet\\\");\\n //queryWords.add(\\\"hous\\\");\\n queryWords.add(\\\"the\\\");\\n queryWords.add(\\\"crystallin\\\");\\n queryWords.add(\\\"len\\\");\\n queryWords.add(\\\"vertebr\\\");\\n queryWords.add(\\\"includ\\\");\\n \\n \\n FrequencySummary frequencySummary = new FrequencySummary();\\n frequencySummary.getSummary(json,docName, queryWords);\\n \\n System.exit(0);\\n \\n Hashtable<Integer,Integer> g = new Hashtable<>();\\n \\n /* wor.entrySet().forEach((wordToDocument) -> {\\n String currentWord = wordToDocument.getKey();\\n Map<String, Integer> documentToWordCount = wordToDocument.getValue();\\n freq.set(0);\\n df.set(0);\\n documentToWordCount.entrySet().forEach((documentToFrequency) -> {\\n String document = documentToFrequency.getKey();\\n Integer wordCount = documentToFrequency.getValue();\\n freq.addAndGet(wordCount);\\n System.out.println(\\\"Word \\\" + currentWord + \\\" found \\\" + wordCount +\\n \\\" times in document \\\" + document);\\n \\n if(g.getOrDefault(currentWord.hashCode(), null)==null){\\n g.put(currentWord.hashCode(),1);\\n \\n }else {\\n System.out.println(\\\"Hello\\\");\\n \\n int i = g.get(currentWord.hashCode());\\n System.out.println(\\\"i \\\"+i);\\n g.put(currentWord.hashCode(), i++);\\n }\\n // System.out.println(currentWord+\\\" \\\"+ g.get(currentWord.hashCode()));\\n // g.put(currentWord.hashCode(), g.getOrDefault(currentWord.hashCode(), 0)+wordCount);\\n \\n });\\n // System.out.println(freq.doubleValue());\\n \\n // System.out.println(\\\"IDF for this word: \\\"+Math.log10( (double)(counter/freq.doubleValue())));\\n });\\n // System.out.println(g.get(\\\"plai\\\".hashCode()));\\n //System.out.println(\\\"IDF for this word: \\\"+Math.log10( (double)(counter/(double)g.get(\\\"plai\\\".hashCode()))));\\n */\\n }\",\n \"static void countSort(List<List<String>> arr) {\\n StringBuilder rs = new StringBuilder(\\\"\\\");\\n int len = arr.size();\\n StringBuilder[] sList = new StringBuilder[100];\\n for (int i = 0; i < 100; i++) {\\n sList[i] = new StringBuilder(\\\"\\\");\\n }\\n for (int i = 0; i < len; i++) {\\n int n = Integer.parseInt(arr.get(i).get(0));\\n if (i < len / 2) {\\n sList[n].append(\\\"- \\\");\\n } else {\\n sList[n].append(arr.get(i).get(1) + \\\" \\\");\\n }\\n }\\n for (StringBuilder ls : sList) {\\n rs.append(ls);\\n }\\n System.out.println(rs.toString());\\n }\",\n \"public void createSummary(){\\n\\n for(int j=0;j<=noOfParagraphs;j++){\\n int primary_set = paragraphs.get(j).sentences.size()/5;\\n\\n //Sort based on score (importance)\\n Collections.sort(paragraphs.get(j).sentences,new SentenceComparator());\\n for(int i=0;i<=primary_set;i++){\\n contentSummary.add(paragraphs.get(j).sentences.get(i));\\n }\\n }\\n\\n //To ensure proper ordering\\n Collections.sort(contentSummary,new SentenceComparatorForSummary());\\n printSummary();\\n }\",\n \"public void sort() {\\n }\",\n \"public void sort() {\\n\\t\\t\\tfor (int j = nowLength - 1; j > 1; j--) {\\n\\t\\t\\t\\tfor (int i = 0; i < j; i++) {\\n\\t\\t\\t\\t\\tif (ray[i] > ray[i+1]) {\\n\\t\\t\\t\\t\\t\\tint tmp = ray [i];\\n\\t\\t\\t\\t\\t\\tray[i] = ray[i+1];\\n\\t\\t\\t\\t\\t\\tray[i+1] = tmp;\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\tprint();\\n\\t\\t\\t}\\n\\t}\",\n \"private static void RankedQueryMode(DiskIndexWriter diskWriter, DiskPositionalIndex disk_posIndex) throws IOException, ClassNotFoundException, InstantiationException, IllegalAccessException {\\n\\n if (query.equals(\\\"q\\\")) {\\n\\n System.exit(0);\\n }\\n\\n List<String> word = new ArrayList();\\n String[] query_array = query.split(\\\"\\\\\\\\s+\\\");\\n TokenProcessor processor = new NewTokenProcessor();\\n\\n for (int i = 0; i < query_array.length; i++) {\\n word.add(processor.processToken(query_array[i]).get(0));\\n }\\n\\n StrategyFactory sf = new StrategyFactory();\\n StrategyInterface strategy = sf.execute(rankedOption);\\n\\n //maps postings to accumulator value\\n HashMap<Integer, Doc_accum> postingMap = new HashMap<Integer, Doc_accum>();\\n\\n PriorityQueue<Doc_accum> queue = new PriorityQueue<>(Collections.reverseOrder());\\n\\n List<Posting> postings = new ArrayList<>();\\n List<Doc_accum> results = new ArrayList<>();\\n\\n for (String term : word) {\\n\\n postings = disk_posIndex.getPosting_noPos(term);\\n for (Posting p : postings) { //for each document in the postings list\\n double t_fd = p.getT_fd();\\n double d_ft = p.getD_ft();\\n double w_qt = strategy.calculate_wqt(N, d_ft);\\n double accum = 0;\\n double w_dt = strategy.get_wdt(t_fd, disk_posIndex, p.getDocumentId());\\n\\n //pairs (Ranked_posting, accumulator factor)\\n if (postingMap.containsKey(p.getDocumentId())) {\\n accum = postingMap.get(p.getDocumentId()).getAccumulator();\\n accum += (w_qt * w_dt);\\n postingMap.replace(p.getDocumentId(), new Doc_accum(p, accum)); //replaces old accum value\\n\\n } else {\\n accum += (w_qt * w_dt);\\n postingMap.put(p.getDocumentId(), new Doc_accum(p, accum));\\n }\\n }\\n\\n }\\n\\n for (Integer p : postingMap.keySet()) {\\n Doc_accum doc_temp = postingMap.get(p);\\n double accum = doc_temp.getAccumulator(); //gets accum associated with doc\\n\\n if (accum > 0) {\\n //search for each p's Ld factor in docWeights.bin\\n double l_d = strategy.calculate_Ld(disk_posIndex, doc_temp.getPosting().getDocumentId());\\n\\n accum /= l_d;\\n doc_temp.setAccumulator(accum);\\n }\\n\\n queue.add(postingMap.get(p));\\n\\n }\\n\\n //returns top K=10 results \\n int topK = 50;\\n\\n while ((results.size() < topK) && queue.size() > 0) {\\n\\n results.add(queue.poll()); //gets the posting acc pair and returns only posting\\n\\n }\\n\\n display_RankedResults(results);\\n\\n }\",\n \"public Iterator rankOrdering(Iterator pages)\\n\\t{\\n\\t\\t//Iterator allWebNode = ind.retrievePages(keyword);\\n\\t\\tIterator allWebNode = pages;\\n\\t\\tif(allWebNode.hasNext()){\\n\\t\\t\\tWebNode wb = (WebNode) allWebNode.next();\\n\\t\\t\\tint score = wb.getInDegree() * wb.getWordFreq(keyword);\\n\\t\\t\\twb.keywordScore = score;\\n\\t\\t\\taL.add(wb); \\n\\t\\t}\\n\\t\\t\\n\\t\\twhile (allWebNode.hasNext()) {\\n\\t\\t\\tWebNode nwb = (WebNode) allWebNode.next();\\n\\t\\t\\tint nscore = nwb.getInDegree() * nwb.getWordFreq(keyword);\\n\\t\\t\\tnwb.keywordScore = nscore;\\n\\t\\t\\tint i = 0; \\n\\t\\t\\twhile(i<aL.size()){\\n\\t\\t\\t\\tif (nwb.keywordScore < ((WebNode) aL.get(i)).keywordScore)\\n\\t\\t\\t \\ti++;\\n\\t\\t\\t else\\n\\t\\t\\t \\taL.add(i,nwb);\\n\\t\\t\\t} \\n\\t\\t}\\n\\t\\t\\n\\t\\treturn aL.iterator();\\n\\t}\",\n \"public void sortManlist(){\\r\\n\\t\\tCollections.sort(Manlist, new MySort());\\r\\n\\t}\",\n \"static void sortByFreq(int arr[], int n)\\r\\n {\\n int[] hash = new int[61];\\r\\n for (int x : arr) {\\r\\n hash[x]++;\\r\\n }\\r\\n HashMap<Integer, ArrayList<Integer>> valueHash = new HashMap<Integer, ArrayList<Integer>>();\\r\\n \\r\\n for (int i = 0; i<hash.length; i++) {\\r\\n int x = hash[i];\\r\\n if (x != 0) {\\r\\n if (valueHash.containsKey(x)) {\\r\\n valueHash.get(x).add(i);\\r\\n } else {\\r\\n ArrayList<Integer> list = new ArrayList<>();\\r\\n list.add(i);\\r\\n valueHash.put(x, list);\\r\\n }\\r\\n }\\r\\n }\\r\\n Set<Integer> keys = valueHash.keySet();\\r\\n List<Integer> list = new ArrayList<Integer>(keys); \\r\\n Collections.sort(list, new Comparator<Integer>()\\r\\n\\t\\t{\\r\\n\\t\\t\\t@Override\\r\\n\\t\\t\\tpublic int compare(Integer o1, Integer o2)\\r\\n\\t\\t\\t{\\r\\n\\t\\t\\t\\tif (o1 > o2) return -1;\\r\\n\\t\\t\\t\\t\\r\\n\\t\\t\\t\\treturn 1;\\r\\n\\t\\t\\t}\\r\\n\\t\\t});\\r\\n StringBuffer buff = new StringBuffer();\\r\\n for (int x : list) {\\r\\n \\tArrayList<Integer> numList = valueHash.get(x);\\r\\n \\tCollections.sort(numList);\\r\\n \\tfor (int num : numList) {\\r\\n \\t\\tint y = x;\\r\\n \\t\\twhile (y > 0) {\\r\\n \\t\\t\\tbuff.append(num + \\\" \\\");\\r\\n \\t\\t\\ty--;\\r\\n \\t\\t}\\r\\n \\t}\\r\\n }\\r\\n System.out.print(buff);\\r\\n }\",\n \"private static void sortingMemo() {\\n\\t\\t\\n\\t}\",\n \"private List<Article> sortTopics(Article queryTopic, List<Article>relatedTopics) throws Exception {\\n for (Article art:relatedTopics) \\n art.setWeight(_comparer.getRelatedness(art, queryTopic)) ;\\n\\n //Now that the weight attribute is set, sorting will be in descending order of weight.\\n //If weight was not set, it would be in ascending order of id. \\n Collections.sort(relatedTopics) ;\\n return relatedTopics ;\\n }\",\n \"public void sort() {\\n compares = 0;\\n shuttlesort((int[]) indexes.clone(), indexes, 0, indexes.length);\\n }\",\n \"private static List<MoneyLoss> sortLosses(Collection<MoneyLoss> unsortedLosses)\\n {\\n //Sort budget items first on frequency and then alphabetically\\n ArrayList<MoneyLoss> oneTimeItems = new ArrayList<MoneyLoss>();\\n ArrayList<MoneyLoss> dailyItems = new ArrayList<MoneyLoss>();\\n ArrayList<MoneyLoss> weeklyItems = new ArrayList<MoneyLoss>();\\n ArrayList<MoneyLoss> biweeklyItems = new ArrayList<MoneyLoss>();\\n ArrayList<MoneyLoss> monthlyItems = new ArrayList<MoneyLoss>();\\n ArrayList<MoneyLoss> yearlyItems = new ArrayList<MoneyLoss>();\\n\\n for (MoneyLoss loss : unsortedLosses)\\n {\\n switch (loss.lossFrequency())\\n {\\n case oneTime:\\n {\\n oneTimeItems.add(loss);\\n break;\\n }\\n case daily:\\n {\\n dailyItems.add(loss);\\n break;\\n }\\n case weekly:\\n {\\n weeklyItems.add(loss);\\n break;\\n }\\n case biWeekly:\\n {\\n biweeklyItems.add(loss);\\n break;\\n }\\n case monthly:\\n {\\n monthlyItems.add(loss);\\n break;\\n }\\n case yearly:\\n {\\n yearlyItems.add(loss);\\n break;\\n }\\n }\\n }\\n\\n Comparator<MoneyLoss> comparator = new Comparator<MoneyLoss>() {\\n @Override\\n public int compare(MoneyLoss lhs, MoneyLoss rhs) {\\n return lhs.expenseDescription().compareTo(rhs.expenseDescription());\\n }\\n };\\n\\n Collections.sort(oneTimeItems, comparator);\\n Collections.sort(dailyItems, comparator);\\n Collections.sort(weeklyItems, comparator);\\n Collections.sort(biweeklyItems, comparator);\\n Collections.sort(monthlyItems, comparator);\\n Collections.sort(yearlyItems, comparator);\\n\\n ArrayList<MoneyLoss> sortedItems = new ArrayList<MoneyLoss>();\\n BadBudgetApplication.appendItems(sortedItems, oneTimeItems);\\n BadBudgetApplication.appendItems(sortedItems, dailyItems);\\n BadBudgetApplication.appendItems(sortedItems, weeklyItems);\\n BadBudgetApplication.appendItems(sortedItems, biweeklyItems);\\n BadBudgetApplication.appendItems(sortedItems, monthlyItems);\\n BadBudgetApplication.appendItems(sortedItems, yearlyItems);\\n\\n return sortedItems;\\n }\",\n \"public void sortTree(TreeNode root){\\r\\n\\t\\tArrayList<TreeNode> newChildrenlist = new ArrayList<TreeNode>();\\r\\n\\t\\tIterator<TreeNode> it = root.children();\\r\\n\\t\\tTreeNode child;\\r\\n\\t\\tint i, j, l, freq;\\r\\n\\t\\twhile(it.hasNext()){\\r\\n\\t\\t\\tchild = it.next();\\r\\n\\t\\t\\tfreq = child.getFrequency();\\r\\n\\t\\t\\tif(newChildrenlist.size() == 0){\\r\\n\\t\\t\\t\\tnewChildrenlist.add(child);\\r\\n\\t\\t\\t}\\t\\t\\t\\r\\n\\t\\t\\telse if(newChildrenlist.get(0).getFrequency() <= freq){\\r\\n\\t\\t\\t\\tnewChildrenlist.add(0, child);\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\telse if(newChildrenlist.get(newChildrenlist.size()-1).getFrequency()\\r\\n\\t\\t\\t\\t\\t>= freq){\\r\\n\\t\\t\\t\\tnewChildrenlist.add(child);\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\telse{\\r\\n\\t\\t\\t\\ti = 0;\\r\\n\\t\\t\\t\\tj = newChildrenlist.size() - 1;\\r\\n\\t\\t\\t\\twhile(i < j){\\r\\n\\t\\t\\t\\t\\tl = (i+j)/2;\\r\\n\\t\\t\\t\\t\\tif(freq == newChildrenlist.get(l).getFrequency()){\\r\\n\\t\\t\\t\\t\\t\\tnewChildrenlist.add(l, child);\\r\\n\\t\\t\\t\\t\\t\\treturn;\\r\\n\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\tif(freq < newChildrenlist.get(l).getFrequency()){\\r\\n\\t\\t\\t\\t\\t\\ti = Math.max(l, i+1);\\r\\n\\t\\t\\t\\t\\t}else{\\r\\n\\t\\t\\t\\t\\t\\tj = Math.min(l, j-1);\\r\\n\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\tif(newChildrenlist.get(i).getFrequency() > freq){\\r\\n\\t\\t\\t\\t\\tnewChildrenlist.add(i+1, child);\\r\\n\\t\\t\\t\\t}else{\\r\\n\\t\\t\\t\\t\\tnewChildrenlist.add(i, child);\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t}\\r\\n\\t\\t}\\r\\n\\r\\n\\t\\troot.setChildren(newChildrenlist);\\r\\n\\t\\tit = root.children();\\r\\n\\t\\twhile(it.hasNext()){\\r\\n\\t\\t\\tchild = it.next();\\r\\n\\t\\t\\tsortTree(child);\\r\\n\\t\\t}\\r\\n\\t}\",\n \"public TreeMap<GenericDocument, LinkedList<Posting>> getDocumentBasedIndex(Collection collection) { \\r\\n\\t\\tTreeMap<GenericDocument, LinkedList<Posting>> result = new TreeMap<GenericDocument, LinkedList<Posting>>();\\r\\n\\t\\t\\r\\n\\t\\tfor(java.util.Collection<Posting> bag : map.values()) {\\r\\n\\t\\t\\tfor (Posting posting : bag) {\\r\\n\\t\\t\\t\\tGenericDocument doc = collection.findArticle(posting.getDocumentID());\\r\\n\\t\\t\\t\\tif (doc != null) {\\r\\n\\t\\t\\t\\t\\tif (result.containsKey(doc))\\r\\n\\t\\t\\t\\t\\t\\tresult.get(doc).add(posting);\\r\\n\\t\\t\\t\\t\\telse {\\r\\n\\t\\t\\t\\t\\t\\tLinkedList<Posting> list = new LinkedList<Posting>();\\r\\n\\t\\t\\t\\t\\t\\tlist.add(posting);\\r\\n\\t\\t\\t\\t\\t\\tresult.put(doc, list);\\r\\n\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\t\\t \\r\\n\\t\\t}\\r\\n\\t\\t \\r\\n\\t\\tSystem.out.println(\\\"Document based indexing complete.\\\");\\r\\n\\t\\treturn result;\\r\\n\\t}\",\n \"@Override\\r\\n\\tpublic void addSort() {\\n\\t\\t\\r\\n\\t}\",\n \"private List<Score> order(List<Score> s)\\n {\\n Collections.sort(s, new Comparator<Score>()\\n {\\n\\n @Override\\n public int compare(Score o1, Score o2) {\\n // TODO Auto-generated method stub\\n\\n return o1.getSentId() - o2.getSentId();\\n }\\n });\\n return s;\\n }\",\n \"public void ArtistAndSource() throws IOException{\\r\\n List<String> ArrangersAndTheirSongs=new ArrayList<>();\\r\\n HashMap <String,Integer> SongCountMap= new HashMap<>();\\r\\n String allsongs=\\\"\\\";\\r\\n String sourcesong=\\\"\\\";\\r\\n for(int id: ArrangersMap.keySet()){\\r\\n String ArrangerName=ArrangersMap.get(id);\\r\\n for(String song:ArrangerLinesList){\\r\\n String perform[];\\r\\n perform=song.split(\\\"/\\\");\\r\\n int arrangeid=Integer.parseInt(perform[1]);\\r\\n if(id==arrangeid){\\r\\n int songid= Integer.parseInt(perform[0]);\\r\\n String songname=test.getsongName(songid);\\r\\n sourcesong=test.SongToSource(songname);\\r\\n allsongs+=sourcesong+\\\",\\\";\\r\\n if (SongCountMap.get(sourcesong) !=null){ \\r\\n SongCountMap.put(sourcesong, SongCountMap.get(sourcesong)+1);\\r\\n }\\r\\n else{\\r\\n SongCountMap.put(sourcesong, 1);\\r\\n }\\r\\n } \\r\\n }\\r\\n for(String song:SongCountMap.keySet()){\\r\\n //System.out.println(song);\\r\\n }\\r\\n HashMap <String,Integer> SortedMap= sortByValues(SongCountMap);\\r\\n SongCountMap.clear();\\r\\n String allsongs2=\\\"\\\";\\r\\n for(String song:SortedMap.keySet()){\\r\\n //System.out.println(\\\"Number\\\"+SortedMap.get(song)+\\\"The song is\\\"+song);\\r\\n allsongs2+=\\\"#occurences:\\\"+SortedMap.get(song)+\\\"The song is\\\"+song+\\\"\\\\n\\\";\\r\\n //System.out.println(\\\"Number of times:\\\"+SortedMap.get(song)+\\\"The song is\\\"+song);\\r\\n }\\r\\n //System.out.println(allsongs2);\\r\\n // ArrangersAndTheirSongs.add(\\\"The Arrangers Name is:\\\"+ArrangerName+ \\\" Their songs are:\\\"+allsongs);\\r\\n ArrangersAndTheirSongs.add(\\\"The Arrangers Name is:\\\"+ArrangerName+ \\\" Their songs are: \\\"\\r\\n + \\\"\\\"+allsongs2);\\r\\n allsongs=\\\"\\\";\\r\\n SortedMap.clear();\\r\\n allsongs2=\\\"\\\";\\r\\n }\\r\\n //method is broken\\r\\n writeListToTextFile(\\\"d:\\\\\\\\documents\\\\\\\\textfiles\\\\\\\\ArrangersAndTheirSources.txt\\\",ArrangersAndTheirSongs);\\r\\n System.out.println(\\\"The size of the list is:\\\"+ArrangersAndTheirSongs.size());\\r\\n System.out.println(\\\"Artist and Their Source Complete\\\");\\r\\n }\",\n \"private void sort() {\\n setFiles(getFileStreamFromView());\\n }\",\n \"@Override\\n \\tpublic void sort() {\\n \\t\\tArrays.sort(data);\\n \\t}\",\n \"public HashMap<String, Integer> getOrder(){\\n\\t\\t\\n\\t\\tHashMap<String, Integer> hm2 = getHashMap();\\n\\t\\n\\t\\tArrayList fq = new ArrayList<>();\\n\\t\\t\\n\\t\\tHashMap<String, Integer> top10 = new HashMap<String, Integer>();\\n\\t\\t\\n\\t\\tfor(String key : hm2.keySet()){\\n\\t\\t\\t\\n\\t\\t\\tfq.add(hm2.get(key));\\n\\t\\t}\\n\\t\\t// use Collection to get the order of frequency\\n\\t\\tCollections.sort(fq);\\n \\tCollections.reverse(fq);\\n \\t\\n \\tfor(int i = 0; i<11; i++){\\n \\t\\t\\n \\t\\tfor(String key : hm2.keySet()){\\n \\t\\t// make sure the word not equals to balck space\\n \\t\\tif(hm2.get(key) == fq.get(i) && !key.equals(\\\"\\\") ){\\n \\t\\t\\t\\n \\t\\t top10.put(key, hm2.get(key));\\n \\t\\t\\t\\t\\n \\t\\t}\\n \\t}\\t\\n\\t}\\n\\t\\treturn top10;\\n\\t}\",\n \"public static void main(String[] args) {\\n\\n List<String> animals = new ArrayList <String>();\\n\\n animals.add(\\\"Elephatn\\\");\\n animals.add(\\\"snake\\\");\\n animals.add(\\\"Lion\\\");\\n animals.add(\\\"Mongoose\\\");\\n animals.add(\\\"Cat\\\");\\n\\n\\n\\n// Collections.sort(animals, new StringLengthComparator());\\n// Collections.sort(animals, new AlphabeticalComparator());\\n Collections.sort(animals, new ReverseAlphabeticalComparator());\\n for(String animal:animals){\\n System.out.println(animal);\\n }\\n\\n//////////////Sorting Numbers ///////////\\n List<Integer> numbers = new ArrayList <Integer>();\\n\\n numbers.add(54);\\n numbers.add(1);\\n numbers.add(36);\\n numbers.add(73);\\n numbers.add(9);\\n\\n Collections.sort(numbers, new Comparator <Integer>() {\\n @Override\\n public int compare(Integer num1, Integer num2) {\\n return num1.compareTo(num2);\\n }\\n });\\n\\n for(Integer number: numbers){\\n System.out.println(number);\\n }\\n\\n\\n///////////////Sorting Arbitrary objects////////\\n\\n\\n List<Person> people = new ArrayList <Person>();\\n\\n people.add(new Person(1,\\\"Joe\\\"));\\n people.add(new Person(5,\\\"Harry\\\"));\\n people.add(new Person(2,\\\"Hermoine\\\"));\\n people.add(new Person(4,\\\"Muffet\\\"));\\n\\n// Sort in order of ID\\n Collections.sort(people, new Comparator <Person>() {\\n @Override\\n public int compare(Person p1, Person p2) {\\n\\n if(p1.getId()>p2.getId()){\\n return 1;\\n }else if(p1.getId()<p2.getId()){\\n return -1;\\n }\\n return 0;\\n\\n }\\n });\\n\\n\\n // Sort in order of Name\\n Collections.sort(people, new Comparator <Person>() {\\n @Override\\n public int compare(Person p1, Person p2) {\\n\\n return p1.getName().compareTo(p2.getName());\\n\\n\\n }\\n });\\n\\n for(Person person: people){\\n System.out.println(person);\\n\\n }\\n\\n }\",\n \"public void sort()\\n\\t{\\n\\t\\tfor(int i=0;i<bowlers.size()-1;i++)\\n\\t\\t{\\n\\t\\t\\tfor(int j=i+1;j<bowlers.size();j++)\\n\\t\\t\\t{\\n\\t\\t\\t\\tif(bowlers.get(i).getBall()<bowlers.get(j).getBall())\\n\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\tBowler bowler=bowlers.get(i);\\n\\t\\t\\t\\t\\tbowlers.set(i,bowlers.get(j));\\n\\t\\t\\t\\t\\tbowlers.set(j,bowler);\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\tfor(int i=0;i<bowlers.size();i++)\\n\\t\\t{\\n\\t\\tSystem.out.println(bowlers.get(i).getBall());\\n\\t\\t}\\n\\t}\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.67374855","0.63989174","0.6172652","0.5989494","0.59094334","0.5851778","0.57968163","0.57893056","0.5646224","0.5625188","0.5610343","0.56095076","0.559386","0.55909723","0.5517896","0.5515005","0.5512062","0.5501602","0.54893845","0.54655427","0.54344296","0.53687227","0.5365804","0.5350844","0.5309958","0.5294334","0.5292904","0.5288388","0.52836674","0.5283448","0.5254197","0.5241266","0.52408475","0.52305454","0.5199939","0.5193841","0.5191041","0.51904106","0.5167683","0.5158811","0.5153203","0.51495206","0.51388747","0.51360935","0.5134825","0.5129145","0.51217264","0.5108417","0.51052976","0.509054","0.5083371","0.5078876","0.50775975","0.50693953","0.50582904","0.5050032","0.5039735","0.5029067","0.50277025","0.502086","0.50188714","0.5014433","0.5007968","0.50066066","0.5006377","0.5003297","0.5003297","0.49968514","0.49889508","0.49878192","0.49824104","0.497999","0.49757186","0.49733847","0.49708334","0.49705762","0.49686417","0.49683836","0.49678463","0.49619532","0.49613643","0.49573746","0.49569228","0.49538016","0.4952879","0.49333644","0.49332356","0.49259087","0.4917477","0.49140754","0.49116108","0.49075755","0.4903684","0.48996446","0.48970988","0.4890063","0.48888302","0.48862502","0.48789436","0.48740909"],"string":"[\n \"0.67374855\",\n \"0.63989174\",\n \"0.6172652\",\n \"0.5989494\",\n \"0.59094334\",\n \"0.5851778\",\n \"0.57968163\",\n \"0.57893056\",\n \"0.5646224\",\n \"0.5625188\",\n \"0.5610343\",\n \"0.56095076\",\n \"0.559386\",\n \"0.55909723\",\n \"0.5517896\",\n \"0.5515005\",\n \"0.5512062\",\n \"0.5501602\",\n \"0.54893845\",\n \"0.54655427\",\n \"0.54344296\",\n \"0.53687227\",\n \"0.5365804\",\n \"0.5350844\",\n \"0.5309958\",\n \"0.5294334\",\n \"0.5292904\",\n \"0.5288388\",\n \"0.52836674\",\n \"0.5283448\",\n \"0.5254197\",\n \"0.5241266\",\n \"0.52408475\",\n \"0.52305454\",\n \"0.5199939\",\n \"0.5193841\",\n \"0.5191041\",\n \"0.51904106\",\n \"0.5167683\",\n \"0.5158811\",\n \"0.5153203\",\n \"0.51495206\",\n \"0.51388747\",\n \"0.51360935\",\n \"0.5134825\",\n \"0.5129145\",\n \"0.51217264\",\n \"0.5108417\",\n \"0.51052976\",\n \"0.509054\",\n \"0.5083371\",\n \"0.5078876\",\n \"0.50775975\",\n \"0.50693953\",\n \"0.50582904\",\n \"0.5050032\",\n \"0.5039735\",\n \"0.5029067\",\n \"0.50277025\",\n \"0.502086\",\n \"0.50188714\",\n \"0.5014433\",\n \"0.5007968\",\n \"0.50066066\",\n \"0.5006377\",\n \"0.5003297\",\n \"0.5003297\",\n \"0.49968514\",\n \"0.49889508\",\n \"0.49878192\",\n \"0.49824104\",\n \"0.497999\",\n \"0.49757186\",\n \"0.49733847\",\n \"0.49708334\",\n \"0.49705762\",\n \"0.49686417\",\n \"0.49683836\",\n \"0.49678463\",\n \"0.49619532\",\n \"0.49613643\",\n \"0.49573746\",\n \"0.49569228\",\n \"0.49538016\",\n \"0.4952879\",\n \"0.49333644\",\n \"0.49332356\",\n \"0.49259087\",\n \"0.4917477\",\n \"0.49140754\",\n \"0.49116108\",\n \"0.49075755\",\n \"0.4903684\",\n \"0.48996446\",\n \"0.48970988\",\n \"0.4890063\",\n \"0.48888302\",\n \"0.48862502\",\n \"0.48789436\",\n \"0.48740909\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.6929145"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":13895,"cells":{"query":{"kind":"string","value":"OTHERS [MODIFIED] Returns all the words in the index."},"document":{"kind":"string","value":"public Set<String> keySet() {\n return this.index.keySet();\n }"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["public Set<String> getWords() {\n\t\treturn Collections.unmodifiableSet(this.invertedIndex.keySet());\n\t}","public Iterator words() {\n return index.keySet().iterator();\n }","public void showAllWords() {//out\n System.out.println(\"No\\t|English\\t|Vietnamese\");\n ArrayList<Word> fullDictionary = dictionaryManagement.getDictionary().getWords();\n for (int i = 0; i < fullDictionary.size(); i++) {\n String aWord = String.valueOf(i + 1) + \"\\t|\" + fullDictionary.get(i).getWordTarget()\n + \"\\t|\" + fullDictionary.get(i).getWordExplain();\n System.out.println(aWord);\n }\n }","private List<String> getFilteredWords() {\r\n\t\tArrayList<String> filteredWords = new ArrayList<String>(16);\r\n\t\t\r\n\t\tfor (String word : allWords) {\r\n\t\t\tif (matchesFilter(word) == true) {\r\n\t\t\t\tfilteredWords.add(word);\r\n\t\t\t}\r\n\t\t}\r\n\t\treturn filteredWords;\r\n\t}","public List<String> getAllWords() {\n List<String> words = new ArrayList<>();\n // get the words to the list\n getAllWords(root, \"\", 0, words);\n // and return the list of words\n return words;\n }","public ArrayList<String> getWords() {\n return new ArrayList<>(words);\n }","public Set<String> getWords() {\n return wordMap.keySet();\n }","static void allDocumentAnalyzer() throws IOException {\n\t\tFile allFiles = new File(\".\"); // current directory\n\t\tFile[] files = allFiles.listFiles(); // file array\n\n\t\t// recurse through all documents\n\t\tfor (File doc : files) {\n\t\t\t// other files we don't need\n\t\t\tif (doc.getName().contains(\".java\") || doc.getName().contains(\"words\") || doc.getName().contains(\"names\")\n\t\t\t\t\t|| doc.getName().contains(\"phrases\") || doc.getName().contains(\".class\")\n\t\t\t\t\t|| doc.getName().contains(\"Data\") || doc.getName().contains(\".sh\") || doc.isDirectory()\n\t\t\t\t\t|| !doc.getName().contains(\".txt\")) {\n\t\t\t\tcontinue;\n\t\t\t}\n\n\t\t\tString name = doc.getName();\n\t\t\tSystem.out.println(name);\n\t\t\tname = name.substring(0, name.length() - 11);\n\t\t\tSystem.out.println(name);\n\n\t\t\tif (!names.contains(name)) {\n\t\t\t\tcontinue;\n\t\t\t}\n\n\t\t\t// make readers\n\t\t\tFileReader fr = new FileReader(doc);\n\t\t\tBufferedReader br = new BufferedReader(fr);\n\n\t\t\t// phrase list\n\t\t\tArrayList<String> words = new ArrayList<String>();\n\n\t\t\t// retrieve all text, trim, refine and add to phrase list\n\t\t\tString nextLine = br.readLine();\n\t\t\twhile (nextLine != null) {\n\t\t\t\tnextLine = nextLine.replace(\"\\n\", \" \");\n\t\t\t\tnextLine = nextLine.trim();\n\n\t\t\t\tif (nextLine.contains(\"no experience listed\")) {\n\t\t\t\t\tbreak;\n\t\t\t\t}\n\n\t\t\t\tString[] lineArray = nextLine.split(\"\\\\s+\");\n\n\t\t\t\t// recurse through every word to find phrases\n\t\t\t\tfor (int i = 0; i < lineArray.length - 1; i++) {\n\t\t\t\t\t// get the current word and refine\n\t\t\t\t\tString currentWord = lineArray[i];\n\n\t\t\t\t\tcurrentWord = currentWord.trim();\n\t\t\t\t\tcurrentWord = refineWord(currentWord);\n\n\t\t\t\t\tif (currentWord.equals(\"\") || currentWord.isEmpty()) {\n\t\t\t\t\t\tcontinue;\n\t\t\t\t\t}\n\n\t\t\t\t\twords.add(currentWord);\n\t\t\t\t}\n\t\t\t\tnextLine = br.readLine();\n\t\t\t}\n\n\t\t\tbr.close();\n\n\t\t\t// continue if empty\n\t\t\tif (words.size() == 0) {\n\t\t\t\tcontinue;\n\t\t\t}\n\n\t\t\t// otherwise, increment number of files in corpus\n\t\t\tsize++;\n\n\t\t\t// updating the phrase count map for tf\n\t\t\tString fileName = doc.getName();\n\t\t\tphraseCountMap.put(fileName, words.size());\n\n\t\t\t// recurse through every word\n\t\t\tfor (String word : words) {\n\t\t\t\t// get map from string to freq\n\t\t\t\tHashMap<String, Integer> textFreqMap = wordFreqMap.get(fileName);\n\n\t\t\t\t// if it's null, make one\n\t\t\t\tif (textFreqMap == null) {\n\t\t\t\t\ttextFreqMap = new HashMap<String, Integer>();\n\t\t\t\t\t// make freq as 1\n\t\t\t\t\ttextFreqMap.put(word, 1);\n\t\t\t\t\t// put that in wordFreq\n\t\t\t\t\twordFreqMap.put(fileName, textFreqMap);\n\t\t\t\t} else {\n\t\t\t\t\t// otherwise, get the current num\n\t\t\t\t\tInteger currentFreq = textFreqMap.get(word);\n\n\t\t\t\t\t// if it's null,\n\t\t\t\t\tif (currentFreq == null) {\n\t\t\t\t\t\t// the frequency is just 0\n\t\t\t\t\t\tcurrentFreq = 0;\n\t\t\t\t\t}\n\n\t\t\t\t\t// increment the frequency\n\t\t\t\t\tcurrentFreq++;\n\n\t\t\t\t\t// put it in the textFreqMap\n\t\t\t\t\ttextFreqMap.put(word, currentFreq);\n\n\t\t\t\t\t// put that in the wordFreqMap\n\t\t\t\t\twordFreqMap.put(fileName, textFreqMap);\n\t\t\t\t}\n\n\t\t\t\t// add this to record (map from phrases to docs with that\n\t\t\t\t// phrase)\n\t\t\t\tinvertedMap.addValue(word, doc);\n\t\t\t}\n\t\t}\n\t}","public ArrayList<String> AIwords(){\n return wordsToDisplay;\n }","public Cursor getWords() \n\t{\n\t\tString query = String.format(_select, getDate()) +\n\t\t\t\t\t\t_havingDataContraint +\n\t\t\t\t\t\t\" ORDER BY \" + DBConstants.WordTable.WORD_KEY;\n\t\t\n\t\treturn _db.rawQuery(query, null);\t\n }","public String get_all_words(){\n\t\tString found_words = \"\";\n\t\t//We try to find the word within our childs\n\t\tfor(LexiNode child: childs){\n\t\t\t\tfound_words += child.get_all_words();\n\t\t}\n\t\tif(current_word != null && !found_words.equals(\"\"))\n\t\t\treturn current_word + \"#\" + found_words;\n\t\telse if(current_word != null && found_words.equals(\"\"))\n\t\t\treturn current_word+ \"#\";\n\t\telse //current_word == null && found_words != null\n\t\t\treturn found_words;\n\t}","public Set<String> getWords() {\n return wordsOccurrences.keySet();\n }","public ArrayList<String> getWords() {\n return words;\n }","public List<OOV> getOOVWords() {\n return this.OOVWords;\n }","private List<SearchWord> getSearchWords(Long lastUpdateTime) {\n return new ArrayList<>();\n }","@Override\r\n\t\t\tpublic Set<String> getStopWords() {\n\t\t\t\treturn null;\r\n\t\t\t}","public abstract Set<String> getTerms(Document doc);","SList oddWords();","public List<Word> getRelatedWordsOtherLanguage() {\n if (this._relatedOppositeLanguage == null) {\n this._relatedOppositeLanguage = MainActivity.db.getRelatedWordsByIdAndLanguage(this._id, this.getOppositeLanguage());\n }\n return this._relatedOppositeLanguage;\n }","private void addCustomWords() {\r\n\r\n }","public JTextPane getWords() {\n\t\treturn words;\n\t}","public final ArrayList<String> GetStringsForCurrentUnit(boolean otherStringsToo)\n {\n return MethodsUnitP.GetStringsUnitCommon(Unit, otherStringsToo);\n }","public List<String> getRelatedWords(String word) throws IOException {\n List<String> result = new ArrayList<String>();\n IDictionary dict = new Dictionary(new File(WORDNET_LOCATION));\n try {\n dict.open();\n IStemmer stemmer = new WordnetStemmer(dict);\n for (POS pos : EnumSet.of(POS.ADJECTIVE, POS.ADVERB, POS.NOUN, POS.VERB)) {\n List<String> resultForPos = new ArrayList<String>();\n List<String> stems = new ArrayList<String>();\n stems.add(word);\n for (String stem : stemmer.findStems(word, pos)) {\n if (!stems.contains(stem))\n stems.add(stem);\n }\n for (String stem : stems) {\n if (!resultForPos.contains(stem)) {\n resultForPos.add(stem);\n IIndexWord idxWord = dict.getIndexWord(stem, pos);\n if (idxWord == null) continue;\n List<IWordID> wordIDs = idxWord.getWordIDs();\n if (wordIDs == null) continue;\n IWordID wordID = wordIDs.get(0);\n IWord iword = dict.getWord(wordID);\n \n ISynset synonyms = iword.getSynset();\n List<IWord> iRelatedWords = synonyms.getWords();\n if (iRelatedWords != null) {\n for (IWord iRelatedWord : iRelatedWords) {\n String relatedWord = iRelatedWord.getLemma();\n if (!resultForPos.contains(relatedWord))\n resultForPos.add(relatedWord);\n }\n }\n \n List<ISynsetID> hypernymIDs = synonyms.getRelatedSynsets();\n if (hypernymIDs != null) {\n for (ISynsetID relatedSynsetID : hypernymIDs) {\n ISynset relatedSynset = dict.getSynset(relatedSynsetID);\n if (relatedSynset != null) {\n iRelatedWords = relatedSynset.getWords();\n if (iRelatedWords != null) {\n for (IWord iRelatedWord : iRelatedWords) {\n String relatedWord = iRelatedWord.getLemma();\n if (!resultForPos.contains(relatedWord))\n resultForPos.add(relatedWord);\n }\n }\n }\n }\n }\n }\n }\n for (String relatedWord : resultForPos) {\n if (relatedWord.length() > 3\n && !relatedWord.contains(\"-\")\n && !result.contains(relatedWord)) {\n // TODO: Hack alert!\n // The - check is to prevent lucene from interpreting hyphenated words as negative search terms\n // Fix!\n result.add(relatedWord);\n }\n }\n }\n } finally {\n dict.close();\n }\n return result;\n }","public Term[] getStopWords() {\n List<Term> allStopWords = new ArrayList<Term>();\n for (String fieldName : stopWordsPerField.keySet()) {\n Set<String> stopWords = stopWordsPerField.get(fieldName);\n for (String text : stopWords) {\n allStopWords.add(new Term(fieldName, text));\n }\n }\n return allStopWords.toArray(new Term[allStopWords.size()]);\n\t}","public ArrayList<Word> getNewWords() {\n\t\tArrayList<Word> newWords = new ArrayList<>();\n\t\tint index = 0;\n\t\twhile (index < m__vocabs.size() && newWords.size() <= m__numberOfNewVocabularies) {\n\t\t\tWord word = (Word)m__vocabs.get(index);\n\t\t\tif (word.getNumberOfRepetitions() == 0) {\n\t\t\t\tnewWords.add(word);\n\t\t\t}\n\t\t\tindex++;\n\t\t}\n\t\treturn newWords;\n\t}","public Set<String> hyponyms(String word) {\n Set<String> toReturn = new HashSet<String>();\n Set<Integer> wordIndexes = new HashSet<Integer>();\n wordIndexes = wnetsi.get(word);\n Set<Integer> toReturnInt = GraphHelper.descendants(g, wordIndexes);\n Object[] returnArray = toReturnInt.toArray();\n for (int i = 0; i < returnArray.length; i += 1) {\n Set<String> stringReturn = wnetis.get(returnArray[i]);\n Iterator<String> strIter = stringReturn.iterator();\n while (strIter.hasNext()) {\n toReturn.add(strIter.next());\n }\n }\n return toReturn;\n }","public void addAll(InvertedIndex other) {\n\t\tfor (String word : other.index.keySet()) {\n\t\t\tif (!this.index.containsKey(word)) {\n\t\t\t\tthis.index.put(word, other.index.get(word));\n\t\t\t}\n\t\t\telse {\n\t\t\t\tfor (String path : other.index.get(word).keySet()) {\n\t\t\t\t\tif (!this.index.get(word).containsKey(path)) {\n\t\t\t\t\t\tthis.index.get(word).put(path, other.index.get(word).get(path));\n\t\t\t\t\t}\n\t\t\t\t\telse {\n\t\t\t\t\t\tthis.index.get(word).get(path).addAll(other.index.get(word).get(path));\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}","public Set<String> getAllKnownWords() throws IOException {\n log.info(\"Reading all data to build known words set.\");\n Set<String> words = new HashSet<>();\n if (this.hasTrain()) {\n for (AnnoSentence sent : getTrainInput()) {\n words.addAll(sent.getWords());\n }\n }\n if (this.hasDev()) {\n for (AnnoSentence sent : getDevInput()) {\n words.addAll(sent.getWords());\n }\n }\n if (this.hasTest()) {\n for (AnnoSentence sent : getTestInput()) {\n words.addAll(sent.getWords());\n }\n }\n return words;\n }","@Override\n public int getNumberOfWords() {\n return 0;\n }","@Test\n\tpublic void singleWordGrepTest4() throws Exception {\n\t\t// word is 'undocumented'\n\t\tHashSet<String> grepFound = loadGrepResults(\"undocumented\");\n\t\tCollection<Page> index = queryTest.query(\"undocumented\");\n\t\tHashSet<String> indexFound = new HashSet<String>();\n\n\t\tfor (Page p : index)\n\t\t\tindexFound.add(p.getURL().getPath().toLowerCase());\n\t\t\n\t\t// tests set equality \n\t\tassertEquals(indexFound, grepFound);\n\t}","@Override\r\n\t@CacheCable(key=\"'wfx:SensitiveWord'\" ,value=\"value\",expiration=24*60*60)\r\n\tpublic List<String> getAllSensitiveWord() {\n\t\treturn shopMapper.getAllSensitiveWord();\r\n\r\n\t}","String[] getReservedWords();","public Set<String> getWordsNotFoundByUser(){\n\n Set<String> validWordsOnBoardCopy = new HashSet<String>();\n validWordsOnBoardCopy.addAll(validWordsOnBoard);\n validWordsOnBoardCopy.removeAll(validWordsFoundByUser);\n\n return validWordsOnBoardCopy;\n }","public ArrayList <String> getWordList () {\r\n return words;\r\n }","public ArrayList<ArrayList> simpleQuery(String word)\n {\n ArrayList<ArrayList> data = new ArrayList();\n\n IndexObject obj = myIndex.get(word.hashCode());\n if(obj == null)\n {\n errorMsg();\n return null;\n }\n data.add(new ArrayList<Document>(obj.getDocuments()));\n data.add(new ArrayList<Double>(obj.getRelevance()));\n data.add(new ArrayList<Integer>(obj.getOccurrence()));\n data.add(new ArrayList<Integer>(obj.getPopularity()));\n return data;\n }","@Override\n\tpublic Set<String> getWordSet() {\n\t\tlock.lockReadOnly();\n\t\ttry {\n\t\t\treturn super.getWordSet();\n\t\t} finally {\n\t\t\tlock.unlockReadOnly();\n\t\t}\n\t}","default List<String> interestingConcepts(int topK, UnitLocation located,\n Set<Location> irrelevantSet){\n // collect frequent words outside the blacklist of locations\n final TokenIterator extractor = new TokenIterator(irrelevantSet);\n located.getUnitNode().accept(extractor);\n\n final WordCounter wordCounter = new WordCounter(extractor.getItems());\n\n return wordCounter.mostFrequent(topK);\n }","public abstract String[][] getTopWords();","public List<String> analogyWords(String w1,String w2,String w3) {\n TreeSet<VocabWord> analogies = analogy(w1, w2, w3);\n List<String> ret = new ArrayList<>();\n for(VocabWord w : analogies) {\n String w4 = cache.wordAtIndex(w.getIndex());\n ret.add(w4);\n }\n return ret;\n }","public Collection<String> words() {\n Collection<String> words = new ArrayList<String>();\n TreeSet<Integer> keyset = new TreeSet<Integer>();\n keyset.addAll(countToWord.keySet());\n for (Integer count : keyset) {\n words.addAll(this.countToWord.get(count));\n }\n return words;\n }","private void setWordsOnly() throws IOException {\n this.wordsOnly = new HashSet<>();\n new InputAnalyzer().removePunctuation(inputText, wordsOnly::add);\n }","public void highLightWords(){\n }","public Iterator<String> words();","public final ArrayList<String> GetStringsForCurrentType(boolean otherStringsToo)\n {\n return MethodsUnitP.GetStringsTypeCommon(UnitType, otherStringsToo);\n }","@Override\r\n public String wordsOriginal(char[] arrayOfword) {\n String origalWord = \"\";//define a String for save the word orignal\r\n try {\r\n for (int i = 0; i < arrayOfword.length; i++) {\r\n origalWord += arrayOfword[i];//each charater put in the string origalWord\r\n }\r\n } catch (Exception e) {\r\n JOptionPane.showMessageDialog(null, \"An error has occured!\");\r\n }\r\n return origalWord;\r\n }","@Override\r\n\tpublic List getAllOtherList() {\n\t\tString HQL = \"\";\r\n\t\tHQL += \" from XzfyOtherSuggest x\";\r\n\t\tHQL += \" where 1 = 1 \";\t\r\n\t\treturn super.find(HQL);\r\n\t}","String getANY_OTHER();","public Vector<Word> allKeyValue(){\n\n\tVector<Word> words = new Vector<Word>();\n\tfor(int w = 0; w < theTable.length; w++){\n\t // System.out.println(\"w: \" + w);\n\t // System.out.println(\"theTable[w]: \" + theTable[w]);\n\t if(theTable[w] != null){\n\t\twords.addElement(theTable[w]);\n\t }\n\t}\n\treturn words;\n }","private StopWords() {\r\n\t\tPath source = Paths.get(\"./dat/zaustavne_rijeci.txt\");\r\n\t\ttry {\r\n\t\t\tbody = new String(Files.readAllBytes(source),\r\n\t\t\t\t\tStandardCharsets.UTF_8);\r\n\t\t} catch (IOException ignorable) {\r\n\t\t}\r\n\t\twords = new LinkedHashSet<>();\r\n\t\tfillSet();\r\n\t}","SList evenWords();","List<T> getWord();","@Override\n public List<DefinitionDTO> findAllWords() {\n List<Word> words = wordRepository.findAll();\n return DTOMapper.mapWordListToDefinitionDTOList(words);\n }","String getSynonyms();","private List<String> getContextWords(Tree tree) {\r\n List<String> words = null;\r\n if (op.trainOptions.useContextWords) {\r\n words = Generics.newArrayList();\r\n List<Label> leaves = tree.yield();\r\n for (Label word : leaves) {\r\n words.add(word.value());\r\n }\r\n }\r\n return words;\r\n }","public String getOthers() {\n return others;\n }","public String getOthers() {\n return others;\n }","private void displayWords() {\r\n\t\tList<String> words = results.getSortedResults();\r\n\t\tif (words.size() == 0) {\r\n\t\t\tSystem.out.println(\"NO results to display.\");\r\n\t\t} else {\r\n\t\t\tfor (String word : words) {\r\n\t\t\t\tSystem.out.println(word);\r\n\t\t\t}\r\n\t\t}\r\n\t}","@SuppressWarnings({ \"deprecation\", \"unchecked\", \"rawtypes\" })\n\tpublic String generateWordlists(Corpus co) {\n\t\tlong startTime = System.currentTimeMillis();\n\t\t// Set up weka word vector\n\t\tFastVector attributes;\n\t\tInstances dataSet;\n\t\tattributes = new FastVector();\n\n\t\tattributes.addElement(new Attribute(\"aspect_id\", (FastVector) null));\n\t\tattributes.addElement(new Attribute(\"tokens\", (FastVector) null));\n\n\t\tdataSet = new Instances(\"BeerAspects\", attributes, 0);\n\n\t\tCorpus topReviews;\n\t\tCorpus lowReviews;\n\n\t\t// Do top and low for all aspects\n\t\tfor (Aspect aspect : Aspect.values()) {\n\n\t\t\t// Only for actual aspects\n\t\t\tif (aspect.equals(Aspect.NONE) || aspect.equals(Aspect.OVERALL))\n\t\t\t\tcontinue;\n\n\t\t\ttopReviews = co.getTopReviews(aspect);\n\t\t\ttopReviews.analyze();\n\t\t\tString tokens = topReviews.getTokenConcatenation(aspect);\n\n\t\t\tInstance instance = new SparseInstance(2);\n\t\t\tinstance.setValue((Attribute) attributes.elementAt(0), aspect.name() + \"_TOP\");\n\t\t\tinstance.setValue((Attribute) attributes.elementAt(1), tokens);\n\n\t\t\tdataSet.add(instance);\n\n\t\t\tlowReviews = co.getLowReviews(aspect);\n\t\t\tlowReviews.analyze();\n\t\t\ttokens = lowReviews.getTokenConcatenation(aspect);\n\t\t\t// System.out.println(tokens);\n\n\t\t\tinstance = new SparseInstance(2);\n\t\t\tinstance.setValue((Attribute) attributes.elementAt(0), aspect.name() + \"_LOW\");\n\t\t\tinstance.setValue((Attribute) attributes.elementAt(1), tokens);\n\n\t\t\tdataSet.add(instance);\n\t\t}\n\n\t\t// System.out.println(dataSet.toString());\n\t\tInstances dataFiltered = transformToWordVector(dataSet, co.getProps());\n\n\t\t// System.out.println(dataFiltered.toString());\n\t\tString pathsToLists = writeWordlists(dataFiltered);\n\n\t\twriteArffFile(dataFiltered, this.outputDir+\"wordvector.arff\");\n\n\t\tlong stopTime = System.currentTimeMillis();\n\t\tlong elapsedTime = stopTime - startTime;\n\t\tSystem.out.println(\"Generated wordlists in: \" + elapsedTime / 1000 + \" s\");\n\t\treturn pathsToLists;\n\t}","public int deleteAllWords()\n\t{\n\t\t_db.delete(DBConstants.StatsTable.TABLENAME, null, null);\n\n\t\t//delete all words\n\t\treturn _db.delete(DBConstants.WordTable.TABLENAME, null, null);\n\t}","public List<Map.Entry<String, Integer>> getWordList(){\n\t\treturn new ArrayList<>(GeneralWordCounter.entrySet());\n\t}","public Set<String> getLocations(String word) {\n\t\tif (this.invertedIndex.get(word) == null) {\n\t\t\treturn Collections.emptySet();\n\t\t} else {\n\t\t\treturn Collections.unmodifiableSet(this.invertedIndex.get(word).keySet());\n\t\t}\n\t}","public synchronized Set<String> getStopWords() throws Exception {\r\n\t\t\r\n\t\tif(stopWords == null){\r\n\t\t\tMTDArquivoEnum enumerado = MTDArquivoEnum.STOP_WORDS;\r\n\t\t\tstopWords = new HashSet<String>();\r\n\t\t\tMTDIterator<String> it = enumerado.lineIterator();\r\n\t\t\twhile (it.hasNext()) {\r\n\t\t\t\tstopWords.add(it.next());\r\n\t\t\t}\r\n\t\t\tit.close();\r\n\t\t}\r\n \r\n return stopWords;\r\n }","@Override\r\n\t\t\tpublic String[] getTerms(Document doc) {\n\t\t\t\treturn null;\r\n\t\t\t}","private void addWords(){\n wordList.add(\"EGE\");\n wordList.add(\"ABBAS\");\n wordList.add(\"KAZIM\");\n }","public List<Query> similarTerms() {\n return this.similarTerms;\n }","public void getWord() {\n\t\t\n\t}","@Test\n\tpublic void singleWordGrepTest3() throws Exception {\n\t\t// word is 'mistress'\n\t\tHashSet<String> grepFound = loadGrepResults(\"mistress\");\n\t\tCollection<Page> index = queryTest.query(\"mistress\");\n\t\tHashSet<String> indexFound = new HashSet<String>();\n\n\t\tfor (Page p : index)\n\t\t\tindexFound.add(p.getURL().getPath().toLowerCase());\n\t\t\n\t\t// tests set equality \n\t\tassertEquals(indexFound, grepFound);\n\t}","private void allWordsListMouseClicked(java.awt.event.MouseEvent evt) {//GEN-FIRST:event_allWordsListMouseClicked\n \n String selectedWord = this.getAllWordsList().getSelectedValue();\n char firstLetterOfWord = selectedWord.charAt(0);\n \n // find the index of the corresponding tree tot he first letter of the word\n int index = -1;\n for(int i = 0 ; i < lexiNodeTrees.size() ; i++)\n {\n if(lexiNodeTrees.get(i).getCurrentCharacter() == firstLetterOfWord)\n {\n index = i;\n i = lexiNodeTrees.size();\n }\n }\n \n // find the word in the tree\n WordDefinition wordQuery = lexiNodeTrees.get(index).searchWord(selectedWord, true).get(0);\n \n // update definition field\n this.getDefinitionTextArea().setText(wordQuery.getDefinition());\n \n // display the word in the search field as well\n this.getSearchField().setText(selectedWord);\n \n // get search suggestion too\n searchWord();\n \n // select the same word in the search suggestion list \n ListModel<String> modelList = getSearchSuggestionList().getModel();\n \n for(int i = 0 ; i < modelList.getSize() ; i++)\n {\n if(modelList.getElementAt(i).equals(selectedWord))\n {\n getSearchSuggestionList().setSelectedIndex(i);\n i = modelList.getSize();\n }\n }\n \n }","public static Set<String> getEnglishWords()\n{\n return english_words;\n}","public static String getStopWords() throws IOException{\n\t\tString filepath1 = \"C:/Naveen/CCS/IR/AP89_DATA/AP_DATA/stoplist.txt\";\n\t\tPath path1 = Paths.get(filepath1);\n\t\tScanner scanner1 = new Scanner(path1);\n\t\tStringBuffer stopWords = new StringBuffer();\n\t\t\n\t\twhile (scanner1.hasNextLine()){\n\t\t\tString line = scanner1.nextLine();\n\t\t\tstopWords.append(line);\n\t\t\tstopWords.append(\"|\");\n\t } \n\t\t\n\t\tstopWords.append(\"document|discuss|identify|report|describe|predict|cite\");\n\t\tString allStopwords = stopWords.toString();\n\t\t//System.out.println(\"\"+allStopwords);\n\t\treturn allStopwords;\n\t}","@Override\n\tpublic List<Affectation> getAllAfByKeyWord(String keString) {\n\t\treturn dao.getAllAfByKeyWord(keString);\n\t}","@Test\n\tpublic void singleWordGrepTest1() throws Exception {\n\t\t// word is 'insane'\n\t\tHashSet<String> grepFound = loadGrepResults(\"insane\");\n\t\tCollection<Page> index = queryTest.query(\"insane\");\n\t\tHashSet<String> indexFound = new HashSet<String>();\n\n\t\tfor (Page p : index)\n\t\t\tindexFound.add(p.getURL().getPath().toLowerCase());\n\t\t\n\t\t// tests set equality with cardinality and one subset\n\t\tassertEquals(indexFound.size(), grepFound.size());\n\t\t\n\t\tHashSet<String> difference = new HashSet<String>(grepFound);\n\t\tdifference.removeAll(indexFound);\n\t\tassertEquals(0, difference.size());\n\t}","private static void splitWord() {\n\t\tint i = 1;\r\n\t\tfor(String doc : DocsTest) {\r\n\t\t\tArrayList<String> wordAll = new ArrayList<String>();\r\n\t\t\tfor (String word : doc.split(\"[,.() ; % : / \\t -]\")) {\r\n\t\t\t\tword = word.toLowerCase();\r\n\t\t\t\tif(word.length()>1 && !mathMethod.isNumeric(word)) {\r\n\t\t\t\t\twordAll.add(word);\r\n\t\t\t\t\tif(!wordList.contains(word)) {\r\n\t\t\t\t\t\twordList.add(word);\r\n\t\t\t\t\t}\r\n\t\t\t\t}\r\n\t\t\t}\r\n\t\t\twordAll.removeAll(stopword);\r\n\t\t\tDoclist.put(i, wordAll);\r\n\t\t\ti++;\r\n\t\t}\r\n\t\twordList.removeAll(stopword);\r\n\t}","public final ArrayList<String> GetStringsForCurrentTypeAndSystem(boolean otherStringsToo)\n {\n return MethodsUnitP.GetStringsTypeAndSystemCommon\n (\n \tUnitType, UnitSystem, otherStringsToo\n );\n }","public static List<String> GetWordsOnly(String pathToAnnFile) throws FileNotFoundException {\r\n\r\n\r\n List<String> originalList = GetFullAnnotations(pathToAnnFile);\r\n List<String> finalList = new ArrayList<>();\r\n\r\n for (String anno : originalList) {\r\n String[] split_anno = anno.split(\"\\t\"); // split each line\r\n String annoWord = split_anno[2]; // extract word\r\n finalList.add(annoWord); // append word to list\r\n }\r\n return finalList;\r\n }","public void computeWords(){\n\n loadDictionary();\n\n CharacterGrid characterGrid = readCharacterGrid();\n\n Set<String> wordSet = characterGrid.findWordMatchingDictionary(dictionary);\n\n System.out.println(wordSet.size());\n for (String word : wordSet) {\n\t System.out.println(word);\n }\n\n // System.out.println(\"Finish scanning character grid in \" + (System.currentTimeMillis() - startTime) + \" ms\");\n }","@Override\n protected FilterResults performFiltering(CharSequence arg0) {\n String[] tmp = API.it().getKeywords(arg0.toString());\n FilterResults results = new FilterResults();\n results.values = tmp;\n results.count = tmp.length;\n return results;\n }","private static void demonstrateListOperation(IndexWord word) throws JWNLException {\n PointerTargetNodeList hypernyms = PointerUtils.getInstance().getDirectHypernyms(word.getSense(1));\n System.out.println(\"Direct hypernyms of \\\"\" + word.getLemma() + \"\\\":\");\n for(int idx = 0; idx < hypernyms.size(); idx++){\n PointerTargetNode nn = (PointerTargetNode)hypernyms.get(idx);\n for(int wrdIdx = 0; wrdIdx < nn.getSynset().getWordsSize(); wrdIdx++){\n System.out.println(\"Syn\" + idx + \" of direct hypernyms of\\\"\" + word.getLemma() + \"\\\" : \" +\n nn.getSynset().getWord(wrdIdx).getLemma());\n }\n }\n hypernyms.print();\n }","public List<BasicString> getTermsAlternative() {\n return termsAlternative;\n }","@Test\n\tpublic void singleWordGrepTest2() throws Exception {\n\t\t// word is 'crazy'\n\t\tHashSet<String> grepFound = loadGrepResults(\"crazy\");\n\t\tCollection<Page> index = queryTest.query(\"crazy\");\n\t\tHashSet<String> indexFound = new HashSet<String>();\n\n\t\tfor (Page p : index)\n\t\t\tindexFound.add(p.getURL().getPath().toLowerCase());\n\t\t\n\t\t// tests set equality \n\t\tassertEquals(indexFound, grepFound);\n\t}","public void addWords(int i) \n\t{\n\t\tFile myFile = new File(i);\n\t\tallWords.addAll(myFile.getAllWords());\n\t\tSystem.out.println(allWords);\n\t}","public static List<Synset> getAllHyponymSynset(IndexWord word) throws JWNLException {\n List<Synset> result=new ArrayList<>();\n\n for(Synset wordSynset:word.getSenses()){\n PointerTargetTree hyponyms = PointerUtils.getInstance().getHyponymTree(wordSynset,4);\n PointerTargetTreeNode rootnode = hyponyms.getRootNode();\n LinkedList<PointerTargetTreeNode> stack = new LinkedList<>();\n if(rootnode==null){\n return result;\n }\n stack.add(rootnode);\n while(!stack.isEmpty()){\n PointerTargetTreeNode node = stack.pollLast();\n result.add(node.getSynset());\n PointerTargetTreeNodeList childList = node.getChildTreeList();\n if(childList!=null){\n for(int i=0;i<childList.size();i++){\n stack.add((PointerTargetTreeNode)childList.get(i));\n }\n }\n\n }\n\n }\n\n return result;\n }","public ArrayList<String> getOther(HashMap<String, String> simplePOSTagged) {\n ArrayList other = new ArrayList();\n for(String word: simplePOSTagged.keySet()){\n if (simplePOSTagged.get(word).equals(\"other\")){\n other.add(word);\n }\n }\n return other;\n }","public Set<String> getCommonTerms(Collection<String> main, Collection<String> searcher, Collection<String> stopwords, boolean lemmatised) {\n Set<String> result = new HashSet();\n\n List<String> newMain = new ArrayList();\n // Remove stopwords in new list\n for (String word : main) {\n if (!stopwords.contains(word.toLowerCase()))\n newMain.add(lemmatise(word.trim()));\n }\n // Get common words\n for (String word : searcher) {\n String nextWord = lemmatise(word.trim());\n if (newMain.contains(nextWord)) {\n if (lemmatised) result.add(nextWord.trim());\n else result.add(word.trim());\n }\n }\n\n return result;\n }","public Collection<Term> getAll() {\n\t\treturn terms.values();\n\t}","public List<String> getRandomWords(int numWords) throws Exception {\n\n List<String> randomWords = new ArrayList();\n\n List<Word> words = WordsApi.randomWords(true, null, null, 2, 0, 2, 0, 0, 0, null, null, numWords);\n\n for (Word word : words) {\n randomWords.add(word.getWord());\n }\n\n return randomWords;\n\n }","@Override\n\tpublic List<Literature> searchKeywords() {\n\t\treturn null;\n\t}","public DynamicArray<String> redactText()\n\t{\n\t\tfor (int i = 0; i < text.length(); i++)\n\t\t{\n\t\t\tif(!checkWord(text.get(i))) // checks if the word is listed to be redacted\n\t\t\t{\n\t\t\t\ttext.set(i, redact(text.get(i))); // Redacts word\n\t\t\t}\n\t\t\telse if (isNoun(i)) // Given the index this checks if the word is a noun, but ignores it if there is a full stop.\n\t\t\t{\n\t\t\t\twords.add(text.get(i)); // Since this is a noun, it is added to the list of redacted words\n\t\t\t\ttext.set(i, redact(text.get(i))); // Word is then redacted\n\t\t\t}\n\t\t}\n\t\t\n\t\tint i = 0;\n\t\tint check;\n\t\twhile (i < fullStops.length()) // Loops through full stop points and checks the word that follows it\n\t\t{\n\t\t\tcheck = fullStops.get(i);\n\t\t\tif(!checkWord(text.get(check)))\n\t\t\t{\n\t\t\t\ttext.set(check, redact(text.get(check)));\n\t\t\t}\n\t\t\ti++;\n\t\t\t\t\n\t\t}\n\t\treturn text;\n\t}","public String [] get_word_array(){\n\t\treturn word_array;\n\t}","public static LinkedList<Word> getPracticedWords() {\n return favWords;\n }","public ArrayList<SearchResult> partialSearch(String[] searchWords) {\n\t\tArrayList<SearchResult> words = new ArrayList<>();\n\t\tHashMap<String, SearchResult> resultMap = new HashMap<>();\n\t\tfor (String word : searchWords) {\n\t\t\tfor (String key : index.tailMap(word, true).navigableKeySet()) {\n\t\t\t\tif (key.startsWith(word)) {\n\t\t\t\t\twordSearch(key, resultMap, words);\n\t\t\t\t}\n\t\t\t\telse {\n\t\t\t\t\tbreak;\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t\t\n\t\tCollections.sort(words);\n\t\treturn words;\n\t}","private List<String> whitespaceSuggestions(String givenWord) {\n List<String> whitespaceWords = new ArrayList<>();\n for (int i = 1; i < givenWord.length() - 1; i++) {\n if (corpus.contains(givenWord.substring(0, i) + \" \"\n + givenWord.substring(i))) {\n whitespaceWords.add(givenWord.substring(0, i) + \" \"\n + givenWord.substring(i));\n } else if (corpus.contains(givenWord.substring(0, i))) {\n whitespaceWords.add(givenWord.substring(0, i));\n } else if (corpus.contains(givenWord.substring(i))) {\n whitespaceWords.add(givenWord.substring(i));\n }\n\n if (shortenings.contains(givenWord.substring(0, i))) {\n String fullWord = courseMappings.get(givenWord.substring(0, i));\n if (!givenWord.contains(fullWord)) {\n whitespaceWords.add(fullWord + \" \" + givenWord.substring(i));\n }\n\n }\n\n }\n\n return whitespaceWords;\n }","private String[] mixedWords(String[] words)\n {\n String[] output = new String[words.length];\n for(int i = 0; i < words.length; i++){\n if(i%2==0){\n output[i] = recombine(words[i], words[i+1]);\n } else {\n output[i] = recombine(words[i], words[i-1]);\n }\n }\n return output;\n }","public PorterStopWords()\r\n\t{\r\n\t\tstopWordsSet.addAll( porterStopWordsSet );\r\n\t}","public static List<Synset> getAllMeronymSynset(IndexWord word) throws JWNLException {\n List<Synset> result=new ArrayList<>();\n\n for(Synset wordSynset:word.getSenses()){\n PointerTargetTree hyponyms = PointerUtils.getInstance().getInheritedMeronyms(wordSynset,4,4);\n PointerTargetTreeNode rootnode = hyponyms.getRootNode();\n LinkedList<PointerTargetTreeNode> stack = new LinkedList<>();\n if(rootnode==null){\n return result;\n }\n stack.add(rootnode);\n while(!stack.isEmpty()){\n PointerTargetTreeNode node = stack.pollLast();\n result.add(node.getSynset());\n PointerTargetTreeNodeList childList = node.getChildTreeList();\n if(childList!=null){\n for(int i=0;i<childList.size();i++){\n stack.add((PointerTargetTreeNode)childList.get(i));\n }\n }\n\n }\n\n }\n\n return result;\n }","public void set_graph() throws ParseException, IOException {\n \tg = new WeightedUndirectedGraph(words.length);\n //g = new WeightedUndirectedGraph(most_important_terms.size());\n \n Directory dir = new SimpleFSDirectory(new File(\".\\\\data\\\\lucene_index_r_r\"));\n Analyzer analyzer = new StandardAnalyzer(LUCENE_41);\n \n // creat a map that stores, for each word (in the cluster), a set of all the documents that contain that word\n HashMap<String,HashSet<Integer>> word_to_docs_map = new HashMap<String,HashSet<Integer>>();\n int n_strings = words.length; \n \n // for each word...\n for (int idx = 0; idx < n_strings; idx++) {\n // query the index with that given word and retrieve all the documents that contains that word\n String query = words[idx]; \n QueryParser parser = new QueryParser(Version.LUCENE_41, \"text\", analyzer); \n Query q = parser.parse(query); \n\n IndexReader reader = DirectoryReader.open(dir);\n IndexSearcher searcher = new IndexSearcher(reader);\n TopDocs docs = searcher.search(q, reader.numDocs());\n ScoreDoc[] hits = docs.scoreDocs;\n \n // update map from word to docs it appears in \n //HashSet<Integer> tmp = null;\n // tmp is the set of all the document ids in which the current word is contained\n HashSet<Integer> tmp = new HashSet<>();\n //word_to_docs_map.put(query, tmp);\n \n // for each document, retrieved from the query\n for(Integer i=0;i<hits.length;i++) {\n Integer docId = hits[i].doc;\n // tmp = word_to_docs_map.get(query); \n // if the document is a document written by an user of interest \n if(indices.contains(docId)) {\n tmp.add(docId);\n }\n //word_to_docs_map.put(query, tmp); \n }\n word_to_docs_map.put(query, tmp);\n\t }\n\t \n\t // add edges: iterate over possible term pairs ...\n\t for(int idx_1 = 0; idx_1 < n_strings - 1; idx_1++) {\n\t \n\t for(int idx_2 = idx_1 + 1 ; idx_2 < n_strings ; idx_2 ++ ) {\n\t \n\t // extract document sets associated with the considered terms \n\t HashSet<Integer> set_a = word_to_docs_map.get(words[idx_1]); \n\t HashSet<Integer> set_b = word_to_docs_map.get(words[idx_2]); \n\t \n\t // compute set intersection \n\t int n = intersectionSize(set_a, set_b);\n\t \n\t // if the terms appear in at least one common document\n\t if(n>0) {\n\t // add edge \n\t g.testAndAdd(idx_1, idx_2 , n); \n\t }\n\t } \n\t }\n\t}","private ArrayList<WordDocument> executeAdvancedQuery(){\n ArrayList<WordDocument> documents = customDijkstrasTwoStack(this.query.split(\" \"));\n ArrayList<WordDocument> result = new ArrayList<WordDocument>();\n\n try{\n String[] orderByPart = query.substring(query.indexOf(\"ORDERBY\")).trim().toLowerCase().split(\" \");\n if(isOrderByCommand(orderByPart[0]))\n result = orderBy(documents, orderByPart[1], orderByPart[2]);\n }catch (StringIndexOutOfBoundsException ex){\n result = documents;\n }\n\n return result;\n }","@Test\n public void printAllWords() {\n // TODO\n }","public static ArrayList<String> findWords(TrieNode root) {\n\t\tArrayList<String> result = new ArrayList<String>();\n\t\tgetWords(root, \"\", result);\n\t\treturn result;\n\t}","public Collection<T> getOthers() {\n return others;\n }","List<VocabWord> document(int index);"],"string":"[\n \"public Set<String> getWords() {\\n\\t\\treturn Collections.unmodifiableSet(this.invertedIndex.keySet());\\n\\t}\",\n \"public Iterator words() {\\n return index.keySet().iterator();\\n }\",\n \"public void showAllWords() {//out\\n System.out.println(\\\"No\\\\t|English\\\\t|Vietnamese\\\");\\n ArrayList<Word> fullDictionary = dictionaryManagement.getDictionary().getWords();\\n for (int i = 0; i < fullDictionary.size(); i++) {\\n String aWord = String.valueOf(i + 1) + \\\"\\\\t|\\\" + fullDictionary.get(i).getWordTarget()\\n + \\\"\\\\t|\\\" + fullDictionary.get(i).getWordExplain();\\n System.out.println(aWord);\\n }\\n }\",\n \"private List<String> getFilteredWords() {\\r\\n\\t\\tArrayList<String> filteredWords = new ArrayList<String>(16);\\r\\n\\t\\t\\r\\n\\t\\tfor (String word : allWords) {\\r\\n\\t\\t\\tif (matchesFilter(word) == true) {\\r\\n\\t\\t\\t\\tfilteredWords.add(word);\\r\\n\\t\\t\\t}\\r\\n\\t\\t}\\r\\n\\t\\treturn filteredWords;\\r\\n\\t}\",\n \"public List<String> getAllWords() {\\n List<String> words = new ArrayList<>();\\n // get the words to the list\\n getAllWords(root, \\\"\\\", 0, words);\\n // and return the list of words\\n return words;\\n }\",\n \"public ArrayList<String> getWords() {\\n return new ArrayList<>(words);\\n }\",\n \"public Set<String> getWords() {\\n return wordMap.keySet();\\n }\",\n \"static void allDocumentAnalyzer() throws IOException {\\n\\t\\tFile allFiles = new File(\\\".\\\"); // current directory\\n\\t\\tFile[] files = allFiles.listFiles(); // file array\\n\\n\\t\\t// recurse through all documents\\n\\t\\tfor (File doc : files) {\\n\\t\\t\\t// other files we don't need\\n\\t\\t\\tif (doc.getName().contains(\\\".java\\\") || doc.getName().contains(\\\"words\\\") || doc.getName().contains(\\\"names\\\")\\n\\t\\t\\t\\t\\t|| doc.getName().contains(\\\"phrases\\\") || doc.getName().contains(\\\".class\\\")\\n\\t\\t\\t\\t\\t|| doc.getName().contains(\\\"Data\\\") || doc.getName().contains(\\\".sh\\\") || doc.isDirectory()\\n\\t\\t\\t\\t\\t|| !doc.getName().contains(\\\".txt\\\")) {\\n\\t\\t\\t\\tcontinue;\\n\\t\\t\\t}\\n\\n\\t\\t\\tString name = doc.getName();\\n\\t\\t\\tSystem.out.println(name);\\n\\t\\t\\tname = name.substring(0, name.length() - 11);\\n\\t\\t\\tSystem.out.println(name);\\n\\n\\t\\t\\tif (!names.contains(name)) {\\n\\t\\t\\t\\tcontinue;\\n\\t\\t\\t}\\n\\n\\t\\t\\t// make readers\\n\\t\\t\\tFileReader fr = new FileReader(doc);\\n\\t\\t\\tBufferedReader br = new BufferedReader(fr);\\n\\n\\t\\t\\t// phrase list\\n\\t\\t\\tArrayList<String> words = new ArrayList<String>();\\n\\n\\t\\t\\t// retrieve all text, trim, refine and add to phrase list\\n\\t\\t\\tString nextLine = br.readLine();\\n\\t\\t\\twhile (nextLine != null) {\\n\\t\\t\\t\\tnextLine = nextLine.replace(\\\"\\\\n\\\", \\\" \\\");\\n\\t\\t\\t\\tnextLine = nextLine.trim();\\n\\n\\t\\t\\t\\tif (nextLine.contains(\\\"no experience listed\\\")) {\\n\\t\\t\\t\\t\\tbreak;\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\tString[] lineArray = nextLine.split(\\\"\\\\\\\\s+\\\");\\n\\n\\t\\t\\t\\t// recurse through every word to find phrases\\n\\t\\t\\t\\tfor (int i = 0; i < lineArray.length - 1; i++) {\\n\\t\\t\\t\\t\\t// get the current word and refine\\n\\t\\t\\t\\t\\tString currentWord = lineArray[i];\\n\\n\\t\\t\\t\\t\\tcurrentWord = currentWord.trim();\\n\\t\\t\\t\\t\\tcurrentWord = refineWord(currentWord);\\n\\n\\t\\t\\t\\t\\tif (currentWord.equals(\\\"\\\") || currentWord.isEmpty()) {\\n\\t\\t\\t\\t\\t\\tcontinue;\\n\\t\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\t\\twords.add(currentWord);\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\tnextLine = br.readLine();\\n\\t\\t\\t}\\n\\n\\t\\t\\tbr.close();\\n\\n\\t\\t\\t// continue if empty\\n\\t\\t\\tif (words.size() == 0) {\\n\\t\\t\\t\\tcontinue;\\n\\t\\t\\t}\\n\\n\\t\\t\\t// otherwise, increment number of files in corpus\\n\\t\\t\\tsize++;\\n\\n\\t\\t\\t// updating the phrase count map for tf\\n\\t\\t\\tString fileName = doc.getName();\\n\\t\\t\\tphraseCountMap.put(fileName, words.size());\\n\\n\\t\\t\\t// recurse through every word\\n\\t\\t\\tfor (String word : words) {\\n\\t\\t\\t\\t// get map from string to freq\\n\\t\\t\\t\\tHashMap<String, Integer> textFreqMap = wordFreqMap.get(fileName);\\n\\n\\t\\t\\t\\t// if it's null, make one\\n\\t\\t\\t\\tif (textFreqMap == null) {\\n\\t\\t\\t\\t\\ttextFreqMap = new HashMap<String, Integer>();\\n\\t\\t\\t\\t\\t// make freq as 1\\n\\t\\t\\t\\t\\ttextFreqMap.put(word, 1);\\n\\t\\t\\t\\t\\t// put that in wordFreq\\n\\t\\t\\t\\t\\twordFreqMap.put(fileName, textFreqMap);\\n\\t\\t\\t\\t} else {\\n\\t\\t\\t\\t\\t// otherwise, get the current num\\n\\t\\t\\t\\t\\tInteger currentFreq = textFreqMap.get(word);\\n\\n\\t\\t\\t\\t\\t// if it's null,\\n\\t\\t\\t\\t\\tif (currentFreq == null) {\\n\\t\\t\\t\\t\\t\\t// the frequency is just 0\\n\\t\\t\\t\\t\\t\\tcurrentFreq = 0;\\n\\t\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\t\\t// increment the frequency\\n\\t\\t\\t\\t\\tcurrentFreq++;\\n\\n\\t\\t\\t\\t\\t// put it in the textFreqMap\\n\\t\\t\\t\\t\\ttextFreqMap.put(word, currentFreq);\\n\\n\\t\\t\\t\\t\\t// put that in the wordFreqMap\\n\\t\\t\\t\\t\\twordFreqMap.put(fileName, textFreqMap);\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\t// add this to record (map from phrases to docs with that\\n\\t\\t\\t\\t// phrase)\\n\\t\\t\\t\\tinvertedMap.addValue(word, doc);\\n\\t\\t\\t}\\n\\t\\t}\\n\\t}\",\n \"public ArrayList<String> AIwords(){\\n return wordsToDisplay;\\n }\",\n \"public Cursor getWords() \\n\\t{\\n\\t\\tString query = String.format(_select, getDate()) +\\n\\t\\t\\t\\t\\t\\t_havingDataContraint +\\n\\t\\t\\t\\t\\t\\t\\\" ORDER BY \\\" + DBConstants.WordTable.WORD_KEY;\\n\\t\\t\\n\\t\\treturn _db.rawQuery(query, null);\\t\\n }\",\n \"public String get_all_words(){\\n\\t\\tString found_words = \\\"\\\";\\n\\t\\t//We try to find the word within our childs\\n\\t\\tfor(LexiNode child: childs){\\n\\t\\t\\t\\tfound_words += child.get_all_words();\\n\\t\\t}\\n\\t\\tif(current_word != null && !found_words.equals(\\\"\\\"))\\n\\t\\t\\treturn current_word + \\\"#\\\" + found_words;\\n\\t\\telse if(current_word != null && found_words.equals(\\\"\\\"))\\n\\t\\t\\treturn current_word+ \\\"#\\\";\\n\\t\\telse //current_word == null && found_words != null\\n\\t\\t\\treturn found_words;\\n\\t}\",\n \"public Set<String> getWords() {\\n return wordsOccurrences.keySet();\\n }\",\n \"public ArrayList<String> getWords() {\\n return words;\\n }\",\n \"public List<OOV> getOOVWords() {\\n return this.OOVWords;\\n }\",\n \"private List<SearchWord> getSearchWords(Long lastUpdateTime) {\\n return new ArrayList<>();\\n }\",\n \"@Override\\r\\n\\t\\t\\tpublic Set<String> getStopWords() {\\n\\t\\t\\t\\treturn null;\\r\\n\\t\\t\\t}\",\n \"public abstract Set<String> getTerms(Document doc);\",\n \"SList oddWords();\",\n \"public List<Word> getRelatedWordsOtherLanguage() {\\n if (this._relatedOppositeLanguage == null) {\\n this._relatedOppositeLanguage = MainActivity.db.getRelatedWordsByIdAndLanguage(this._id, this.getOppositeLanguage());\\n }\\n return this._relatedOppositeLanguage;\\n }\",\n \"private void addCustomWords() {\\r\\n\\r\\n }\",\n \"public JTextPane getWords() {\\n\\t\\treturn words;\\n\\t}\",\n \"public final ArrayList<String> GetStringsForCurrentUnit(boolean otherStringsToo)\\n {\\n return MethodsUnitP.GetStringsUnitCommon(Unit, otherStringsToo);\\n }\",\n \"public List<String> getRelatedWords(String word) throws IOException {\\n List<String> result = new ArrayList<String>();\\n IDictionary dict = new Dictionary(new File(WORDNET_LOCATION));\\n try {\\n dict.open();\\n IStemmer stemmer = new WordnetStemmer(dict);\\n for (POS pos : EnumSet.of(POS.ADJECTIVE, POS.ADVERB, POS.NOUN, POS.VERB)) {\\n List<String> resultForPos = new ArrayList<String>();\\n List<String> stems = new ArrayList<String>();\\n stems.add(word);\\n for (String stem : stemmer.findStems(word, pos)) {\\n if (!stems.contains(stem))\\n stems.add(stem);\\n }\\n for (String stem : stems) {\\n if (!resultForPos.contains(stem)) {\\n resultForPos.add(stem);\\n IIndexWord idxWord = dict.getIndexWord(stem, pos);\\n if (idxWord == null) continue;\\n List<IWordID> wordIDs = idxWord.getWordIDs();\\n if (wordIDs == null) continue;\\n IWordID wordID = wordIDs.get(0);\\n IWord iword = dict.getWord(wordID);\\n \\n ISynset synonyms = iword.getSynset();\\n List<IWord> iRelatedWords = synonyms.getWords();\\n if (iRelatedWords != null) {\\n for (IWord iRelatedWord : iRelatedWords) {\\n String relatedWord = iRelatedWord.getLemma();\\n if (!resultForPos.contains(relatedWord))\\n resultForPos.add(relatedWord);\\n }\\n }\\n \\n List<ISynsetID> hypernymIDs = synonyms.getRelatedSynsets();\\n if (hypernymIDs != null) {\\n for (ISynsetID relatedSynsetID : hypernymIDs) {\\n ISynset relatedSynset = dict.getSynset(relatedSynsetID);\\n if (relatedSynset != null) {\\n iRelatedWords = relatedSynset.getWords();\\n if (iRelatedWords != null) {\\n for (IWord iRelatedWord : iRelatedWords) {\\n String relatedWord = iRelatedWord.getLemma();\\n if (!resultForPos.contains(relatedWord))\\n resultForPos.add(relatedWord);\\n }\\n }\\n }\\n }\\n }\\n }\\n }\\n for (String relatedWord : resultForPos) {\\n if (relatedWord.length() > 3\\n && !relatedWord.contains(\\\"-\\\")\\n && !result.contains(relatedWord)) {\\n // TODO: Hack alert!\\n // The - check is to prevent lucene from interpreting hyphenated words as negative search terms\\n // Fix!\\n result.add(relatedWord);\\n }\\n }\\n }\\n } finally {\\n dict.close();\\n }\\n return result;\\n }\",\n \"public Term[] getStopWords() {\\n List<Term> allStopWords = new ArrayList<Term>();\\n for (String fieldName : stopWordsPerField.keySet()) {\\n Set<String> stopWords = stopWordsPerField.get(fieldName);\\n for (String text : stopWords) {\\n allStopWords.add(new Term(fieldName, text));\\n }\\n }\\n return allStopWords.toArray(new Term[allStopWords.size()]);\\n\\t}\",\n \"public ArrayList<Word> getNewWords() {\\n\\t\\tArrayList<Word> newWords = new ArrayList<>();\\n\\t\\tint index = 0;\\n\\t\\twhile (index < m__vocabs.size() && newWords.size() <= m__numberOfNewVocabularies) {\\n\\t\\t\\tWord word = (Word)m__vocabs.get(index);\\n\\t\\t\\tif (word.getNumberOfRepetitions() == 0) {\\n\\t\\t\\t\\tnewWords.add(word);\\n\\t\\t\\t}\\n\\t\\t\\tindex++;\\n\\t\\t}\\n\\t\\treturn newWords;\\n\\t}\",\n \"public Set<String> hyponyms(String word) {\\n Set<String> toReturn = new HashSet<String>();\\n Set<Integer> wordIndexes = new HashSet<Integer>();\\n wordIndexes = wnetsi.get(word);\\n Set<Integer> toReturnInt = GraphHelper.descendants(g, wordIndexes);\\n Object[] returnArray = toReturnInt.toArray();\\n for (int i = 0; i < returnArray.length; i += 1) {\\n Set<String> stringReturn = wnetis.get(returnArray[i]);\\n Iterator<String> strIter = stringReturn.iterator();\\n while (strIter.hasNext()) {\\n toReturn.add(strIter.next());\\n }\\n }\\n return toReturn;\\n }\",\n \"public void addAll(InvertedIndex other) {\\n\\t\\tfor (String word : other.index.keySet()) {\\n\\t\\t\\tif (!this.index.containsKey(word)) {\\n\\t\\t\\t\\tthis.index.put(word, other.index.get(word));\\n\\t\\t\\t}\\n\\t\\t\\telse {\\n\\t\\t\\t\\tfor (String path : other.index.get(word).keySet()) {\\n\\t\\t\\t\\t\\tif (!this.index.get(word).containsKey(path)) {\\n\\t\\t\\t\\t\\t\\tthis.index.get(word).put(path, other.index.get(word).get(path));\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\telse {\\n\\t\\t\\t\\t\\t\\tthis.index.get(word).get(path).addAll(other.index.get(word).get(path));\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t}\\n\\t}\",\n \"public Set<String> getAllKnownWords() throws IOException {\\n log.info(\\\"Reading all data to build known words set.\\\");\\n Set<String> words = new HashSet<>();\\n if (this.hasTrain()) {\\n for (AnnoSentence sent : getTrainInput()) {\\n words.addAll(sent.getWords());\\n }\\n }\\n if (this.hasDev()) {\\n for (AnnoSentence sent : getDevInput()) {\\n words.addAll(sent.getWords());\\n }\\n }\\n if (this.hasTest()) {\\n for (AnnoSentence sent : getTestInput()) {\\n words.addAll(sent.getWords());\\n }\\n }\\n return words;\\n }\",\n \"@Override\\n public int getNumberOfWords() {\\n return 0;\\n }\",\n \"@Test\\n\\tpublic void singleWordGrepTest4() throws Exception {\\n\\t\\t// word is 'undocumented'\\n\\t\\tHashSet<String> grepFound = loadGrepResults(\\\"undocumented\\\");\\n\\t\\tCollection<Page> index = queryTest.query(\\\"undocumented\\\");\\n\\t\\tHashSet<String> indexFound = new HashSet<String>();\\n\\n\\t\\tfor (Page p : index)\\n\\t\\t\\tindexFound.add(p.getURL().getPath().toLowerCase());\\n\\t\\t\\n\\t\\t// tests set equality \\n\\t\\tassertEquals(indexFound, grepFound);\\n\\t}\",\n \"@Override\\r\\n\\t@CacheCable(key=\\\"'wfx:SensitiveWord'\\\" ,value=\\\"value\\\",expiration=24*60*60)\\r\\n\\tpublic List<String> getAllSensitiveWord() {\\n\\t\\treturn shopMapper.getAllSensitiveWord();\\r\\n\\r\\n\\t}\",\n \"String[] getReservedWords();\",\n \"public Set<String> getWordsNotFoundByUser(){\\n\\n Set<String> validWordsOnBoardCopy = new HashSet<String>();\\n validWordsOnBoardCopy.addAll(validWordsOnBoard);\\n validWordsOnBoardCopy.removeAll(validWordsFoundByUser);\\n\\n return validWordsOnBoardCopy;\\n }\",\n \"public ArrayList <String> getWordList () {\\r\\n return words;\\r\\n }\",\n \"public ArrayList<ArrayList> simpleQuery(String word)\\n {\\n ArrayList<ArrayList> data = new ArrayList();\\n\\n IndexObject obj = myIndex.get(word.hashCode());\\n if(obj == null)\\n {\\n errorMsg();\\n return null;\\n }\\n data.add(new ArrayList<Document>(obj.getDocuments()));\\n data.add(new ArrayList<Double>(obj.getRelevance()));\\n data.add(new ArrayList<Integer>(obj.getOccurrence()));\\n data.add(new ArrayList<Integer>(obj.getPopularity()));\\n return data;\\n }\",\n \"@Override\\n\\tpublic Set<String> getWordSet() {\\n\\t\\tlock.lockReadOnly();\\n\\t\\ttry {\\n\\t\\t\\treturn super.getWordSet();\\n\\t\\t} finally {\\n\\t\\t\\tlock.unlockReadOnly();\\n\\t\\t}\\n\\t}\",\n \"default List<String> interestingConcepts(int topK, UnitLocation located,\\n Set<Location> irrelevantSet){\\n // collect frequent words outside the blacklist of locations\\n final TokenIterator extractor = new TokenIterator(irrelevantSet);\\n located.getUnitNode().accept(extractor);\\n\\n final WordCounter wordCounter = new WordCounter(extractor.getItems());\\n\\n return wordCounter.mostFrequent(topK);\\n }\",\n \"public abstract String[][] getTopWords();\",\n \"public List<String> analogyWords(String w1,String w2,String w3) {\\n TreeSet<VocabWord> analogies = analogy(w1, w2, w3);\\n List<String> ret = new ArrayList<>();\\n for(VocabWord w : analogies) {\\n String w4 = cache.wordAtIndex(w.getIndex());\\n ret.add(w4);\\n }\\n return ret;\\n }\",\n \"public Collection<String> words() {\\n Collection<String> words = new ArrayList<String>();\\n TreeSet<Integer> keyset = new TreeSet<Integer>();\\n keyset.addAll(countToWord.keySet());\\n for (Integer count : keyset) {\\n words.addAll(this.countToWord.get(count));\\n }\\n return words;\\n }\",\n \"private void setWordsOnly() throws IOException {\\n this.wordsOnly = new HashSet<>();\\n new InputAnalyzer().removePunctuation(inputText, wordsOnly::add);\\n }\",\n \"public void highLightWords(){\\n }\",\n \"public Iterator<String> words();\",\n \"public final ArrayList<String> GetStringsForCurrentType(boolean otherStringsToo)\\n {\\n return MethodsUnitP.GetStringsTypeCommon(UnitType, otherStringsToo);\\n }\",\n \"@Override\\r\\n public String wordsOriginal(char[] arrayOfword) {\\n String origalWord = \\\"\\\";//define a String for save the word orignal\\r\\n try {\\r\\n for (int i = 0; i < arrayOfword.length; i++) {\\r\\n origalWord += arrayOfword[i];//each charater put in the string origalWord\\r\\n }\\r\\n } catch (Exception e) {\\r\\n JOptionPane.showMessageDialog(null, \\\"An error has occured!\\\");\\r\\n }\\r\\n return origalWord;\\r\\n }\",\n \"@Override\\r\\n\\tpublic List getAllOtherList() {\\n\\t\\tString HQL = \\\"\\\";\\r\\n\\t\\tHQL += \\\" from XzfyOtherSuggest x\\\";\\r\\n\\t\\tHQL += \\\" where 1 = 1 \\\";\\t\\r\\n\\t\\treturn super.find(HQL);\\r\\n\\t}\",\n \"String getANY_OTHER();\",\n \"public Vector<Word> allKeyValue(){\\n\\n\\tVector<Word> words = new Vector<Word>();\\n\\tfor(int w = 0; w < theTable.length; w++){\\n\\t // System.out.println(\\\"w: \\\" + w);\\n\\t // System.out.println(\\\"theTable[w]: \\\" + theTable[w]);\\n\\t if(theTable[w] != null){\\n\\t\\twords.addElement(theTable[w]);\\n\\t }\\n\\t}\\n\\treturn words;\\n }\",\n \"private StopWords() {\\r\\n\\t\\tPath source = Paths.get(\\\"./dat/zaustavne_rijeci.txt\\\");\\r\\n\\t\\ttry {\\r\\n\\t\\t\\tbody = new String(Files.readAllBytes(source),\\r\\n\\t\\t\\t\\t\\tStandardCharsets.UTF_8);\\r\\n\\t\\t} catch (IOException ignorable) {\\r\\n\\t\\t}\\r\\n\\t\\twords = new LinkedHashSet<>();\\r\\n\\t\\tfillSet();\\r\\n\\t}\",\n \"SList evenWords();\",\n \"List<T> getWord();\",\n \"@Override\\n public List<DefinitionDTO> findAllWords() {\\n List<Word> words = wordRepository.findAll();\\n return DTOMapper.mapWordListToDefinitionDTOList(words);\\n }\",\n \"String getSynonyms();\",\n \"private List<String> getContextWords(Tree tree) {\\r\\n List<String> words = null;\\r\\n if (op.trainOptions.useContextWords) {\\r\\n words = Generics.newArrayList();\\r\\n List<Label> leaves = tree.yield();\\r\\n for (Label word : leaves) {\\r\\n words.add(word.value());\\r\\n }\\r\\n }\\r\\n return words;\\r\\n }\",\n \"public String getOthers() {\\n return others;\\n }\",\n \"public String getOthers() {\\n return others;\\n }\",\n \"private void displayWords() {\\r\\n\\t\\tList<String> words = results.getSortedResults();\\r\\n\\t\\tif (words.size() == 0) {\\r\\n\\t\\t\\tSystem.out.println(\\\"NO results to display.\\\");\\r\\n\\t\\t} else {\\r\\n\\t\\t\\tfor (String word : words) {\\r\\n\\t\\t\\t\\tSystem.out.println(word);\\r\\n\\t\\t\\t}\\r\\n\\t\\t}\\r\\n\\t}\",\n \"@SuppressWarnings({ \\\"deprecation\\\", \\\"unchecked\\\", \\\"rawtypes\\\" })\\n\\tpublic String generateWordlists(Corpus co) {\\n\\t\\tlong startTime = System.currentTimeMillis();\\n\\t\\t// Set up weka word vector\\n\\t\\tFastVector attributes;\\n\\t\\tInstances dataSet;\\n\\t\\tattributes = new FastVector();\\n\\n\\t\\tattributes.addElement(new Attribute(\\\"aspect_id\\\", (FastVector) null));\\n\\t\\tattributes.addElement(new Attribute(\\\"tokens\\\", (FastVector) null));\\n\\n\\t\\tdataSet = new Instances(\\\"BeerAspects\\\", attributes, 0);\\n\\n\\t\\tCorpus topReviews;\\n\\t\\tCorpus lowReviews;\\n\\n\\t\\t// Do top and low for all aspects\\n\\t\\tfor (Aspect aspect : Aspect.values()) {\\n\\n\\t\\t\\t// Only for actual aspects\\n\\t\\t\\tif (aspect.equals(Aspect.NONE) || aspect.equals(Aspect.OVERALL))\\n\\t\\t\\t\\tcontinue;\\n\\n\\t\\t\\ttopReviews = co.getTopReviews(aspect);\\n\\t\\t\\ttopReviews.analyze();\\n\\t\\t\\tString tokens = topReviews.getTokenConcatenation(aspect);\\n\\n\\t\\t\\tInstance instance = new SparseInstance(2);\\n\\t\\t\\tinstance.setValue((Attribute) attributes.elementAt(0), aspect.name() + \\\"_TOP\\\");\\n\\t\\t\\tinstance.setValue((Attribute) attributes.elementAt(1), tokens);\\n\\n\\t\\t\\tdataSet.add(instance);\\n\\n\\t\\t\\tlowReviews = co.getLowReviews(aspect);\\n\\t\\t\\tlowReviews.analyze();\\n\\t\\t\\ttokens = lowReviews.getTokenConcatenation(aspect);\\n\\t\\t\\t// System.out.println(tokens);\\n\\n\\t\\t\\tinstance = new SparseInstance(2);\\n\\t\\t\\tinstance.setValue((Attribute) attributes.elementAt(0), aspect.name() + \\\"_LOW\\\");\\n\\t\\t\\tinstance.setValue((Attribute) attributes.elementAt(1), tokens);\\n\\n\\t\\t\\tdataSet.add(instance);\\n\\t\\t}\\n\\n\\t\\t// System.out.println(dataSet.toString());\\n\\t\\tInstances dataFiltered = transformToWordVector(dataSet, co.getProps());\\n\\n\\t\\t// System.out.println(dataFiltered.toString());\\n\\t\\tString pathsToLists = writeWordlists(dataFiltered);\\n\\n\\t\\twriteArffFile(dataFiltered, this.outputDir+\\\"wordvector.arff\\\");\\n\\n\\t\\tlong stopTime = System.currentTimeMillis();\\n\\t\\tlong elapsedTime = stopTime - startTime;\\n\\t\\tSystem.out.println(\\\"Generated wordlists in: \\\" + elapsedTime / 1000 + \\\" s\\\");\\n\\t\\treturn pathsToLists;\\n\\t}\",\n \"public int deleteAllWords()\\n\\t{\\n\\t\\t_db.delete(DBConstants.StatsTable.TABLENAME, null, null);\\n\\n\\t\\t//delete all words\\n\\t\\treturn _db.delete(DBConstants.WordTable.TABLENAME, null, null);\\n\\t}\",\n \"public List<Map.Entry<String, Integer>> getWordList(){\\n\\t\\treturn new ArrayList<>(GeneralWordCounter.entrySet());\\n\\t}\",\n \"public Set<String> getLocations(String word) {\\n\\t\\tif (this.invertedIndex.get(word) == null) {\\n\\t\\t\\treturn Collections.emptySet();\\n\\t\\t} else {\\n\\t\\t\\treturn Collections.unmodifiableSet(this.invertedIndex.get(word).keySet());\\n\\t\\t}\\n\\t}\",\n \"public synchronized Set<String> getStopWords() throws Exception {\\r\\n\\t\\t\\r\\n\\t\\tif(stopWords == null){\\r\\n\\t\\t\\tMTDArquivoEnum enumerado = MTDArquivoEnum.STOP_WORDS;\\r\\n\\t\\t\\tstopWords = new HashSet<String>();\\r\\n\\t\\t\\tMTDIterator<String> it = enumerado.lineIterator();\\r\\n\\t\\t\\twhile (it.hasNext()) {\\r\\n\\t\\t\\t\\tstopWords.add(it.next());\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\tit.close();\\r\\n\\t\\t}\\r\\n \\r\\n return stopWords;\\r\\n }\",\n \"@Override\\r\\n\\t\\t\\tpublic String[] getTerms(Document doc) {\\n\\t\\t\\t\\treturn null;\\r\\n\\t\\t\\t}\",\n \"private void addWords(){\\n wordList.add(\\\"EGE\\\");\\n wordList.add(\\\"ABBAS\\\");\\n wordList.add(\\\"KAZIM\\\");\\n }\",\n \"public List<Query> similarTerms() {\\n return this.similarTerms;\\n }\",\n \"public void getWord() {\\n\\t\\t\\n\\t}\",\n \"@Test\\n\\tpublic void singleWordGrepTest3() throws Exception {\\n\\t\\t// word is 'mistress'\\n\\t\\tHashSet<String> grepFound = loadGrepResults(\\\"mistress\\\");\\n\\t\\tCollection<Page> index = queryTest.query(\\\"mistress\\\");\\n\\t\\tHashSet<String> indexFound = new HashSet<String>();\\n\\n\\t\\tfor (Page p : index)\\n\\t\\t\\tindexFound.add(p.getURL().getPath().toLowerCase());\\n\\t\\t\\n\\t\\t// tests set equality \\n\\t\\tassertEquals(indexFound, grepFound);\\n\\t}\",\n \"private void allWordsListMouseClicked(java.awt.event.MouseEvent evt) {//GEN-FIRST:event_allWordsListMouseClicked\\n \\n String selectedWord = this.getAllWordsList().getSelectedValue();\\n char firstLetterOfWord = selectedWord.charAt(0);\\n \\n // find the index of the corresponding tree tot he first letter of the word\\n int index = -1;\\n for(int i = 0 ; i < lexiNodeTrees.size() ; i++)\\n {\\n if(lexiNodeTrees.get(i).getCurrentCharacter() == firstLetterOfWord)\\n {\\n index = i;\\n i = lexiNodeTrees.size();\\n }\\n }\\n \\n // find the word in the tree\\n WordDefinition wordQuery = lexiNodeTrees.get(index).searchWord(selectedWord, true).get(0);\\n \\n // update definition field\\n this.getDefinitionTextArea().setText(wordQuery.getDefinition());\\n \\n // display the word in the search field as well\\n this.getSearchField().setText(selectedWord);\\n \\n // get search suggestion too\\n searchWord();\\n \\n // select the same word in the search suggestion list \\n ListModel<String> modelList = getSearchSuggestionList().getModel();\\n \\n for(int i = 0 ; i < modelList.getSize() ; i++)\\n {\\n if(modelList.getElementAt(i).equals(selectedWord))\\n {\\n getSearchSuggestionList().setSelectedIndex(i);\\n i = modelList.getSize();\\n }\\n }\\n \\n }\",\n \"public static Set<String> getEnglishWords()\\n{\\n return english_words;\\n}\",\n \"public static String getStopWords() throws IOException{\\n\\t\\tString filepath1 = \\\"C:/Naveen/CCS/IR/AP89_DATA/AP_DATA/stoplist.txt\\\";\\n\\t\\tPath path1 = Paths.get(filepath1);\\n\\t\\tScanner scanner1 = new Scanner(path1);\\n\\t\\tStringBuffer stopWords = new StringBuffer();\\n\\t\\t\\n\\t\\twhile (scanner1.hasNextLine()){\\n\\t\\t\\tString line = scanner1.nextLine();\\n\\t\\t\\tstopWords.append(line);\\n\\t\\t\\tstopWords.append(\\\"|\\\");\\n\\t } \\n\\t\\t\\n\\t\\tstopWords.append(\\\"document|discuss|identify|report|describe|predict|cite\\\");\\n\\t\\tString allStopwords = stopWords.toString();\\n\\t\\t//System.out.println(\\\"\\\"+allStopwords);\\n\\t\\treturn allStopwords;\\n\\t}\",\n \"@Override\\n\\tpublic List<Affectation> getAllAfByKeyWord(String keString) {\\n\\t\\treturn dao.getAllAfByKeyWord(keString);\\n\\t}\",\n \"@Test\\n\\tpublic void singleWordGrepTest1() throws Exception {\\n\\t\\t// word is 'insane'\\n\\t\\tHashSet<String> grepFound = loadGrepResults(\\\"insane\\\");\\n\\t\\tCollection<Page> index = queryTest.query(\\\"insane\\\");\\n\\t\\tHashSet<String> indexFound = new HashSet<String>();\\n\\n\\t\\tfor (Page p : index)\\n\\t\\t\\tindexFound.add(p.getURL().getPath().toLowerCase());\\n\\t\\t\\n\\t\\t// tests set equality with cardinality and one subset\\n\\t\\tassertEquals(indexFound.size(), grepFound.size());\\n\\t\\t\\n\\t\\tHashSet<String> difference = new HashSet<String>(grepFound);\\n\\t\\tdifference.removeAll(indexFound);\\n\\t\\tassertEquals(0, difference.size());\\n\\t}\",\n \"private static void splitWord() {\\n\\t\\tint i = 1;\\r\\n\\t\\tfor(String doc : DocsTest) {\\r\\n\\t\\t\\tArrayList<String> wordAll = new ArrayList<String>();\\r\\n\\t\\t\\tfor (String word : doc.split(\\\"[,.() ; % : / \\\\t -]\\\")) {\\r\\n\\t\\t\\t\\tword = word.toLowerCase();\\r\\n\\t\\t\\t\\tif(word.length()>1 && !mathMethod.isNumeric(word)) {\\r\\n\\t\\t\\t\\t\\twordAll.add(word);\\r\\n\\t\\t\\t\\t\\tif(!wordList.contains(word)) {\\r\\n\\t\\t\\t\\t\\t\\twordList.add(word);\\r\\n\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\twordAll.removeAll(stopword);\\r\\n\\t\\t\\tDoclist.put(i, wordAll);\\r\\n\\t\\t\\ti++;\\r\\n\\t\\t}\\r\\n\\t\\twordList.removeAll(stopword);\\r\\n\\t}\",\n \"public final ArrayList<String> GetStringsForCurrentTypeAndSystem(boolean otherStringsToo)\\n {\\n return MethodsUnitP.GetStringsTypeAndSystemCommon\\n (\\n \\tUnitType, UnitSystem, otherStringsToo\\n );\\n }\",\n \"public static List<String> GetWordsOnly(String pathToAnnFile) throws FileNotFoundException {\\r\\n\\r\\n\\r\\n List<String> originalList = GetFullAnnotations(pathToAnnFile);\\r\\n List<String> finalList = new ArrayList<>();\\r\\n\\r\\n for (String anno : originalList) {\\r\\n String[] split_anno = anno.split(\\\"\\\\t\\\"); // split each line\\r\\n String annoWord = split_anno[2]; // extract word\\r\\n finalList.add(annoWord); // append word to list\\r\\n }\\r\\n return finalList;\\r\\n }\",\n \"public void computeWords(){\\n\\n loadDictionary();\\n\\n CharacterGrid characterGrid = readCharacterGrid();\\n\\n Set<String> wordSet = characterGrid.findWordMatchingDictionary(dictionary);\\n\\n System.out.println(wordSet.size());\\n for (String word : wordSet) {\\n\\t System.out.println(word);\\n }\\n\\n // System.out.println(\\\"Finish scanning character grid in \\\" + (System.currentTimeMillis() - startTime) + \\\" ms\\\");\\n }\",\n \"@Override\\n protected FilterResults performFiltering(CharSequence arg0) {\\n String[] tmp = API.it().getKeywords(arg0.toString());\\n FilterResults results = new FilterResults();\\n results.values = tmp;\\n results.count = tmp.length;\\n return results;\\n }\",\n \"private static void demonstrateListOperation(IndexWord word) throws JWNLException {\\n PointerTargetNodeList hypernyms = PointerUtils.getInstance().getDirectHypernyms(word.getSense(1));\\n System.out.println(\\\"Direct hypernyms of \\\\\\\"\\\" + word.getLemma() + \\\"\\\\\\\":\\\");\\n for(int idx = 0; idx < hypernyms.size(); idx++){\\n PointerTargetNode nn = (PointerTargetNode)hypernyms.get(idx);\\n for(int wrdIdx = 0; wrdIdx < nn.getSynset().getWordsSize(); wrdIdx++){\\n System.out.println(\\\"Syn\\\" + idx + \\\" of direct hypernyms of\\\\\\\"\\\" + word.getLemma() + \\\"\\\\\\\" : \\\" +\\n nn.getSynset().getWord(wrdIdx).getLemma());\\n }\\n }\\n hypernyms.print();\\n }\",\n \"public List<BasicString> getTermsAlternative() {\\n return termsAlternative;\\n }\",\n \"@Test\\n\\tpublic void singleWordGrepTest2() throws Exception {\\n\\t\\t// word is 'crazy'\\n\\t\\tHashSet<String> grepFound = loadGrepResults(\\\"crazy\\\");\\n\\t\\tCollection<Page> index = queryTest.query(\\\"crazy\\\");\\n\\t\\tHashSet<String> indexFound = new HashSet<String>();\\n\\n\\t\\tfor (Page p : index)\\n\\t\\t\\tindexFound.add(p.getURL().getPath().toLowerCase());\\n\\t\\t\\n\\t\\t// tests set equality \\n\\t\\tassertEquals(indexFound, grepFound);\\n\\t}\",\n \"public void addWords(int i) \\n\\t{\\n\\t\\tFile myFile = new File(i);\\n\\t\\tallWords.addAll(myFile.getAllWords());\\n\\t\\tSystem.out.println(allWords);\\n\\t}\",\n \"public static List<Synset> getAllHyponymSynset(IndexWord word) throws JWNLException {\\n List<Synset> result=new ArrayList<>();\\n\\n for(Synset wordSynset:word.getSenses()){\\n PointerTargetTree hyponyms = PointerUtils.getInstance().getHyponymTree(wordSynset,4);\\n PointerTargetTreeNode rootnode = hyponyms.getRootNode();\\n LinkedList<PointerTargetTreeNode> stack = new LinkedList<>();\\n if(rootnode==null){\\n return result;\\n }\\n stack.add(rootnode);\\n while(!stack.isEmpty()){\\n PointerTargetTreeNode node = stack.pollLast();\\n result.add(node.getSynset());\\n PointerTargetTreeNodeList childList = node.getChildTreeList();\\n if(childList!=null){\\n for(int i=0;i<childList.size();i++){\\n stack.add((PointerTargetTreeNode)childList.get(i));\\n }\\n }\\n\\n }\\n\\n }\\n\\n return result;\\n }\",\n \"public ArrayList<String> getOther(HashMap<String, String> simplePOSTagged) {\\n ArrayList other = new ArrayList();\\n for(String word: simplePOSTagged.keySet()){\\n if (simplePOSTagged.get(word).equals(\\\"other\\\")){\\n other.add(word);\\n }\\n }\\n return other;\\n }\",\n \"public Set<String> getCommonTerms(Collection<String> main, Collection<String> searcher, Collection<String> stopwords, boolean lemmatised) {\\n Set<String> result = new HashSet();\\n\\n List<String> newMain = new ArrayList();\\n // Remove stopwords in new list\\n for (String word : main) {\\n if (!stopwords.contains(word.toLowerCase()))\\n newMain.add(lemmatise(word.trim()));\\n }\\n // Get common words\\n for (String word : searcher) {\\n String nextWord = lemmatise(word.trim());\\n if (newMain.contains(nextWord)) {\\n if (lemmatised) result.add(nextWord.trim());\\n else result.add(word.trim());\\n }\\n }\\n\\n return result;\\n }\",\n \"public Collection<Term> getAll() {\\n\\t\\treturn terms.values();\\n\\t}\",\n \"public List<String> getRandomWords(int numWords) throws Exception {\\n\\n List<String> randomWords = new ArrayList();\\n\\n List<Word> words = WordsApi.randomWords(true, null, null, 2, 0, 2, 0, 0, 0, null, null, numWords);\\n\\n for (Word word : words) {\\n randomWords.add(word.getWord());\\n }\\n\\n return randomWords;\\n\\n }\",\n \"@Override\\n\\tpublic List<Literature> searchKeywords() {\\n\\t\\treturn null;\\n\\t}\",\n \"public DynamicArray<String> redactText()\\n\\t{\\n\\t\\tfor (int i = 0; i < text.length(); i++)\\n\\t\\t{\\n\\t\\t\\tif(!checkWord(text.get(i))) // checks if the word is listed to be redacted\\n\\t\\t\\t{\\n\\t\\t\\t\\ttext.set(i, redact(text.get(i))); // Redacts word\\n\\t\\t\\t}\\n\\t\\t\\telse if (isNoun(i)) // Given the index this checks if the word is a noun, but ignores it if there is a full stop.\\n\\t\\t\\t{\\n\\t\\t\\t\\twords.add(text.get(i)); // Since this is a noun, it is added to the list of redacted words\\n\\t\\t\\t\\ttext.set(i, redact(text.get(i))); // Word is then redacted\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\t\\n\\t\\tint i = 0;\\n\\t\\tint check;\\n\\t\\twhile (i < fullStops.length()) // Loops through full stop points and checks the word that follows it\\n\\t\\t{\\n\\t\\t\\tcheck = fullStops.get(i);\\n\\t\\t\\tif(!checkWord(text.get(check)))\\n\\t\\t\\t{\\n\\t\\t\\t\\ttext.set(check, redact(text.get(check)));\\n\\t\\t\\t}\\n\\t\\t\\ti++;\\n\\t\\t\\t\\t\\n\\t\\t}\\n\\t\\treturn text;\\n\\t}\",\n \"public String [] get_word_array(){\\n\\t\\treturn word_array;\\n\\t}\",\n \"public static LinkedList<Word> getPracticedWords() {\\n return favWords;\\n }\",\n \"public ArrayList<SearchResult> partialSearch(String[] searchWords) {\\n\\t\\tArrayList<SearchResult> words = new ArrayList<>();\\n\\t\\tHashMap<String, SearchResult> resultMap = new HashMap<>();\\n\\t\\tfor (String word : searchWords) {\\n\\t\\t\\tfor (String key : index.tailMap(word, true).navigableKeySet()) {\\n\\t\\t\\t\\tif (key.startsWith(word)) {\\n\\t\\t\\t\\t\\twordSearch(key, resultMap, words);\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\telse {\\n\\t\\t\\t\\t\\tbreak;\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\t\\n\\t\\tCollections.sort(words);\\n\\t\\treturn words;\\n\\t}\",\n \"private List<String> whitespaceSuggestions(String givenWord) {\\n List<String> whitespaceWords = new ArrayList<>();\\n for (int i = 1; i < givenWord.length() - 1; i++) {\\n if (corpus.contains(givenWord.substring(0, i) + \\\" \\\"\\n + givenWord.substring(i))) {\\n whitespaceWords.add(givenWord.substring(0, i) + \\\" \\\"\\n + givenWord.substring(i));\\n } else if (corpus.contains(givenWord.substring(0, i))) {\\n whitespaceWords.add(givenWord.substring(0, i));\\n } else if (corpus.contains(givenWord.substring(i))) {\\n whitespaceWords.add(givenWord.substring(i));\\n }\\n\\n if (shortenings.contains(givenWord.substring(0, i))) {\\n String fullWord = courseMappings.get(givenWord.substring(0, i));\\n if (!givenWord.contains(fullWord)) {\\n whitespaceWords.add(fullWord + \\\" \\\" + givenWord.substring(i));\\n }\\n\\n }\\n\\n }\\n\\n return whitespaceWords;\\n }\",\n \"private String[] mixedWords(String[] words)\\n {\\n String[] output = new String[words.length];\\n for(int i = 0; i < words.length; i++){\\n if(i%2==0){\\n output[i] = recombine(words[i], words[i+1]);\\n } else {\\n output[i] = recombine(words[i], words[i-1]);\\n }\\n }\\n return output;\\n }\",\n \"public PorterStopWords()\\r\\n\\t{\\r\\n\\t\\tstopWordsSet.addAll( porterStopWordsSet );\\r\\n\\t}\",\n \"public static List<Synset> getAllMeronymSynset(IndexWord word) throws JWNLException {\\n List<Synset> result=new ArrayList<>();\\n\\n for(Synset wordSynset:word.getSenses()){\\n PointerTargetTree hyponyms = PointerUtils.getInstance().getInheritedMeronyms(wordSynset,4,4);\\n PointerTargetTreeNode rootnode = hyponyms.getRootNode();\\n LinkedList<PointerTargetTreeNode> stack = new LinkedList<>();\\n if(rootnode==null){\\n return result;\\n }\\n stack.add(rootnode);\\n while(!stack.isEmpty()){\\n PointerTargetTreeNode node = stack.pollLast();\\n result.add(node.getSynset());\\n PointerTargetTreeNodeList childList = node.getChildTreeList();\\n if(childList!=null){\\n for(int i=0;i<childList.size();i++){\\n stack.add((PointerTargetTreeNode)childList.get(i));\\n }\\n }\\n\\n }\\n\\n }\\n\\n return result;\\n }\",\n \"public void set_graph() throws ParseException, IOException {\\n \\tg = new WeightedUndirectedGraph(words.length);\\n //g = new WeightedUndirectedGraph(most_important_terms.size());\\n \\n Directory dir = new SimpleFSDirectory(new File(\\\".\\\\\\\\data\\\\\\\\lucene_index_r_r\\\"));\\n Analyzer analyzer = new StandardAnalyzer(LUCENE_41);\\n \\n // creat a map that stores, for each word (in the cluster), a set of all the documents that contain that word\\n HashMap<String,HashSet<Integer>> word_to_docs_map = new HashMap<String,HashSet<Integer>>();\\n int n_strings = words.length; \\n \\n // for each word...\\n for (int idx = 0; idx < n_strings; idx++) {\\n // query the index with that given word and retrieve all the documents that contains that word\\n String query = words[idx]; \\n QueryParser parser = new QueryParser(Version.LUCENE_41, \\\"text\\\", analyzer); \\n Query q = parser.parse(query); \\n\\n IndexReader reader = DirectoryReader.open(dir);\\n IndexSearcher searcher = new IndexSearcher(reader);\\n TopDocs docs = searcher.search(q, reader.numDocs());\\n ScoreDoc[] hits = docs.scoreDocs;\\n \\n // update map from word to docs it appears in \\n //HashSet<Integer> tmp = null;\\n // tmp is the set of all the document ids in which the current word is contained\\n HashSet<Integer> tmp = new HashSet<>();\\n //word_to_docs_map.put(query, tmp);\\n \\n // for each document, retrieved from the query\\n for(Integer i=0;i<hits.length;i++) {\\n Integer docId = hits[i].doc;\\n // tmp = word_to_docs_map.get(query); \\n // if the document is a document written by an user of interest \\n if(indices.contains(docId)) {\\n tmp.add(docId);\\n }\\n //word_to_docs_map.put(query, tmp); \\n }\\n word_to_docs_map.put(query, tmp);\\n\\t }\\n\\t \\n\\t // add edges: iterate over possible term pairs ...\\n\\t for(int idx_1 = 0; idx_1 < n_strings - 1; idx_1++) {\\n\\t \\n\\t for(int idx_2 = idx_1 + 1 ; idx_2 < n_strings ; idx_2 ++ ) {\\n\\t \\n\\t // extract document sets associated with the considered terms \\n\\t HashSet<Integer> set_a = word_to_docs_map.get(words[idx_1]); \\n\\t HashSet<Integer> set_b = word_to_docs_map.get(words[idx_2]); \\n\\t \\n\\t // compute set intersection \\n\\t int n = intersectionSize(set_a, set_b);\\n\\t \\n\\t // if the terms appear in at least one common document\\n\\t if(n>0) {\\n\\t // add edge \\n\\t g.testAndAdd(idx_1, idx_2 , n); \\n\\t }\\n\\t } \\n\\t }\\n\\t}\",\n \"private ArrayList<WordDocument> executeAdvancedQuery(){\\n ArrayList<WordDocument> documents = customDijkstrasTwoStack(this.query.split(\\\" \\\"));\\n ArrayList<WordDocument> result = new ArrayList<WordDocument>();\\n\\n try{\\n String[] orderByPart = query.substring(query.indexOf(\\\"ORDERBY\\\")).trim().toLowerCase().split(\\\" \\\");\\n if(isOrderByCommand(orderByPart[0]))\\n result = orderBy(documents, orderByPart[1], orderByPart[2]);\\n }catch (StringIndexOutOfBoundsException ex){\\n result = documents;\\n }\\n\\n return result;\\n }\",\n \"@Test\\n public void printAllWords() {\\n // TODO\\n }\",\n \"public static ArrayList<String> findWords(TrieNode root) {\\n\\t\\tArrayList<String> result = new ArrayList<String>();\\n\\t\\tgetWords(root, \\\"\\\", result);\\n\\t\\treturn result;\\n\\t}\",\n \"public Collection<T> getOthers() {\\n return others;\\n }\",\n \"List<VocabWord> document(int index);\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6683834","0.63288605","0.60075307","0.5970147","0.5862826","0.5859984","0.58519155","0.5818616","0.57877696","0.57772887","0.57062596","0.5672519","0.5668082","0.56145406","0.5612684","0.5563824","0.55119944","0.550613","0.54892987","0.5488961","0.54867476","0.5484216","0.5478647","0.5477962","0.5467526","0.54585654","0.54574835","0.5407511","0.5400108","0.53965956","0.5380105","0.53677","0.5366047","0.5360735","0.5359129","0.53370553","0.53344905","0.5329311","0.5322003","0.5297501","0.5297448","0.5294027","0.5292795","0.52726495","0.5249178","0.5241796","0.5237376","0.52354527","0.52325404","0.5229205","0.52278227","0.52264744","0.522249","0.5214448","0.5213645","0.5213645","0.52132887","0.52065766","0.52062374","0.5201753","0.5194637","0.5172482","0.5158054","0.514881","0.51451224","0.5143833","0.51387954","0.5137619","0.51346004","0.51320964","0.5126617","0.51226324","0.5114986","0.50959784","0.5095697","0.50912124","0.50835204","0.5083114","0.5078823","0.50551194","0.5053635","0.5044055","0.5039378","0.50331753","0.5032151","0.502768","0.502248","0.5021816","0.5011882","0.50062335","0.500186","0.5000975","0.49871063","0.49844384","0.4979746","0.49788868","0.4976851","0.49605525","0.49602985","0.49561593","0.4947553"],"string":"[\n \"0.6683834\",\n \"0.63288605\",\n \"0.60075307\",\n \"0.5970147\",\n \"0.5862826\",\n \"0.5859984\",\n \"0.58519155\",\n \"0.5818616\",\n \"0.57877696\",\n \"0.57772887\",\n \"0.57062596\",\n \"0.5672519\",\n \"0.5668082\",\n \"0.56145406\",\n \"0.5612684\",\n \"0.5563824\",\n \"0.55119944\",\n \"0.550613\",\n \"0.54892987\",\n \"0.5488961\",\n \"0.54867476\",\n \"0.5484216\",\n \"0.5478647\",\n \"0.5477962\",\n \"0.5467526\",\n \"0.54585654\",\n \"0.54574835\",\n \"0.5407511\",\n \"0.5400108\",\n \"0.53965956\",\n \"0.5380105\",\n \"0.53677\",\n \"0.5366047\",\n \"0.5360735\",\n \"0.5359129\",\n \"0.53370553\",\n \"0.53344905\",\n \"0.5329311\",\n \"0.5322003\",\n \"0.5297501\",\n \"0.5297448\",\n \"0.5294027\",\n \"0.5292795\",\n \"0.52726495\",\n \"0.5249178\",\n \"0.5241796\",\n \"0.5237376\",\n \"0.52354527\",\n \"0.52325404\",\n \"0.5229205\",\n \"0.52278227\",\n \"0.52264744\",\n \"0.522249\",\n \"0.5214448\",\n \"0.5213645\",\n \"0.5213645\",\n \"0.52132887\",\n \"0.52065766\",\n \"0.52062374\",\n \"0.5201753\",\n \"0.5194637\",\n \"0.5172482\",\n \"0.5158054\",\n \"0.514881\",\n \"0.51451224\",\n \"0.5143833\",\n \"0.51387954\",\n \"0.5137619\",\n \"0.51346004\",\n \"0.51320964\",\n \"0.5126617\",\n \"0.51226324\",\n \"0.5114986\",\n \"0.50959784\",\n \"0.5095697\",\n \"0.50912124\",\n \"0.50835204\",\n \"0.5083114\",\n \"0.5078823\",\n \"0.50551194\",\n \"0.5053635\",\n \"0.5044055\",\n \"0.5039378\",\n \"0.50331753\",\n \"0.5032151\",\n \"0.502768\",\n \"0.502248\",\n \"0.5021816\",\n \"0.5011882\",\n \"0.50062335\",\n \"0.500186\",\n \"0.5000975\",\n \"0.49871063\",\n \"0.49844384\",\n \"0.4979746\",\n \"0.49788868\",\n \"0.4976851\",\n \"0.49605525\",\n \"0.49602985\",\n \"0.49561593\",\n \"0.4947553\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}},{"rowIdx":13896,"cells":{"query":{"kind":"string","value":"[NEW] Hashes the string to unique int representation"},"document":{"kind":"string","value":"public static String hash(String token){\n return Integer.toString( token.hashCode() );\n }"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["int toHashKey(String s)\n\t{\n\t\tint A = 1952786893;\n\t\tint B = 367257;\n\t\tint v = B;\n\t\tfor (int j = 0; j < s.length(); j++)\n\t\t{\n\t\t\tchar c = s.charAt(j);\n\t\t\tv = A * (v + (int) c + j) + B;\n\t\t}\n\n\t\tif (v < 0) v = -v;\n\t\treturn v;\n\t}","private int hash(String string) {\n\t\tint hash = 0;\n\t\tint temp = 0;\n\n\t\tfor (byte b : string.toLowerCase().getBytes(StandardCharsets.US_ASCII)) {\n\t\t\thash = (hash << 4) + b;\n\t\t\ttemp = hash & 0xF0000000;\n\n\t\t\tif (temp != 0) {\n\t\t\t\thash = hash ^ (temp >>> 24);\n\t\t\t\thash = hash ^ temp;\n\t\t\t}\n\t\t}\n\n\t\treturn hash;\n\t}","public static long stringHashCode(String string){\r\n\t\t// return number value if number, otherwise use string hash code\r\n\t\tboolean isNumber = true;\r\n\t\tfor(int i = 0; i < string.length(); i++){\r\n\t\t\tif(i == 0 && string.charAt(i) == '-') continue;\r\n\t\t\tif(Character.isDigit(string.charAt(i)) == false){\r\n\t\t\t\tisNumber = false;\r\n\t\t\t\tbreak;\r\n\t\t\t}\r\n\t\t}\r\n\t\tif(isNumber){\r\n\t\t\ttry{\r\n\t\t\t\treturn Long.parseLong(string);\r\n\t\t\t} catch(NumberFormatException ex){\r\n\t\t\t\t// not a number, do nothing\r\n\t\t\t}\r\n\t\t}\r\n\t\tlong h = 0;\r\n\t\tfor (int i = 0; i < string.length(); i++) {\r\n\t\t\th = 31*h + string.charAt(i);\r\n\t\t}\r\n\t\treturn h;\r\n\t}","public int hashCode(String str) {\n\t\tchar[] s = str.toCharArray();\n\t\tint total = 1;\n\t\tfor (char value : s) {\n\t\t\ttotal = 34 * total + value;\n\t\t}\n\t\ttotal = Math.abs(total);\n\t\tif(HashTester.useJavaAPIForHashCodeFunction)\n\t\t\ttotal = Math.abs(str.hashCode());\n\t\twhile (total > HashTester.hashTableSize) {\n\t\t\ttotal %= HashTester.hashTableSize;\n\t\t}\n\t\treturn total;\n\t}","HugeUInt(String str) {\r\n array = new int[str.length()];\r\n int x = str.length() - 1;\r\n for (int i = x; i >= 0; i--) {\r\n array[x-i] = Character.getNumericValue(str.charAt(i));\r\n }\r\n }","@Override\n\tpublic int hash(String str) {\n\t\tint result = 0;\n\t\tfor (int i = 0; i < str.length(); i++) {\n\t\t\tint temp = (int) str.charAt(i);\n\t\t\tresult += (temp * (Math.pow(37, i)));\n\t\t}\n\t\treturn result;\n\t}","public long JSHash(String str) {\n\t\tlong hash = 1315423911;\n\n\t\tfor (int i = 0; i < str.length(); i++) {\n\t\t\thash ^= ((hash << 5) + str.charAt(i) + (hash >> 2));\n\t\t}\n\n\t\treturn hash;\n\t}","public int hashCode(String s){\r\n int length = s.length();\r\n int h = 0;\r\n for(int i = 0; i < length; i++){\r\n h = h + ((int)s.indexOf(i))*(37^(length - 1));\r\n }\r\n return h;\r\n }","@Override\n\tpublic int hash(String item) {\n\t\tlong hashCode = 0l;\n\t\tchar[] c = item.toCharArray();\n\t\tfor (int i = 0; i < c.length; i++) {\n\t\t\thashCode += c[i] * Math.pow(31, c.length - (i + 1));\n\t\t}\n\t\tint i = (int) hashCode % 2147483647;\n\n\t\n\t\treturn Math.abs(i);\n\t\t\n\t}","private static String normalizeID(String id) {\r\n\t\tint hashcode = id.hashCode();\r\n\t\tboolean positive = hashcode >= 0;\r\n\t\tlong longcode = positive ? (long) hashcode : -(long) hashcode;\r\n\t\tStringBuffer hexstring = new StringBuffer(Long.toHexString(longcode));\r\n\t\twhile (hexstring.length() < 8) {\r\n\t\t\thexstring.insert(0, '0');\r\n\t\t}\r\n\t\tif (positive) {\r\n\t\t\thexstring.insert(0, '0');\r\n\t\t} else {\r\n\t\t\thexstring.insert(0, '1');\r\n\t\t}\r\n\t\treturn hexstring.toString();\r\n\t}","private static int initHash() {\n return 0x811c9DC5; // unsigned 2166136261\n }","public static int hash(String key) {\n int result = 1;\n\n for (int i=0; i<key.length(); ++i) {\n char c = key.charAt(i);\n int c_int = (int) c; //Gjør om ved å bruke ascii-tabellen ('A' = 65, ...\n\n result = (result*31) + c_int;\n }\n\n if (result < 0) {\n result = result * -1;\n }\n\n return result;\n }","private int hashFunc(String input) {\n\t\tBigInteger value = BigInteger.valueOf(0);\n\t\tBigInteger k2 = new BigInteger(\"27\");\n\t\tchar c = input.charAt(0);\n\t\tlong i1 = (int) c - 96;\n\t\tBigInteger k1 = new BigInteger(\"0\");\n\t\tk1 = k1.add(BigInteger.valueOf(i1));\n\t\tvalue = k1;\n\n\t\tfor (int i = 1; i < input.length(); i++) {\n\n\t\t\tchar c2 = input.charAt(i);\n\n\t\t\tvalue = value.multiply(k2);\n\n\t\t\tlong i2 = (int) c2 - 96;\n\t\t\tBigInteger k3 = new BigInteger(\"0\");\n\t\t\tk3 = k3.add(BigInteger.valueOf(i2));\n\n\t\t\tvalue = value.add(k3);\n\n\t\t}\n\t\tBigInteger size = new BigInteger(\"0\");\n\t\tsize = size.add(BigInteger.valueOf(this.size));\n\t\tvalue = value.mod(size);\n\n\t\treturn value.intValue();\n\t}","public long APHash(String str) {\n\t\tlong hash = 0xAAAAAAAA;\n\n\t\tfor (int i = 0; i < str.length(); i++) {\n\t\t\tif ((i & 1) == 0) {\n\t\t\t\thash ^= ((hash << 7) ^ str.charAt(i) * (hash >> 3));\n\t\t\t} else {\n\t\t\t\thash ^= (~((hash << 11) + str.charAt(i) ^ (hash >> 5)));\n\t\t\t}\n\t\t}\n\n\t\treturn hash;\n\t}","public static int stringToDictId(String str) {\n try {\n byte[] bytes = str.getBytes(\"ISO-8859-1\");\n return BytesUtil.readUnsigned(bytes, 0, bytes.length);\n } catch (UnsupportedEncodingException e) {\n // never happen\n return 0;\n }\n }","public int stringIntegerEncoding(String str) {\n if (!str.matches(\"[0-9-]+\"))\n return -1;\n\n char[] strArr = str.toCharArray();\n int number = (strArr[0] != '-') ? Character.getNumericValue(strArr[0]) : 0;\n for (int i =1; i < strArr.length; i++) {\n number = 10*number + Character.getNumericValue(strArr[i]);\n }\n return (strArr[0] == '-')? -number : number;\n }","public long BPHash(String str) {\n\t\tlong hash = 0;\n\n\t\tfor (int i = 0; i < str.length(); i++) {\n\t\t\thash = hash << 7 ^ str.charAt(i);\n\t\t}\n\n\t\treturn hash;\n\t}","public static int stringToInt(String aKey){\r\n\t\t\r\n\t\tint pseudoKey = 0;\r\n\t\tint n = 1;\r\n\t\tint cn = 0;\r\n\t\tchar c[] = aKey.toCharArray();\r\n\t\tint grouping = 0;\r\n\t\t\r\n\t\twhile(cn < aKey.length()){\r\n\t\t\t\r\n\t\t\tgrouping = grouping << 8;\r\n\t\t\tgrouping += c[cn];\r\n\t\t\tcn++;\r\n\t\t\t\r\n\t\t\tif(n == 4 || cn == aKey.length()){\r\n\t\t\t\tpseudoKey += grouping;\r\n\t\t\t\tn = 0;\r\n\t\t\t\tgrouping = 0;\r\n\t\t\t}\r\n\t\t\t\r\n\t\t\tn++;\r\n\t\t\t\r\n\t\t}// End of while loop\r\n\t\treturn Math.abs(pseudoKey);\r\n\t\t\r\n\t}","public String doHash2(String str) {\n if(str.length() == 1) return \"-1\";\n\n String key = \"\";\n for (int i = 0; i < str.length() - 1; i++) {\n int val = str.charAt(i + 1) - str.charAt(i);\n if (val < 0) val = 26 + val;\n key += val + \"_\";\n }\n return key;\n }","public int hash(String w){\n return (Math.abs(w.hashCode()) % hashTable.length);\n }","private int getHash(String word){\n\t\tif (word == null){\n\t\t\treturn INVALID;\n\t\t}\n\n\t\tint hash = 52;\n\t\tif ((word.charAt(0) >= 'a') && (word.charAt(0) <= 'z')){\n\t\t\thash = word.charAt(0) - 'a';\n\t\t}\n\t\telse if ((word.charAt(0) >= 'A') && (word.charAt(0) <= 'Z')){\n\t\t\thash = word.charAt(0) - 'A' + 26;\n\t\t}\n\t\treturn hash;\n\t}","private int hasher() {\n int i = 0;\n int hash = 0;\n while (i != length) {\n hash += hashableKey.charAt(i++);\n hash += hash << 10;\n hash ^= hash >> 6;\n }\n hash += hash << 3;\n hash ^= hash >> 11;\n hash += hash << 15;\n return getHash(hash);\n }","private int hash(String str, int h){\n int v=0;\n\n /* FILL IN HERE */\n v = Math.floorMod(MurmurHash.hash32(str, seeds[h]) >>> h, 1 << logNbOfBuckets);\n\n return v;\n }","public static int stringHash(String str) {\r\n return str.hashCode();\r\n }","@Override\n\tpublic long getHashCode(String key) {\n\t\tlong hash = 0;\n\t\tlong b = 378551;\n\t\tlong a = 63689;\n\t\tint tmp = 0;\n\t\tfor (int i = 0; i < key.length(); i++) {\n\t\t\ttmp = key.charAt(i);\n\t\t\thash = hash * a + tmp;\n\t\t\ta *= b;\n\t\t}\n\t\treturn hash;\n\t}","private String generateId(String input) {\n\t\treturn StringUtil.hashSHA256(input);\n\t}","public static final int hash32(String key)\r\n {\n return hash32(key.getBytes());\r\n //So pre JDK7 could try suggestion from here: http://blog.rapleaf.com/dev/2010/04/26/faster-string-to-utf-8-encoding-in-java/\r\n // return hash32(fastStringToBytes(key));\r\n }","public static int m2197ao(String str) {\n try {\n return Integer.valueOf(str).intValue();\n } catch (Exception e) {\n return -1;\n }\n }","public void encodeInt() {\n charToInt = new int[uniqueChars.size()];\n Iterator<Character> mover = uniqueChars.iterator();\n for(int b = 0; b < uniqueChars.size(); b++) {\n charToInt[b] = mover.next();\n }\n System.out.print(\"\\nEncoding integer value to its ASCII characters:\\n\");\n intToChars = new char[uniqueChars.size()];\n for(int c = 0; c < uniqueChars.size(); c++) {\n intToChars[c] = (char)charToInt[c];\n charToInt[c] = charToInt[c] / charToInt[c] + c - 1;\n System.out.print(charToInt[c] + \" : \" + intToChars[c] + \", \");\n }\n\n }","public long SDBMHash(String str) {\n\t\tlong hash = 0;\n\n\t\tfor (int i = 0; i < str.length(); i++) {\n\t\t\thash = str.charAt(i) + (hash << 6) + (hash << 16) - hash;\n\t\t}\n\n\t\treturn hash;\n\t}","public static String getCheckNumber(String paramString){\n int i =paramString.substring(0, 1).getBytes()[0];\n for(int j=1;;j++){\n if(j>=paramString.length())\n return intToHex(Integer.valueOf(i));\n i=(byte)(i^paramString.substring(j, j+1).getBytes()[0]);\n\n }\n }","public int hash(String item);","public String doHash(String str) {\n String key = \"\";\n int offset = str.charAt(0) - 'a';\n for (int i=0; i<str.length(); i++) {\n char res = str.charAt(i) - offset;\n if (res < 'a') res += 26;\n key += res;\n }\n return key;\n }","public long ELFHash(String str) {\n\t\tlong hash = 0;\n\t\tlong x = 0;\n\n\t\tfor (int i = 0; i < str.length(); i++) {\n\t\t\thash = (hash << 4) + str.charAt(i);\n\n\t\t\tif ((x = hash & 0xF0000000L) != 0) {\n\t\t\t\thash ^= (x >> 24);\n\t\t\t}\n\t\t\thash &= ~x;\n\t\t}\n\n\t\treturn hash;\n\t}","public static final String hash(final String string) {\n\t\treturn Hex.fromByteArray(digest(string));\n\t}","private int calculateHash(int id, String uri) {\n\t\treturn uri.hashCode() * Constants.HASH_PRIMES[0]\n\t\t\t\t+ Integer.toString(id).hashCode() * Constants.HASH_PRIMES[1];\n\t}","@Override\r\n public int hashCode() {\n return id % 10;\r\n }","public static long hashName(String name) {\n\t\t\tlong res = 123;\n\t\t\tfor (int i = 0; i < name.length(); ++i) {\n\t\t\t\tres = (res << 8) | (res >>> 56);\n\t\t\t\tres += name.charAt(i);\n\t\t\t\tif ((res & 1) == 0) {\n\t\t\t\t\tres ^= 0x00000000feabfeabL; // Some kind of feedback\n\t\t\t\t}\n\t\t\t}\n\t\t\tres |= 0x8000000000000000L; // Make sure the hash is negative (to distinguish it from database id's)\n\t\t\treturn res;\n\t\t}","public static int convertStringToInt(String input){\n\t if(input.length()==0)\n\t return 0;\n\t \n\t int m=(int)input.charAt(0)-48;\n\t int n=input.length();\n\t \n\t while(n!=1)\n\t {\n\t m*=10;\n\t n--;\n\t }\n\t \n\t return m+convertStringToInt(input.substring(1,input.length()));\n\t \n\t \n\t\t\n\t}","int hash(String makeHash, int mod);","private static int getIntValue(String s) {\n try {\n return Integer.parseInt(s, 16);\n } catch (NumberFormatException e) {\n e.printStackTrace();\n return -1;\n }\n }","public static String hash(String st) {\r\n MessageDigest messageDigest = null;\r\n byte[] digest = new byte[0];\r\n\r\n try {\r\n messageDigest = MessageDigest.getInstance(\"SHA-256\");\r\n messageDigest.reset();\r\n messageDigest.update(st.getBytes());\r\n digest = messageDigest.digest();\r\n } catch (NoSuchAlgorithmException e) {\r\n e.printStackTrace();\r\n }\r\n\r\n BigInteger bigInt = new BigInteger(1, digest);\r\n StringBuilder hex = new StringBuilder(bigInt.toString(16));\r\n\r\n while (hex.length() < 32) {\r\n hex.insert(0, \"0\");\r\n }\r\n\r\n return hex.toString();\r\n }","private int hashOf(String key) {\n return key.length();\n }","public int hashCode() {\n/* 389 */ return this.m_str.hashCode();\n/* */ }","private static int letterToNumber(String str) {\n return (\"ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz\".indexOf(str))%26+1;\n }","public static String m106643a(String str) {\n try {\n return m106642a(Integer.valueOf(str));\n } catch (Exception unused) {\n return \"\";\n }\n }","@Override\n\tpublic int hashCode() {\n\t\treturn Integer.parseInt(sid);\n\t}","public static String hash(String in) {\r\n\t\treturn DigestUtils.md5Hex(in.getBytes());\r\n\t}","public int hash2 ( String key )\n {\n int hashVal = 0;\n if(key != null){\n for( int i = 0; i < key.length(); i++ )\n hashVal = (37 * hashVal) + key.charAt(i);\n //if(hashVal != 0)\n return hashVal % tableSize;\n //else\n // return 0;\n }\n else{\n //System.out.println(\"Key is null\");\n return 0;\n }\n }","public int hashcode();","int decodeInt();","public static int intFromHexString(CharSequence str) {\n\t\tint n = 0;\n\t\tfor (int i = 0; i < str.length(); i++) {\n\t\t\tchar c = str.charAt(i);\n\t\t\tint v = c <= '9' ? c - '0' : c - 'a' + 10;\n\t\t\tn <<= 4;\n\t\t\tn |= (v & 0x0f);\n\t\t}\n\t\treturn n;\n\t}","public long DEKHash(String str) {\n\t\tlong hash = str.length();\n\n\t\tfor (int i = 0; i < str.length(); i++) {\n\t\t\thash = ((hash << 5) ^ (hash >> 27)) ^ str.charAt(i);\n\t\t}\n\n\t\treturn hash;\n\t}","@Test\n public void testHashCode() {\n LOGGER.info(\"testHashCode\");\n final String value = \"Hello\";\n final int actual = new AtomString(value).hashCode();\n final int expected = 61 * 7 + Objects.hashCode(value);\n assertEquals(expected, actual);\n }","String getIntegerEncoding();","public int hashCode() {\n\t\treturn hashString.hashCode();\n\t}","public static int randomHashOfString(String s)\r\n\t{\r\n\t\tBigInteger hash=FNV64INIT;\r\n\t\tfor(int j=0;j<s.length();j++)\r\n\t\t{\r\n\t\t\thash=hash.xor(BigInteger.valueOf(s.charAt(j)));\r\n\t\t\thash=hash.multiply(FNV64PRIME).mod(TWO.pow(64));\r\n\t\t}\r\n\t\treturn hash.intValue();\r\n\t}","public long DJBHash(String str) {\n\t\tlong hash = 5381;\n\n\t\tfor (int i = 0; i < str.length(); i++) {\n\t\t\thash = ((hash << 5) + hash) + str.charAt(i);\n\t\t}\n\n\t\treturn hash;\n\t}","public int hash(String key){\r\n\t\tint i;\r\n\t\tint v = 0;\r\n\t\tfor(i = 0; i < key.length(); i++)\r\n\t\t\tv += key.charAt(i);\r\n\t\treturn v % M;\r\n\t}","public long BKDRHash(String str) {\n\t\tlong seed = 131; // 31 131 1313 13131 131313 etc..\n\t\tlong hash = 0;\n\n\t\tfor (int i = 0; i < str.length(); i++) {\n\t\t\thash = (hash * seed) + str.charAt(i);\n\t\t}\n\n\t\treturn hash;\n\t}","public int numDecodings(String s) {\n if(s==null||s.length()==0){\n return 0;\n }\n\n int n=s.length();\n int[] mem=new int[n+1];\n\n mem[n]=1;\n if(Integer.parseInt(s.substring(n-1))!=0){\n mem[n-1]=1;\n }\n\n for(int i=n-2;i>=0;i--){\n if(Integer.parseInt(s.substring(i,i+1))==0){\n continue;\n }\n if(Integer.parseInt(s.substring(i,i+2))<26){\n mem[i]=mem[i+1]+mem[i+2];\n }else{\n mem[i]=mem[i+1];\n }\n }\n\n return mem[0];\n }","int toInt(String a){\n\t\tint name=0;\r\n\t\tfor(int i=0;i<a.length();i++){\r\n\t\t\tname+=(int)a.charAt(i);\r\n\t\t}\r\n\t\treturn name;\r\n\t}","public int hashCode(){\n\t\treturn toString().hashCode();\n\t}","@Override\r\n public int hashCode() {\n int key=(Integer)(this.capsule.get(0)); // Get the key\r\n Integer bkey=Integer.parseInt(Integer.toBinaryString(key)); // Convert into binary \r\n int n=setcount(bkey); //counts the number of 1's in the binary\r\n key=key*n + Objects.hashCode(this.capsule.get(0)); //multiplies that with the hashcode of the pId\r\n return key;\r\n }","public int mo29670a(String str) {\n int length = str.length();\n int i = this.f19526c;\n for (int i2 = 0; i2 < length; i2++) {\n i = (i * 33) + str.charAt(i2);\n }\n if (i == 0) {\n return 1;\n }\n return i;\n }","public static int toInt(String str){\r\n\t\tInteger i = toInteger(str);\r\n\t\treturn i==null?0:i;\r\n\t}","@Override\n public int hashCode() {\n int result = 42;\n int prime = 37;\n for (char ch : key.toCharArray()) {\n result = prime * result + (int) ch;\n }\n result = prime * result + summary.length();\n result = prime * result + value;\n return result;\n }","public static long hash(String stringToHash) {\n byte[] data;\n try {\n data = stringToHash.getBytes(\"UTF-8\");\n long h = HSTART;\n final long hmult = HMULT;\n final long[] ht = byteTable;\n for (int len = data.length, i = 0; i < len; i++) {\n h = (h * hmult) ^ ht[data[i] & 0xff];\n }\n return h;\n } catch (UnsupportedEncodingException e) {\n e.printStackTrace();\n throw new AssertionError(\"Hash failures on encoding\");\n }\n }","String toStringAsInt();","@Override\r\n\tpublic int hashCode() {\n\t\tint result = 17;\r\n\t\tresult = 37*result+(int) (id ^ (id>>>32));\r\n\t\t//result = 37*result+(name==null?0:name.hashCode());\r\n\t\t//result = 37*result+displayOrder;\r\n\t\t//result = 37*result+(this.url==null?0:url.hashCode());\r\n\t\treturn result;\r\n\t}","static int sherlockAndAnagrams(String s) {\n HashTable hashTable = new HashTable(s.length() * s.length() * 4);\n substrings(s).map(Solution::ordered).forEach(hashTable::insert);\n return substrings(s).map(Solution::ordered).mapToInt(s1 -> {\n hashTable.remove(s1);\n return hashTable.count(s1);\n }).sum();\n }","public long PJWHash(String str) {\n\t\tlong BitsInUnsignedInt = (long) (4 * 8);\n\t\tlong ThreeQuarters = (long) ((BitsInUnsignedInt * 3) / 4);\n\t\tlong OneEighth = (long) (BitsInUnsignedInt / 8);\n\t\tlong HighBits = (long) (0xFFFFFFFF) << (BitsInUnsignedInt - OneEighth);\n\t\tlong hash = 0;\n\t\tlong test = 0;\n\n\t\tfor (int i = 0; i < str.length(); i++) {\n\t\t\thash = (hash << OneEighth) + str.charAt(i);\n\n\t\t\tif ((test = hash & HighBits) != 0) {\n\t\t\t\thash = ((hash ^ (test >> ThreeQuarters)) & (~HighBits));\n\t\t\t}\n\t\t}\n\n\t\treturn hash;\n\t}","protected static final int getUnitId(String inputHex) {\r\n\t\t\r\n\t\tString msb = inputHex.substring(0, 2);\r\n\t\tString lsb = inputHex.substring(2, 4);\r\n\r\n\t\tint val = ( Integer.parseInt(msb, 16) * 256 ) + ( Integer.parseInt(lsb, 16) * 1 );\r\n//\t\tGQDKPMConstants.logger.debug(\"incoming lsb = \" + lsb +\" lsb hex-dec = \"+Integer.parseInt(lsb, 16) * 1 +\r\n//\t\t\t\t\" , msb = \"+ msb + \" msb hex-dec = \"+Integer.parseInt(msb, 16) * 256 + \" , val = \" + val );\r\n\t\treturn val;\r\n\t}","public String intToString(String s) {\r\n int x = s.length();\r\n char[] bytes = new char[4];\r\n for(int i = 3; i > -1; --i) {\r\n bytes[3 - i] = (char) (x >> (i * 8) & 0xff);\r\n }\r\n return new String(bytes);\r\n }","@SuppressWarnings(\"WeakerAccess\")\n abstract public int hash(char c);","public static int hashCode(String str, int b) {\n\tint result = 0;\n\tfor(int i = 0; i < str.length(); i++) {\n\t\tresult += (str.charAt(i)) * (int)Math.pow(b, str.length() - (1+i));\n\t\t}\n\treturn result;\n\t}","@Override\n public int hashCode() {\n return String.valueOf(this).hashCode();\n }","public int hash3 ( String key )\n {\n int hashVal = 0;\n if(key != null){\n for( int i = 0; i < key.length(); i++ ){\n hashVal = (37 * hashVal) + key.charAt(i);}\n hashVal %= tableSize;\n if(hashVal<0)\n hashVal += tableSize; \n if(hashVal != 0)\n return hashVal;\n else\n return 0;\n }\n else\n {\n //System.out.println(\"Key is null\");\n return 0;\n }\n }","public static String uniqueChar(String str){\n\n char[] ch=str.toCharArray();\n str=\"\";\n HashMap<Character,Integer> map=new HashMap<>();\n for(int i=0;i<ch.length;i++)\n {\n if(map.containsKey(ch[i]));\n else\n {\n str+=ch[i];\n map.put(ch[i],1);\n }\n }\n \n return str;\n\t}","@Override\n public int hashCode() {\n if (!(uuid instanceof String)) {\n uuid = UUID.randomUUID().toString();\n }\n\n return uuid.hashCode();\n }","public static int hashCodeForStrings(String... strings) {\n\t\tint hash = 0;\n\t\tfor(String str : strings) {\n\t\t\tfor(int i=0;i<str.length();++i) {\n\t\t\t\thash = 31 * hash + str.charAt(i);\n\t\t\t}\n\t\t}\n\t\treturn hash;\n\t}","public int firstUniqChar2(String s) {\r\n \r\n char[] arr= s.toCharArray();\r\n int index = -1;\r\n HashMap<Character, Integer> map = new HashMap<>();\r\n \r\n for (int i=0;i<arr.length;i++){\r\n if (map.containsKey(arr[i])){\r\n map.put(arr[i], -1);\r\n } else {\r\n map.put(arr[i],i);\r\n }\r\n }\r\n \r\n for (int i : map.values()){\r\n if (i >-1){\r\n if (index == -1){\r\n index = i;\r\n } else if (i<index) {\r\n index = i; \r\n }\r\n \r\n }\r\n }\r\n \r\n return index;\r\n }","public boolean isUnique(String s){\n // int[] visited = new int[256]; // O:256\n int[] visited = new int[8]; // int = 4 bytes = 32 bits, 8 ints = 32 bytes = 256 bits\n char[] array = s.toCharArray();\n for(char c:array){\n // for a value c in range of 0 - 256\n // it maps to the int at c/32 as index\n // it also maps the c%32 as the index of bits\n if(((visited[c/32] >>> (c%32)) & 1) != 0){\n // bit-tester of the k-th bits, k = c%32\n return false;\n }\n // bit-setter to 1 in the k-th bits\n visited[c/32] |= 1 << (c%32);\n }\n return true;\n }","private static int firstUniqChar2(String s) {\n Map<Character, Integer> seen = new HashMap<>();\n for (int i = 0; i < s.length(); i++) {\n char c = s.charAt(i);\n seen.put(c, seen.getOrDefault(c, 0) + 1);\n }\n\n int uniqueIdx = -1;\n for (int i = 0; i < s.length(); i++) {\n if (seen.get(s.charAt(i)) == 1) {\n uniqueIdx = i;\n break;\n }\n }\n\n return uniqueIdx;\n }","static int getKey(String raw) {\n\t\tint key = 0;\n\t\tfor (int i = 0; i < raw.length(); i++) {\n\t\t\tkey = key * HASH_VALUE + raw.charAt(i);\n\t\t}\n\t\tif (key < 0) {\n\t\t\tkey = -key;\n\t\t}\n\t\treturn key % HASH_SIZE;\n\t}","int getHash();","public static String generateId(String s){\n\t\tString date = LocalDate.now().format(DateTimeFormatter.ofPattern(\"yyMMdd\"));\n\t\tString key = s +\"_\" + date;\n\t\t//com.incr(key);\n\t\tredisTemplate.opsForValue().increment(key);\n\t\tInteger num = redisTemplate.opsForValue().get(key);\n\t\treturn date + \"-\" + String.format(\"%08d\",num);\n\t}","public int hash1 ( String key )\n {\n int hashVal = 0;\n if(key != null){\n for( int i = 0; i < key.length(); i++ )\n hashVal += key.charAt(i);\n \n //if(hashVal != 0)\n return hashVal % tableSize;\n //else\n // return 0;\n }\n else{\n //System.out.println(\"Key is null\");\n return 0 ;\n }\n\n }","public BigInteger hash(String element)\n\t{ \n\t\treturn (BigInteger.valueOf(element.hashCode())).mod(modulus);\n\t}","@Override\n public int hexToInt(String source) {\n try {\n return Integer.parseInt(source, 16);\n } catch (NumberFormatException nfe) {\n return 0;\n }\n }","@Override\n\tpublic int hashCode() {\n\t\t\n\t\treturn (int)id * name.hashCode() * email.hashCode();\n\t\t//int hash = new HashCodeBuilder(17,37).append(id).append(name); //can be added from Apache Commons Lang's HashCodeBuilder class\n\t}","public static String toAscii(String s){\r\n StringBuilder sb = new StringBuilder();\r\n long asciiInt;\r\n // loop through all values in the string, including blanks\r\n for (int i = 0; i < s.length(); i++){\r\n //getting Ascii value of character and adding it to the string.\r\n char c = s.charAt(i);\r\n asciiInt = (int)c; \r\n sb.append(asciiInt);\r\n }\r\n return String.valueOf(sb);\r\n }","private static int hashCode(byte key) {\n return (int) key;\n }","public int titleToNumber(String s) {\n int val = 0;\n //go thru string\n for (int i = 0; i < s.length(); i++){\n \t//26 letts of alph add the int val of that character \n val = val * 26 + (int) s.charAt(i) - (int) 'A' + 1;\n }\n return val;\n }","@Override\n public int hashCode() {\n \n final int code = 24;\n int result = 1;\n result = code * result + ((id == null) ? 0 : id.hashCode());\n return result;\n }","public static int firstUniqChar(String s) {\n\n HashMap<String, Integer> hm = new HashMap<>();\n\n for(int i = 0; i < s.length(); i++) {\n if(hm.containsKey(s.substring(i, i+1))) {\n hm.put(s.substring(i,i+1), hm.get(s.substring(i,i+1))+1);\n }\n else {\n hm.put(s.substring(i,i+1), 1);\n }\n }\n\n for(int i = 0; i< s.length(); i++) {\n if(hm.get(s.substring(i,i+1)) == 1) {\n return i;\n }\n }\n //this means all the string is repeating\n return -1;\n }","@Override\n\tpublic int hashValue(String value) {\n\t\treturn hashFunc(value);\n\t}","public static String GetHash(String input)\n {\n String hash = DigestUtils.sha1Hex(input);\n System.out.println(hash);\n return hash;\n }","private String intChecker(String s) {\n\t\tString newS = \"\";\n\t\tfor(int i = 0; i < s.length(); i++) {\n\t\t\tif(s.charAt(i) > 47 && s.charAt(i) < 58) {\n\t\t\t\tnewS += s.charAt(i);\n\t\t\t}\n\t\t}\n\t\treturn newS;\n\t}","private static int parseInt(String sn) {\n\t\treturn Integer.parseInt(sn.substring(2), 16);\n\t}"],"string":"[\n \"int toHashKey(String s)\\n\\t{\\n\\t\\tint A = 1952786893;\\n\\t\\tint B = 367257;\\n\\t\\tint v = B;\\n\\t\\tfor (int j = 0; j < s.length(); j++)\\n\\t\\t{\\n\\t\\t\\tchar c = s.charAt(j);\\n\\t\\t\\tv = A * (v + (int) c + j) + B;\\n\\t\\t}\\n\\n\\t\\tif (v < 0) v = -v;\\n\\t\\treturn v;\\n\\t}\",\n \"private int hash(String string) {\\n\\t\\tint hash = 0;\\n\\t\\tint temp = 0;\\n\\n\\t\\tfor (byte b : string.toLowerCase().getBytes(StandardCharsets.US_ASCII)) {\\n\\t\\t\\thash = (hash << 4) + b;\\n\\t\\t\\ttemp = hash & 0xF0000000;\\n\\n\\t\\t\\tif (temp != 0) {\\n\\t\\t\\t\\thash = hash ^ (temp >>> 24);\\n\\t\\t\\t\\thash = hash ^ temp;\\n\\t\\t\\t}\\n\\t\\t}\\n\\n\\t\\treturn hash;\\n\\t}\",\n \"public static long stringHashCode(String string){\\r\\n\\t\\t// return number value if number, otherwise use string hash code\\r\\n\\t\\tboolean isNumber = true;\\r\\n\\t\\tfor(int i = 0; i < string.length(); i++){\\r\\n\\t\\t\\tif(i == 0 && string.charAt(i) == '-') continue;\\r\\n\\t\\t\\tif(Character.isDigit(string.charAt(i)) == false){\\r\\n\\t\\t\\t\\tisNumber = false;\\r\\n\\t\\t\\t\\tbreak;\\r\\n\\t\\t\\t}\\r\\n\\t\\t}\\r\\n\\t\\tif(isNumber){\\r\\n\\t\\t\\ttry{\\r\\n\\t\\t\\t\\treturn Long.parseLong(string);\\r\\n\\t\\t\\t} catch(NumberFormatException ex){\\r\\n\\t\\t\\t\\t// not a number, do nothing\\r\\n\\t\\t\\t}\\r\\n\\t\\t}\\r\\n\\t\\tlong h = 0;\\r\\n\\t\\tfor (int i = 0; i < string.length(); i++) {\\r\\n\\t\\t\\th = 31*h + string.charAt(i);\\r\\n\\t\\t}\\r\\n\\t\\treturn h;\\r\\n\\t}\",\n \"public int hashCode(String str) {\\n\\t\\tchar[] s = str.toCharArray();\\n\\t\\tint total = 1;\\n\\t\\tfor (char value : s) {\\n\\t\\t\\ttotal = 34 * total + value;\\n\\t\\t}\\n\\t\\ttotal = Math.abs(total);\\n\\t\\tif(HashTester.useJavaAPIForHashCodeFunction)\\n\\t\\t\\ttotal = Math.abs(str.hashCode());\\n\\t\\twhile (total > HashTester.hashTableSize) {\\n\\t\\t\\ttotal %= HashTester.hashTableSize;\\n\\t\\t}\\n\\t\\treturn total;\\n\\t}\",\n \"HugeUInt(String str) {\\r\\n array = new int[str.length()];\\r\\n int x = str.length() - 1;\\r\\n for (int i = x; i >= 0; i--) {\\r\\n array[x-i] = Character.getNumericValue(str.charAt(i));\\r\\n }\\r\\n }\",\n \"@Override\\n\\tpublic int hash(String str) {\\n\\t\\tint result = 0;\\n\\t\\tfor (int i = 0; i < str.length(); i++) {\\n\\t\\t\\tint temp = (int) str.charAt(i);\\n\\t\\t\\tresult += (temp * (Math.pow(37, i)));\\n\\t\\t}\\n\\t\\treturn result;\\n\\t}\",\n \"public long JSHash(String str) {\\n\\t\\tlong hash = 1315423911;\\n\\n\\t\\tfor (int i = 0; i < str.length(); i++) {\\n\\t\\t\\thash ^= ((hash << 5) + str.charAt(i) + (hash >> 2));\\n\\t\\t}\\n\\n\\t\\treturn hash;\\n\\t}\",\n \"public int hashCode(String s){\\r\\n int length = s.length();\\r\\n int h = 0;\\r\\n for(int i = 0; i < length; i++){\\r\\n h = h + ((int)s.indexOf(i))*(37^(length - 1));\\r\\n }\\r\\n return h;\\r\\n }\",\n \"@Override\\n\\tpublic int hash(String item) {\\n\\t\\tlong hashCode = 0l;\\n\\t\\tchar[] c = item.toCharArray();\\n\\t\\tfor (int i = 0; i < c.length; i++) {\\n\\t\\t\\thashCode += c[i] * Math.pow(31, c.length - (i + 1));\\n\\t\\t}\\n\\t\\tint i = (int) hashCode % 2147483647;\\n\\n\\t\\n\\t\\treturn Math.abs(i);\\n\\t\\t\\n\\t}\",\n \"private static String normalizeID(String id) {\\r\\n\\t\\tint hashcode = id.hashCode();\\r\\n\\t\\tboolean positive = hashcode >= 0;\\r\\n\\t\\tlong longcode = positive ? (long) hashcode : -(long) hashcode;\\r\\n\\t\\tStringBuffer hexstring = new StringBuffer(Long.toHexString(longcode));\\r\\n\\t\\twhile (hexstring.length() < 8) {\\r\\n\\t\\t\\thexstring.insert(0, '0');\\r\\n\\t\\t}\\r\\n\\t\\tif (positive) {\\r\\n\\t\\t\\thexstring.insert(0, '0');\\r\\n\\t\\t} else {\\r\\n\\t\\t\\thexstring.insert(0, '1');\\r\\n\\t\\t}\\r\\n\\t\\treturn hexstring.toString();\\r\\n\\t}\",\n \"private static int initHash() {\\n return 0x811c9DC5; // unsigned 2166136261\\n }\",\n \"public static int hash(String key) {\\n int result = 1;\\n\\n for (int i=0; i<key.length(); ++i) {\\n char c = key.charAt(i);\\n int c_int = (int) c; //Gjør om ved å bruke ascii-tabellen ('A' = 65, ...\\n\\n result = (result*31) + c_int;\\n }\\n\\n if (result < 0) {\\n result = result * -1;\\n }\\n\\n return result;\\n }\",\n \"private int hashFunc(String input) {\\n\\t\\tBigInteger value = BigInteger.valueOf(0);\\n\\t\\tBigInteger k2 = new BigInteger(\\\"27\\\");\\n\\t\\tchar c = input.charAt(0);\\n\\t\\tlong i1 = (int) c - 96;\\n\\t\\tBigInteger k1 = new BigInteger(\\\"0\\\");\\n\\t\\tk1 = k1.add(BigInteger.valueOf(i1));\\n\\t\\tvalue = k1;\\n\\n\\t\\tfor (int i = 1; i < input.length(); i++) {\\n\\n\\t\\t\\tchar c2 = input.charAt(i);\\n\\n\\t\\t\\tvalue = value.multiply(k2);\\n\\n\\t\\t\\tlong i2 = (int) c2 - 96;\\n\\t\\t\\tBigInteger k3 = new BigInteger(\\\"0\\\");\\n\\t\\t\\tk3 = k3.add(BigInteger.valueOf(i2));\\n\\n\\t\\t\\tvalue = value.add(k3);\\n\\n\\t\\t}\\n\\t\\tBigInteger size = new BigInteger(\\\"0\\\");\\n\\t\\tsize = size.add(BigInteger.valueOf(this.size));\\n\\t\\tvalue = value.mod(size);\\n\\n\\t\\treturn value.intValue();\\n\\t}\",\n \"public long APHash(String str) {\\n\\t\\tlong hash = 0xAAAAAAAA;\\n\\n\\t\\tfor (int i = 0; i < str.length(); i++) {\\n\\t\\t\\tif ((i & 1) == 0) {\\n\\t\\t\\t\\thash ^= ((hash << 7) ^ str.charAt(i) * (hash >> 3));\\n\\t\\t\\t} else {\\n\\t\\t\\t\\thash ^= (~((hash << 11) + str.charAt(i) ^ (hash >> 5)));\\n\\t\\t\\t}\\n\\t\\t}\\n\\n\\t\\treturn hash;\\n\\t}\",\n \"public static int stringToDictId(String str) {\\n try {\\n byte[] bytes = str.getBytes(\\\"ISO-8859-1\\\");\\n return BytesUtil.readUnsigned(bytes, 0, bytes.length);\\n } catch (UnsupportedEncodingException e) {\\n // never happen\\n return 0;\\n }\\n }\",\n \"public int stringIntegerEncoding(String str) {\\n if (!str.matches(\\\"[0-9-]+\\\"))\\n return -1;\\n\\n char[] strArr = str.toCharArray();\\n int number = (strArr[0] != '-') ? Character.getNumericValue(strArr[0]) : 0;\\n for (int i =1; i < strArr.length; i++) {\\n number = 10*number + Character.getNumericValue(strArr[i]);\\n }\\n return (strArr[0] == '-')? -number : number;\\n }\",\n \"public long BPHash(String str) {\\n\\t\\tlong hash = 0;\\n\\n\\t\\tfor (int i = 0; i < str.length(); i++) {\\n\\t\\t\\thash = hash << 7 ^ str.charAt(i);\\n\\t\\t}\\n\\n\\t\\treturn hash;\\n\\t}\",\n \"public static int stringToInt(String aKey){\\r\\n\\t\\t\\r\\n\\t\\tint pseudoKey = 0;\\r\\n\\t\\tint n = 1;\\r\\n\\t\\tint cn = 0;\\r\\n\\t\\tchar c[] = aKey.toCharArray();\\r\\n\\t\\tint grouping = 0;\\r\\n\\t\\t\\r\\n\\t\\twhile(cn < aKey.length()){\\r\\n\\t\\t\\t\\r\\n\\t\\t\\tgrouping = grouping << 8;\\r\\n\\t\\t\\tgrouping += c[cn];\\r\\n\\t\\t\\tcn++;\\r\\n\\t\\t\\t\\r\\n\\t\\t\\tif(n == 4 || cn == aKey.length()){\\r\\n\\t\\t\\t\\tpseudoKey += grouping;\\r\\n\\t\\t\\t\\tn = 0;\\r\\n\\t\\t\\t\\tgrouping = 0;\\r\\n\\t\\t\\t}\\r\\n\\t\\t\\t\\r\\n\\t\\t\\tn++;\\r\\n\\t\\t\\t\\r\\n\\t\\t}// End of while loop\\r\\n\\t\\treturn Math.abs(pseudoKey);\\r\\n\\t\\t\\r\\n\\t}\",\n \"public String doHash2(String str) {\\n if(str.length() == 1) return \\\"-1\\\";\\n\\n String key = \\\"\\\";\\n for (int i = 0; i < str.length() - 1; i++) {\\n int val = str.charAt(i + 1) - str.charAt(i);\\n if (val < 0) val = 26 + val;\\n key += val + \\\"_\\\";\\n }\\n return key;\\n }\",\n \"public int hash(String w){\\n return (Math.abs(w.hashCode()) % hashTable.length);\\n }\",\n \"private int getHash(String word){\\n\\t\\tif (word == null){\\n\\t\\t\\treturn INVALID;\\n\\t\\t}\\n\\n\\t\\tint hash = 52;\\n\\t\\tif ((word.charAt(0) >= 'a') && (word.charAt(0) <= 'z')){\\n\\t\\t\\thash = word.charAt(0) - 'a';\\n\\t\\t}\\n\\t\\telse if ((word.charAt(0) >= 'A') && (word.charAt(0) <= 'Z')){\\n\\t\\t\\thash = word.charAt(0) - 'A' + 26;\\n\\t\\t}\\n\\t\\treturn hash;\\n\\t}\",\n \"private int hasher() {\\n int i = 0;\\n int hash = 0;\\n while (i != length) {\\n hash += hashableKey.charAt(i++);\\n hash += hash << 10;\\n hash ^= hash >> 6;\\n }\\n hash += hash << 3;\\n hash ^= hash >> 11;\\n hash += hash << 15;\\n return getHash(hash);\\n }\",\n \"private int hash(String str, int h){\\n int v=0;\\n\\n /* FILL IN HERE */\\n v = Math.floorMod(MurmurHash.hash32(str, seeds[h]) >>> h, 1 << logNbOfBuckets);\\n\\n return v;\\n }\",\n \"public static int stringHash(String str) {\\r\\n return str.hashCode();\\r\\n }\",\n \"@Override\\n\\tpublic long getHashCode(String key) {\\n\\t\\tlong hash = 0;\\n\\t\\tlong b = 378551;\\n\\t\\tlong a = 63689;\\n\\t\\tint tmp = 0;\\n\\t\\tfor (int i = 0; i < key.length(); i++) {\\n\\t\\t\\ttmp = key.charAt(i);\\n\\t\\t\\thash = hash * a + tmp;\\n\\t\\t\\ta *= b;\\n\\t\\t}\\n\\t\\treturn hash;\\n\\t}\",\n \"private String generateId(String input) {\\n\\t\\treturn StringUtil.hashSHA256(input);\\n\\t}\",\n \"public static final int hash32(String key)\\r\\n {\\n return hash32(key.getBytes());\\r\\n //So pre JDK7 could try suggestion from here: http://blog.rapleaf.com/dev/2010/04/26/faster-string-to-utf-8-encoding-in-java/\\r\\n // return hash32(fastStringToBytes(key));\\r\\n }\",\n \"public static int m2197ao(String str) {\\n try {\\n return Integer.valueOf(str).intValue();\\n } catch (Exception e) {\\n return -1;\\n }\\n }\",\n \"public void encodeInt() {\\n charToInt = new int[uniqueChars.size()];\\n Iterator<Character> mover = uniqueChars.iterator();\\n for(int b = 0; b < uniqueChars.size(); b++) {\\n charToInt[b] = mover.next();\\n }\\n System.out.print(\\\"\\\\nEncoding integer value to its ASCII characters:\\\\n\\\");\\n intToChars = new char[uniqueChars.size()];\\n for(int c = 0; c < uniqueChars.size(); c++) {\\n intToChars[c] = (char)charToInt[c];\\n charToInt[c] = charToInt[c] / charToInt[c] + c - 1;\\n System.out.print(charToInt[c] + \\\" : \\\" + intToChars[c] + \\\", \\\");\\n }\\n\\n }\",\n \"public long SDBMHash(String str) {\\n\\t\\tlong hash = 0;\\n\\n\\t\\tfor (int i = 0; i < str.length(); i++) {\\n\\t\\t\\thash = str.charAt(i) + (hash << 6) + (hash << 16) - hash;\\n\\t\\t}\\n\\n\\t\\treturn hash;\\n\\t}\",\n \"public static String getCheckNumber(String paramString){\\n int i =paramString.substring(0, 1).getBytes()[0];\\n for(int j=1;;j++){\\n if(j>=paramString.length())\\n return intToHex(Integer.valueOf(i));\\n i=(byte)(i^paramString.substring(j, j+1).getBytes()[0]);\\n\\n }\\n }\",\n \"public int hash(String item);\",\n \"public String doHash(String str) {\\n String key = \\\"\\\";\\n int offset = str.charAt(0) - 'a';\\n for (int i=0; i<str.length(); i++) {\\n char res = str.charAt(i) - offset;\\n if (res < 'a') res += 26;\\n key += res;\\n }\\n return key;\\n }\",\n \"public long ELFHash(String str) {\\n\\t\\tlong hash = 0;\\n\\t\\tlong x = 0;\\n\\n\\t\\tfor (int i = 0; i < str.length(); i++) {\\n\\t\\t\\thash = (hash << 4) + str.charAt(i);\\n\\n\\t\\t\\tif ((x = hash & 0xF0000000L) != 0) {\\n\\t\\t\\t\\thash ^= (x >> 24);\\n\\t\\t\\t}\\n\\t\\t\\thash &= ~x;\\n\\t\\t}\\n\\n\\t\\treturn hash;\\n\\t}\",\n \"public static final String hash(final String string) {\\n\\t\\treturn Hex.fromByteArray(digest(string));\\n\\t}\",\n \"private int calculateHash(int id, String uri) {\\n\\t\\treturn uri.hashCode() * Constants.HASH_PRIMES[0]\\n\\t\\t\\t\\t+ Integer.toString(id).hashCode() * Constants.HASH_PRIMES[1];\\n\\t}\",\n \"@Override\\r\\n public int hashCode() {\\n return id % 10;\\r\\n }\",\n \"public static long hashName(String name) {\\n\\t\\t\\tlong res = 123;\\n\\t\\t\\tfor (int i = 0; i < name.length(); ++i) {\\n\\t\\t\\t\\tres = (res << 8) | (res >>> 56);\\n\\t\\t\\t\\tres += name.charAt(i);\\n\\t\\t\\t\\tif ((res & 1) == 0) {\\n\\t\\t\\t\\t\\tres ^= 0x00000000feabfeabL; // Some kind of feedback\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t\\tres |= 0x8000000000000000L; // Make sure the hash is negative (to distinguish it from database id's)\\n\\t\\t\\treturn res;\\n\\t\\t}\",\n \"public static int convertStringToInt(String input){\\n\\t if(input.length()==0)\\n\\t return 0;\\n\\t \\n\\t int m=(int)input.charAt(0)-48;\\n\\t int n=input.length();\\n\\t \\n\\t while(n!=1)\\n\\t {\\n\\t m*=10;\\n\\t n--;\\n\\t }\\n\\t \\n\\t return m+convertStringToInt(input.substring(1,input.length()));\\n\\t \\n\\t \\n\\t\\t\\n\\t}\",\n \"int hash(String makeHash, int mod);\",\n \"private static int getIntValue(String s) {\\n try {\\n return Integer.parseInt(s, 16);\\n } catch (NumberFormatException e) {\\n e.printStackTrace();\\n return -1;\\n }\\n }\",\n \"public static String hash(String st) {\\r\\n MessageDigest messageDigest = null;\\r\\n byte[] digest = new byte[0];\\r\\n\\r\\n try {\\r\\n messageDigest = MessageDigest.getInstance(\\\"SHA-256\\\");\\r\\n messageDigest.reset();\\r\\n messageDigest.update(st.getBytes());\\r\\n digest = messageDigest.digest();\\r\\n } catch (NoSuchAlgorithmException e) {\\r\\n e.printStackTrace();\\r\\n }\\r\\n\\r\\n BigInteger bigInt = new BigInteger(1, digest);\\r\\n StringBuilder hex = new StringBuilder(bigInt.toString(16));\\r\\n\\r\\n while (hex.length() < 32) {\\r\\n hex.insert(0, \\\"0\\\");\\r\\n }\\r\\n\\r\\n return hex.toString();\\r\\n }\",\n \"private int hashOf(String key) {\\n return key.length();\\n }\",\n \"public int hashCode() {\\n/* 389 */ return this.m_str.hashCode();\\n/* */ }\",\n \"private static int letterToNumber(String str) {\\n return (\\\"ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz\\\".indexOf(str))%26+1;\\n }\",\n \"public static String m106643a(String str) {\\n try {\\n return m106642a(Integer.valueOf(str));\\n } catch (Exception unused) {\\n return \\\"\\\";\\n }\\n }\",\n \"@Override\\n\\tpublic int hashCode() {\\n\\t\\treturn Integer.parseInt(sid);\\n\\t}\",\n \"public static String hash(String in) {\\r\\n\\t\\treturn DigestUtils.md5Hex(in.getBytes());\\r\\n\\t}\",\n \"public int hash2 ( String key )\\n {\\n int hashVal = 0;\\n if(key != null){\\n for( int i = 0; i < key.length(); i++ )\\n hashVal = (37 * hashVal) + key.charAt(i);\\n //if(hashVal != 0)\\n return hashVal % tableSize;\\n //else\\n // return 0;\\n }\\n else{\\n //System.out.println(\\\"Key is null\\\");\\n return 0;\\n }\\n }\",\n \"public int hashcode();\",\n \"int decodeInt();\",\n \"public static int intFromHexString(CharSequence str) {\\n\\t\\tint n = 0;\\n\\t\\tfor (int i = 0; i < str.length(); i++) {\\n\\t\\t\\tchar c = str.charAt(i);\\n\\t\\t\\tint v = c <= '9' ? c - '0' : c - 'a' + 10;\\n\\t\\t\\tn <<= 4;\\n\\t\\t\\tn |= (v & 0x0f);\\n\\t\\t}\\n\\t\\treturn n;\\n\\t}\",\n \"public long DEKHash(String str) {\\n\\t\\tlong hash = str.length();\\n\\n\\t\\tfor (int i = 0; i < str.length(); i++) {\\n\\t\\t\\thash = ((hash << 5) ^ (hash >> 27)) ^ str.charAt(i);\\n\\t\\t}\\n\\n\\t\\treturn hash;\\n\\t}\",\n \"@Test\\n public void testHashCode() {\\n LOGGER.info(\\\"testHashCode\\\");\\n final String value = \\\"Hello\\\";\\n final int actual = new AtomString(value).hashCode();\\n final int expected = 61 * 7 + Objects.hashCode(value);\\n assertEquals(expected, actual);\\n }\",\n \"String getIntegerEncoding();\",\n \"public int hashCode() {\\n\\t\\treturn hashString.hashCode();\\n\\t}\",\n \"public static int randomHashOfString(String s)\\r\\n\\t{\\r\\n\\t\\tBigInteger hash=FNV64INIT;\\r\\n\\t\\tfor(int j=0;j<s.length();j++)\\r\\n\\t\\t{\\r\\n\\t\\t\\thash=hash.xor(BigInteger.valueOf(s.charAt(j)));\\r\\n\\t\\t\\thash=hash.multiply(FNV64PRIME).mod(TWO.pow(64));\\r\\n\\t\\t}\\r\\n\\t\\treturn hash.intValue();\\r\\n\\t}\",\n \"public long DJBHash(String str) {\\n\\t\\tlong hash = 5381;\\n\\n\\t\\tfor (int i = 0; i < str.length(); i++) {\\n\\t\\t\\thash = ((hash << 5) + hash) + str.charAt(i);\\n\\t\\t}\\n\\n\\t\\treturn hash;\\n\\t}\",\n \"public int hash(String key){\\r\\n\\t\\tint i;\\r\\n\\t\\tint v = 0;\\r\\n\\t\\tfor(i = 0; i < key.length(); i++)\\r\\n\\t\\t\\tv += key.charAt(i);\\r\\n\\t\\treturn v % M;\\r\\n\\t}\",\n \"public long BKDRHash(String str) {\\n\\t\\tlong seed = 131; // 31 131 1313 13131 131313 etc..\\n\\t\\tlong hash = 0;\\n\\n\\t\\tfor (int i = 0; i < str.length(); i++) {\\n\\t\\t\\thash = (hash * seed) + str.charAt(i);\\n\\t\\t}\\n\\n\\t\\treturn hash;\\n\\t}\",\n \"public int numDecodings(String s) {\\n if(s==null||s.length()==0){\\n return 0;\\n }\\n\\n int n=s.length();\\n int[] mem=new int[n+1];\\n\\n mem[n]=1;\\n if(Integer.parseInt(s.substring(n-1))!=0){\\n mem[n-1]=1;\\n }\\n\\n for(int i=n-2;i>=0;i--){\\n if(Integer.parseInt(s.substring(i,i+1))==0){\\n continue;\\n }\\n if(Integer.parseInt(s.substring(i,i+2))<26){\\n mem[i]=mem[i+1]+mem[i+2];\\n }else{\\n mem[i]=mem[i+1];\\n }\\n }\\n\\n return mem[0];\\n }\",\n \"int toInt(String a){\\n\\t\\tint name=0;\\r\\n\\t\\tfor(int i=0;i<a.length();i++){\\r\\n\\t\\t\\tname+=(int)a.charAt(i);\\r\\n\\t\\t}\\r\\n\\t\\treturn name;\\r\\n\\t}\",\n \"public int hashCode(){\\n\\t\\treturn toString().hashCode();\\n\\t}\",\n \"@Override\\r\\n public int hashCode() {\\n int key=(Integer)(this.capsule.get(0)); // Get the key\\r\\n Integer bkey=Integer.parseInt(Integer.toBinaryString(key)); // Convert into binary \\r\\n int n=setcount(bkey); //counts the number of 1's in the binary\\r\\n key=key*n + Objects.hashCode(this.capsule.get(0)); //multiplies that with the hashcode of the pId\\r\\n return key;\\r\\n }\",\n \"public int mo29670a(String str) {\\n int length = str.length();\\n int i = this.f19526c;\\n for (int i2 = 0; i2 < length; i2++) {\\n i = (i * 33) + str.charAt(i2);\\n }\\n if (i == 0) {\\n return 1;\\n }\\n return i;\\n }\",\n \"public static int toInt(String str){\\r\\n\\t\\tInteger i = toInteger(str);\\r\\n\\t\\treturn i==null?0:i;\\r\\n\\t}\",\n \"@Override\\n public int hashCode() {\\n int result = 42;\\n int prime = 37;\\n for (char ch : key.toCharArray()) {\\n result = prime * result + (int) ch;\\n }\\n result = prime * result + summary.length();\\n result = prime * result + value;\\n return result;\\n }\",\n \"public static long hash(String stringToHash) {\\n byte[] data;\\n try {\\n data = stringToHash.getBytes(\\\"UTF-8\\\");\\n long h = HSTART;\\n final long hmult = HMULT;\\n final long[] ht = byteTable;\\n for (int len = data.length, i = 0; i < len; i++) {\\n h = (h * hmult) ^ ht[data[i] & 0xff];\\n }\\n return h;\\n } catch (UnsupportedEncodingException e) {\\n e.printStackTrace();\\n throw new AssertionError(\\\"Hash failures on encoding\\\");\\n }\\n }\",\n \"String toStringAsInt();\",\n \"@Override\\r\\n\\tpublic int hashCode() {\\n\\t\\tint result = 17;\\r\\n\\t\\tresult = 37*result+(int) (id ^ (id>>>32));\\r\\n\\t\\t//result = 37*result+(name==null?0:name.hashCode());\\r\\n\\t\\t//result = 37*result+displayOrder;\\r\\n\\t\\t//result = 37*result+(this.url==null?0:url.hashCode());\\r\\n\\t\\treturn result;\\r\\n\\t}\",\n \"static int sherlockAndAnagrams(String s) {\\n HashTable hashTable = new HashTable(s.length() * s.length() * 4);\\n substrings(s).map(Solution::ordered).forEach(hashTable::insert);\\n return substrings(s).map(Solution::ordered).mapToInt(s1 -> {\\n hashTable.remove(s1);\\n return hashTable.count(s1);\\n }).sum();\\n }\",\n \"public long PJWHash(String str) {\\n\\t\\tlong BitsInUnsignedInt = (long) (4 * 8);\\n\\t\\tlong ThreeQuarters = (long) ((BitsInUnsignedInt * 3) / 4);\\n\\t\\tlong OneEighth = (long) (BitsInUnsignedInt / 8);\\n\\t\\tlong HighBits = (long) (0xFFFFFFFF) << (BitsInUnsignedInt - OneEighth);\\n\\t\\tlong hash = 0;\\n\\t\\tlong test = 0;\\n\\n\\t\\tfor (int i = 0; i < str.length(); i++) {\\n\\t\\t\\thash = (hash << OneEighth) + str.charAt(i);\\n\\n\\t\\t\\tif ((test = hash & HighBits) != 0) {\\n\\t\\t\\t\\thash = ((hash ^ (test >> ThreeQuarters)) & (~HighBits));\\n\\t\\t\\t}\\n\\t\\t}\\n\\n\\t\\treturn hash;\\n\\t}\",\n \"protected static final int getUnitId(String inputHex) {\\r\\n\\t\\t\\r\\n\\t\\tString msb = inputHex.substring(0, 2);\\r\\n\\t\\tString lsb = inputHex.substring(2, 4);\\r\\n\\r\\n\\t\\tint val = ( Integer.parseInt(msb, 16) * 256 ) + ( Integer.parseInt(lsb, 16) * 1 );\\r\\n//\\t\\tGQDKPMConstants.logger.debug(\\\"incoming lsb = \\\" + lsb +\\\" lsb hex-dec = \\\"+Integer.parseInt(lsb, 16) * 1 +\\r\\n//\\t\\t\\t\\t\\\" , msb = \\\"+ msb + \\\" msb hex-dec = \\\"+Integer.parseInt(msb, 16) * 256 + \\\" , val = \\\" + val );\\r\\n\\t\\treturn val;\\r\\n\\t}\",\n \"public String intToString(String s) {\\r\\n int x = s.length();\\r\\n char[] bytes = new char[4];\\r\\n for(int i = 3; i > -1; --i) {\\r\\n bytes[3 - i] = (char) (x >> (i * 8) & 0xff);\\r\\n }\\r\\n return new String(bytes);\\r\\n }\",\n \"@SuppressWarnings(\\\"WeakerAccess\\\")\\n abstract public int hash(char c);\",\n \"public static int hashCode(String str, int b) {\\n\\tint result = 0;\\n\\tfor(int i = 0; i < str.length(); i++) {\\n\\t\\tresult += (str.charAt(i)) * (int)Math.pow(b, str.length() - (1+i));\\n\\t\\t}\\n\\treturn result;\\n\\t}\",\n \"@Override\\n public int hashCode() {\\n return String.valueOf(this).hashCode();\\n }\",\n \"public int hash3 ( String key )\\n {\\n int hashVal = 0;\\n if(key != null){\\n for( int i = 0; i < key.length(); i++ ){\\n hashVal = (37 * hashVal) + key.charAt(i);}\\n hashVal %= tableSize;\\n if(hashVal<0)\\n hashVal += tableSize; \\n if(hashVal != 0)\\n return hashVal;\\n else\\n return 0;\\n }\\n else\\n {\\n //System.out.println(\\\"Key is null\\\");\\n return 0;\\n }\\n }\",\n \"public static String uniqueChar(String str){\\n\\n char[] ch=str.toCharArray();\\n str=\\\"\\\";\\n HashMap<Character,Integer> map=new HashMap<>();\\n for(int i=0;i<ch.length;i++)\\n {\\n if(map.containsKey(ch[i]));\\n else\\n {\\n str+=ch[i];\\n map.put(ch[i],1);\\n }\\n }\\n \\n return str;\\n\\t}\",\n \"@Override\\n public int hashCode() {\\n if (!(uuid instanceof String)) {\\n uuid = UUID.randomUUID().toString();\\n }\\n\\n return uuid.hashCode();\\n }\",\n \"public static int hashCodeForStrings(String... strings) {\\n\\t\\tint hash = 0;\\n\\t\\tfor(String str : strings) {\\n\\t\\t\\tfor(int i=0;i<str.length();++i) {\\n\\t\\t\\t\\thash = 31 * hash + str.charAt(i);\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\treturn hash;\\n\\t}\",\n \"public int firstUniqChar2(String s) {\\r\\n \\r\\n char[] arr= s.toCharArray();\\r\\n int index = -1;\\r\\n HashMap<Character, Integer> map = new HashMap<>();\\r\\n \\r\\n for (int i=0;i<arr.length;i++){\\r\\n if (map.containsKey(arr[i])){\\r\\n map.put(arr[i], -1);\\r\\n } else {\\r\\n map.put(arr[i],i);\\r\\n }\\r\\n }\\r\\n \\r\\n for (int i : map.values()){\\r\\n if (i >-1){\\r\\n if (index == -1){\\r\\n index = i;\\r\\n } else if (i<index) {\\r\\n index = i; \\r\\n }\\r\\n \\r\\n }\\r\\n }\\r\\n \\r\\n return index;\\r\\n }\",\n \"public boolean isUnique(String s){\\n // int[] visited = new int[256]; // O:256\\n int[] visited = new int[8]; // int = 4 bytes = 32 bits, 8 ints = 32 bytes = 256 bits\\n char[] array = s.toCharArray();\\n for(char c:array){\\n // for a value c in range of 0 - 256\\n // it maps to the int at c/32 as index\\n // it also maps the c%32 as the index of bits\\n if(((visited[c/32] >>> (c%32)) & 1) != 0){\\n // bit-tester of the k-th bits, k = c%32\\n return false;\\n }\\n // bit-setter to 1 in the k-th bits\\n visited[c/32] |= 1 << (c%32);\\n }\\n return true;\\n }\",\n \"private static int firstUniqChar2(String s) {\\n Map<Character, Integer> seen = new HashMap<>();\\n for (int i = 0; i < s.length(); i++) {\\n char c = s.charAt(i);\\n seen.put(c, seen.getOrDefault(c, 0) + 1);\\n }\\n\\n int uniqueIdx = -1;\\n for (int i = 0; i < s.length(); i++) {\\n if (seen.get(s.charAt(i)) == 1) {\\n uniqueIdx = i;\\n break;\\n }\\n }\\n\\n return uniqueIdx;\\n }\",\n \"static int getKey(String raw) {\\n\\t\\tint key = 0;\\n\\t\\tfor (int i = 0; i < raw.length(); i++) {\\n\\t\\t\\tkey = key * HASH_VALUE + raw.charAt(i);\\n\\t\\t}\\n\\t\\tif (key < 0) {\\n\\t\\t\\tkey = -key;\\n\\t\\t}\\n\\t\\treturn key % HASH_SIZE;\\n\\t}\",\n \"int getHash();\",\n \"public static String generateId(String s){\\n\\t\\tString date = LocalDate.now().format(DateTimeFormatter.ofPattern(\\\"yyMMdd\\\"));\\n\\t\\tString key = s +\\\"_\\\" + date;\\n\\t\\t//com.incr(key);\\n\\t\\tredisTemplate.opsForValue().increment(key);\\n\\t\\tInteger num = redisTemplate.opsForValue().get(key);\\n\\t\\treturn date + \\\"-\\\" + String.format(\\\"%08d\\\",num);\\n\\t}\",\n \"public int hash1 ( String key )\\n {\\n int hashVal = 0;\\n if(key != null){\\n for( int i = 0; i < key.length(); i++ )\\n hashVal += key.charAt(i);\\n \\n //if(hashVal != 0)\\n return hashVal % tableSize;\\n //else\\n // return 0;\\n }\\n else{\\n //System.out.println(\\\"Key is null\\\");\\n return 0 ;\\n }\\n\\n }\",\n \"public BigInteger hash(String element)\\n\\t{ \\n\\t\\treturn (BigInteger.valueOf(element.hashCode())).mod(modulus);\\n\\t}\",\n \"@Override\\n public int hexToInt(String source) {\\n try {\\n return Integer.parseInt(source, 16);\\n } catch (NumberFormatException nfe) {\\n return 0;\\n }\\n }\",\n \"@Override\\n\\tpublic int hashCode() {\\n\\t\\t\\n\\t\\treturn (int)id * name.hashCode() * email.hashCode();\\n\\t\\t//int hash = new HashCodeBuilder(17,37).append(id).append(name); //can be added from Apache Commons Lang's HashCodeBuilder class\\n\\t}\",\n \"public static String toAscii(String s){\\r\\n StringBuilder sb = new StringBuilder();\\r\\n long asciiInt;\\r\\n // loop through all values in the string, including blanks\\r\\n for (int i = 0; i < s.length(); i++){\\r\\n //getting Ascii value of character and adding it to the string.\\r\\n char c = s.charAt(i);\\r\\n asciiInt = (int)c; \\r\\n sb.append(asciiInt);\\r\\n }\\r\\n return String.valueOf(sb);\\r\\n }\",\n \"private static int hashCode(byte key) {\\n return (int) key;\\n }\",\n \"public int titleToNumber(String s) {\\n int val = 0;\\n //go thru string\\n for (int i = 0; i < s.length(); i++){\\n \\t//26 letts of alph add the int val of that character \\n val = val * 26 + (int) s.charAt(i) - (int) 'A' + 1;\\n }\\n return val;\\n }\",\n \"@Override\\n public int hashCode() {\\n \\n final int code = 24;\\n int result = 1;\\n result = code * result + ((id == null) ? 0 : id.hashCode());\\n return result;\\n }\",\n \"public static int firstUniqChar(String s) {\\n\\n HashMap<String, Integer> hm = new HashMap<>();\\n\\n for(int i = 0; i < s.length(); i++) {\\n if(hm.containsKey(s.substring(i, i+1))) {\\n hm.put(s.substring(i,i+1), hm.get(s.substring(i,i+1))+1);\\n }\\n else {\\n hm.put(s.substring(i,i+1), 1);\\n }\\n }\\n\\n for(int i = 0; i< s.length(); i++) {\\n if(hm.get(s.substring(i,i+1)) == 1) {\\n return i;\\n }\\n }\\n //this means all the string is repeating\\n return -1;\\n }\",\n \"@Override\\n\\tpublic int hashValue(String value) {\\n\\t\\treturn hashFunc(value);\\n\\t}\",\n \"public static String GetHash(String input)\\n {\\n String hash = DigestUtils.sha1Hex(input);\\n System.out.println(hash);\\n return hash;\\n }\",\n \"private String intChecker(String s) {\\n\\t\\tString newS = \\\"\\\";\\n\\t\\tfor(int i = 0; i < s.length(); i++) {\\n\\t\\t\\tif(s.charAt(i) > 47 && s.charAt(i) < 58) {\\n\\t\\t\\t\\tnewS += s.charAt(i);\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\treturn newS;\\n\\t}\",\n \"private static int parseInt(String sn) {\\n\\t\\treturn Integer.parseInt(sn.substring(2), 16);\\n\\t}\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7137949","0.6897674","0.6708983","0.6634139","0.6602896","0.6580906","0.6529667","0.6447881","0.64134866","0.64026445","0.6386157","0.6376087","0.6344094","0.6320488","0.6314912","0.6302626","0.62619746","0.62537754","0.62481886","0.62098116","0.6183987","0.61695445","0.61648166","0.6151573","0.6118675","0.610952","0.6062072","0.6049026","0.6041182","0.601919","0.59589964","0.59352666","0.5933174","0.59162694","0.5915166","0.59013146","0.5899446","0.58977044","0.5892935","0.58910304","0.58871675","0.58836824","0.58672094","0.5863218","0.5855458","0.58538884","0.5852898","0.5835477","0.5825108","0.5822998","0.5820961","0.58193785","0.58154017","0.5813452","0.58017397","0.57987857","0.5786249","0.57729685","0.5770759","0.5769217","0.57676256","0.5761375","0.5757552","0.57561576","0.574713","0.5737351","0.57352346","0.57240844","0.57240236","0.5717949","0.5714614","0.5714337","0.57105243","0.570995","0.5697737","0.56914055","0.56810874","0.56795025","0.5662679","0.56610316","0.56572944","0.56481045","0.5643867","0.5643672","0.564038","0.5634936","0.563335","0.5626031","0.56197244","0.561072","0.56103605","0.5608213","0.5600049","0.5597365","0.55969185","0.5595143","0.55853474","0.5579451","0.55745256","0.55616313"],"string":"[\n \"0.7137949\",\n \"0.6897674\",\n \"0.6708983\",\n \"0.6634139\",\n \"0.6602896\",\n \"0.6580906\",\n \"0.6529667\",\n \"0.6447881\",\n \"0.64134866\",\n \"0.64026445\",\n \"0.6386157\",\n \"0.6376087\",\n \"0.6344094\",\n \"0.6320488\",\n \"0.6314912\",\n \"0.6302626\",\n \"0.62619746\",\n \"0.62537754\",\n \"0.62481886\",\n \"0.62098116\",\n \"0.6183987\",\n \"0.61695445\",\n \"0.61648166\",\n \"0.6151573\",\n \"0.6118675\",\n \"0.610952\",\n \"0.6062072\",\n \"0.6049026\",\n \"0.6041182\",\n \"0.601919\",\n \"0.59589964\",\n \"0.59352666\",\n \"0.5933174\",\n \"0.59162694\",\n \"0.5915166\",\n \"0.59013146\",\n \"0.5899446\",\n \"0.58977044\",\n \"0.5892935\",\n \"0.58910304\",\n \"0.58871675\",\n \"0.58836824\",\n \"0.58672094\",\n \"0.5863218\",\n \"0.5855458\",\n \"0.58538884\",\n \"0.5852898\",\n \"0.5835477\",\n \"0.5825108\",\n \"0.5822998\",\n \"0.5820961\",\n \"0.58193785\",\n \"0.58154017\",\n \"0.5813452\",\n \"0.58017397\",\n \"0.57987857\",\n \"0.5786249\",\n \"0.57729685\",\n \"0.5770759\",\n \"0.5769217\",\n \"0.57676256\",\n \"0.5761375\",\n \"0.5757552\",\n \"0.57561576\",\n \"0.574713\",\n \"0.5737351\",\n \"0.57352346\",\n \"0.57240844\",\n \"0.57240236\",\n \"0.5717949\",\n \"0.5714614\",\n \"0.5714337\",\n \"0.57105243\",\n \"0.570995\",\n \"0.5697737\",\n \"0.56914055\",\n \"0.56810874\",\n \"0.56795025\",\n \"0.5662679\",\n \"0.56610316\",\n \"0.56572944\",\n \"0.56481045\",\n \"0.5643867\",\n \"0.5643672\",\n \"0.564038\",\n \"0.5634936\",\n \"0.563335\",\n \"0.5626031\",\n \"0.56197244\",\n \"0.561072\",\n \"0.56103605\",\n \"0.5608213\",\n \"0.5600049\",\n \"0.5597365\",\n \"0.55969185\",\n \"0.5595143\",\n \"0.55853474\",\n \"0.5579451\",\n \"0.55745256\",\n \"0.55616313\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.5671831"},"document_rank":{"kind":"string","value":"78"}}},{"rowIdx":13897,"cells":{"query":{"kind":"string","value":"[NEW] Strings the map containing all postingslist and tokens"},"document":{"kind":"string","value":"public String toString(){\n String s = \" \";\n for (Map.Entry<String, PostingsList> entry : this.index.entrySet()) {\n s += entry.getKey()+\" - \" + entry.getValue().toString() + \"\\n\";\n }\n return s;//this.indexInMemory.toString();\n }"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["Map<String, String> getTokens();","@Override\r\n public String toString() {\r\n String s = new String();\r\n for (String t : tokenList)\r\n s = s + \"~\" + t;\r\n return s;\r\n }","@Override\n public String toString() {\n StringJoiner sj = new StringJoiner(\", \", \"{\", \"}\\n\");\n wordMap.forEach((k, v) -> sj.add(String.format(\"%s -> %s\", k, v)));\n return sj.toString();\n }","public static HashMap<String, String> simplifiedTags(List<List<TaggedWord>> taggedList) {\n HashMap<String, String> simplePOSTagged = new HashMap<>();\n for (List<TaggedWord> tags : taggedList) { // iterate over list\n for (TaggedWord taggedWord : tags) {//for each word in the sentence\n String word = taggedWord.toString().replaceFirst(\"/\\\\w+\", \"\");\n if (taggedWord.tag().equals(\"NN\") | taggedWord.tag().equals(\"NNS\") |\n taggedWord.tag().equals(\"NNP\") | taggedWord.tag().equals(\"NNPS\")) {\n simplePOSTagged.put(word, \"noun\");\n } else if (taggedWord.tag().equals(\"MD\") | taggedWord.tag().equals(\"VB\") |\n taggedWord.tag().equals(\"VBD\") | taggedWord.tag().equals(\"VBG\") |\n taggedWord.tag().equals(\"VBN\") | taggedWord.tag().equals(\"VBP\")\n | taggedWord.tag().equals(\"VBZ\")) {\n simplePOSTagged.put(word, \"verb\");\n } else if (taggedWord.tag().equals(\"JJ\") | taggedWord.tag().equals(\"JJR\") |\n taggedWord.tag().equals(\"JJS\")) {\n simplePOSTagged.put(word, \"adj\");\n } else if (taggedWord.tag().equals(\"PRP\") | taggedWord.tag().equals(\"PRP$\")) {\n simplePOSTagged.put(word, \"pron\");\n } else if (taggedWord.tag().equals(\"RB\") | taggedWord.tag().equals(\"RBR\") |\n taggedWord.tag().equals(\"RBS\")) {\n simplePOSTagged.put(word, \"adv\");\n } else if (taggedWord.tag().equals(\"CD\") | taggedWord.tag().equals(\"LS\")) {\n simplePOSTagged.put(word, \"num\");\n } else if (taggedWord.tag().equals(\"WDT\") | taggedWord.tag().equals(\"WP\") |\n taggedWord.tag().equals(\"WP$\") | taggedWord.tag().equals(\"WRB\")) {\n simplePOSTagged.put(word, \"wh\");\n } else if (taggedWord.tag().equals(\"DT\") | taggedWord.tag().equals(\"PDT\")) {\n simplePOSTagged.put(word, \"det\");\n } else if (taggedWord.tag().equals(\"CC\") | taggedWord.tag().equals(\"IN\")) {\n simplePOSTagged.put(word, \"prepconj\");\n } else {\n simplePOSTagged.put(word, \"other\");\n }\n }\n }\n return simplePOSTagged;\n }","List<String> getTokens();","public Map<String, String> getTokens() {\n return tokens;\n }","@Override\n public String toString() {\n return token.toString();\n }","private static Map<String, Integer> getWords(){\n\t\tMap<String, Integer> map = new HashMap<String, Integer>();\n\t\t\n\t\tfor(Status status : statusList){\n\t\t\tStringTokenizer tokens = new StringTokenizer(status.getText());\n\t\t\twhile(tokens.hasMoreTokens()){\n\t\t\t\tString token = tokens.nextToken();\n\t\t\t\tif(!token.equals(\"RT\")){\n\t\t\t\t\tif(map.containsKey(token)){\n\t\t\t\t\t\tint count = map.get(token);\n\t\t\t\t\t\tmap.put(token, ++count);\n\t\t\t\t\t}else{\n\t\t\t\t\t\tmap.put(token, 1);\n\t\t\t\t\t}\n\t\t\t\t}\t\t\n\t\t\t}\n\t\t}\n\t\t\n\t\treturn map;\n\t}","@Override\n\t\tprotected void map(Object key, Text value, Context context)\n\t\t\t\tthrows IOException, InterruptedException {\n\t\t\tStringTokenizer str=new StringTokenizer(value.toString());\n//\t\t\tString[]str=new String(value.toString()).split(\"a\");\n\t\t\twhile(str.hasMoreTokens()){\n\t\t\t\tword.set(str.nextToken());\n\t\t\t\tcontext.write(word, one);\n\t\t\t\t}\n//\t\t\tfor(String b:str){\n//\t\t\t\tword.set(b);\n//\t\t\t\tcontext.write(word, one);\n//\t\t\t\t\n//\t\t\t}\n\t\t\t\n\t\t}","String getTokenString();","public void buildMap()\n {\n for(int letterNum=0; letterNum < myText.length()-myNum; letterNum++) {\n String key = myText.substring(letterNum,letterNum+myNum);\n String nextLetter = String.valueOf(myText.charAt(letterNum + myNum));\n if (!map.containsKey(key)) {\n ArrayList<String> lettersArray = new ArrayList<String>();\n lettersArray.add(nextLetter);\n map.put(key,lettersArray);\n }else\n {\n map.get(key).add(nextLetter);\n }\n }\n }","public MapToken() {\n\t\tmData = new FastMap<String, Object>();\n\t}","private List<String> getSubstitutes(String postScriptName) {\n/* 218 */ List<String> subs = this.substitutes.get(postScriptName.replaceAll(\" \", \"\"));\n/* 219 */ if (subs != null)\n/* */ {\n/* 221 */ return subs;\n/* */ }\n/* */ \n/* */ \n/* 225 */ return Collections.emptyList();\n/* */ }","@Override\n\tpublic String toString()\n\t{\n\t\tfinal AppendingStringBuffer buffer = new AppendingStringBuffer();\n\t\tboolean first = true;\n\t\tfor (Map.Entry<String, Object> entry : entrySet())\n\t\t{\n\t\t\tif (first == false)\n\t\t\t{\n\t\t\t\tbuffer.append(' ');\n\t\t\t}\n\t\t\tfirst = false;\n\n\t\t\tbuffer.append(entry.getKey());\n\t\t\tbuffer.append(\" = \\\"\");\n\t\t\tfinal Object value = entry.getValue();\n\t\t\tif (value == null)\n\t\t\t{\n\t\t\t\tbuffer.append(\"null\");\n\t\t\t}\n\t\t\telse if (value.getClass().isArray())\n\t\t\t{\n\t\t\t\tbuffer.append(Arrays.asList((Object[])value));\n\t\t\t}\n\t\t\telse\n\t\t\t{\n\t\t\t\tbuffer.append(value);\n\t\t\t}\n\n\t\t\tbuffer.append('\\\"');\n\t\t}\n\t\treturn buffer.toString();\n\t}","public String toString() {\r\n\t\tStringBuffer sb = new StringBuffer();\r\n\t\tsb.append(\"Tokens:\\n\");\r\n\t\tfor (int i = 0; i < tokens.size(); i++) {\r\n\t\t\tsb.append(tokens.get(i)).append('\\n');\r\n\t\t}\r\n\t\treturn sb.toString();\r\n\t}","private Map<String, String> locationListToString(List<Element> locations) {\r\n Map<String, String> locMap = new LinkedHashMap<String, String>();\r\n for (Element location : locations) {\r\n String fileName = location.attributeValue(\"filename\");\r\n String lineNumber = location.attributeValue(\"line\");\r\n String current = locMap.get(fileName);\r\n locMap.put(fileName, null == current ? lineNumber : current + \", \" + lineNumber);\r\n }\r\n return locMap;\r\n }","public PostingsList getPostings( String token ) {\n PostingsList post = new PostingsList();\n if(this.index.containsKey(token))\n post = (this.index.get(token)).clone();\n /*System.err.println(\"start search...\");\n // Read JSON file associated to token and return it as a postingslist\n String filename = \"postings/t\"+hash(token)+\".json\";\n PostingsList post = new PostingsList();\n try(Reader reader = new FileReader(filename)){\n post = (new Gson()).fromJson(reader, PostingsList.class);\n } catch (IOException e) {\n e.printStackTrace();\n }*/\n return post;\n }","public String getTokenString() {\n String tokenString = \"\";\n\n for (int i = 0; i < clueTokens.size(); i++) {\n tokenString += clueTokens.get(i).getName();\n if (i < clueTokens.size() - 1)\n tokenString += \", \";\n }\n\n return tokenString;\n }","Map<String, String> tags();","Map<String, String> tags();","Map<String, String> tags();","Map<String, String> tags();","Map<String, String> tags();","Map<String, String> tags();","Map<String, String> tags();","Map<String, String> tags();","public Map<String, List<String>> genericsTokens() {\n return genericsTokens;\n }","public PostingsList getPostings( String token ) {\r\n PostingsList element = index.get(token) ;\r\n if (element != null)\r\n {\r\n return element;\r\n }\r\n return null;\r\n }","String getToken();","String getToken();","String getToken();","String getToken();","String getToken();","protected String getTokenString (int token) {\r\n switch (token) {\r\n case START:\r\n return \"START\";\r\n case STRING:\r\n return \"STRING\";\r\n case SQSTRING:\r\n return \"SQSTRING\";\r\n case DQSTRING:\r\n return \"DQSTRING\";\r\n case SINGELQUOTE:\r\n return \"SINGELQUOTE\";\r\n case DOUBLEQUOTE:\r\n return \"DOUBLEQUOTE\";\r\n case LT:\r\n return \"LT\";\r\n case MT:\r\n return \"MT\";\r\n case EQUALS:\r\n return \"EQUALS\";\r\n case COMMENT:\r\n return \"COMMENT\";\r\n case END:\r\n return \"END\";\r\n case UNKNOWN:\r\n return \"UNKNOWN\";\r\n default:\r\n return \"unknown\";\r\n }\r\n }","private static Map<String, String> parseInstanceValues(String data) {\r\n \t\tMap<String, String> responseMap = new HashMap<String, String>();\r\n \t\tif (data != null) {\r\n \t\t\tStringTokenizer strTok = new StringTokenizer(data, \",\\n\");\r\n \t\t\twhile (strTok.hasMoreTokens()) {\r\n \t\t\t\tString key = strTok.nextToken();\r\n \t\t\t\tString val = strTok.nextToken();\r\n \t\t\t\tString oldVal = responseMap.get(key);\r\n \t\t\t\tif (oldVal != null) {\r\n \t\t\t\t\tif (val != null) {\r\n \t\t\t\t\t\tif (oldVal.trim().length() < val.trim().length()) {\r\n \t\t\t\t\t\t\tresponseMap.put(key, val);\r\n \t\t\t\t\t\t}\r\n \t\t\t\t\t}\r\n \t\t\t\t} else {\r\n \t\t\t\t\tresponseMap.put(key, val);\r\n \t\t\t\t}\r\n \t\t\t}\r\n \t\t}\r\n \t\treturn responseMap;\r\n \t}","private static String listOfTokensToString(List<Token> tokenList) {\n\n StringBuilder stringBuilder = new StringBuilder();\n for (Token token : tokenList) {\n stringBuilder.append(String.format(\"%s\", token.getPattern()));\n }\n return stringBuilder.toString().trim();\n }","java.lang.String getToken();","java.lang.String getToken();","java.lang.String getToken();","java.lang.String getToken();","java.lang.String getToken();","java.lang.String getToken();","public static String string() {\n\t\t\tString s = \"\";\n\t\t\ts += \"Locaux :\\n\";\n\t\t\tfor(String key : locaux.keySet()) {\n\t\t\t\tIdent i = locaux.get(key);\n\t\t\t\ts += key+\", \"+i.toString()+\"\\n\";\n\t\t\t}\n\t\t\ts += \"Globaux :\\n\";\n\t\t\tfor(String key : globaux.keySet()) {\n\t\t\t\tIdent i = globaux.get(key);\n\t\t\t\ts += key+\", \"+i.toString()+\"\\n\";\n\t\t\t}\n\n\t\t\treturn s;\n\t\t}","@Override\n public String mapping() {\n return StringUtils.lines(\n \"foo.bar.Baz -> foo.bar.Baz:\", \" java.lang.Object f1 -> a\", \" java.lang.String f2 -> a\");\n }","@Override\n\tpublic String toString() {\n\t\tStringBuilder buf = new StringBuilder();\n\t\t\n\t\tCIntMap termsFrequencies = null;\n\t\tfor( String tag : keySet()) {\n\t\t\tbuf.append(tag);\n\t\t\tbuf.append(\"\\n\");\n\t\t\ttermsFrequencies = get(tag);\n\t\t\tbuf.append(termsFrequencies);\n\t\t}\n\t\t\n\t\treturn buf.toString();\n\t}","@Override\n public String toString() {\n if (this.map.getMap().isEmpty()) return \"\";\n final StringBuilder param = new StringBuilder(this.map.getMap().size() * 40);\n for (final Map.Entry<String, String> entry: entrySet()) {\n param.append(MultiProtocolURL.escape(entry.getKey()))\n .append('=')\n .append(MultiProtocolURL.escape(entry.getValue()))\n .append('&');\n }\n param.setLength(param.length() - 1);\n return param.toString();\n }","private static Map<String, Integer> getHashTags(){\n\t\t\n\t\tMap<String, Integer> map = new HashMap<String, Integer>();\n\t\t\n\t\tfor(Status status : statusList){\n\t\t\tHashtagEntity[] entitles = status.getHashtagEntities();\n\t\t\tfor(HashtagEntity entity : entitles){\n\t\t\t\tString str = entity.getText();\n\t\t\t\t\n\t\t\t\tif(map.containsKey(str)){\n\t\t\t\t\tint count = map.get(str);\n\t\t\t\t\tmap.put(str, ++count);\n\t\t\t\t}else{\n\t\t\t\t\tmap.put(str, 1);\n\t\t\t\t}\n\t\t\t\t\n\t\t\t}\n\t\t}\n\t\treturn map;\n\t}","@Override\r\n\tpublic Map<Integer, String> getMakingMtList() {\n\t\treturn null;\r\n\t}","Iterator<String> getTokenIterator();","@Override public String toString(){\r\n StringBuilder output = new StringBuilder();\r\n for (Iterator<NoteToken> i = NotesList.iterator(); i.hasNext();){\r\n output.append(i.next().toString());\r\n output.append(\" \");\r\n \r\n }\r\n return output.toString();\r\n }","public Map<String, Set<String>> getSubStringAlias(Set<String> enSet){\n EntityUtils alias = new EntityUtils();\n Map<String, Set<String>> mentions_map = alias.getAliasMapFromSet(enSet);\n return mentions_map;\n\n }","public String toString (Token T);","private Map<String, String> processPostRequest(String content) {\n Map<String, String> store = new HashMap<String, String>();\n\n // Split the post data by &\n for (String entry : content.split(\"&\")) {\n // Split it by =\n String[] data = entry.split(\"=\");\n\n // Check that there is sufficient data in the data array\n if (data.length != 2) {\n continue;\n }\n\n // decode the data\n String key = URLUtils.decode(data[0]);\n String value = URLUtils.decode(data[1]);\n\n // Add it to the store\n store.put(key, value);\n }\n\n return store;\n }","public String valuesFromMap() {\n\t\thashMap = createSimpleMap(\"Breakfast\", \"Eggs\");\n\t\treturn hashMap.get(\"Breakfast\");\n\t}","public String toString() {\n return PARSER_KEY;\n }","private String toString(String pre) {\n StringBuilder sb = new StringBuilder();\n\n sb.append(key);\n if (values1 != null) {\n sb.append(\" \");\n sb.append(values1);\n sb.append(\", \");\n sb.append(values2);\n }\n sb.append(\"\\n\");\n\n String newpre = pre + \" \";\n if (!son.empty) {\n sb.append(newpre);\n sb.append(\"son: \");\n sb.append(son.toString(newpre));\n }\n if (!left.empty) {\n sb.append(newpre);\n sb.append(\"left: \");\n sb.append(left.toString(newpre));\n }\n if (!right.empty) {\n sb.append(newpre);\n sb.append(\"right: \");\n sb.append(right.toString(newpre));\n }\n return sb.toString();\n }","private void setupTokenHashTable() {\n this.tokenHashTable = new Hashtable<>();\n \t\n /* Identifier Token */\n this.getTokenHashTable().put(1001, \"idTK\");\n this.getTokenHashTable().put(1002, \"integerTK\");\n \t\n /* Operators and Delimiters */\n this.getTokenHashTable().put(1003, \"equalsTK\");\n this.getTokenHashTable().put(1004, \"lessThanTK\");\n this.getTokenHashTable().put(1005, \"greaterThanTK\");\n this.getTokenHashTable().put(1006, \"compareEqualTK\");\n this.getTokenHashTable().put(1007, \"colonTK\");\n this.getTokenHashTable().put(1008, \"plusTK\");\n this.getTokenHashTable().put(1009, \"minusTK\");\n this.getTokenHashTable().put(1010, \"multiplyTK\");\n this.getTokenHashTable().put(1011, \"divideTK\");\n this.getTokenHashTable().put(1012, \"modulusTK\");\n this.getTokenHashTable().put(1013, \"periodTK\");\n this.getTokenHashTable().put(1014, \"leftParenTK\");\n this.getTokenHashTable().put(1015, \"rightParenTK\");\n this.getTokenHashTable().put(1016, \"commaTK\");\n this.getTokenHashTable().put(1017, \"leftBraceTK\");\n this.getTokenHashTable().put(1018, \"rightBraceTK\");\n this.getTokenHashTable().put(1019, \"semicolonTK\");\n this.getTokenHashTable().put(1020, \"leftBracketTK\");\n this.getTokenHashTable().put(1021, \"rightBracketTK\");\n \n /* Extra Tokens */\n this.getTokenHashTable().put(1022, \"EofTK\");\n this.getTokenHashTable().put(-2, \"Invalid Character\");\n this.getTokenHashTable().put(-3, \"Invalid Comment\");\n }","String getShortToken();","String getShortToken();","String getShortToken();","String getShortToken();","String getShortToken();","String getShortToken();","String getShortToken();","String getShortToken();","String getShortToken();","String getShortToken();","@Override\n\tpublic String toString()\n\t{\n\t\treturn CommonNames.PARSER.CORE.TOKENS.TOKENIZER_STATE.WHITE_SPACE;\n\t}","private static void readWordsIntoMap(SimpleReader in,\n Map<String, Integer> wordMap, char[] seps) {\n String line = \"\";\n wordMap.clear();\n\n while (!in.atEOS()) {\n line = in.nextLine();\n for (char sep : seps) {\n line = line.replace(sep, ':');\n }\n\n String[] words = line.split(\":\");\n\n for (String word : words) {\n if (!wordMap.hasKey(word) && word != \" \") {\n wordMap.add(word, 1);\n } else {\n int count = wordMap.value(word);\n count++;\n wordMap.replaceValue(word, count);\n }\n }\n }\n\n }","private Map<String, String> interpretStyle(StringTokenizer st) {\n Map<String, String> map = new HashMap<String, String>();\n String name;\n String value;\n\n while (st.hasMoreElements()) {\n String namevaluepair = st.nextToken();\n int equalsPos = namevaluepair.indexOf('=');\n if (equalsPos < 0) {\n name = namevaluepair;\n value = \"true\";\n } else {\n name = namevaluepair.substring(0, equalsPos);\n value = namevaluepair.substring(equalsPos + 1);\n }\n\n map.put(name, value);\n }\n return map;\n }","public Map<String, List<List<String>>> otherTags() {\n return otherTags;\n }","private String getTokenizedUrl() {\n SharedPreferences sharedPreferences = getSharedPreferences();\n String tokenKey = MainActivity.sharedPrefKeys.TOKENIZED_URL.toString();\n\n if (sharedPreferences.contains(tokenKey)) {\n return sharedPreferences.getString(tokenKey, \"\");\n }\n return \"\";\n }","private String getUsersToString()\n {\n ArrayList<String> list = new ArrayList<>();\n Iterator iterator = userList.entrySet().iterator();\n while (iterator.hasNext())\n {\n Map.Entry mapEntry = (Map.Entry) iterator.next();\n list.add(\"\" + mapEntry.getKey());\n }\n \n String returnString = \"\";\n if(list.size() > 0)\n {\n returnString = list.get(0);\n for(int i = 1; i < list.size(); i++)\n {\n returnString = returnString + \",\" + list.get(i);\n }\n }\n return returnString;\n }","public String EventMapStringRepresentation(){\n ArrayList<String> lines = new ArrayList<String>();\n ArrayList<String> idsSorted = sort(eventIdsList);\n for(String id : idsSorted){\n String line = toStringEvent(id);\n lines.add(line);\n }\n String totalString = \"\";\n Integer i = 1;\n for(String line: lines){\n totalString += i + \") \" + line + System.lineSeparator();\n i++;\n }\n return totalString;\n }","List<Object> getTokens()\r\n\t{\r\n\t\treturn appearanceTokens;\r\n\t}","default Map<String, String> get() {\n Map<String, String> tags = new HashMap<>();\n tags.put(\"application\", serviceInfo().getServiceName());\n tags.put(\"host\", serviceInfo().getHost());\n tags.put(\"environment\", serviceInfo().getEnvironment());\n return tags;\n }","@Override\n\tpublic String toString() {\n\t\treturn \"{\" + Strings.join(\",\", keyValuePair) + \"}\";\n\t}","public void buildTokenIdentifierArrayList() {\n\t\t/**\n\t\t * Maintain the order while adding. Give it in a greedy way. The most specific to most common. Eg: DECIMAL Should \n\t\t * be added first then INTEGER else INTEGER will be matched first and '.' will be matched as a TOKEN and then\n\t\t * the succeeding number will be parsed as an INTEGER\n\t\t */\n\t\tlistTokenIdentifier.add(new TokenIdentifier(Pattern.compile(RegularExpression.DECIMAL), TokenType.DECIMAL_LITERAL));\n\t\tlistTokenIdentifier.add(new TokenIdentifier(Pattern.compile(RegularExpression.IDENTIFIER), TokenType.IDENTIFIER));\n\t\tlistTokenIdentifier.add(new TokenIdentifier(Pattern.compile(RegularExpression.INTEGER), TokenType.INTEGER_LITERAL));\n\t\tlistTokenIdentifier.add(new TokenIdentifier(Pattern.compile(RegularExpression.STRING), TokenType.STRING_LITERAL));\n\n\t\tfor (String t: new String[] {\"=\", \"\\\\(\",\"\\\\)\", \"\\\\.\",\"\\\\,\"}) {\n\t\t\tlistTokenIdentifier.add(new TokenIdentifier(Pattern.compile(\"^(\" + t + \")\"), TokenType.TOKEN));\t\n\t\t}\n\t}","@Override\n\tpublic String toString()\n\t{\n\t\tStringBuilder buffer = new StringBuilder(128);\n\t\tIterator<Map.Entry<String, AbstractNode>> it = pairs.entrySet().iterator();\n\t\twhile (it.hasNext())\n\t\t{\n\t\t\tMap.Entry<String, AbstractNode> pair = it.next();\n\t\t\tbuffer.append(keyToString(pair.getKey()));\n\t\t\tbuffer.append(KEY_VALUE_SEPARATOR_CHAR);\n\t\t\tbuffer.append(' ');\n\t\t\tbuffer.append(pair.getValue());\n\t\t\tif (it.hasNext())\n\t\t\t{\n\t\t\t\tbuffer.append(PAIR_SEPARATOR_CHAR);\n\t\t\t\tbuffer.append(' ');\n\t\t\t}\n\t\t}\n\t\treturn buffer.toString();\n\t}","public String toString() {\n\tStringBuffer buf = new StringBuffer();\n\tfor (int i = 0; i < tokens.length; i++) {\n\t\tif (i > 0) {\n\t\t\tbuf.append(\" \");\n\t\t}\t\n\t\tbuf.append(tokens[i]);\n\t}\n\treturn buf.toString();\n}","private String string(Token t) {\n\n return expansionString.substring(t.start, t.end);\n\n }","public static Map<String, String> listTokenFromCSP()\r\n\t\t\tthrows BkavSignaturesException {\r\n\t\tMap<String, String> result = new HashMap<>();\r\n\t\ttry {\r\n\t\t\tSunMSCAPI providerMSCAPI = new SunMSCAPI();\r\n\t\t\tSecurity.addProvider(providerMSCAPI);\r\n\t\t\tKeyStore ks = KeyStore.getInstance(CSP_KEYSTORE);\r\n\t\t\tks.load(null, null);\r\n\r\n\t\t\tEnumeration<String> aliases = ks.aliases();\r\n\t\t\tString alias = null;\r\n\r\n\t\t\twhile (aliases.hasMoreElements()) {\r\n\t\t\t\talias = aliases.nextElement();\r\n\t\t\t\tCertificate cert = ks.getCertificate(alias);\r\n\t\t\t\tif (cert instanceof X509Certificate) {\r\n\t\t\t\t\tX509Certificate x509Cert = (X509Certificate) cert;\r\n\t\t\t\t\tString certSerial = x509Cert.getSerialNumber().toString(16);\r\n\r\n\t\t\t\t\tString subjectDN = x509Cert.getSubjectDN().getName();\r\n\t\t\t\t\tString author = \"\";\r\n\t\t\t\t\tLdapName ldap;\r\n\t\t\t\t\ttry {\r\n\t\t\t\t\t\tldap = new LdapName(subjectDN);\r\n\t\t\t\t\t\tfor (Rdn rdn : ldap.getRdns()) {\r\n\t\t\t\t\t\t\tif (\"CN\".equalsIgnoreCase(rdn.getType())) {\r\n\t\t\t\t\t\t\t\tauthor = rdn.getValue().toString();\r\n\t\t\t\t\t\t\t\tbreak;\r\n\t\t\t\t\t\t\t}\r\n\t\t\t\t\t\t}\r\n\t\t\t\t\t} catch (InvalidNameException e) {\r\n\t\t\t\t\t}\r\n\r\n\t\t\t\t\tresult.put(certSerial, author);\r\n\t\t\t\t}\r\n\t\t\t}\r\n\t\t} catch (KeyStoreException e) {\r\n\t\t\tthrow new BkavSignaturesException(\"KeyStoreException\", e);\r\n\t\t} catch (NoSuchAlgorithmException e) {\r\n\t\t\tthrow new BkavSignaturesException(\"NoSuchAlgorithmException\", e);\r\n\t\t} catch (CertificateException e) {\r\n\t\t\tthrow new BkavSignaturesException(\"CertificateException\", e);\r\n\t\t} catch (IOException e) {\r\n\t\t\tthrow new BkavSignaturesException(\"IOException\", e);\r\n\t\t}\r\n\r\n\t\treturn result;\r\n\t}","@Override\n public String toString() {\n return gateAdr + \", \" + postNr + \" \" + postSted;\n }","String getBShortToken();","public Map<CharSequence, CharSequence> getReplacableNames();","private String createCustomInfoString() {\r\n String CustomInfo = \"\";\r\n Iterator<String> iterator = mCustomParameters.keySet().iterator();\r\n while (iterator.hasNext()) {\r\n String CurrentKey = iterator.next();\r\n String CurrentVal = mCustomParameters.get(CurrentKey);\r\n CustomInfo += CurrentKey + \" = \" + CurrentVal + \"\\n\";\r\n }\r\n return CustomInfo;\r\n }","public void display() {\n\tString tm = \"{ \";\n\tIterator it = entrySet().iterator();\n\twhile(it.hasNext()) {\n\t\ttm += it.next() + \" ,\";\n\t}\n\ttm = tm.substring(0, tm.length() - 2) + \" }\";\n\tSystem.out.println(tm);\n }","@Override\n\tpublic String toString()\n\t{\n\t\tStringBuilder s = new StringBuilder();\n\t\tjava.util.Iterator<java.util.Map.Entry<String, Object>> iterator = entrySet().iterator();\n\t\twhile (iterator.hasNext()) {\n\t\t\tjava.util.Map.Entry<String, Object> entry = iterator.next();\n\n\t\t\ts.append('\\n');\n\t\t\ts.append(\"\\t\");\n\t\t\ts.append(entry.getKey());\n\t\t\ts.append(':');\n\t\t\ts.append(' ');\n\t\t\ts.append(entry.getValue().toString());\n\t\t}\n\t\treturn s.toString();\n\t}","public static String[] gatherTokenStrings (Document doc, Span span) {\n\t\tAnnotation[] tokens = gatherTokens(doc, span);\n\t\tint length = tokens.length;\n\t\tString[] stgs = new String[length];\n\t\tfor (int i=0; i<length; i++)\n\t\t\tstgs[i] = doc.text(tokens[i]).trim();\n\t\treturn stgs;\n\t}","@Override\r\n public String encodeAll(List<LinkedHashMap<String, String>> dataList) {\n StringBuilder str = new StringBuilder();\r\n\r\n for (LinkedHashMap<String, String> dataMap : dataList) {\r\n Collection<String> value = dataMap.values();\r\n\r\n for (Iterator<String> itr = value.iterator(); itr.hasNext();) {\r\n str = str.append(\"\\\"\").append(itr.next()).append(\"\\\"\").append(\",\");\r\n\r\n }\r\n str = str.deleteCharAt(str.length() - 1);\r\n str = str.append(\"\\n\");\r\n }\r\n\r\n return str.toString();\r\n\r\n }","void Create(){\n map = new TreeMap<>();\r\n\r\n // Now we split the words up using punction and spaces\r\n String wordArray[] = wordSource.split(\"[{ \\n\\r.,]}}?\");\r\n\r\n // Now we loop through the array\r\n for (String wordArray1 : wordArray) {\r\n String key = wordArray1.toLowerCase();\r\n // If this word is not present in the map then add it\r\n // and set the word count to 1\r\n if (key.length() > 0){\r\n if (!map.containsKey(map)){\r\n map.put(key, 1);\r\n }\r\n else {\r\n int wordCount = map.get(key);\r\n wordCount++;\r\n map.put(key, wordCount);\r\n }\r\n }\r\n } // end of for loop\r\n \r\n // Get all entries into a set\r\n // I think that before this we just have key-value pairs\r\n entrySet = map.entrySet();\r\n \r\n }","@Override\n\tpublic Map<String, Integer> parseWordCountMap(String text, List<String> delimeter) {\n\t\treturn new HashMap<>();\n\t}","@Override\n\tpublic String toString() {\n\t\tStringBuffer buf = new StringBuffer(\"Dictionary contents:\\n\");\n\t\tfor (Iterator iter = entrySet().iterator(); iter.hasNext();) {\n\t\t\tMap.Entry entry = (Map.Entry) iter.next();\n\t\t\tbuf.append(\" \").append(entry.getKey()).append(\" = \").append(\n\t\t\t\t\tentry.getValue()).append(\"\\n\");\n\t\t}\n\t\treturn buf.toString();\n\t}","private HashMap<String,HashMap<String,Integer>> computeTFForQueryWords(ArrayList<String> queryPostingLines) {\n HashMap<String,HashMap<String,Integer>> queryWordsTF = new HashMap<>();\n HashMap<String,HashMap<String,Integer>> queryWordsTFPerDoc = new HashMap<>();\n String docID,term;\n Integer tf;\n HashSet<String> docIDs = new HashSet<>();\n for(String postingLine : queryPostingLines){\n HashMap<String,Integer> frequenciesInDocuments = new HashMap<>();\n term = postingLine.substring(0,postingLine.indexOf(\"|\"));\n postingLine = postingLine.substring(postingLine.indexOf(\"|\")+1);\n while(!postingLine.equals(\"\")) {\n docID = postingLine.substring(0, postingLine.indexOf(\":\"));\n docIDs.add(docID);\n postingLine = postingLine.substring(postingLine.indexOf(\"_\") + 1);\n tf = Integer.valueOf(postingLine.substring(0, postingLine.indexOf(\"_\")));\n postingLine = postingLine.substring(postingLine.indexOf(\"_\") + 1);\n frequenciesInDocuments.put(docID,tf);\n }\n queryWordsTF.put(term,frequenciesInDocuments);\n }\n\n ArrayList<String> allTermsInQuery = new ArrayList<>(queryWordsTF.keySet());\n for(String doc : docIDs){\n HashMap<String,Integer> tfsInDoc = new HashMap<>();\n for(String termInQuery : allTermsInQuery){\n HashMap<String,Integer> termsTFInDoc = queryWordsTF.get(termInQuery);\n if(termsTFInDoc.containsKey(doc)){\n tfsInDoc.put(termInQuery,termsTFInDoc.get(doc));\n }\n }\n queryWordsTFPerDoc.put(doc,tfsInDoc);\n }\n return queryWordsTFPerDoc;\n }","private void initRegs(){\n\n keyWordReg = \"\";\n\n for (String seg: keyWordMap.keySet()){\n\n keyWordReg += seg + \"|\";\n\n }\n\n symbolReg = \"[\\\\&\\\\*\\\\+\\\\(\\\\)\\\\.\\\\/\\\\,\\\\-\\\\]\\\\;\\\\~\\\\}\\\\|\\\\{\\\\>\\\\=\\\\[\\\\<]\";\n intReg = \"[0-9]+\";\n strReg = \"\\\"[^\\\"\\n]*\\\"\";\n idReg = \"[a-zA-Z_]\\\\w*\";\n\n tokenPatterns = Pattern.compile(idReg + \"|\" + keyWordReg + symbolReg + \"|\" + intReg + \"|\" + strReg);\n }","private static String[] getMapStrings(boolean desc) {\n\n\n\n ArrayList list = new ArrayList();\n Locale locale = Locale.getDefault();\n String name = locale.toString();\n if (desc)\n name = \"locale=\" + name;\n list.add(0, name);\n\n String os = \"-\" + getOSType();\n if (desc)\n os = \" (os=\" + System.getProperty(\"os.name\")\n + \", \" + System.getProperty(\"os.version\") + \")\";\n name += os;\n list.add(0, name);\n\n // Allow the invoker to override the keyStrokeMap to support\n // case where you are working on a remote machine with a different\n // local or platform.\n \n String override = System.getProperty(\"abbot.keyStrokeMap\");\n if (override!=null) {\n list.add(0, override);\n }\n \n \n /*\n String vm = System.getProperty(\"java.version\");\n name += \" vm=\" + vm;\n list.add(0, name);\n String version = System.getProperty(\"os.version\");\n name += \" version=\" + version;\n list.add(0, name);\n String arch = System.getProperty(\"os.arch\");\n name += \" arch=\" + arch;\n list.add(0, name);\n */\n return (String[])list.toArray(new String[list.size()]);\n }","public String getPostingText() {\n return postingText;\n }","@Override\n\tpublic Map<String, Object> getGradeMyStu(String token) {\n\t\treturn null;\n\t}","public void printMap() {\n String s = \"\";\n Stack st = new Stack();\n st.addAll(map.entrySet());\n while (!st.isEmpty()) {\n s += st.pop().toString() + \"\\n\";\n }\n window.getDHTText().setText(s);\n }","public String toString()\n {\n String ret = \"\";\n String s = adjMaps.toString();\n String[] parts = s.split(\"},\");\n for(int i=0; i< parts.length; i++){\n ret += parts[i] + \"}\\n\";\n }\n return ret;\n }"],"string":"[\n \"Map<String, String> getTokens();\",\n \"@Override\\r\\n public String toString() {\\r\\n String s = new String();\\r\\n for (String t : tokenList)\\r\\n s = s + \\\"~\\\" + t;\\r\\n return s;\\r\\n }\",\n \"@Override\\n public String toString() {\\n StringJoiner sj = new StringJoiner(\\\", \\\", \\\"{\\\", \\\"}\\\\n\\\");\\n wordMap.forEach((k, v) -> sj.add(String.format(\\\"%s -> %s\\\", k, v)));\\n return sj.toString();\\n }\",\n \"public static HashMap<String, String> simplifiedTags(List<List<TaggedWord>> taggedList) {\\n HashMap<String, String> simplePOSTagged = new HashMap<>();\\n for (List<TaggedWord> tags : taggedList) { // iterate over list\\n for (TaggedWord taggedWord : tags) {//for each word in the sentence\\n String word = taggedWord.toString().replaceFirst(\\\"/\\\\\\\\w+\\\", \\\"\\\");\\n if (taggedWord.tag().equals(\\\"NN\\\") | taggedWord.tag().equals(\\\"NNS\\\") |\\n taggedWord.tag().equals(\\\"NNP\\\") | taggedWord.tag().equals(\\\"NNPS\\\")) {\\n simplePOSTagged.put(word, \\\"noun\\\");\\n } else if (taggedWord.tag().equals(\\\"MD\\\") | taggedWord.tag().equals(\\\"VB\\\") |\\n taggedWord.tag().equals(\\\"VBD\\\") | taggedWord.tag().equals(\\\"VBG\\\") |\\n taggedWord.tag().equals(\\\"VBN\\\") | taggedWord.tag().equals(\\\"VBP\\\")\\n | taggedWord.tag().equals(\\\"VBZ\\\")) {\\n simplePOSTagged.put(word, \\\"verb\\\");\\n } else if (taggedWord.tag().equals(\\\"JJ\\\") | taggedWord.tag().equals(\\\"JJR\\\") |\\n taggedWord.tag().equals(\\\"JJS\\\")) {\\n simplePOSTagged.put(word, \\\"adj\\\");\\n } else if (taggedWord.tag().equals(\\\"PRP\\\") | taggedWord.tag().equals(\\\"PRP$\\\")) {\\n simplePOSTagged.put(word, \\\"pron\\\");\\n } else if (taggedWord.tag().equals(\\\"RB\\\") | taggedWord.tag().equals(\\\"RBR\\\") |\\n taggedWord.tag().equals(\\\"RBS\\\")) {\\n simplePOSTagged.put(word, \\\"adv\\\");\\n } else if (taggedWord.tag().equals(\\\"CD\\\") | taggedWord.tag().equals(\\\"LS\\\")) {\\n simplePOSTagged.put(word, \\\"num\\\");\\n } else if (taggedWord.tag().equals(\\\"WDT\\\") | taggedWord.tag().equals(\\\"WP\\\") |\\n taggedWord.tag().equals(\\\"WP$\\\") | taggedWord.tag().equals(\\\"WRB\\\")) {\\n simplePOSTagged.put(word, \\\"wh\\\");\\n } else if (taggedWord.tag().equals(\\\"DT\\\") | taggedWord.tag().equals(\\\"PDT\\\")) {\\n simplePOSTagged.put(word, \\\"det\\\");\\n } else if (taggedWord.tag().equals(\\\"CC\\\") | taggedWord.tag().equals(\\\"IN\\\")) {\\n simplePOSTagged.put(word, \\\"prepconj\\\");\\n } else {\\n simplePOSTagged.put(word, \\\"other\\\");\\n }\\n }\\n }\\n return simplePOSTagged;\\n }\",\n \"List<String> getTokens();\",\n \"public Map<String, String> getTokens() {\\n return tokens;\\n }\",\n \"@Override\\n public String toString() {\\n return token.toString();\\n }\",\n \"private static Map<String, Integer> getWords(){\\n\\t\\tMap<String, Integer> map = new HashMap<String, Integer>();\\n\\t\\t\\n\\t\\tfor(Status status : statusList){\\n\\t\\t\\tStringTokenizer tokens = new StringTokenizer(status.getText());\\n\\t\\t\\twhile(tokens.hasMoreTokens()){\\n\\t\\t\\t\\tString token = tokens.nextToken();\\n\\t\\t\\t\\tif(!token.equals(\\\"RT\\\")){\\n\\t\\t\\t\\t\\tif(map.containsKey(token)){\\n\\t\\t\\t\\t\\t\\tint count = map.get(token);\\n\\t\\t\\t\\t\\t\\tmap.put(token, ++count);\\n\\t\\t\\t\\t\\t}else{\\n\\t\\t\\t\\t\\t\\tmap.put(token, 1);\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t}\\t\\t\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\t\\n\\t\\treturn map;\\n\\t}\",\n \"@Override\\n\\t\\tprotected void map(Object key, Text value, Context context)\\n\\t\\t\\t\\tthrows IOException, InterruptedException {\\n\\t\\t\\tStringTokenizer str=new StringTokenizer(value.toString());\\n//\\t\\t\\tString[]str=new String(value.toString()).split(\\\"a\\\");\\n\\t\\t\\twhile(str.hasMoreTokens()){\\n\\t\\t\\t\\tword.set(str.nextToken());\\n\\t\\t\\t\\tcontext.write(word, one);\\n\\t\\t\\t\\t}\\n//\\t\\t\\tfor(String b:str){\\n//\\t\\t\\t\\tword.set(b);\\n//\\t\\t\\t\\tcontext.write(word, one);\\n//\\t\\t\\t\\t\\n//\\t\\t\\t}\\n\\t\\t\\t\\n\\t\\t}\",\n \"String getTokenString();\",\n \"public void buildMap()\\n {\\n for(int letterNum=0; letterNum < myText.length()-myNum; letterNum++) {\\n String key = myText.substring(letterNum,letterNum+myNum);\\n String nextLetter = String.valueOf(myText.charAt(letterNum + myNum));\\n if (!map.containsKey(key)) {\\n ArrayList<String> lettersArray = new ArrayList<String>();\\n lettersArray.add(nextLetter);\\n map.put(key,lettersArray);\\n }else\\n {\\n map.get(key).add(nextLetter);\\n }\\n }\\n }\",\n \"public MapToken() {\\n\\t\\tmData = new FastMap<String, Object>();\\n\\t}\",\n \"private List<String> getSubstitutes(String postScriptName) {\\n/* 218 */ List<String> subs = this.substitutes.get(postScriptName.replaceAll(\\\" \\\", \\\"\\\"));\\n/* 219 */ if (subs != null)\\n/* */ {\\n/* 221 */ return subs;\\n/* */ }\\n/* */ \\n/* */ \\n/* 225 */ return Collections.emptyList();\\n/* */ }\",\n \"@Override\\n\\tpublic String toString()\\n\\t{\\n\\t\\tfinal AppendingStringBuffer buffer = new AppendingStringBuffer();\\n\\t\\tboolean first = true;\\n\\t\\tfor (Map.Entry<String, Object> entry : entrySet())\\n\\t\\t{\\n\\t\\t\\tif (first == false)\\n\\t\\t\\t{\\n\\t\\t\\t\\tbuffer.append(' ');\\n\\t\\t\\t}\\n\\t\\t\\tfirst = false;\\n\\n\\t\\t\\tbuffer.append(entry.getKey());\\n\\t\\t\\tbuffer.append(\\\" = \\\\\\\"\\\");\\n\\t\\t\\tfinal Object value = entry.getValue();\\n\\t\\t\\tif (value == null)\\n\\t\\t\\t{\\n\\t\\t\\t\\tbuffer.append(\\\"null\\\");\\n\\t\\t\\t}\\n\\t\\t\\telse if (value.getClass().isArray())\\n\\t\\t\\t{\\n\\t\\t\\t\\tbuffer.append(Arrays.asList((Object[])value));\\n\\t\\t\\t}\\n\\t\\t\\telse\\n\\t\\t\\t{\\n\\t\\t\\t\\tbuffer.append(value);\\n\\t\\t\\t}\\n\\n\\t\\t\\tbuffer.append('\\\\\\\"');\\n\\t\\t}\\n\\t\\treturn buffer.toString();\\n\\t}\",\n \"public String toString() {\\r\\n\\t\\tStringBuffer sb = new StringBuffer();\\r\\n\\t\\tsb.append(\\\"Tokens:\\\\n\\\");\\r\\n\\t\\tfor (int i = 0; i < tokens.size(); i++) {\\r\\n\\t\\t\\tsb.append(tokens.get(i)).append('\\\\n');\\r\\n\\t\\t}\\r\\n\\t\\treturn sb.toString();\\r\\n\\t}\",\n \"private Map<String, String> locationListToString(List<Element> locations) {\\r\\n Map<String, String> locMap = new LinkedHashMap<String, String>();\\r\\n for (Element location : locations) {\\r\\n String fileName = location.attributeValue(\\\"filename\\\");\\r\\n String lineNumber = location.attributeValue(\\\"line\\\");\\r\\n String current = locMap.get(fileName);\\r\\n locMap.put(fileName, null == current ? lineNumber : current + \\\", \\\" + lineNumber);\\r\\n }\\r\\n return locMap;\\r\\n }\",\n \"public PostingsList getPostings( String token ) {\\n PostingsList post = new PostingsList();\\n if(this.index.containsKey(token))\\n post = (this.index.get(token)).clone();\\n /*System.err.println(\\\"start search...\\\");\\n // Read JSON file associated to token and return it as a postingslist\\n String filename = \\\"postings/t\\\"+hash(token)+\\\".json\\\";\\n PostingsList post = new PostingsList();\\n try(Reader reader = new FileReader(filename)){\\n post = (new Gson()).fromJson(reader, PostingsList.class);\\n } catch (IOException e) {\\n e.printStackTrace();\\n }*/\\n return post;\\n }\",\n \"public String getTokenString() {\\n String tokenString = \\\"\\\";\\n\\n for (int i = 0; i < clueTokens.size(); i++) {\\n tokenString += clueTokens.get(i).getName();\\n if (i < clueTokens.size() - 1)\\n tokenString += \\\", \\\";\\n }\\n\\n return tokenString;\\n }\",\n \"Map<String, String> tags();\",\n \"Map<String, String> tags();\",\n \"Map<String, String> tags();\",\n \"Map<String, String> tags();\",\n \"Map<String, String> tags();\",\n \"Map<String, String> tags();\",\n \"Map<String, String> tags();\",\n \"Map<String, String> tags();\",\n \"public Map<String, List<String>> genericsTokens() {\\n return genericsTokens;\\n }\",\n \"public PostingsList getPostings( String token ) {\\r\\n PostingsList element = index.get(token) ;\\r\\n if (element != null)\\r\\n {\\r\\n return element;\\r\\n }\\r\\n return null;\\r\\n }\",\n \"String getToken();\",\n \"String getToken();\",\n \"String getToken();\",\n \"String getToken();\",\n \"String getToken();\",\n \"protected String getTokenString (int token) {\\r\\n switch (token) {\\r\\n case START:\\r\\n return \\\"START\\\";\\r\\n case STRING:\\r\\n return \\\"STRING\\\";\\r\\n case SQSTRING:\\r\\n return \\\"SQSTRING\\\";\\r\\n case DQSTRING:\\r\\n return \\\"DQSTRING\\\";\\r\\n case SINGELQUOTE:\\r\\n return \\\"SINGELQUOTE\\\";\\r\\n case DOUBLEQUOTE:\\r\\n return \\\"DOUBLEQUOTE\\\";\\r\\n case LT:\\r\\n return \\\"LT\\\";\\r\\n case MT:\\r\\n return \\\"MT\\\";\\r\\n case EQUALS:\\r\\n return \\\"EQUALS\\\";\\r\\n case COMMENT:\\r\\n return \\\"COMMENT\\\";\\r\\n case END:\\r\\n return \\\"END\\\";\\r\\n case UNKNOWN:\\r\\n return \\\"UNKNOWN\\\";\\r\\n default:\\r\\n return \\\"unknown\\\";\\r\\n }\\r\\n }\",\n \"private static Map<String, String> parseInstanceValues(String data) {\\r\\n \\t\\tMap<String, String> responseMap = new HashMap<String, String>();\\r\\n \\t\\tif (data != null) {\\r\\n \\t\\t\\tStringTokenizer strTok = new StringTokenizer(data, \\\",\\\\n\\\");\\r\\n \\t\\t\\twhile (strTok.hasMoreTokens()) {\\r\\n \\t\\t\\t\\tString key = strTok.nextToken();\\r\\n \\t\\t\\t\\tString val = strTok.nextToken();\\r\\n \\t\\t\\t\\tString oldVal = responseMap.get(key);\\r\\n \\t\\t\\t\\tif (oldVal != null) {\\r\\n \\t\\t\\t\\t\\tif (val != null) {\\r\\n \\t\\t\\t\\t\\t\\tif (oldVal.trim().length() < val.trim().length()) {\\r\\n \\t\\t\\t\\t\\t\\t\\tresponseMap.put(key, val);\\r\\n \\t\\t\\t\\t\\t\\t}\\r\\n \\t\\t\\t\\t\\t}\\r\\n \\t\\t\\t\\t} else {\\r\\n \\t\\t\\t\\t\\tresponseMap.put(key, val);\\r\\n \\t\\t\\t\\t}\\r\\n \\t\\t\\t}\\r\\n \\t\\t}\\r\\n \\t\\treturn responseMap;\\r\\n \\t}\",\n \"private static String listOfTokensToString(List<Token> tokenList) {\\n\\n StringBuilder stringBuilder = new StringBuilder();\\n for (Token token : tokenList) {\\n stringBuilder.append(String.format(\\\"%s\\\", token.getPattern()));\\n }\\n return stringBuilder.toString().trim();\\n }\",\n \"java.lang.String getToken();\",\n \"java.lang.String getToken();\",\n \"java.lang.String getToken();\",\n \"java.lang.String getToken();\",\n \"java.lang.String getToken();\",\n \"java.lang.String getToken();\",\n \"public static String string() {\\n\\t\\t\\tString s = \\\"\\\";\\n\\t\\t\\ts += \\\"Locaux :\\\\n\\\";\\n\\t\\t\\tfor(String key : locaux.keySet()) {\\n\\t\\t\\t\\tIdent i = locaux.get(key);\\n\\t\\t\\t\\ts += key+\\\", \\\"+i.toString()+\\\"\\\\n\\\";\\n\\t\\t\\t}\\n\\t\\t\\ts += \\\"Globaux :\\\\n\\\";\\n\\t\\t\\tfor(String key : globaux.keySet()) {\\n\\t\\t\\t\\tIdent i = globaux.get(key);\\n\\t\\t\\t\\ts += key+\\\", \\\"+i.toString()+\\\"\\\\n\\\";\\n\\t\\t\\t}\\n\\n\\t\\t\\treturn s;\\n\\t\\t}\",\n \"@Override\\n public String mapping() {\\n return StringUtils.lines(\\n \\\"foo.bar.Baz -> foo.bar.Baz:\\\", \\\" java.lang.Object f1 -> a\\\", \\\" java.lang.String f2 -> a\\\");\\n }\",\n \"@Override\\n\\tpublic String toString() {\\n\\t\\tStringBuilder buf = new StringBuilder();\\n\\t\\t\\n\\t\\tCIntMap termsFrequencies = null;\\n\\t\\tfor( String tag : keySet()) {\\n\\t\\t\\tbuf.append(tag);\\n\\t\\t\\tbuf.append(\\\"\\\\n\\\");\\n\\t\\t\\ttermsFrequencies = get(tag);\\n\\t\\t\\tbuf.append(termsFrequencies);\\n\\t\\t}\\n\\t\\t\\n\\t\\treturn buf.toString();\\n\\t}\",\n \"@Override\\n public String toString() {\\n if (this.map.getMap().isEmpty()) return \\\"\\\";\\n final StringBuilder param = new StringBuilder(this.map.getMap().size() * 40);\\n for (final Map.Entry<String, String> entry: entrySet()) {\\n param.append(MultiProtocolURL.escape(entry.getKey()))\\n .append('=')\\n .append(MultiProtocolURL.escape(entry.getValue()))\\n .append('&');\\n }\\n param.setLength(param.length() - 1);\\n return param.toString();\\n }\",\n \"private static Map<String, Integer> getHashTags(){\\n\\t\\t\\n\\t\\tMap<String, Integer> map = new HashMap<String, Integer>();\\n\\t\\t\\n\\t\\tfor(Status status : statusList){\\n\\t\\t\\tHashtagEntity[] entitles = status.getHashtagEntities();\\n\\t\\t\\tfor(HashtagEntity entity : entitles){\\n\\t\\t\\t\\tString str = entity.getText();\\n\\t\\t\\t\\t\\n\\t\\t\\t\\tif(map.containsKey(str)){\\n\\t\\t\\t\\t\\tint count = map.get(str);\\n\\t\\t\\t\\t\\tmap.put(str, ++count);\\n\\t\\t\\t\\t}else{\\n\\t\\t\\t\\t\\tmap.put(str, 1);\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\treturn map;\\n\\t}\",\n \"@Override\\r\\n\\tpublic Map<Integer, String> getMakingMtList() {\\n\\t\\treturn null;\\r\\n\\t}\",\n \"Iterator<String> getTokenIterator();\",\n \"@Override public String toString(){\\r\\n StringBuilder output = new StringBuilder();\\r\\n for (Iterator<NoteToken> i = NotesList.iterator(); i.hasNext();){\\r\\n output.append(i.next().toString());\\r\\n output.append(\\\" \\\");\\r\\n \\r\\n }\\r\\n return output.toString();\\r\\n }\",\n \"public Map<String, Set<String>> getSubStringAlias(Set<String> enSet){\\n EntityUtils alias = new EntityUtils();\\n Map<String, Set<String>> mentions_map = alias.getAliasMapFromSet(enSet);\\n return mentions_map;\\n\\n }\",\n \"public String toString (Token T);\",\n \"private Map<String, String> processPostRequest(String content) {\\n Map<String, String> store = new HashMap<String, String>();\\n\\n // Split the post data by &\\n for (String entry : content.split(\\\"&\\\")) {\\n // Split it by =\\n String[] data = entry.split(\\\"=\\\");\\n\\n // Check that there is sufficient data in the data array\\n if (data.length != 2) {\\n continue;\\n }\\n\\n // decode the data\\n String key = URLUtils.decode(data[0]);\\n String value = URLUtils.decode(data[1]);\\n\\n // Add it to the store\\n store.put(key, value);\\n }\\n\\n return store;\\n }\",\n \"public String valuesFromMap() {\\n\\t\\thashMap = createSimpleMap(\\\"Breakfast\\\", \\\"Eggs\\\");\\n\\t\\treturn hashMap.get(\\\"Breakfast\\\");\\n\\t}\",\n \"public String toString() {\\n return PARSER_KEY;\\n }\",\n \"private String toString(String pre) {\\n StringBuilder sb = new StringBuilder();\\n\\n sb.append(key);\\n if (values1 != null) {\\n sb.append(\\\" \\\");\\n sb.append(values1);\\n sb.append(\\\", \\\");\\n sb.append(values2);\\n }\\n sb.append(\\\"\\\\n\\\");\\n\\n String newpre = pre + \\\" \\\";\\n if (!son.empty) {\\n sb.append(newpre);\\n sb.append(\\\"son: \\\");\\n sb.append(son.toString(newpre));\\n }\\n if (!left.empty) {\\n sb.append(newpre);\\n sb.append(\\\"left: \\\");\\n sb.append(left.toString(newpre));\\n }\\n if (!right.empty) {\\n sb.append(newpre);\\n sb.append(\\\"right: \\\");\\n sb.append(right.toString(newpre));\\n }\\n return sb.toString();\\n }\",\n \"private void setupTokenHashTable() {\\n this.tokenHashTable = new Hashtable<>();\\n \\t\\n /* Identifier Token */\\n this.getTokenHashTable().put(1001, \\\"idTK\\\");\\n this.getTokenHashTable().put(1002, \\\"integerTK\\\");\\n \\t\\n /* Operators and Delimiters */\\n this.getTokenHashTable().put(1003, \\\"equalsTK\\\");\\n this.getTokenHashTable().put(1004, \\\"lessThanTK\\\");\\n this.getTokenHashTable().put(1005, \\\"greaterThanTK\\\");\\n this.getTokenHashTable().put(1006, \\\"compareEqualTK\\\");\\n this.getTokenHashTable().put(1007, \\\"colonTK\\\");\\n this.getTokenHashTable().put(1008, \\\"plusTK\\\");\\n this.getTokenHashTable().put(1009, \\\"minusTK\\\");\\n this.getTokenHashTable().put(1010, \\\"multiplyTK\\\");\\n this.getTokenHashTable().put(1011, \\\"divideTK\\\");\\n this.getTokenHashTable().put(1012, \\\"modulusTK\\\");\\n this.getTokenHashTable().put(1013, \\\"periodTK\\\");\\n this.getTokenHashTable().put(1014, \\\"leftParenTK\\\");\\n this.getTokenHashTable().put(1015, \\\"rightParenTK\\\");\\n this.getTokenHashTable().put(1016, \\\"commaTK\\\");\\n this.getTokenHashTable().put(1017, \\\"leftBraceTK\\\");\\n this.getTokenHashTable().put(1018, \\\"rightBraceTK\\\");\\n this.getTokenHashTable().put(1019, \\\"semicolonTK\\\");\\n this.getTokenHashTable().put(1020, \\\"leftBracketTK\\\");\\n this.getTokenHashTable().put(1021, \\\"rightBracketTK\\\");\\n \\n /* Extra Tokens */\\n this.getTokenHashTable().put(1022, \\\"EofTK\\\");\\n this.getTokenHashTable().put(-2, \\\"Invalid Character\\\");\\n this.getTokenHashTable().put(-3, \\\"Invalid Comment\\\");\\n }\",\n \"String getShortToken();\",\n \"String getShortToken();\",\n \"String getShortToken();\",\n \"String getShortToken();\",\n \"String getShortToken();\",\n \"String getShortToken();\",\n \"String getShortToken();\",\n \"String getShortToken();\",\n \"String getShortToken();\",\n \"String getShortToken();\",\n \"@Override\\n\\tpublic String toString()\\n\\t{\\n\\t\\treturn CommonNames.PARSER.CORE.TOKENS.TOKENIZER_STATE.WHITE_SPACE;\\n\\t}\",\n \"private static void readWordsIntoMap(SimpleReader in,\\n Map<String, Integer> wordMap, char[] seps) {\\n String line = \\\"\\\";\\n wordMap.clear();\\n\\n while (!in.atEOS()) {\\n line = in.nextLine();\\n for (char sep : seps) {\\n line = line.replace(sep, ':');\\n }\\n\\n String[] words = line.split(\\\":\\\");\\n\\n for (String word : words) {\\n if (!wordMap.hasKey(word) && word != \\\" \\\") {\\n wordMap.add(word, 1);\\n } else {\\n int count = wordMap.value(word);\\n count++;\\n wordMap.replaceValue(word, count);\\n }\\n }\\n }\\n\\n }\",\n \"private Map<String, String> interpretStyle(StringTokenizer st) {\\n Map<String, String> map = new HashMap<String, String>();\\n String name;\\n String value;\\n\\n while (st.hasMoreElements()) {\\n String namevaluepair = st.nextToken();\\n int equalsPos = namevaluepair.indexOf('=');\\n if (equalsPos < 0) {\\n name = namevaluepair;\\n value = \\\"true\\\";\\n } else {\\n name = namevaluepair.substring(0, equalsPos);\\n value = namevaluepair.substring(equalsPos + 1);\\n }\\n\\n map.put(name, value);\\n }\\n return map;\\n }\",\n \"public Map<String, List<List<String>>> otherTags() {\\n return otherTags;\\n }\",\n \"private String getTokenizedUrl() {\\n SharedPreferences sharedPreferences = getSharedPreferences();\\n String tokenKey = MainActivity.sharedPrefKeys.TOKENIZED_URL.toString();\\n\\n if (sharedPreferences.contains(tokenKey)) {\\n return sharedPreferences.getString(tokenKey, \\\"\\\");\\n }\\n return \\\"\\\";\\n }\",\n \"private String getUsersToString()\\n {\\n ArrayList<String> list = new ArrayList<>();\\n Iterator iterator = userList.entrySet().iterator();\\n while (iterator.hasNext())\\n {\\n Map.Entry mapEntry = (Map.Entry) iterator.next();\\n list.add(\\\"\\\" + mapEntry.getKey());\\n }\\n \\n String returnString = \\\"\\\";\\n if(list.size() > 0)\\n {\\n returnString = list.get(0);\\n for(int i = 1; i < list.size(); i++)\\n {\\n returnString = returnString + \\\",\\\" + list.get(i);\\n }\\n }\\n return returnString;\\n }\",\n \"public String EventMapStringRepresentation(){\\n ArrayList<String> lines = new ArrayList<String>();\\n ArrayList<String> idsSorted = sort(eventIdsList);\\n for(String id : idsSorted){\\n String line = toStringEvent(id);\\n lines.add(line);\\n }\\n String totalString = \\\"\\\";\\n Integer i = 1;\\n for(String line: lines){\\n totalString += i + \\\") \\\" + line + System.lineSeparator();\\n i++;\\n }\\n return totalString;\\n }\",\n \"List<Object> getTokens()\\r\\n\\t{\\r\\n\\t\\treturn appearanceTokens;\\r\\n\\t}\",\n \"default Map<String, String> get() {\\n Map<String, String> tags = new HashMap<>();\\n tags.put(\\\"application\\\", serviceInfo().getServiceName());\\n tags.put(\\\"host\\\", serviceInfo().getHost());\\n tags.put(\\\"environment\\\", serviceInfo().getEnvironment());\\n return tags;\\n }\",\n \"@Override\\n\\tpublic String toString() {\\n\\t\\treturn \\\"{\\\" + Strings.join(\\\",\\\", keyValuePair) + \\\"}\\\";\\n\\t}\",\n \"public void buildTokenIdentifierArrayList() {\\n\\t\\t/**\\n\\t\\t * Maintain the order while adding. Give it in a greedy way. The most specific to most common. Eg: DECIMAL Should \\n\\t\\t * be added first then INTEGER else INTEGER will be matched first and '.' will be matched as a TOKEN and then\\n\\t\\t * the succeeding number will be parsed as an INTEGER\\n\\t\\t */\\n\\t\\tlistTokenIdentifier.add(new TokenIdentifier(Pattern.compile(RegularExpression.DECIMAL), TokenType.DECIMAL_LITERAL));\\n\\t\\tlistTokenIdentifier.add(new TokenIdentifier(Pattern.compile(RegularExpression.IDENTIFIER), TokenType.IDENTIFIER));\\n\\t\\tlistTokenIdentifier.add(new TokenIdentifier(Pattern.compile(RegularExpression.INTEGER), TokenType.INTEGER_LITERAL));\\n\\t\\tlistTokenIdentifier.add(new TokenIdentifier(Pattern.compile(RegularExpression.STRING), TokenType.STRING_LITERAL));\\n\\n\\t\\tfor (String t: new String[] {\\\"=\\\", \\\"\\\\\\\\(\\\",\\\"\\\\\\\\)\\\", \\\"\\\\\\\\.\\\",\\\"\\\\\\\\,\\\"}) {\\n\\t\\t\\tlistTokenIdentifier.add(new TokenIdentifier(Pattern.compile(\\\"^(\\\" + t + \\\")\\\"), TokenType.TOKEN));\\t\\n\\t\\t}\\n\\t}\",\n \"@Override\\n\\tpublic String toString()\\n\\t{\\n\\t\\tStringBuilder buffer = new StringBuilder(128);\\n\\t\\tIterator<Map.Entry<String, AbstractNode>> it = pairs.entrySet().iterator();\\n\\t\\twhile (it.hasNext())\\n\\t\\t{\\n\\t\\t\\tMap.Entry<String, AbstractNode> pair = it.next();\\n\\t\\t\\tbuffer.append(keyToString(pair.getKey()));\\n\\t\\t\\tbuffer.append(KEY_VALUE_SEPARATOR_CHAR);\\n\\t\\t\\tbuffer.append(' ');\\n\\t\\t\\tbuffer.append(pair.getValue());\\n\\t\\t\\tif (it.hasNext())\\n\\t\\t\\t{\\n\\t\\t\\t\\tbuffer.append(PAIR_SEPARATOR_CHAR);\\n\\t\\t\\t\\tbuffer.append(' ');\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\treturn buffer.toString();\\n\\t}\",\n \"public String toString() {\\n\\tStringBuffer buf = new StringBuffer();\\n\\tfor (int i = 0; i < tokens.length; i++) {\\n\\t\\tif (i > 0) {\\n\\t\\t\\tbuf.append(\\\" \\\");\\n\\t\\t}\\t\\n\\t\\tbuf.append(tokens[i]);\\n\\t}\\n\\treturn buf.toString();\\n}\",\n \"private String string(Token t) {\\n\\n return expansionString.substring(t.start, t.end);\\n\\n }\",\n \"public static Map<String, String> listTokenFromCSP()\\r\\n\\t\\t\\tthrows BkavSignaturesException {\\r\\n\\t\\tMap<String, String> result = new HashMap<>();\\r\\n\\t\\ttry {\\r\\n\\t\\t\\tSunMSCAPI providerMSCAPI = new SunMSCAPI();\\r\\n\\t\\t\\tSecurity.addProvider(providerMSCAPI);\\r\\n\\t\\t\\tKeyStore ks = KeyStore.getInstance(CSP_KEYSTORE);\\r\\n\\t\\t\\tks.load(null, null);\\r\\n\\r\\n\\t\\t\\tEnumeration<String> aliases = ks.aliases();\\r\\n\\t\\t\\tString alias = null;\\r\\n\\r\\n\\t\\t\\twhile (aliases.hasMoreElements()) {\\r\\n\\t\\t\\t\\talias = aliases.nextElement();\\r\\n\\t\\t\\t\\tCertificate cert = ks.getCertificate(alias);\\r\\n\\t\\t\\t\\tif (cert instanceof X509Certificate) {\\r\\n\\t\\t\\t\\t\\tX509Certificate x509Cert = (X509Certificate) cert;\\r\\n\\t\\t\\t\\t\\tString certSerial = x509Cert.getSerialNumber().toString(16);\\r\\n\\r\\n\\t\\t\\t\\t\\tString subjectDN = x509Cert.getSubjectDN().getName();\\r\\n\\t\\t\\t\\t\\tString author = \\\"\\\";\\r\\n\\t\\t\\t\\t\\tLdapName ldap;\\r\\n\\t\\t\\t\\t\\ttry {\\r\\n\\t\\t\\t\\t\\t\\tldap = new LdapName(subjectDN);\\r\\n\\t\\t\\t\\t\\t\\tfor (Rdn rdn : ldap.getRdns()) {\\r\\n\\t\\t\\t\\t\\t\\t\\tif (\\\"CN\\\".equalsIgnoreCase(rdn.getType())) {\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tauthor = rdn.getValue().toString();\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tbreak;\\r\\n\\t\\t\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\t\\t}\\r\\n\\t\\t\\t\\t\\t} catch (InvalidNameException e) {\\r\\n\\t\\t\\t\\t\\t}\\r\\n\\r\\n\\t\\t\\t\\t\\tresult.put(certSerial, author);\\r\\n\\t\\t\\t\\t}\\r\\n\\t\\t\\t}\\r\\n\\t\\t} catch (KeyStoreException e) {\\r\\n\\t\\t\\tthrow new BkavSignaturesException(\\\"KeyStoreException\\\", e);\\r\\n\\t\\t} catch (NoSuchAlgorithmException e) {\\r\\n\\t\\t\\tthrow new BkavSignaturesException(\\\"NoSuchAlgorithmException\\\", e);\\r\\n\\t\\t} catch (CertificateException e) {\\r\\n\\t\\t\\tthrow new BkavSignaturesException(\\\"CertificateException\\\", e);\\r\\n\\t\\t} catch (IOException e) {\\r\\n\\t\\t\\tthrow new BkavSignaturesException(\\\"IOException\\\", e);\\r\\n\\t\\t}\\r\\n\\r\\n\\t\\treturn result;\\r\\n\\t}\",\n \"@Override\\n public String toString() {\\n return gateAdr + \\\", \\\" + postNr + \\\" \\\" + postSted;\\n }\",\n \"String getBShortToken();\",\n \"public Map<CharSequence, CharSequence> getReplacableNames();\",\n \"private String createCustomInfoString() {\\r\\n String CustomInfo = \\\"\\\";\\r\\n Iterator<String> iterator = mCustomParameters.keySet().iterator();\\r\\n while (iterator.hasNext()) {\\r\\n String CurrentKey = iterator.next();\\r\\n String CurrentVal = mCustomParameters.get(CurrentKey);\\r\\n CustomInfo += CurrentKey + \\\" = \\\" + CurrentVal + \\\"\\\\n\\\";\\r\\n }\\r\\n return CustomInfo;\\r\\n }\",\n \"public void display() {\\n\\tString tm = \\\"{ \\\";\\n\\tIterator it = entrySet().iterator();\\n\\twhile(it.hasNext()) {\\n\\t\\ttm += it.next() + \\\" ,\\\";\\n\\t}\\n\\ttm = tm.substring(0, tm.length() - 2) + \\\" }\\\";\\n\\tSystem.out.println(tm);\\n }\",\n \"@Override\\n\\tpublic String toString()\\n\\t{\\n\\t\\tStringBuilder s = new StringBuilder();\\n\\t\\tjava.util.Iterator<java.util.Map.Entry<String, Object>> iterator = entrySet().iterator();\\n\\t\\twhile (iterator.hasNext()) {\\n\\t\\t\\tjava.util.Map.Entry<String, Object> entry = iterator.next();\\n\\n\\t\\t\\ts.append('\\\\n');\\n\\t\\t\\ts.append(\\\"\\\\t\\\");\\n\\t\\t\\ts.append(entry.getKey());\\n\\t\\t\\ts.append(':');\\n\\t\\t\\ts.append(' ');\\n\\t\\t\\ts.append(entry.getValue().toString());\\n\\t\\t}\\n\\t\\treturn s.toString();\\n\\t}\",\n \"public static String[] gatherTokenStrings (Document doc, Span span) {\\n\\t\\tAnnotation[] tokens = gatherTokens(doc, span);\\n\\t\\tint length = tokens.length;\\n\\t\\tString[] stgs = new String[length];\\n\\t\\tfor (int i=0; i<length; i++)\\n\\t\\t\\tstgs[i] = doc.text(tokens[i]).trim();\\n\\t\\treturn stgs;\\n\\t}\",\n \"@Override\\r\\n public String encodeAll(List<LinkedHashMap<String, String>> dataList) {\\n StringBuilder str = new StringBuilder();\\r\\n\\r\\n for (LinkedHashMap<String, String> dataMap : dataList) {\\r\\n Collection<String> value = dataMap.values();\\r\\n\\r\\n for (Iterator<String> itr = value.iterator(); itr.hasNext();) {\\r\\n str = str.append(\\\"\\\\\\\"\\\").append(itr.next()).append(\\\"\\\\\\\"\\\").append(\\\",\\\");\\r\\n\\r\\n }\\r\\n str = str.deleteCharAt(str.length() - 1);\\r\\n str = str.append(\\\"\\\\n\\\");\\r\\n }\\r\\n\\r\\n return str.toString();\\r\\n\\r\\n }\",\n \"void Create(){\\n map = new TreeMap<>();\\r\\n\\r\\n // Now we split the words up using punction and spaces\\r\\n String wordArray[] = wordSource.split(\\\"[{ \\\\n\\\\r.,]}}?\\\");\\r\\n\\r\\n // Now we loop through the array\\r\\n for (String wordArray1 : wordArray) {\\r\\n String key = wordArray1.toLowerCase();\\r\\n // If this word is not present in the map then add it\\r\\n // and set the word count to 1\\r\\n if (key.length() > 0){\\r\\n if (!map.containsKey(map)){\\r\\n map.put(key, 1);\\r\\n }\\r\\n else {\\r\\n int wordCount = map.get(key);\\r\\n wordCount++;\\r\\n map.put(key, wordCount);\\r\\n }\\r\\n }\\r\\n } // end of for loop\\r\\n \\r\\n // Get all entries into a set\\r\\n // I think that before this we just have key-value pairs\\r\\n entrySet = map.entrySet();\\r\\n \\r\\n }\",\n \"@Override\\n\\tpublic Map<String, Integer> parseWordCountMap(String text, List<String> delimeter) {\\n\\t\\treturn new HashMap<>();\\n\\t}\",\n \"@Override\\n\\tpublic String toString() {\\n\\t\\tStringBuffer buf = new StringBuffer(\\\"Dictionary contents:\\\\n\\\");\\n\\t\\tfor (Iterator iter = entrySet().iterator(); iter.hasNext();) {\\n\\t\\t\\tMap.Entry entry = (Map.Entry) iter.next();\\n\\t\\t\\tbuf.append(\\\" \\\").append(entry.getKey()).append(\\\" = \\\").append(\\n\\t\\t\\t\\t\\tentry.getValue()).append(\\\"\\\\n\\\");\\n\\t\\t}\\n\\t\\treturn buf.toString();\\n\\t}\",\n \"private HashMap<String,HashMap<String,Integer>> computeTFForQueryWords(ArrayList<String> queryPostingLines) {\\n HashMap<String,HashMap<String,Integer>> queryWordsTF = new HashMap<>();\\n HashMap<String,HashMap<String,Integer>> queryWordsTFPerDoc = new HashMap<>();\\n String docID,term;\\n Integer tf;\\n HashSet<String> docIDs = new HashSet<>();\\n for(String postingLine : queryPostingLines){\\n HashMap<String,Integer> frequenciesInDocuments = new HashMap<>();\\n term = postingLine.substring(0,postingLine.indexOf(\\\"|\\\"));\\n postingLine = postingLine.substring(postingLine.indexOf(\\\"|\\\")+1);\\n while(!postingLine.equals(\\\"\\\")) {\\n docID = postingLine.substring(0, postingLine.indexOf(\\\":\\\"));\\n docIDs.add(docID);\\n postingLine = postingLine.substring(postingLine.indexOf(\\\"_\\\") + 1);\\n tf = Integer.valueOf(postingLine.substring(0, postingLine.indexOf(\\\"_\\\")));\\n postingLine = postingLine.substring(postingLine.indexOf(\\\"_\\\") + 1);\\n frequenciesInDocuments.put(docID,tf);\\n }\\n queryWordsTF.put(term,frequenciesInDocuments);\\n }\\n\\n ArrayList<String> allTermsInQuery = new ArrayList<>(queryWordsTF.keySet());\\n for(String doc : docIDs){\\n HashMap<String,Integer> tfsInDoc = new HashMap<>();\\n for(String termInQuery : allTermsInQuery){\\n HashMap<String,Integer> termsTFInDoc = queryWordsTF.get(termInQuery);\\n if(termsTFInDoc.containsKey(doc)){\\n tfsInDoc.put(termInQuery,termsTFInDoc.get(doc));\\n }\\n }\\n queryWordsTFPerDoc.put(doc,tfsInDoc);\\n }\\n return queryWordsTFPerDoc;\\n }\",\n \"private void initRegs(){\\n\\n keyWordReg = \\\"\\\";\\n\\n for (String seg: keyWordMap.keySet()){\\n\\n keyWordReg += seg + \\\"|\\\";\\n\\n }\\n\\n symbolReg = \\\"[\\\\\\\\&\\\\\\\\*\\\\\\\\+\\\\\\\\(\\\\\\\\)\\\\\\\\.\\\\\\\\/\\\\\\\\,\\\\\\\\-\\\\\\\\]\\\\\\\\;\\\\\\\\~\\\\\\\\}\\\\\\\\|\\\\\\\\{\\\\\\\\>\\\\\\\\=\\\\\\\\[\\\\\\\\<]\\\";\\n intReg = \\\"[0-9]+\\\";\\n strReg = \\\"\\\\\\\"[^\\\\\\\"\\\\n]*\\\\\\\"\\\";\\n idReg = \\\"[a-zA-Z_]\\\\\\\\w*\\\";\\n\\n tokenPatterns = Pattern.compile(idReg + \\\"|\\\" + keyWordReg + symbolReg + \\\"|\\\" + intReg + \\\"|\\\" + strReg);\\n }\",\n \"private static String[] getMapStrings(boolean desc) {\\n\\n\\n\\n ArrayList list = new ArrayList();\\n Locale locale = Locale.getDefault();\\n String name = locale.toString();\\n if (desc)\\n name = \\\"locale=\\\" + name;\\n list.add(0, name);\\n\\n String os = \\\"-\\\" + getOSType();\\n if (desc)\\n os = \\\" (os=\\\" + System.getProperty(\\\"os.name\\\")\\n + \\\", \\\" + System.getProperty(\\\"os.version\\\") + \\\")\\\";\\n name += os;\\n list.add(0, name);\\n\\n // Allow the invoker to override the keyStrokeMap to support\\n // case where you are working on a remote machine with a different\\n // local or platform.\\n \\n String override = System.getProperty(\\\"abbot.keyStrokeMap\\\");\\n if (override!=null) {\\n list.add(0, override);\\n }\\n \\n \\n /*\\n String vm = System.getProperty(\\\"java.version\\\");\\n name += \\\" vm=\\\" + vm;\\n list.add(0, name);\\n String version = System.getProperty(\\\"os.version\\\");\\n name += \\\" version=\\\" + version;\\n list.add(0, name);\\n String arch = System.getProperty(\\\"os.arch\\\");\\n name += \\\" arch=\\\" + arch;\\n list.add(0, name);\\n */\\n return (String[])list.toArray(new String[list.size()]);\\n }\",\n \"public String getPostingText() {\\n return postingText;\\n }\",\n \"@Override\\n\\tpublic Map<String, Object> getGradeMyStu(String token) {\\n\\t\\treturn null;\\n\\t}\",\n \"public void printMap() {\\n String s = \\\"\\\";\\n Stack st = new Stack();\\n st.addAll(map.entrySet());\\n while (!st.isEmpty()) {\\n s += st.pop().toString() + \\\"\\\\n\\\";\\n }\\n window.getDHTText().setText(s);\\n }\",\n \"public String toString()\\n {\\n String ret = \\\"\\\";\\n String s = adjMaps.toString();\\n String[] parts = s.split(\\\"},\\\");\\n for(int i=0; i< parts.length; i++){\\n ret += parts[i] + \\\"}\\\\n\\\";\\n }\\n return ret;\\n }\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6758433","0.58897084","0.5630534","0.5508794","0.5503969","0.54728544","0.5447173","0.53018135","0.5263845","0.5251088","0.5191312","0.51761514","0.51590157","0.51570046","0.5153402","0.5152076","0.51318806","0.5107668","0.51008123","0.51008123","0.51008123","0.51008123","0.51008123","0.51008123","0.51008123","0.51008123","0.5055568","0.50479263","0.503786","0.503786","0.503786","0.503786","0.503786","0.50339925","0.49792716","0.49732354","0.4948449","0.4948449","0.4948449","0.4948449","0.4948449","0.4948449","0.49290907","0.49272466","0.4926927","0.49177918","0.48872748","0.4882073","0.4875693","0.4872941","0.48675936","0.48646176","0.48546845","0.48535758","0.4837421","0.4833374","0.48333004","0.48302263","0.48302263","0.48302263","0.48302263","0.48302263","0.48302263","0.48302263","0.48302263","0.48302263","0.48302263","0.48260513","0.4821346","0.48115867","0.48032847","0.4792706","0.4786155","0.47853503","0.47852436","0.4784183","0.47662842","0.47626793","0.47597602","0.47591612","0.4757793","0.4757347","0.47521752","0.47454002","0.47441196","0.47393447","0.47368416","0.4733769","0.47319713","0.47301406","0.47205356","0.47153443","0.47133312","0.47094762","0.47070792","0.4705306","0.47011784","0.4697039","0.46943098","0.46827918"],"string":"[\n \"0.6758433\",\n \"0.58897084\",\n \"0.5630534\",\n \"0.5508794\",\n \"0.5503969\",\n \"0.54728544\",\n \"0.5447173\",\n \"0.53018135\",\n \"0.5263845\",\n \"0.5251088\",\n \"0.5191312\",\n \"0.51761514\",\n \"0.51590157\",\n \"0.51570046\",\n \"0.5153402\",\n \"0.5152076\",\n \"0.51318806\",\n \"0.5107668\",\n \"0.51008123\",\n \"0.51008123\",\n \"0.51008123\",\n \"0.51008123\",\n \"0.51008123\",\n \"0.51008123\",\n \"0.51008123\",\n \"0.51008123\",\n \"0.5055568\",\n \"0.50479263\",\n \"0.503786\",\n \"0.503786\",\n \"0.503786\",\n \"0.503786\",\n \"0.503786\",\n \"0.50339925\",\n \"0.49792716\",\n \"0.49732354\",\n \"0.4948449\",\n \"0.4948449\",\n \"0.4948449\",\n \"0.4948449\",\n \"0.4948449\",\n \"0.4948449\",\n \"0.49290907\",\n \"0.49272466\",\n \"0.4926927\",\n \"0.49177918\",\n \"0.48872748\",\n \"0.4882073\",\n \"0.4875693\",\n \"0.4872941\",\n \"0.48675936\",\n \"0.48646176\",\n \"0.48546845\",\n \"0.48535758\",\n \"0.4837421\",\n \"0.4833374\",\n \"0.48333004\",\n \"0.48302263\",\n \"0.48302263\",\n \"0.48302263\",\n \"0.48302263\",\n \"0.48302263\",\n \"0.48302263\",\n \"0.48302263\",\n \"0.48302263\",\n \"0.48302263\",\n \"0.48302263\",\n \"0.48260513\",\n \"0.4821346\",\n \"0.48115867\",\n \"0.48032847\",\n \"0.4792706\",\n \"0.4786155\",\n \"0.47853503\",\n \"0.47852436\",\n \"0.4784183\",\n \"0.47662842\",\n \"0.47626793\",\n \"0.47597602\",\n \"0.47591612\",\n \"0.4757793\",\n \"0.4757347\",\n \"0.47521752\",\n \"0.47454002\",\n \"0.47441196\",\n \"0.47393447\",\n \"0.47368416\",\n \"0.4733769\",\n \"0.47319713\",\n \"0.47301406\",\n \"0.47205356\",\n \"0.47153443\",\n \"0.47133312\",\n \"0.47094762\",\n \"0.47070792\",\n \"0.4705306\",\n \"0.47011784\",\n \"0.4697039\",\n \"0.46943098\",\n \"0.46827918\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.5571595"},"document_rank":{"kind":"string","value":"3"}}},{"rowIdx":13898,"cells":{"query":{"kind":"string","value":"This method is called from within the constructor to initialize the form. WARNING: Do NOT modify this code. The content of this method is always regenerated by the Form Editor."},"document":{"kind":"string","value":"@SuppressWarnings(\"unchecked\")\n // <editor-fold defaultstate=\"collapsed\" desc=\"Generated Code\">//GEN-BEGIN:initComponents\n private void initComponents() {\n\n jLabel1 = new javax.swing.JLabel();\n jLabel2 = new javax.swing.JLabel();\n jLabel3 = new javax.swing.JLabel();\n txtNombre = new javax.swing.JTextField();\n txtPuesto = new javax.swing.JTextField();\n txtDepartamento = new javax.swing.JTextField();\n btnInsertar = new javax.swing.JButton();\n btnAyudas = new javax.swing.JButton();\n btnReportes = new javax.swing.JButton();\n\n setDefaultCloseOperation(javax.swing.WindowConstants.EXIT_ON_CLOSE);\n\n jLabel1.setFont(new java.awt.Font(\"Times New Roman\", 0, 12)); // NOI18N\n jLabel1.setText(\"Nombre\");\n\n jLabel2.setFont(new java.awt.Font(\"Times New Roman\", 0, 12)); // NOI18N\n jLabel2.setText(\"Puesto\");\n\n jLabel3.setFont(new java.awt.Font(\"Times New Roman\", 0, 12)); // NOI18N\n jLabel3.setText(\"Departamento\");\n\n txtNombre.setFont(new java.awt.Font(\"Times New Roman\", 0, 12)); // NOI18N\n\n txtPuesto.setFont(new java.awt.Font(\"Times New Roman\", 0, 12)); // NOI18N\n\n txtDepartamento.setFont(new java.awt.Font(\"Times New Roman\", 0, 12)); // NOI18N\n\n btnInsertar.setFont(new java.awt.Font(\"Times New Roman\", 0, 14)); // NOI18N\n btnInsertar.setText(\"Ingresar\");\n btnInsertar.addActionListener(new java.awt.event.ActionListener() {\n public void actionPerformed(java.awt.event.ActionEvent evt) {\n btnInsertarActionPerformed(evt);\n }\n });\n\n btnAyudas.setFont(new java.awt.Font(\"Times New Roman\", 0, 14)); // NOI18N\n btnAyudas.setText(\"Ayudas\");\n btnAyudas.addActionListener(new java.awt.event.ActionListener() {\n public void actionPerformed(java.awt.event.ActionEvent evt) {\n btnAyudasActionPerformed(evt);\n }\n });\n\n btnReportes.setText(\"Reportes\");\n btnReportes.addActionListener(new java.awt.event.ActionListener() {\n public void actionPerformed(java.awt.event.ActionEvent evt) {\n btnReportesActionPerformed(evt);\n }\n });\n\n javax.swing.GroupLayout layout = new javax.swing.GroupLayout(getContentPane());\n getContentPane().setLayout(layout);\n layout.setHorizontalGroup(\n layout.createParallelGroup(javax.swing.GroupLayout.Alignment.LEADING)\n .addGroup(layout.createSequentialGroup()\n .addGap(33, 33, 33)\n .addGroup(layout.createParallelGroup(javax.swing.GroupLayout.Alignment.TRAILING)\n .addGroup(layout.createSequentialGroup()\n .addGroup(layout.createParallelGroup(javax.swing.GroupLayout.Alignment.LEADING)\n .addComponent(jLabel3)\n .addComponent(jLabel2, javax.swing.GroupLayout.Alignment.TRAILING)\n .addComponent(jLabel1, javax.swing.GroupLayout.Alignment.TRAILING))\n .addGap(18, 18, 18)\n .addGroup(layout.createParallelGroup(javax.swing.GroupLayout.Alignment.LEADING, false)\n .addComponent(txtNombre, javax.swing.GroupLayout.DEFAULT_SIZE, 171, Short.MAX_VALUE)\n .addComponent(txtPuesto)\n .addComponent(txtDepartamento))\n .addGap(49, 81, Short.MAX_VALUE))\n .addGroup(layout.createSequentialGroup()\n .addComponent(btnInsertar, javax.swing.GroupLayout.PREFERRED_SIZE, 85, javax.swing.GroupLayout.PREFERRED_SIZE)\n .addPreferredGap(javax.swing.LayoutStyle.ComponentPlacement.UNRELATED)\n .addComponent(btnAyudas, javax.swing.GroupLayout.PREFERRED_SIZE, 85, javax.swing.GroupLayout.PREFERRED_SIZE)\n .addPreferredGap(javax.swing.LayoutStyle.ComponentPlacement.UNRELATED)\n .addComponent(btnReportes, javax.swing.GroupLayout.PREFERRED_SIZE, 84, javax.swing.GroupLayout.PREFERRED_SIZE)\n .addGap(43, 43, 43))))\n );\n layout.setVerticalGroup(\n layout.createParallelGroup(javax.swing.GroupLayout.Alignment.LEADING)\n .addGroup(layout.createSequentialGroup()\n .addGap(35, 35, 35)\n .addGroup(layout.createParallelGroup(javax.swing.GroupLayout.Alignment.BASELINE)\n .addComponent(jLabel1)\n .addComponent(txtNombre, javax.swing.GroupLayout.PREFERRED_SIZE, javax.swing.GroupLayout.DEFAULT_SIZE, javax.swing.GroupLayout.PREFERRED_SIZE))\n .addGap(18, 18, 18)\n .addGroup(layout.createParallelGroup(javax.swing.GroupLayout.Alignment.BASELINE)\n .addComponent(jLabel2)\n .addComponent(txtPuesto, javax.swing.GroupLayout.PREFERRED_SIZE, javax.swing.GroupLayout.DEFAULT_SIZE, javax.swing.GroupLayout.PREFERRED_SIZE))\n .addGap(18, 18, 18)\n .addGroup(layout.createParallelGroup(javax.swing.GroupLayout.Alignment.BASELINE)\n .addComponent(jLabel3)\n .addComponent(txtDepartamento, javax.swing.GroupLayout.PREFERRED_SIZE, javax.swing.GroupLayout.DEFAULT_SIZE, javax.swing.GroupLayout.PREFERRED_SIZE))\n .addGap(38, 38, 38)\n .addGroup(layout.createParallelGroup(javax.swing.GroupLayout.Alignment.LEADING)\n .addGroup(layout.createParallelGroup(javax.swing.GroupLayout.Alignment.BASELINE)\n .addComponent(btnInsertar, javax.swing.GroupLayout.PREFERRED_SIZE, 47, javax.swing.GroupLayout.PREFERRED_SIZE)\n .addComponent(btnAyudas, javax.swing.GroupLayout.PREFERRED_SIZE, 47, javax.swing.GroupLayout.PREFERRED_SIZE))\n .addComponent(btnReportes, javax.swing.GroupLayout.Alignment.TRAILING, javax.swing.GroupLayout.PREFERRED_SIZE, 47, javax.swing.GroupLayout.PREFERRED_SIZE))\n .addContainerGap(64, Short.MAX_VALUE))\n );\n\n pack();\n }"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["public Form() {\n initComponents();\n }","public MainForm() {\n initComponents();\n }","public MainForm() {\n initComponents();\n }","public MainForm() {\n initComponents();\n }","public frmRectangulo() {\n initComponents();\n }","public form() {\n initComponents();\n }","public AdjointForm() {\n initComponents();\n setDefaultCloseOperation(HIDE_ON_CLOSE);\n }","public FormListRemarking() {\n initComponents();\n }","public MainForm() {\n initComponents();\n \n }","public FormPemilihan() {\n initComponents();\n }","public GUIForm() { \n initComponents();\n }","public FrameForm() {\n initComponents();\n }","public TorneoForm() {\n initComponents();\n }","public FormCompra() {\n initComponents();\n }","public muveletek() {\n initComponents();\n }","public Interfax_D() {\n initComponents();\n }","public quanlixe_form() {\n initComponents();\n }","public SettingsForm() {\n initComponents();\n }","public RegistrationForm() {\n initComponents();\n this.setLocationRelativeTo(null);\n }","public Soru1() {\n initComponents();\n }","public FMainForm() {\n initComponents();\n this.setResizable(false);\n setLocationRelativeTo(null);\n }","public soal2GUI() {\n initComponents();\n }","public EindopdrachtGUI() {\n initComponents();\n }","public MechanicForm() {\n initComponents();\n }","public AddDocumentLineForm(java.awt.Frame parent) {\n super(parent);\n initComponents();\n myInit();\n }","public BloodDonationGUI() {\n initComponents();\n }","public quotaGUI() {\n initComponents();\n }","public PatientUI() {\n initComponents();\n }","public Customer_Form() {\n initComponents();\n setSize(890,740);\n \n \n }","public Oddeven() {\n initComponents();\n }","public myForm() {\n\t\t\tinitComponents();\n\t\t}","public Magasin() {\n initComponents();\n }","public intrebarea() {\n initComponents();\n }","public RadioUI()\n {\n initComponents();\n }","public NewCustomerGUI() {\n initComponents();\n }","public ZobrazUdalost() {\n initComponents();\n }","public FormUtama() {\n initComponents();\n }","public p0() {\n initComponents();\n }","public INFORMACION() {\n initComponents();\n this.setLocationRelativeTo(null); \n }","public ProgramForm() {\n setLookAndFeel();\n initComponents();\n }","public AmountReleasedCommentsForm() {\r\n initComponents();\r\n }","public form2() {\n initComponents();\n }","public MainForm() {\n\t\tsuper(\"Hospital\", List.IMPLICIT);\n\n\t\tstartComponents();\n\t}","public kunde() {\n initComponents();\n }","public LixeiraForm() {\n initComponents();\n setLocationRelativeTo(null);\n }","@SuppressWarnings(\"unchecked\")\n // <editor-fold defaultstate=\"collapsed\" desc=\"Generated Code\">//GEN-BEGIN:initComponents\n private void initComponents() {\n\n setName(\"Form\"); // NOI18N\n setRequestFocusEnabled(false);\n setVerifyInputWhenFocusTarget(false);\n\n javax.swing.GroupLayout layout = new javax.swing.GroupLayout(this);\n this.setLayout(layout);\n layout.setHorizontalGroup(\n layout.createParallelGroup(javax.swing.GroupLayout.Alignment.LEADING)\n .addGap(0, 465, Short.MAX_VALUE)\n );\n layout.setVerticalGroup(\n layout.createParallelGroup(javax.swing.GroupLayout.Alignment.LEADING)\n .addGap(0, 357, Short.MAX_VALUE)\n );\n }","public MusteriEkle() {\n initComponents();\n }","public frmMain() {\n initComponents();\n }","public frmMain() {\n initComponents();\n }","public DESHBORDPANAL() {\n initComponents();\n }","public frmVenda() {\n initComponents();\n }","public GUIForm() {\n initComponents();\n inputField.setText(NO_FILE_SELECTED);\n outputField.setText(NO_FILE_SELECTED);\n progressLabel.setBackground(INFO);\n progressLabel.setText(SELECT_FILE);\n }","public Botonera() {\n initComponents();\n }","public FrmMenu() {\n initComponents();\n }","public OffertoryGUI() {\n initComponents();\n setTypes();\n }","public JFFornecedores() {\n initComponents();\n }","@SuppressWarnings(\"unchecked\")\n // <editor-fold defaultstate=\"collapsed\" desc=\"Generated Code\">//GEN-BEGIN:initComponents\n private void initComponents()\n {\n\n setDefaultCloseOperation(javax.swing.WindowConstants.EXIT_ON_CLOSE);\n setBackground(new java.awt.Color(255, 255, 255));\n\n javax.swing.GroupLayout layout = new javax.swing.GroupLayout(getContentPane());\n getContentPane().setLayout(layout);\n layout.setHorizontalGroup(\n layout.createParallelGroup(javax.swing.GroupLayout.Alignment.LEADING)\n .addGap(0, 983, Short.MAX_VALUE)\n );\n layout.setVerticalGroup(\n layout.createParallelGroup(javax.swing.GroupLayout.Alignment.LEADING)\n .addGap(0, 769, Short.MAX_VALUE)\n );\n\n pack();\n }","public EnterDetailsGUI() {\n initComponents();\n }","public vpemesanan1() {\n initComponents();\n }","public Kost() {\n initComponents();\n }","public FormHorarioSSE() {\n initComponents();\n }","public frmacceso() {\n initComponents();\n }","public UploadForm() {\n initComponents();\n }","public HW3() {\n initComponents();\n }","public Managing_Staff_Main_Form() {\n initComponents();\n }","@SuppressWarnings(\"unchecked\")\n // <editor-fold defaultstate=\"collapsed\" desc=\"Generated Code\">//GEN-BEGIN:initComponents\n private void initComponents()\n {\n\n setDefaultCloseOperation(javax.swing.WindowConstants.EXIT_ON_CLOSE);\n getContentPane().setLayout(null);\n\n pack();\n }","@SuppressWarnings(\"unchecked\")\n // <editor-fold defaultstate=\"collapsed\" desc=\"Generated Code\">//GEN-BEGIN:initComponents\n private void initComponents() {\n\n setName(\"Form\"); // NOI18N\n\n javax.swing.GroupLayout layout = new javax.swing.GroupLayout(this);\n this.setLayout(layout);\n layout.setHorizontalGroup(\n layout.createParallelGroup(javax.swing.GroupLayout.Alignment.LEADING)\n .addGap(0, 400, Short.MAX_VALUE)\n );\n layout.setVerticalGroup(\n layout.createParallelGroup(javax.swing.GroupLayout.Alignment.LEADING)\n .addGap(0, 300, Short.MAX_VALUE)\n );\n }","public sinavlar2() {\n initComponents();\n }","public P0405() {\n initComponents();\n }","public IssueBookForm() {\n initComponents();\n }","public MiFrame2() {\n initComponents();\n }","public Choose1() {\n initComponents();\n }","public MainForm() {\n initComponents();\n\n String oldAuthor = prefs.get(\"AUTHOR\", \"\");\n if(oldAuthor != null) {\n this.authorTextField.setText(oldAuthor);\n }\n String oldBook = prefs.get(\"BOOK\", \"\");\n if(oldBook != null) {\n this.bookTextField.setText(oldBook);\n }\n String oldDisc = prefs.get(\"DISC\", \"\");\n if(oldDisc != null) {\n try {\n int oldDiscNum = Integer.parseInt(oldDisc);\n oldDiscNum++;\n this.discNumberTextField.setText(Integer.toString(oldDiscNum));\n } catch (Exception ex) {\n this.discNumberTextField.setText(oldDisc);\n }\n this.bookTextField.setText(oldBook);\n }\n\n\n }","public GUI_StudentInfo() {\n initComponents();\n }","public Lihat_Dokter_Keseluruhan() {\n initComponents();\n }","public JFrmPrincipal() {\n initComponents();\n }","public bt526() {\n initComponents();\n }","public Pemilihan_Dokter() {\n initComponents();\n }","public Ablak() {\n initComponents();\n }","@Override\n\tprotected void initUi() {\n\t\t\n\t}","@SuppressWarnings(\"unchecked\")\n\t// <editor-fold defaultstate=\"collapsed\" desc=\"Generated\n\t// Code\">//GEN-BEGIN:initComponents\n\tprivate void initComponents() {\n\n\t\tlabel1 = new java.awt.Label();\n\t\tlabel2 = new java.awt.Label();\n\t\tlabel3 = new java.awt.Label();\n\t\tlabel4 = new java.awt.Label();\n\t\tlabel5 = new java.awt.Label();\n\t\tlabel6 = new java.awt.Label();\n\t\tlabel7 = new java.awt.Label();\n\t\tlabel8 = new java.awt.Label();\n\t\tlabel9 = new java.awt.Label();\n\t\tlabel10 = new java.awt.Label();\n\t\ttextField1 = new java.awt.TextField();\n\t\ttextField2 = new java.awt.TextField();\n\t\tlabel14 = new java.awt.Label();\n\t\tlabel15 = new java.awt.Label();\n\t\tlabel16 = new java.awt.Label();\n\t\ttextField3 = new java.awt.TextField();\n\t\ttextField4 = new java.awt.TextField();\n\t\ttextField5 = new java.awt.TextField();\n\t\tlabel17 = new java.awt.Label();\n\t\tlabel18 = new java.awt.Label();\n\t\tlabel19 = new java.awt.Label();\n\t\tlabel20 = new java.awt.Label();\n\t\tlabel21 = new java.awt.Label();\n\t\tlabel22 = new java.awt.Label();\n\t\ttextField6 = new java.awt.TextField();\n\t\ttextField7 = new java.awt.TextField();\n\t\ttextField8 = new java.awt.TextField();\n\t\tlabel23 = new java.awt.Label();\n\t\ttextField9 = new java.awt.TextField();\n\t\ttextField10 = new java.awt.TextField();\n\t\ttextField11 = new java.awt.TextField();\n\t\ttextField12 = new java.awt.TextField();\n\t\tlabel24 = new java.awt.Label();\n\t\tlabel25 = new java.awt.Label();\n\t\tlabel26 = new java.awt.Label();\n\t\tlabel27 = new java.awt.Label();\n\t\tlabel28 = new java.awt.Label();\n\t\tlabel30 = new java.awt.Label();\n\t\tlabel31 = new java.awt.Label();\n\t\tlabel32 = new java.awt.Label();\n\t\tjButton1 = new javax.swing.JButton();\n\n\t\tlabel1.setFont(new java.awt.Font(\"Segoe UI Semibold\", 0, 18)); // NOI18N\n\t\tlabel1.setText(\"It seems that some of the buttons on the ATM machine are not working!\");\n\n\t\tlabel2.setFont(new java.awt.Font(\"Segoe UI Semibold\", 0, 18)); // NOI18N\n\t\tlabel2.setText(\"Unfortunately these numbers are exactly what Professor has to use to type in his password.\");\n\n\t\tlabel3.setFont(new java.awt.Font(\"Segoe UI Semibold\", 0, 18)); // NOI18N\n\t\tlabel3.setText(\n\t\t\t\t\"If you want to eat tonight, you have to help him out and construct the numbers of the password with the working buttons and math operators.\");\n\n\t\tlabel4.setFont(new java.awt.Font(\"Segoe UI Semibold\", 0, 14)); // NOI18N\n\t\tlabel4.setText(\"Denver's Password: 2792\");\n\n\t\tlabel5.setFont(new java.awt.Font(\"Consolas\", 0, 14)); // NOI18N\n\t\tlabel5.setText(\"import java.util.Scanner;\\n\");\n\n\t\tlabel6.setFont(new java.awt.Font(\"Consolas\", 0, 14)); // NOI18N\n\t\tlabel6.setText(\"public class ATM{\");\n\n\t\tlabel7.setFont(new java.awt.Font(\"Consolas\", 0, 14)); // NOI18N\n\t\tlabel7.setText(\"public static void main(String[] args){\");\n\n\t\tlabel8.setFont(new java.awt.Font(\"Consolas\", 0, 14)); // NOI18N\n\t\tlabel8.setText(\"System.out.print(\");\n\n\t\tlabel9.setFont(new java.awt.Font(\"Dialog\", 0, 14)); // NOI18N\n\t\tlabel9.setText(\" -\");\n\n\t\tlabel10.setFont(new java.awt.Font(\"Consolas\", 0, 14)); // NOI18N\n\t\tlabel10.setText(\");\");\n\n\t\ttextField1.addActionListener(new java.awt.event.ActionListener() {\n\t\t\tpublic void actionPerformed(java.awt.event.ActionEvent evt) {\n\t\t\t\ttextField1ActionPerformed(evt);\n\t\t\t}\n\t\t});\n\n\t\tlabel14.setFont(new java.awt.Font(\"Consolas\", 0, 14)); // NOI18N\n\t\tlabel14.setText(\"System.out.print( (\");\n\n\t\tlabel15.setFont(new java.awt.Font(\"Consolas\", 0, 14)); // NOI18N\n\t\tlabel15.setText(\"System.out.print(\");\n\n\t\tlabel16.setFont(new java.awt.Font(\"Consolas\", 0, 14)); // NOI18N\n\t\tlabel16.setText(\"System.out.print( ( (\");\n\n\t\tlabel17.setFont(new java.awt.Font(\"Dialog\", 0, 14)); // NOI18N\n\t\tlabel17.setText(\")\");\n\n\t\tlabel18.setFont(new java.awt.Font(\"Dialog\", 0, 14)); // NOI18N\n\t\tlabel18.setText(\" +\");\n\n\t\tlabel19.setFont(new java.awt.Font(\"Consolas\", 0, 14)); // NOI18N\n\t\tlabel19.setText(\");\");\n\n\t\tlabel20.setFont(new java.awt.Font(\"Dialog\", 0, 14)); // NOI18N\n\t\tlabel20.setText(\" /\");\n\n\t\tlabel21.setFont(new java.awt.Font(\"Dialog\", 0, 14)); // NOI18N\n\t\tlabel21.setText(\" %\");\n\n\t\tlabel22.setFont(new java.awt.Font(\"Dialog\", 0, 14)); // NOI18N\n\t\tlabel22.setText(\" +\");\n\n\t\tlabel23.setFont(new java.awt.Font(\"Consolas\", 0, 14)); // NOI18N\n\t\tlabel23.setText(\");\");\n\n\t\tlabel24.setFont(new java.awt.Font(\"Dialog\", 0, 14)); // NOI18N\n\t\tlabel24.setText(\" +\");\n\n\t\tlabel25.setFont(new java.awt.Font(\"Dialog\", 0, 14)); // NOI18N\n\t\tlabel25.setText(\" /\");\n\n\t\tlabel26.setFont(new java.awt.Font(\"Dialog\", 0, 14)); // NOI18N\n\t\tlabel26.setText(\" *\");\n\n\t\tlabel27.setCursor(new java.awt.Cursor(java.awt.Cursor.DEFAULT_CURSOR));\n\t\tlabel27.setFont(new java.awt.Font(\"Consolas\", 0, 14)); // NOI18N\n\t\tlabel27.setText(\")\");\n\n\t\tlabel28.setFont(new java.awt.Font(\"Dialog\", 0, 14)); // NOI18N\n\t\tlabel28.setText(\")\");\n\n\t\tlabel30.setFont(new java.awt.Font(\"Consolas\", 0, 14)); // NOI18N\n\t\tlabel30.setText(\"}\");\n\n\t\tlabel31.setFont(new java.awt.Font(\"Consolas\", 0, 14)); // NOI18N\n\t\tlabel31.setText(\"}\");\n\n\t\tlabel32.setFont(new java.awt.Font(\"Consolas\", 0, 14)); // NOI18N\n\t\tlabel32.setText(\");\");\n\n\t\tjButton1.setFont(new java.awt.Font(\"Segoe UI Semibold\", 0, 14)); // NOI18N\n\t\tjButton1.setText(\"Check\");\n\t\tjButton1.addActionListener(new java.awt.event.ActionListener() {\n\t\t\tpublic void actionPerformed(java.awt.event.ActionEvent evt) {\n\t\t\t\tjButton1ActionPerformed(evt);\n\t\t\t}\n\t\t});\n\n\t\tjavax.swing.GroupLayout layout = new javax.swing.GroupLayout(this);\n\t\tlayout.setHorizontalGroup(layout.createParallelGroup(Alignment.LEADING)\n\t\t\t\t.addGroup(layout.createSequentialGroup().addGap(28).addGroup(layout\n\t\t\t\t\t\t.createParallelGroup(Alignment.LEADING).addComponent(getDoneButton()).addComponent(jButton1)\n\t\t\t\t\t\t.addComponent(label7, GroupLayout.PREFERRED_SIZE, GroupLayout.DEFAULT_SIZE,\n\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t.addComponent(label6, GroupLayout.PREFERRED_SIZE, GroupLayout.DEFAULT_SIZE,\n\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t.addComponent(label5, GroupLayout.PREFERRED_SIZE, GroupLayout.DEFAULT_SIZE,\n\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t.addComponent(label4, GroupLayout.PREFERRED_SIZE, GroupLayout.DEFAULT_SIZE,\n\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t.addComponent(label3, GroupLayout.PREFERRED_SIZE, GroupLayout.DEFAULT_SIZE,\n\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t.addGroup(layout.createSequentialGroup()\n\t\t\t\t\t\t\t\t.addComponent(label1, GroupLayout.PREFERRED_SIZE, GroupLayout.DEFAULT_SIZE,\n\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t\t\t.addGap(1)\n\t\t\t\t\t\t\t\t.addComponent(label2, GroupLayout.PREFERRED_SIZE, 774, GroupLayout.PREFERRED_SIZE))\n\t\t\t\t\t\t.addGroup(layout.createSequentialGroup()\n\t\t\t\t\t\t\t\t.addGap(92).addGroup(layout.createParallelGroup(Alignment.LEADING).addGroup(layout\n\t\t\t\t\t\t\t\t\t\t.createSequentialGroup()\n\t\t\t\t\t\t\t\t\t\t.addGroup(layout.createParallelGroup(Alignment.LEADING, false)\n\t\t\t\t\t\t\t\t\t\t\t\t.addGroup(layout.createSequentialGroup()\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(label15, GroupLayout.PREFERRED_SIZE, 145,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addPreferredGap(ComponentPlacement.RELATED)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(textField8, GroupLayout.PREFERRED_SIZE, 20,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addGap(2)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(label21, GroupLayout.PREFERRED_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.DEFAULT_SIZE, GroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addPreferredGap(ComponentPlacement.RELATED,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.DEFAULT_SIZE, Short.MAX_VALUE)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(textField7, GroupLayout.PREFERRED_SIZE, 20,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE))\n\t\t\t\t\t\t\t\t\t\t\t\t.addGroup(layout.createSequentialGroup()\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(label8, GroupLayout.PREFERRED_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.DEFAULT_SIZE, GroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addPreferredGap(ComponentPlacement.RELATED)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(textField1, GroupLayout.PREFERRED_SIZE, 20,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addPreferredGap(ComponentPlacement.RELATED)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(label9, GroupLayout.PREFERRED_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.DEFAULT_SIZE, GroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addPreferredGap(ComponentPlacement.RELATED).addComponent(\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\ttextField2, GroupLayout.PREFERRED_SIZE, 20,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE))\n\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(label31, GroupLayout.PREFERRED_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.DEFAULT_SIZE, GroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t\t\t\t\t\t\t.addGroup(layout.createSequentialGroup().addGroup(layout\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t.createParallelGroup(Alignment.LEADING)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addGroup(layout.createSequentialGroup()\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(label14, GroupLayout.DEFAULT_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.DEFAULT_SIZE, Short.MAX_VALUE)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addGap(37))\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addGroup(layout.createSequentialGroup().addGap(174)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(textField5, GroupLayout.PREFERRED_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t20, GroupLayout.PREFERRED_SIZE)))\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(label18, GroupLayout.PREFERRED_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.DEFAULT_SIZE, GroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addGap(7)))\n\t\t\t\t\t\t\t\t\t\t.addPreferredGap(ComponentPlacement.RELATED)\n\t\t\t\t\t\t\t\t\t\t.addGroup(layout.createParallelGroup(Alignment.LEADING).addGroup(layout\n\t\t\t\t\t\t\t\t\t\t\t\t.createSequentialGroup()\n\t\t\t\t\t\t\t\t\t\t\t\t.addGroup(layout\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t.createParallelGroup(Alignment.TRAILING, false).addGroup(layout\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.createSequentialGroup()\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(textField4, GroupLayout.PREFERRED_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t20, GroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addPreferredGap(ComponentPlacement.RELATED,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.DEFAULT_SIZE, Short.MAX_VALUE)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(label17, GroupLayout.PREFERRED_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.DEFAULT_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE))\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addGroup(layout.createSequentialGroup()\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(label22, GroupLayout.PREFERRED_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.DEFAULT_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addPreferredGap(ComponentPlacement.RELATED)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(textField9, GroupLayout.PREFERRED_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t20, GroupLayout.PREFERRED_SIZE)))\n\t\t\t\t\t\t\t\t\t\t\t\t.addGap(20)\n\t\t\t\t\t\t\t\t\t\t\t\t.addGroup(layout.createParallelGroup(Alignment.TRAILING)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(label23, GroupLayout.PREFERRED_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.DEFAULT_SIZE, GroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addGroup(layout.createSequentialGroup()\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(label20, GroupLayout.PREFERRED_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.DEFAULT_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addPreferredGap(ComponentPlacement.RELATED)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(textField3, GroupLayout.PREFERRED_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t20, GroupLayout.PREFERRED_SIZE)))\n\t\t\t\t\t\t\t\t\t\t\t\t.addGap(20).addComponent(label19, GroupLayout.PREFERRED_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.DEFAULT_SIZE, GroupLayout.PREFERRED_SIZE))\n\t\t\t\t\t\t\t\t\t\t\t\t.addGroup(layout.createSequentialGroup().addGap(23).addComponent(\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tlabel10, GroupLayout.PREFERRED_SIZE, GroupLayout.DEFAULT_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE))))\n\t\t\t\t\t\t\t\t\t\t.addGroup(layout.createSequentialGroup()\n\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(label16, GroupLayout.PREFERRED_SIZE, 177,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t\t\t\t\t\t\t.addPreferredGap(ComponentPlacement.RELATED)\n\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(textField12, GroupLayout.PREFERRED_SIZE, 20,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t\t\t\t\t\t\t.addPreferredGap(ComponentPlacement.RELATED)\n\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(label24, GroupLayout.PREFERRED_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.DEFAULT_SIZE, GroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t\t\t\t\t\t\t.addPreferredGap(ComponentPlacement.RELATED)\n\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(textField6, GroupLayout.PREFERRED_SIZE, 20,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t\t\t\t\t\t\t.addPreferredGap(ComponentPlacement.RELATED)\n\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(label27, GroupLayout.PREFERRED_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.DEFAULT_SIZE, GroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t\t\t\t\t\t\t.addPreferredGap(ComponentPlacement.RELATED)\n\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(label25, GroupLayout.PREFERRED_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.DEFAULT_SIZE, GroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t\t\t\t\t\t\t.addPreferredGap(ComponentPlacement.RELATED)\n\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(textField11, GroupLayout.PREFERRED_SIZE, 20,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t\t\t\t\t\t\t.addPreferredGap(ComponentPlacement.RELATED)\n\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(label28, GroupLayout.PREFERRED_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.DEFAULT_SIZE, GroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t\t\t\t\t\t\t.addGap(1)\n\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(label26, GroupLayout.PREFERRED_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.DEFAULT_SIZE, GroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t\t\t\t\t\t\t.addPreferredGap(ComponentPlacement.RELATED)\n\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(textField10, GroupLayout.PREFERRED_SIZE, 20,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t\t\t\t\t\t\t.addPreferredGap(ComponentPlacement.RELATED).addComponent(label32,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE, GroupLayout.DEFAULT_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE))))\n\t\t\t\t\t\t.addComponent(label30, GroupLayout.PREFERRED_SIZE, GroupLayout.DEFAULT_SIZE,\n\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE))\n\t\t\t\t\t\t.addContainerGap(GroupLayout.DEFAULT_SIZE, Short.MAX_VALUE)));\n\t\tlayout.setVerticalGroup(\n\t\t\t\tlayout.createParallelGroup(Alignment.LEADING).addGroup(layout.createSequentialGroup().addContainerGap()\n\t\t\t\t\t\t.addGroup(layout.createParallelGroup(Alignment.TRAILING)\n\t\t\t\t\t\t\t\t.addComponent(label1, GroupLayout.PREFERRED_SIZE, GroupLayout.DEFAULT_SIZE,\n\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t\t\t.addComponent(label2, GroupLayout.PREFERRED_SIZE, GroupLayout.DEFAULT_SIZE,\n\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE))\n\t\t\t\t\t\t.addGap(1)\n\t\t\t\t\t\t.addComponent(label3, GroupLayout.PREFERRED_SIZE, GroupLayout.DEFAULT_SIZE,\n\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t.addPreferredGap(ComponentPlacement.RELATED)\n\t\t\t\t\t\t.addComponent(label4, GroupLayout.PREFERRED_SIZE, GroupLayout.DEFAULT_SIZE,\n\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t.addPreferredGap(ComponentPlacement.RELATED)\n\t\t\t\t\t\t.addComponent(label5, GroupLayout.PREFERRED_SIZE, GroupLayout.DEFAULT_SIZE,\n\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t.addPreferredGap(ComponentPlacement.RELATED)\n\t\t\t\t\t\t.addComponent(label6, GroupLayout.PREFERRED_SIZE, GroupLayout.DEFAULT_SIZE,\n\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t.addPreferredGap(ComponentPlacement.RELATED)\n\t\t\t\t\t\t.addComponent(label7, GroupLayout.PREFERRED_SIZE, GroupLayout.DEFAULT_SIZE,\n\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t.addPreferredGap(ComponentPlacement.RELATED)\n\t\t\t\t\t\t.addGroup(layout\n\t\t\t\t\t\t\t\t.createParallelGroup(\n\t\t\t\t\t\t\t\t\t\tAlignment.TRAILING)\n\t\t\t\t\t\t\t\t.addGroup(\n\t\t\t\t\t\t\t\t\t\tlayout.createSequentialGroup().addGroup(layout.createParallelGroup(\n\t\t\t\t\t\t\t\t\t\t\t\tAlignment.TRAILING)\n\t\t\t\t\t\t\t\t\t\t\t\t.addGroup(layout\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t.createSequentialGroup().addGroup(layout\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.createParallelGroup(Alignment.TRAILING).addGroup(layout\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.createParallelGroup(Alignment.LEADING)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(label9,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.DEFAULT_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addGroup(layout\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.createParallelGroup(Alignment.TRAILING)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(label8,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.DEFAULT_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(textField1,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.DEFAULT_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE))\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\ttextField2, GroupLayout.PREFERRED_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.DEFAULT_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE))\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addGroup(layout.createSequentialGroup()\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(label10,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.DEFAULT_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addGap(3)))\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addGap(19)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addGroup(layout.createParallelGroup(Alignment.TRAILING)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addGroup(layout.createParallelGroup(Alignment.LEADING)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(textField5,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.DEFAULT_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(label14,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.DEFAULT_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE))\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addGroup(layout.createSequentialGroup().addGroup(layout\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.createParallelGroup(Alignment.LEADING)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(label18,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.DEFAULT_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addGroup(layout\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.createParallelGroup(Alignment.TRAILING)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(label17,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.DEFAULT_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(textField4,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.DEFAULT_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE)))\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addGap(1))))\n\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(label20, GroupLayout.PREFERRED_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.DEFAULT_SIZE, GroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t\t\t\t\t\t\t.addGroup(layout.createParallelGroup(Alignment.LEADING)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(label19, GroupLayout.PREFERRED_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.DEFAULT_SIZE, GroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(textField3, GroupLayout.PREFERRED_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.DEFAULT_SIZE, GroupLayout.PREFERRED_SIZE)))\n\t\t\t\t\t\t\t\t\t\t\t\t.addGroup(layout.createParallelGroup(Alignment.LEADING)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addGroup(layout.createSequentialGroup().addGap(78)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(label27, GroupLayout.PREFERRED_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.DEFAULT_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE))\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addGroup(layout.createSequentialGroup().addGap(76)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(textField11, GroupLayout.PREFERRED_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.DEFAULT_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE))\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addGroup(layout.createSequentialGroup().addGap(75)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addGroup(layout.createParallelGroup(Alignment.TRAILING)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(label32,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.DEFAULT_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(textField10,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.DEFAULT_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE)))\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addGroup(layout.createSequentialGroup()\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addPreferredGap(ComponentPlacement.RELATED, 20,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tShort.MAX_VALUE)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addGroup(layout\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.createParallelGroup(Alignment.TRAILING, false)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addGroup(layout.createSequentialGroup()\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addGroup(layout\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.createParallelGroup(\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tAlignment.TRAILING)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(label15,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.DEFAULT_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(textField8,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.DEFAULT_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(label21,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.DEFAULT_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(textField7,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.DEFAULT_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE))\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addGap(27))\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addGroup(layout.createSequentialGroup()\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addGroup(layout\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.createParallelGroup(\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tAlignment.TRAILING)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(textField9,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.DEFAULT_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addGroup(layout\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.createParallelGroup(\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tAlignment.LEADING)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(label22,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.DEFAULT_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addGroup(\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tlayout.createSequentialGroup()\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addGap(3)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tlabel23,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.DEFAULT_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE))))\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addGap(29)))\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addGroup(layout.createParallelGroup(Alignment.TRAILING)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addGroup(layout\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.createParallelGroup(Alignment.LEADING)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(label16,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.DEFAULT_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(textField12,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.DEFAULT_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE))\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addGroup(layout.createSequentialGroup()\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addGroup(layout\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.createParallelGroup(\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tAlignment.TRAILING)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(label24,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.DEFAULT_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addComponent(textField6,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.DEFAULT_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE))\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t.addGap(1))))))\n\t\t\t\t\t\t\t\t.addGroup(layout.createParallelGroup(Alignment.LEADING)\n\t\t\t\t\t\t\t\t\t\t.addComponent(label25, GroupLayout.PREFERRED_SIZE, GroupLayout.DEFAULT_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t\t\t\t\t.addComponent(label28, GroupLayout.PREFERRED_SIZE, GroupLayout.DEFAULT_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t\t\t\t\t.addComponent(label26, GroupLayout.PREFERRED_SIZE, GroupLayout.DEFAULT_SIZE,\n\t\t\t\t\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE)))\n\t\t\t\t\t\t.addGap(30)\n\t\t\t\t\t\t.addComponent(label31, GroupLayout.PREFERRED_SIZE, GroupLayout.DEFAULT_SIZE,\n\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t.addGap(25)\n\t\t\t\t\t\t.addComponent(label30, GroupLayout.PREFERRED_SIZE, GroupLayout.DEFAULT_SIZE,\n\t\t\t\t\t\t\t\tGroupLayout.PREFERRED_SIZE)\n\t\t\t\t\t\t.addGap(26).addComponent(jButton1).addPreferredGap(ComponentPlacement.RELATED)\n\t\t\t\t\t\t.addComponent(getDoneButton()).addContainerGap(23, Short.MAX_VALUE)));\n\t\tthis.setLayout(layout);\n\n\t\tlabel16.getAccessibleContext().setAccessibleName(\"System.out.print( ( (\");\n\t\tlabel17.getAccessibleContext().setAccessibleName(\"\");\n\t\tlabel18.getAccessibleContext().setAccessibleName(\" +\");\n\t}","public Pregunta23() {\n initComponents();\n }","public FormMenuUser() {\n super(\"Form Menu User\");\n initComponents();\n }","public AvtekOkno() {\n initComponents();\n }","public busdet() {\n initComponents();\n }","public ViewPrescriptionForm() {\n initComponents();\n }","public Ventaform() {\n initComponents();\n }","public Kuis2() {\n initComponents();\n }","public CreateAccount_GUI() {\n initComponents();\n }","public POS1() {\n initComponents();\n }","public Carrera() {\n initComponents();\n }","public EqGUI() {\n initComponents();\n }","public JFriau() {\n initComponents();\n this.setLocationRelativeTo(null);\n this.setTitle(\"BuNus - Budaya Nusantara\");\n }","@SuppressWarnings(\"unchecked\")\n // <editor-fold defaultstate=\"collapsed\" desc=\"Generated Code\">//GEN-BEGIN:initComponents\n private void initComponents() {\n\n setBackground(new java.awt.Color(204, 204, 204));\n setMinimumSize(new java.awt.Dimension(1, 1));\n setPreferredSize(new java.awt.Dimension(760, 402));\n\n javax.swing.GroupLayout layout = new javax.swing.GroupLayout(this);\n this.setLayout(layout);\n layout.setHorizontalGroup(\n layout.createParallelGroup(javax.swing.GroupLayout.Alignment.LEADING)\n .addGap(0, 750, Short.MAX_VALUE)\n );\n layout.setVerticalGroup(\n layout.createParallelGroup(javax.swing.GroupLayout.Alignment.LEADING)\n .addGap(0, 400, Short.MAX_VALUE)\n );\n }","public nokno() {\n initComponents();\n }","public dokter() {\n initComponents();\n }","public ConverterGUI() {\n initComponents();\n }","public hitungan() {\n initComponents();\n }","public Modify() {\n initComponents();\n }","public frmAddIncidencias() {\n initComponents();\n }","public CovidGUI(){\n initComponents();\n }"],"string":"[\n \"public Form() {\\n initComponents();\\n }\",\n \"public MainForm() {\\n initComponents();\\n }\",\n \"public MainForm() {\\n initComponents();\\n }\",\n \"public MainForm() {\\n initComponents();\\n }\",\n \"public frmRectangulo() {\\n initComponents();\\n }\",\n \"public form() {\\n initComponents();\\n }\",\n \"public AdjointForm() {\\n initComponents();\\n setDefaultCloseOperation(HIDE_ON_CLOSE);\\n }\",\n \"public FormListRemarking() {\\n initComponents();\\n }\",\n \"public MainForm() {\\n initComponents();\\n \\n }\",\n \"public FormPemilihan() {\\n initComponents();\\n }\",\n \"public GUIForm() { \\n initComponents();\\n }\",\n \"public FrameForm() {\\n initComponents();\\n }\",\n \"public TorneoForm() {\\n initComponents();\\n }\",\n \"public FormCompra() {\\n initComponents();\\n }\",\n \"public muveletek() {\\n initComponents();\\n }\",\n \"public Interfax_D() {\\n initComponents();\\n }\",\n \"public quanlixe_form() {\\n initComponents();\\n }\",\n \"public SettingsForm() {\\n initComponents();\\n }\",\n \"public RegistrationForm() {\\n initComponents();\\n this.setLocationRelativeTo(null);\\n }\",\n \"public Soru1() {\\n initComponents();\\n }\",\n \"public FMainForm() {\\n initComponents();\\n this.setResizable(false);\\n setLocationRelativeTo(null);\\n }\",\n \"public soal2GUI() {\\n initComponents();\\n }\",\n \"public EindopdrachtGUI() {\\n initComponents();\\n }\",\n \"public MechanicForm() {\\n initComponents();\\n }\",\n \"public AddDocumentLineForm(java.awt.Frame parent) {\\n super(parent);\\n initComponents();\\n myInit();\\n }\",\n \"public BloodDonationGUI() {\\n initComponents();\\n }\",\n \"public quotaGUI() {\\n initComponents();\\n }\",\n \"public PatientUI() {\\n initComponents();\\n }\",\n \"public Customer_Form() {\\n initComponents();\\n setSize(890,740);\\n \\n \\n }\",\n \"public Oddeven() {\\n initComponents();\\n }\",\n \"public myForm() {\\n\\t\\t\\tinitComponents();\\n\\t\\t}\",\n \"public Magasin() {\\n initComponents();\\n }\",\n \"public intrebarea() {\\n initComponents();\\n }\",\n \"public RadioUI()\\n {\\n initComponents();\\n }\",\n \"public NewCustomerGUI() {\\n initComponents();\\n }\",\n \"public ZobrazUdalost() {\\n initComponents();\\n }\",\n \"public FormUtama() {\\n initComponents();\\n }\",\n \"public p0() {\\n initComponents();\\n }\",\n \"public INFORMACION() {\\n initComponents();\\n this.setLocationRelativeTo(null); \\n }\",\n \"public ProgramForm() {\\n setLookAndFeel();\\n initComponents();\\n }\",\n \"public AmountReleasedCommentsForm() {\\r\\n initComponents();\\r\\n }\",\n \"public form2() {\\n initComponents();\\n }\",\n \"public MainForm() {\\n\\t\\tsuper(\\\"Hospital\\\", List.IMPLICIT);\\n\\n\\t\\tstartComponents();\\n\\t}\",\n \"public kunde() {\\n initComponents();\\n }\",\n \"public LixeiraForm() {\\n initComponents();\\n setLocationRelativeTo(null);\\n }\",\n \"@SuppressWarnings(\\\"unchecked\\\")\\n // <editor-fold defaultstate=\\\"collapsed\\\" desc=\\\"Generated Code\\\">//GEN-BEGIN:initComponents\\n private void initComponents() {\\n\\n setName(\\\"Form\\\"); // NOI18N\\n setRequestFocusEnabled(false);\\n setVerifyInputWhenFocusTarget(false);\\n\\n javax.swing.GroupLayout layout = new javax.swing.GroupLayout(this);\\n this.setLayout(layout);\\n layout.setHorizontalGroup(\\n layout.createParallelGroup(javax.swing.GroupLayout.Alignment.LEADING)\\n .addGap(0, 465, Short.MAX_VALUE)\\n );\\n layout.setVerticalGroup(\\n layout.createParallelGroup(javax.swing.GroupLayout.Alignment.LEADING)\\n .addGap(0, 357, Short.MAX_VALUE)\\n );\\n }\",\n \"public MusteriEkle() {\\n initComponents();\\n }\",\n \"public frmMain() {\\n initComponents();\\n }\",\n \"public frmMain() {\\n initComponents();\\n }\",\n \"public DESHBORDPANAL() {\\n initComponents();\\n }\",\n \"public frmVenda() {\\n initComponents();\\n }\",\n \"public GUIForm() {\\n initComponents();\\n inputField.setText(NO_FILE_SELECTED);\\n outputField.setText(NO_FILE_SELECTED);\\n progressLabel.setBackground(INFO);\\n progressLabel.setText(SELECT_FILE);\\n }\",\n \"public Botonera() {\\n initComponents();\\n }\",\n \"public FrmMenu() {\\n initComponents();\\n }\",\n \"public OffertoryGUI() {\\n initComponents();\\n setTypes();\\n }\",\n \"public JFFornecedores() {\\n initComponents();\\n }\",\n \"@SuppressWarnings(\\\"unchecked\\\")\\n // <editor-fold defaultstate=\\\"collapsed\\\" desc=\\\"Generated Code\\\">//GEN-BEGIN:initComponents\\n private void initComponents()\\n {\\n\\n setDefaultCloseOperation(javax.swing.WindowConstants.EXIT_ON_CLOSE);\\n setBackground(new java.awt.Color(255, 255, 255));\\n\\n javax.swing.GroupLayout layout = new javax.swing.GroupLayout(getContentPane());\\n getContentPane().setLayout(layout);\\n layout.setHorizontalGroup(\\n layout.createParallelGroup(javax.swing.GroupLayout.Alignment.LEADING)\\n .addGap(0, 983, Short.MAX_VALUE)\\n );\\n layout.setVerticalGroup(\\n layout.createParallelGroup(javax.swing.GroupLayout.Alignment.LEADING)\\n .addGap(0, 769, Short.MAX_VALUE)\\n );\\n\\n pack();\\n }\",\n \"public EnterDetailsGUI() {\\n initComponents();\\n }\",\n \"public vpemesanan1() {\\n initComponents();\\n }\",\n \"public Kost() {\\n initComponents();\\n }\",\n \"public FormHorarioSSE() {\\n initComponents();\\n }\",\n \"public frmacceso() {\\n initComponents();\\n }\",\n \"public UploadForm() {\\n initComponents();\\n }\",\n \"public HW3() {\\n initComponents();\\n }\",\n \"public Managing_Staff_Main_Form() {\\n initComponents();\\n }\",\n \"@SuppressWarnings(\\\"unchecked\\\")\\n // <editor-fold defaultstate=\\\"collapsed\\\" desc=\\\"Generated Code\\\">//GEN-BEGIN:initComponents\\n private void initComponents()\\n {\\n\\n setDefaultCloseOperation(javax.swing.WindowConstants.EXIT_ON_CLOSE);\\n getContentPane().setLayout(null);\\n\\n pack();\\n }\",\n \"@SuppressWarnings(\\\"unchecked\\\")\\n // <editor-fold defaultstate=\\\"collapsed\\\" desc=\\\"Generated Code\\\">//GEN-BEGIN:initComponents\\n private void initComponents() {\\n\\n setName(\\\"Form\\\"); // NOI18N\\n\\n javax.swing.GroupLayout layout = new javax.swing.GroupLayout(this);\\n this.setLayout(layout);\\n layout.setHorizontalGroup(\\n layout.createParallelGroup(javax.swing.GroupLayout.Alignment.LEADING)\\n .addGap(0, 400, Short.MAX_VALUE)\\n );\\n layout.setVerticalGroup(\\n layout.createParallelGroup(javax.swing.GroupLayout.Alignment.LEADING)\\n .addGap(0, 300, Short.MAX_VALUE)\\n );\\n }\",\n \"public sinavlar2() {\\n initComponents();\\n }\",\n \"public P0405() {\\n initComponents();\\n }\",\n \"public IssueBookForm() {\\n initComponents();\\n }\",\n \"public MiFrame2() {\\n initComponents();\\n }\",\n \"public Choose1() {\\n initComponents();\\n }\",\n \"public MainForm() {\\n initComponents();\\n\\n String oldAuthor = prefs.get(\\\"AUTHOR\\\", \\\"\\\");\\n if(oldAuthor != null) {\\n this.authorTextField.setText(oldAuthor);\\n }\\n String oldBook = prefs.get(\\\"BOOK\\\", \\\"\\\");\\n if(oldBook != null) {\\n this.bookTextField.setText(oldBook);\\n }\\n String oldDisc = prefs.get(\\\"DISC\\\", \\\"\\\");\\n if(oldDisc != null) {\\n try {\\n int oldDiscNum = Integer.parseInt(oldDisc);\\n oldDiscNum++;\\n this.discNumberTextField.setText(Integer.toString(oldDiscNum));\\n } catch (Exception ex) {\\n this.discNumberTextField.setText(oldDisc);\\n }\\n this.bookTextField.setText(oldBook);\\n }\\n\\n\\n }\",\n \"public GUI_StudentInfo() {\\n initComponents();\\n }\",\n \"public Lihat_Dokter_Keseluruhan() {\\n initComponents();\\n }\",\n \"public JFrmPrincipal() {\\n initComponents();\\n }\",\n \"public bt526() {\\n initComponents();\\n }\",\n \"public Pemilihan_Dokter() {\\n initComponents();\\n }\",\n \"public Ablak() {\\n initComponents();\\n }\",\n \"@Override\\n\\tprotected void initUi() {\\n\\t\\t\\n\\t}\",\n \"@SuppressWarnings(\\\"unchecked\\\")\\n\\t// <editor-fold defaultstate=\\\"collapsed\\\" desc=\\\"Generated\\n\\t// Code\\\">//GEN-BEGIN:initComponents\\n\\tprivate void initComponents() {\\n\\n\\t\\tlabel1 = new java.awt.Label();\\n\\t\\tlabel2 = new java.awt.Label();\\n\\t\\tlabel3 = new java.awt.Label();\\n\\t\\tlabel4 = new java.awt.Label();\\n\\t\\tlabel5 = new java.awt.Label();\\n\\t\\tlabel6 = new java.awt.Label();\\n\\t\\tlabel7 = new java.awt.Label();\\n\\t\\tlabel8 = new java.awt.Label();\\n\\t\\tlabel9 = new java.awt.Label();\\n\\t\\tlabel10 = new java.awt.Label();\\n\\t\\ttextField1 = new java.awt.TextField();\\n\\t\\ttextField2 = new java.awt.TextField();\\n\\t\\tlabel14 = new java.awt.Label();\\n\\t\\tlabel15 = new java.awt.Label();\\n\\t\\tlabel16 = new java.awt.Label();\\n\\t\\ttextField3 = new java.awt.TextField();\\n\\t\\ttextField4 = new java.awt.TextField();\\n\\t\\ttextField5 = new java.awt.TextField();\\n\\t\\tlabel17 = new java.awt.Label();\\n\\t\\tlabel18 = new java.awt.Label();\\n\\t\\tlabel19 = new java.awt.Label();\\n\\t\\tlabel20 = new java.awt.Label();\\n\\t\\tlabel21 = new java.awt.Label();\\n\\t\\tlabel22 = new java.awt.Label();\\n\\t\\ttextField6 = new java.awt.TextField();\\n\\t\\ttextField7 = new java.awt.TextField();\\n\\t\\ttextField8 = new java.awt.TextField();\\n\\t\\tlabel23 = new java.awt.Label();\\n\\t\\ttextField9 = new java.awt.TextField();\\n\\t\\ttextField10 = new java.awt.TextField();\\n\\t\\ttextField11 = new java.awt.TextField();\\n\\t\\ttextField12 = new java.awt.TextField();\\n\\t\\tlabel24 = new java.awt.Label();\\n\\t\\tlabel25 = new java.awt.Label();\\n\\t\\tlabel26 = new java.awt.Label();\\n\\t\\tlabel27 = new java.awt.Label();\\n\\t\\tlabel28 = new java.awt.Label();\\n\\t\\tlabel30 = new java.awt.Label();\\n\\t\\tlabel31 = new java.awt.Label();\\n\\t\\tlabel32 = new java.awt.Label();\\n\\t\\tjButton1 = new javax.swing.JButton();\\n\\n\\t\\tlabel1.setFont(new java.awt.Font(\\\"Segoe UI Semibold\\\", 0, 18)); // NOI18N\\n\\t\\tlabel1.setText(\\\"It seems that some of the buttons on the ATM machine are not working!\\\");\\n\\n\\t\\tlabel2.setFont(new java.awt.Font(\\\"Segoe UI Semibold\\\", 0, 18)); // NOI18N\\n\\t\\tlabel2.setText(\\\"Unfortunately these numbers are exactly what Professor has to use to type in his password.\\\");\\n\\n\\t\\tlabel3.setFont(new java.awt.Font(\\\"Segoe UI Semibold\\\", 0, 18)); // NOI18N\\n\\t\\tlabel3.setText(\\n\\t\\t\\t\\t\\\"If you want to eat tonight, you have to help him out and construct the numbers of the password with the working buttons and math operators.\\\");\\n\\n\\t\\tlabel4.setFont(new java.awt.Font(\\\"Segoe UI Semibold\\\", 0, 14)); // NOI18N\\n\\t\\tlabel4.setText(\\\"Denver's Password: 2792\\\");\\n\\n\\t\\tlabel5.setFont(new java.awt.Font(\\\"Consolas\\\", 0, 14)); // NOI18N\\n\\t\\tlabel5.setText(\\\"import java.util.Scanner;\\\\n\\\");\\n\\n\\t\\tlabel6.setFont(new java.awt.Font(\\\"Consolas\\\", 0, 14)); // NOI18N\\n\\t\\tlabel6.setText(\\\"public class ATM{\\\");\\n\\n\\t\\tlabel7.setFont(new java.awt.Font(\\\"Consolas\\\", 0, 14)); // NOI18N\\n\\t\\tlabel7.setText(\\\"public static void main(String[] args){\\\");\\n\\n\\t\\tlabel8.setFont(new java.awt.Font(\\\"Consolas\\\", 0, 14)); // NOI18N\\n\\t\\tlabel8.setText(\\\"System.out.print(\\\");\\n\\n\\t\\tlabel9.setFont(new java.awt.Font(\\\"Dialog\\\", 0, 14)); // NOI18N\\n\\t\\tlabel9.setText(\\\" -\\\");\\n\\n\\t\\tlabel10.setFont(new java.awt.Font(\\\"Consolas\\\", 0, 14)); // NOI18N\\n\\t\\tlabel10.setText(\\\");\\\");\\n\\n\\t\\ttextField1.addActionListener(new java.awt.event.ActionListener() {\\n\\t\\t\\tpublic void actionPerformed(java.awt.event.ActionEvent evt) {\\n\\t\\t\\t\\ttextField1ActionPerformed(evt);\\n\\t\\t\\t}\\n\\t\\t});\\n\\n\\t\\tlabel14.setFont(new java.awt.Font(\\\"Consolas\\\", 0, 14)); // NOI18N\\n\\t\\tlabel14.setText(\\\"System.out.print( (\\\");\\n\\n\\t\\tlabel15.setFont(new java.awt.Font(\\\"Consolas\\\", 0, 14)); // NOI18N\\n\\t\\tlabel15.setText(\\\"System.out.print(\\\");\\n\\n\\t\\tlabel16.setFont(new java.awt.Font(\\\"Consolas\\\", 0, 14)); // NOI18N\\n\\t\\tlabel16.setText(\\\"System.out.print( ( (\\\");\\n\\n\\t\\tlabel17.setFont(new java.awt.Font(\\\"Dialog\\\", 0, 14)); // NOI18N\\n\\t\\tlabel17.setText(\\\")\\\");\\n\\n\\t\\tlabel18.setFont(new java.awt.Font(\\\"Dialog\\\", 0, 14)); // NOI18N\\n\\t\\tlabel18.setText(\\\" +\\\");\\n\\n\\t\\tlabel19.setFont(new java.awt.Font(\\\"Consolas\\\", 0, 14)); // NOI18N\\n\\t\\tlabel19.setText(\\\");\\\");\\n\\n\\t\\tlabel20.setFont(new java.awt.Font(\\\"Dialog\\\", 0, 14)); // NOI18N\\n\\t\\tlabel20.setText(\\\" /\\\");\\n\\n\\t\\tlabel21.setFont(new java.awt.Font(\\\"Dialog\\\", 0, 14)); // NOI18N\\n\\t\\tlabel21.setText(\\\" %\\\");\\n\\n\\t\\tlabel22.setFont(new java.awt.Font(\\\"Dialog\\\", 0, 14)); // NOI18N\\n\\t\\tlabel22.setText(\\\" +\\\");\\n\\n\\t\\tlabel23.setFont(new java.awt.Font(\\\"Consolas\\\", 0, 14)); // NOI18N\\n\\t\\tlabel23.setText(\\\");\\\");\\n\\n\\t\\tlabel24.setFont(new java.awt.Font(\\\"Dialog\\\", 0, 14)); // NOI18N\\n\\t\\tlabel24.setText(\\\" +\\\");\\n\\n\\t\\tlabel25.setFont(new java.awt.Font(\\\"Dialog\\\", 0, 14)); // NOI18N\\n\\t\\tlabel25.setText(\\\" /\\\");\\n\\n\\t\\tlabel26.setFont(new java.awt.Font(\\\"Dialog\\\", 0, 14)); // NOI18N\\n\\t\\tlabel26.setText(\\\" *\\\");\\n\\n\\t\\tlabel27.setCursor(new java.awt.Cursor(java.awt.Cursor.DEFAULT_CURSOR));\\n\\t\\tlabel27.setFont(new java.awt.Font(\\\"Consolas\\\", 0, 14)); // NOI18N\\n\\t\\tlabel27.setText(\\\")\\\");\\n\\n\\t\\tlabel28.setFont(new java.awt.Font(\\\"Dialog\\\", 0, 14)); // NOI18N\\n\\t\\tlabel28.setText(\\\")\\\");\\n\\n\\t\\tlabel30.setFont(new java.awt.Font(\\\"Consolas\\\", 0, 14)); // NOI18N\\n\\t\\tlabel30.setText(\\\"}\\\");\\n\\n\\t\\tlabel31.setFont(new java.awt.Font(\\\"Consolas\\\", 0, 14)); // NOI18N\\n\\t\\tlabel31.setText(\\\"}\\\");\\n\\n\\t\\tlabel32.setFont(new java.awt.Font(\\\"Consolas\\\", 0, 14)); // NOI18N\\n\\t\\tlabel32.setText(\\\");\\\");\\n\\n\\t\\tjButton1.setFont(new java.awt.Font(\\\"Segoe UI Semibold\\\", 0, 14)); // NOI18N\\n\\t\\tjButton1.setText(\\\"Check\\\");\\n\\t\\tjButton1.addActionListener(new java.awt.event.ActionListener() {\\n\\t\\t\\tpublic void actionPerformed(java.awt.event.ActionEvent evt) {\\n\\t\\t\\t\\tjButton1ActionPerformed(evt);\\n\\t\\t\\t}\\n\\t\\t});\\n\\n\\t\\tjavax.swing.GroupLayout layout = new javax.swing.GroupLayout(this);\\n\\t\\tlayout.setHorizontalGroup(layout.createParallelGroup(Alignment.LEADING)\\n\\t\\t\\t\\t.addGroup(layout.createSequentialGroup().addGap(28).addGroup(layout\\n\\t\\t\\t\\t\\t\\t.createParallelGroup(Alignment.LEADING).addComponent(getDoneButton()).addComponent(jButton1)\\n\\t\\t\\t\\t\\t\\t.addComponent(label7, GroupLayout.PREFERRED_SIZE, GroupLayout.DEFAULT_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t.addComponent(label6, GroupLayout.PREFERRED_SIZE, GroupLayout.DEFAULT_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t.addComponent(label5, GroupLayout.PREFERRED_SIZE, GroupLayout.DEFAULT_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t.addComponent(label4, GroupLayout.PREFERRED_SIZE, GroupLayout.DEFAULT_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t.addComponent(label3, GroupLayout.PREFERRED_SIZE, GroupLayout.DEFAULT_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t.addGroup(layout.createSequentialGroup()\\n\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(label1, GroupLayout.PREFERRED_SIZE, GroupLayout.DEFAULT_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t\\t\\t.addGap(1)\\n\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(label2, GroupLayout.PREFERRED_SIZE, 774, GroupLayout.PREFERRED_SIZE))\\n\\t\\t\\t\\t\\t\\t.addGroup(layout.createSequentialGroup()\\n\\t\\t\\t\\t\\t\\t\\t\\t.addGap(92).addGroup(layout.createParallelGroup(Alignment.LEADING).addGroup(layout\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.createSequentialGroup()\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addGroup(layout.createParallelGroup(Alignment.LEADING, false)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addGroup(layout.createSequentialGroup()\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(label15, GroupLayout.PREFERRED_SIZE, 145,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addPreferredGap(ComponentPlacement.RELATED)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(textField8, GroupLayout.PREFERRED_SIZE, 20,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addGap(2)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(label21, GroupLayout.PREFERRED_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.DEFAULT_SIZE, GroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addPreferredGap(ComponentPlacement.RELATED,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.DEFAULT_SIZE, Short.MAX_VALUE)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(textField7, GroupLayout.PREFERRED_SIZE, 20,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE))\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addGroup(layout.createSequentialGroup()\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(label8, GroupLayout.PREFERRED_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.DEFAULT_SIZE, GroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addPreferredGap(ComponentPlacement.RELATED)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(textField1, GroupLayout.PREFERRED_SIZE, 20,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addPreferredGap(ComponentPlacement.RELATED)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(label9, GroupLayout.PREFERRED_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.DEFAULT_SIZE, GroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addPreferredGap(ComponentPlacement.RELATED).addComponent(\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\ttextField2, GroupLayout.PREFERRED_SIZE, 20,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE))\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(label31, GroupLayout.PREFERRED_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.DEFAULT_SIZE, GroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addGroup(layout.createSequentialGroup().addGroup(layout\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.createParallelGroup(Alignment.LEADING)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addGroup(layout.createSequentialGroup()\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(label14, GroupLayout.DEFAULT_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.DEFAULT_SIZE, Short.MAX_VALUE)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addGap(37))\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addGroup(layout.createSequentialGroup().addGap(174)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(textField5, GroupLayout.PREFERRED_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t20, GroupLayout.PREFERRED_SIZE)))\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(label18, GroupLayout.PREFERRED_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.DEFAULT_SIZE, GroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addGap(7)))\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addPreferredGap(ComponentPlacement.RELATED)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addGroup(layout.createParallelGroup(Alignment.LEADING).addGroup(layout\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.createSequentialGroup()\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addGroup(layout\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.createParallelGroup(Alignment.TRAILING, false).addGroup(layout\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.createSequentialGroup()\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(textField4, GroupLayout.PREFERRED_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t20, GroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addPreferredGap(ComponentPlacement.RELATED,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.DEFAULT_SIZE, Short.MAX_VALUE)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(label17, GroupLayout.PREFERRED_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.DEFAULT_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE))\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addGroup(layout.createSequentialGroup()\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(label22, GroupLayout.PREFERRED_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.DEFAULT_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addPreferredGap(ComponentPlacement.RELATED)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(textField9, GroupLayout.PREFERRED_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t20, GroupLayout.PREFERRED_SIZE)))\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addGap(20)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addGroup(layout.createParallelGroup(Alignment.TRAILING)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(label23, GroupLayout.PREFERRED_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.DEFAULT_SIZE, GroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addGroup(layout.createSequentialGroup()\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(label20, GroupLayout.PREFERRED_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.DEFAULT_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addPreferredGap(ComponentPlacement.RELATED)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(textField3, GroupLayout.PREFERRED_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t20, GroupLayout.PREFERRED_SIZE)))\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addGap(20).addComponent(label19, GroupLayout.PREFERRED_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.DEFAULT_SIZE, GroupLayout.PREFERRED_SIZE))\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addGroup(layout.createSequentialGroup().addGap(23).addComponent(\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tlabel10, GroupLayout.PREFERRED_SIZE, GroupLayout.DEFAULT_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE))))\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addGroup(layout.createSequentialGroup()\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(label16, GroupLayout.PREFERRED_SIZE, 177,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addPreferredGap(ComponentPlacement.RELATED)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(textField12, GroupLayout.PREFERRED_SIZE, 20,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addPreferredGap(ComponentPlacement.RELATED)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(label24, GroupLayout.PREFERRED_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.DEFAULT_SIZE, GroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addPreferredGap(ComponentPlacement.RELATED)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(textField6, GroupLayout.PREFERRED_SIZE, 20,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addPreferredGap(ComponentPlacement.RELATED)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(label27, GroupLayout.PREFERRED_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.DEFAULT_SIZE, GroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addPreferredGap(ComponentPlacement.RELATED)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(label25, GroupLayout.PREFERRED_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.DEFAULT_SIZE, GroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addPreferredGap(ComponentPlacement.RELATED)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(textField11, GroupLayout.PREFERRED_SIZE, 20,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addPreferredGap(ComponentPlacement.RELATED)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(label28, GroupLayout.PREFERRED_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.DEFAULT_SIZE, GroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addGap(1)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(label26, GroupLayout.PREFERRED_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.DEFAULT_SIZE, GroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addPreferredGap(ComponentPlacement.RELATED)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(textField10, GroupLayout.PREFERRED_SIZE, 20,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addPreferredGap(ComponentPlacement.RELATED).addComponent(label32,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE, GroupLayout.DEFAULT_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE))))\\n\\t\\t\\t\\t\\t\\t.addComponent(label30, GroupLayout.PREFERRED_SIZE, GroupLayout.DEFAULT_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE))\\n\\t\\t\\t\\t\\t\\t.addContainerGap(GroupLayout.DEFAULT_SIZE, Short.MAX_VALUE)));\\n\\t\\tlayout.setVerticalGroup(\\n\\t\\t\\t\\tlayout.createParallelGroup(Alignment.LEADING).addGroup(layout.createSequentialGroup().addContainerGap()\\n\\t\\t\\t\\t\\t\\t.addGroup(layout.createParallelGroup(Alignment.TRAILING)\\n\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(label1, GroupLayout.PREFERRED_SIZE, GroupLayout.DEFAULT_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(label2, GroupLayout.PREFERRED_SIZE, GroupLayout.DEFAULT_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE))\\n\\t\\t\\t\\t\\t\\t.addGap(1)\\n\\t\\t\\t\\t\\t\\t.addComponent(label3, GroupLayout.PREFERRED_SIZE, GroupLayout.DEFAULT_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t.addPreferredGap(ComponentPlacement.RELATED)\\n\\t\\t\\t\\t\\t\\t.addComponent(label4, GroupLayout.PREFERRED_SIZE, GroupLayout.DEFAULT_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t.addPreferredGap(ComponentPlacement.RELATED)\\n\\t\\t\\t\\t\\t\\t.addComponent(label5, GroupLayout.PREFERRED_SIZE, GroupLayout.DEFAULT_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t.addPreferredGap(ComponentPlacement.RELATED)\\n\\t\\t\\t\\t\\t\\t.addComponent(label6, GroupLayout.PREFERRED_SIZE, GroupLayout.DEFAULT_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t.addPreferredGap(ComponentPlacement.RELATED)\\n\\t\\t\\t\\t\\t\\t.addComponent(label7, GroupLayout.PREFERRED_SIZE, GroupLayout.DEFAULT_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t.addPreferredGap(ComponentPlacement.RELATED)\\n\\t\\t\\t\\t\\t\\t.addGroup(layout\\n\\t\\t\\t\\t\\t\\t\\t\\t.createParallelGroup(\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tAlignment.TRAILING)\\n\\t\\t\\t\\t\\t\\t\\t\\t.addGroup(\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tlayout.createSequentialGroup().addGroup(layout.createParallelGroup(\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tAlignment.TRAILING)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addGroup(layout\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.createSequentialGroup().addGroup(layout\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.createParallelGroup(Alignment.TRAILING).addGroup(layout\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.createParallelGroup(Alignment.LEADING)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(label9,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.DEFAULT_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addGroup(layout\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.createParallelGroup(Alignment.TRAILING)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(label8,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.DEFAULT_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(textField1,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.DEFAULT_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE))\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\ttextField2, GroupLayout.PREFERRED_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.DEFAULT_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE))\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addGroup(layout.createSequentialGroup()\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(label10,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.DEFAULT_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addGap(3)))\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addGap(19)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addGroup(layout.createParallelGroup(Alignment.TRAILING)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addGroup(layout.createParallelGroup(Alignment.LEADING)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(textField5,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.DEFAULT_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(label14,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.DEFAULT_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE))\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addGroup(layout.createSequentialGroup().addGroup(layout\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.createParallelGroup(Alignment.LEADING)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(label18,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.DEFAULT_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addGroup(layout\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.createParallelGroup(Alignment.TRAILING)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(label17,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.DEFAULT_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(textField4,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.DEFAULT_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE)))\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addGap(1))))\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(label20, GroupLayout.PREFERRED_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.DEFAULT_SIZE, GroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addGroup(layout.createParallelGroup(Alignment.LEADING)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(label19, GroupLayout.PREFERRED_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.DEFAULT_SIZE, GroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(textField3, GroupLayout.PREFERRED_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.DEFAULT_SIZE, GroupLayout.PREFERRED_SIZE)))\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addGroup(layout.createParallelGroup(Alignment.LEADING)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addGroup(layout.createSequentialGroup().addGap(78)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(label27, GroupLayout.PREFERRED_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.DEFAULT_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE))\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addGroup(layout.createSequentialGroup().addGap(76)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(textField11, GroupLayout.PREFERRED_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.DEFAULT_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE))\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addGroup(layout.createSequentialGroup().addGap(75)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addGroup(layout.createParallelGroup(Alignment.TRAILING)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(label32,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.DEFAULT_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(textField10,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.DEFAULT_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE)))\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addGroup(layout.createSequentialGroup()\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addPreferredGap(ComponentPlacement.RELATED, 20,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tShort.MAX_VALUE)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addGroup(layout\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.createParallelGroup(Alignment.TRAILING, false)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addGroup(layout.createSequentialGroup()\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addGroup(layout\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.createParallelGroup(\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tAlignment.TRAILING)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(label15,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.DEFAULT_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(textField8,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.DEFAULT_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(label21,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.DEFAULT_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(textField7,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.DEFAULT_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE))\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addGap(27))\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addGroup(layout.createSequentialGroup()\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addGroup(layout\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.createParallelGroup(\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tAlignment.TRAILING)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(textField9,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.DEFAULT_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addGroup(layout\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.createParallelGroup(\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tAlignment.LEADING)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(label22,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.DEFAULT_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addGroup(\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tlayout.createSequentialGroup()\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addGap(3)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tlabel23,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.DEFAULT_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE))))\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addGap(29)))\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addGroup(layout.createParallelGroup(Alignment.TRAILING)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addGroup(layout\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.createParallelGroup(Alignment.LEADING)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(label16,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.DEFAULT_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(textField12,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.DEFAULT_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE))\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addGroup(layout.createSequentialGroup()\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addGroup(layout\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.createParallelGroup(\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tAlignment.TRAILING)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(label24,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.DEFAULT_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(textField6,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.DEFAULT_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE))\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addGap(1))))))\\n\\t\\t\\t\\t\\t\\t\\t\\t.addGroup(layout.createParallelGroup(Alignment.LEADING)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(label25, GroupLayout.PREFERRED_SIZE, GroupLayout.DEFAULT_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(label28, GroupLayout.PREFERRED_SIZE, GroupLayout.DEFAULT_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t.addComponent(label26, GroupLayout.PREFERRED_SIZE, GroupLayout.DEFAULT_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE)))\\n\\t\\t\\t\\t\\t\\t.addGap(30)\\n\\t\\t\\t\\t\\t\\t.addComponent(label31, GroupLayout.PREFERRED_SIZE, GroupLayout.DEFAULT_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t.addGap(25)\\n\\t\\t\\t\\t\\t\\t.addComponent(label30, GroupLayout.PREFERRED_SIZE, GroupLayout.DEFAULT_SIZE,\\n\\t\\t\\t\\t\\t\\t\\t\\tGroupLayout.PREFERRED_SIZE)\\n\\t\\t\\t\\t\\t\\t.addGap(26).addComponent(jButton1).addPreferredGap(ComponentPlacement.RELATED)\\n\\t\\t\\t\\t\\t\\t.addComponent(getDoneButton()).addContainerGap(23, Short.MAX_VALUE)));\\n\\t\\tthis.setLayout(layout);\\n\\n\\t\\tlabel16.getAccessibleContext().setAccessibleName(\\\"System.out.print( ( (\\\");\\n\\t\\tlabel17.getAccessibleContext().setAccessibleName(\\\"\\\");\\n\\t\\tlabel18.getAccessibleContext().setAccessibleName(\\\" +\\\");\\n\\t}\",\n \"public Pregunta23() {\\n initComponents();\\n }\",\n \"public FormMenuUser() {\\n super(\\\"Form Menu User\\\");\\n initComponents();\\n }\",\n \"public AvtekOkno() {\\n initComponents();\\n }\",\n \"public busdet() {\\n initComponents();\\n }\",\n \"public ViewPrescriptionForm() {\\n initComponents();\\n }\",\n \"public Ventaform() {\\n initComponents();\\n }\",\n \"public Kuis2() {\\n initComponents();\\n }\",\n \"public CreateAccount_GUI() {\\n initComponents();\\n }\",\n \"public POS1() {\\n initComponents();\\n }\",\n \"public Carrera() {\\n initComponents();\\n }\",\n \"public EqGUI() {\\n initComponents();\\n }\",\n \"public JFriau() {\\n initComponents();\\n this.setLocationRelativeTo(null);\\n this.setTitle(\\\"BuNus - Budaya Nusantara\\\");\\n }\",\n \"@SuppressWarnings(\\\"unchecked\\\")\\n // <editor-fold defaultstate=\\\"collapsed\\\" desc=\\\"Generated Code\\\">//GEN-BEGIN:initComponents\\n private void initComponents() {\\n\\n setBackground(new java.awt.Color(204, 204, 204));\\n setMinimumSize(new java.awt.Dimension(1, 1));\\n setPreferredSize(new java.awt.Dimension(760, 402));\\n\\n javax.swing.GroupLayout layout = new javax.swing.GroupLayout(this);\\n this.setLayout(layout);\\n layout.setHorizontalGroup(\\n layout.createParallelGroup(javax.swing.GroupLayout.Alignment.LEADING)\\n .addGap(0, 750, Short.MAX_VALUE)\\n );\\n layout.setVerticalGroup(\\n layout.createParallelGroup(javax.swing.GroupLayout.Alignment.LEADING)\\n .addGap(0, 400, Short.MAX_VALUE)\\n );\\n }\",\n \"public nokno() {\\n initComponents();\\n }\",\n \"public dokter() {\\n initComponents();\\n }\",\n \"public ConverterGUI() {\\n initComponents();\\n }\",\n \"public hitungan() {\\n initComponents();\\n }\",\n \"public Modify() {\\n initComponents();\\n }\",\n \"public frmAddIncidencias() {\\n initComponents();\\n }\",\n \"public CovidGUI(){\\n initComponents();\\n }\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.73206544","0.7291311","0.7291311","0.7291311","0.7286492","0.7249181","0.7213362","0.72085494","0.71965617","0.7190475","0.7184897","0.7159234","0.71483016","0.7094075","0.7081491","0.70579433","0.6987627","0.69776064","0.69552463","0.69549114","0.69453007","0.69439274","0.69369227","0.6932056","0.6927733","0.6925948","0.69254535","0.69121534","0.6911907","0.6894101","0.6892413","0.68919593","0.6891924","0.6889863","0.6884052","0.6883223","0.688166","0.68787736","0.68764126","0.68745583","0.68721986","0.68595314","0.685675","0.68565613","0.6855288","0.6854687","0.6854457","0.685303","0.685303","0.68448347","0.6837389","0.6837193","0.6829965","0.6829964","0.68275386","0.68249714","0.6823691","0.6818224","0.68173605","0.6811417","0.6809674","0.680964","0.6809329","0.68085754","0.6802194","0.67955625","0.67938477","0.6793322","0.679176","0.67900634","0.6789749","0.67888486","0.6781942","0.6767308","0.6766431","0.6765252","0.67573947","0.6756327","0.6753509","0.67520833","0.6741834","0.6740361","0.6737793","0.67370224","0.6734898","0.6727867","0.6727453","0.67214817","0.6716735","0.67162156","0.6715855","0.6709997","0.6707508","0.67042965","0.6702483","0.67014945","0.67007315","0.6699097","0.669545","0.6692102","0.6690473"],"string":"[\n \"0.73206544\",\n \"0.7291311\",\n \"0.7291311\",\n \"0.7291311\",\n \"0.7286492\",\n \"0.7249181\",\n \"0.7213362\",\n \"0.72085494\",\n \"0.71965617\",\n \"0.7190475\",\n \"0.7184897\",\n \"0.7159234\",\n \"0.71483016\",\n \"0.7094075\",\n \"0.7081491\",\n \"0.70579433\",\n \"0.6987627\",\n \"0.69776064\",\n \"0.69552463\",\n \"0.69549114\",\n \"0.69453007\",\n \"0.69439274\",\n \"0.69369227\",\n \"0.6932056\",\n \"0.6927733\",\n \"0.6925948\",\n \"0.69254535\",\n \"0.69121534\",\n \"0.6911907\",\n \"0.6894101\",\n \"0.6892413\",\n \"0.68919593\",\n \"0.6891924\",\n \"0.6889863\",\n \"0.6884052\",\n \"0.6883223\",\n \"0.688166\",\n \"0.68787736\",\n \"0.68764126\",\n \"0.68745583\",\n \"0.68721986\",\n \"0.68595314\",\n \"0.685675\",\n \"0.68565613\",\n \"0.6855288\",\n \"0.6854687\",\n \"0.6854457\",\n \"0.685303\",\n \"0.685303\",\n \"0.68448347\",\n \"0.6837389\",\n \"0.6837193\",\n \"0.6829965\",\n \"0.6829964\",\n \"0.68275386\",\n \"0.68249714\",\n \"0.6823691\",\n \"0.6818224\",\n \"0.68173605\",\n \"0.6811417\",\n \"0.6809674\",\n \"0.680964\",\n \"0.6809329\",\n \"0.68085754\",\n \"0.6802194\",\n \"0.67955625\",\n \"0.67938477\",\n \"0.6793322\",\n \"0.679176\",\n \"0.67900634\",\n \"0.6789749\",\n \"0.67888486\",\n \"0.6781942\",\n \"0.6767308\",\n \"0.6766431\",\n \"0.6765252\",\n \"0.67573947\",\n \"0.6756327\",\n \"0.6753509\",\n \"0.67520833\",\n \"0.6741834\",\n \"0.6740361\",\n \"0.6737793\",\n \"0.67370224\",\n \"0.6734898\",\n \"0.6727867\",\n \"0.6727453\",\n \"0.67214817\",\n \"0.6716735\",\n \"0.67162156\",\n \"0.6715855\",\n \"0.6709997\",\n \"0.6707508\",\n \"0.67042965\",\n \"0.6702483\",\n \"0.67014945\",\n \"0.67007315\",\n \"0.6699097\",\n \"0.669545\",\n \"0.6692102\",\n \"0.6690473\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}},{"rowIdx":13899,"cells":{"query":{"kind":"string","value":"TODO Autogenerated method stub"},"document":{"kind":"string","value":"public void addUser(User user) {\n\t\tuserMapper.insert(user);\n\n\t}"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["@Override\r\n\tpublic void comer() \r\n\t{\n\t\t\r\n\t}","@Override\n\tpublic void comer() {\n\t\t\n\t}","@Override\n public void perish() {\n \n }","@Override\r\n\t\t\tpublic void annadir() {\n\r\n\t\t\t}","@Override\n\tpublic void anular() {\n\n\t}","@Override\n\tprotected void getExras() {\n\n\t}","@Override\r\n\tpublic void anularFact() {\n\t\t\r\n\t}","@Override\n\tpublic void entrenar() {\n\t\t\n\t}","@Override\n\tpublic void nadar() {\n\t\t\n\t}","@Override\r\n\tpublic void tires() {\n\t\t\r\n\t}","@Override\r\n\t\t\tpublic void ayuda() {\n\r\n\t\t\t}","@Override\n\tprotected void interr() {\n\t}","@Override\n\tpublic void emprestimo() {\n\n\t}","@Override\r\n\tpublic void bicar() {\n\t\t\r\n\t}","@Override\r\n\tpublic void bicar() {\n\t\t\r\n\t}","@Override\n\tpublic void grabar() {\n\t\t\n\t}","@Override\n\tpublic void gravarBd() {\n\t\t\n\t}","@Override\r\n\tpublic void rozmnozovat() {\n\t}","@Override\r\n\tpublic void dormir() {\n\t\t\r\n\t}","@Override\n protected void getExras() {\n }","@Override\r\n\tpublic void publierEnchere() {\n\t\t\r\n\t}","@Override\n\tpublic void nefesAl() {\n\n\t}","@Override\n\tpublic void ligar() {\n\t\t\n\t}","@Override\n public void func_104112_b() {\n \n }","@Override\n\tprotected void initdata() {\n\n\t}","@Override\n\tpublic void nghe() {\n\n\t}","@Override\n public void function()\n {\n }","@Override\n public void function()\n {\n }","public final void mo51373a() {\n }","@Override\r\n\tpublic void stehReagieren() {\r\n\t\t//\r\n\t}","@Override\n public void inizializza() {\n\n super.inizializza();\n }","@Override\n\tprotected void initData() {\n\t\t\n\t}","@Override\r\n\t\tpublic void init() {\n\t\t\t\r\n\t\t}","@Override\n\tpublic void sacrifier() {\n\t\t\n\t}","@Override\r\n\tprotected void InitData() {\n\t\t\r\n\t}","public void designBasement() {\n\t\t\r\n\t}","@Override\r\n\tprotected void initialize() {\r\n\t\t\r\n\t\t\r\n\t}","public void gored() {\n\t\t\n\t}","@Override\r\n\tprotected void initData() {\n\r\n\t}","@Override\n\tpublic void einkaufen() {\n\t}","@Override\n protected void initialize() {\n\n \n }","public void mo38117a() {\n }","@Override\n\tprotected void getData() {\n\t\t\n\t}","Constructor() {\r\n\t\t \r\n\t }","@Override\r\n\tpublic void dibujar() {\n\t\t\r\n\t}","@Override\r\n\tpublic void dibujar() {\n\t\t\r\n\t}","@Override\n\tpublic void one() {\n\t\t\n\t}","@Override\r\n\tprotected void initData() {\n\t\t\r\n\t}","@Override\r\n\tprotected void initData() {\n\t\t\r\n\t}","@Override\r\n\tprotected void initData() {\n\t\t\r\n\t}","@Override\r\n\tprotected void initData() {\n\t\t\r\n\t}","@Override\r\n\tprotected void initData() {\n\t\t\r\n\t}","@Override\r\n\tprotected void initData() {\n\t\t\r\n\t}","private stendhal() {\n\t}","@Override\n\tprotected void update() {\n\t\t\n\t}","@Override\n\t\t\tpublic void ic() {\n\t\t\t\t\n\t\t\t}","@Override\n\tprotected void initData() {\n\n\t}","@Override\n\tprotected void initData() {\n\n\t}","@Override\n\tpublic void init() {\n\t\t\n\t}","@Override\n\tpublic void init() {\n\t\t\n\t}","@Override\n\tpublic void init() {\n\t\t\n\t}","@Override\n\tpublic void init() {\n\t\t\n\t}","@Override\n\tpublic void init() {\n\t\t\n\t}","@Override\n public void init() {\n\n }","@Override\n\tprotected void initialize() {\n\t\t\n\t}","@Override\n\tprotected void initialize() {\n\t\t\n\t}","@Override\r\n\tpublic void init() {\n\t\t\r\n\t}","@Override\r\n\tpublic void init() {\n\t\t\r\n\t}","@Override\r\n\tpublic void init() {\n\t\t\r\n\t}","@Override\n\tpublic void debite() {\n\t\t\n\t}","@Override\r\n\tpublic void init() {\n\r\n\t}","@Override\r\n\tpublic void init() {\n\r\n\t}","@Override\r\n\tpublic void init() {\n\r\n\t}","public contrustor(){\r\n\t}","@Override\n\tprotected void initialize() {\n\n\t}","@Override\r\n\tpublic void dispase() {\n\r\n\t}","public void mo55254a() {\n }","public void mo55254a() {\n }","public void mo55254a() {\n }","public void mo55254a() {\n }","public void mo55254a() {\n }","public void mo55254a() {\n }","public void mo55254a() {\n }","@Override\n\tpublic void dtd() {\n\t\t\n\t}","@Override\n\tprotected void logic() {\n\n\t}","@Override\n\tprotected void lazyLoad() {\n\t\t\n\t}","public void mo4359a() {\n }","@Override\r\n\tprotected void initialize() {\n\r\n\t}","@Override\n public void memoria() {\n \n }","@Override\n\t\tpublic void method() {\n\t\t\t\n\t\t}","private RepositorioAtendimentoPublicoHBM() {\r\t}","@Override\n protected void initialize() \n {\n \n }","@Override\r\n\tpublic void getProposition() {\n\r\n\t}","@Override\n\tpublic void particular1() {\n\t\t\n\t}","@Override\n\tpublic void init() {\n\n\t}","@Override\n\tpublic void init() {\n\n\t}","@Override\n\tpublic void init() {\n\n\t}","@Override\n protected void prot() {\n }","@Override\r\n\tpublic void init()\r\n\t{\n\t}","@Override\n\tprotected void initValue()\n\t{\n\n\t}","public void mo55254a() {\n }"],"string":"[\n \"@Override\\r\\n\\tpublic void comer() \\r\\n\\t{\\n\\t\\t\\r\\n\\t}\",\n \"@Override\\n\\tpublic void comer() {\\n\\t\\t\\n\\t}\",\n \"@Override\\n public void perish() {\\n \\n }\",\n \"@Override\\r\\n\\t\\t\\tpublic void annadir() {\\n\\r\\n\\t\\t\\t}\",\n \"@Override\\n\\tpublic void anular() {\\n\\n\\t}\",\n \"@Override\\n\\tprotected void getExras() {\\n\\n\\t}\",\n \"@Override\\r\\n\\tpublic void anularFact() {\\n\\t\\t\\r\\n\\t}\",\n \"@Override\\n\\tpublic void entrenar() {\\n\\t\\t\\n\\t}\",\n \"@Override\\n\\tpublic void nadar() {\\n\\t\\t\\n\\t}\",\n \"@Override\\r\\n\\tpublic void tires() {\\n\\t\\t\\r\\n\\t}\",\n \"@Override\\r\\n\\t\\t\\tpublic void ayuda() {\\n\\r\\n\\t\\t\\t}\",\n \"@Override\\n\\tprotected void interr() {\\n\\t}\",\n \"@Override\\n\\tpublic void emprestimo() {\\n\\n\\t}\",\n \"@Override\\r\\n\\tpublic void bicar() {\\n\\t\\t\\r\\n\\t}\",\n \"@Override\\r\\n\\tpublic void bicar() {\\n\\t\\t\\r\\n\\t}\",\n \"@Override\\n\\tpublic void grabar() {\\n\\t\\t\\n\\t}\",\n \"@Override\\n\\tpublic void gravarBd() {\\n\\t\\t\\n\\t}\",\n \"@Override\\r\\n\\tpublic void rozmnozovat() {\\n\\t}\",\n \"@Override\\r\\n\\tpublic void dormir() {\\n\\t\\t\\r\\n\\t}\",\n \"@Override\\n protected void getExras() {\\n }\",\n \"@Override\\r\\n\\tpublic void publierEnchere() {\\n\\t\\t\\r\\n\\t}\",\n \"@Override\\n\\tpublic void nefesAl() {\\n\\n\\t}\",\n \"@Override\\n\\tpublic void ligar() {\\n\\t\\t\\n\\t}\",\n \"@Override\\n public void func_104112_b() {\\n \\n }\",\n \"@Override\\n\\tprotected void initdata() {\\n\\n\\t}\",\n \"@Override\\n\\tpublic void nghe() {\\n\\n\\t}\",\n \"@Override\\n public void function()\\n {\\n }\",\n \"@Override\\n public void function()\\n {\\n }\",\n \"public final void mo51373a() {\\n }\",\n \"@Override\\r\\n\\tpublic void stehReagieren() {\\r\\n\\t\\t//\\r\\n\\t}\",\n \"@Override\\n public void inizializza() {\\n\\n super.inizializza();\\n }\",\n \"@Override\\n\\tprotected void initData() {\\n\\t\\t\\n\\t}\",\n \"@Override\\r\\n\\t\\tpublic void init() {\\n\\t\\t\\t\\r\\n\\t\\t}\",\n \"@Override\\n\\tpublic void sacrifier() {\\n\\t\\t\\n\\t}\",\n \"@Override\\r\\n\\tprotected void InitData() {\\n\\t\\t\\r\\n\\t}\",\n \"public void designBasement() {\\n\\t\\t\\r\\n\\t}\",\n \"@Override\\r\\n\\tprotected void initialize() {\\r\\n\\t\\t\\r\\n\\t\\t\\r\\n\\t}\",\n \"public void gored() {\\n\\t\\t\\n\\t}\",\n \"@Override\\r\\n\\tprotected void initData() {\\n\\r\\n\\t}\",\n \"@Override\\n\\tpublic void einkaufen() {\\n\\t}\",\n \"@Override\\n protected void initialize() {\\n\\n \\n }\",\n \"public void mo38117a() {\\n }\",\n \"@Override\\n\\tprotected void getData() {\\n\\t\\t\\n\\t}\",\n \"Constructor() {\\r\\n\\t\\t \\r\\n\\t }\",\n \"@Override\\r\\n\\tpublic void dibujar() {\\n\\t\\t\\r\\n\\t}\",\n \"@Override\\r\\n\\tpublic void dibujar() {\\n\\t\\t\\r\\n\\t}\",\n \"@Override\\n\\tpublic void one() {\\n\\t\\t\\n\\t}\",\n \"@Override\\r\\n\\tprotected void initData() {\\n\\t\\t\\r\\n\\t}\",\n \"@Override\\r\\n\\tprotected void initData() {\\n\\t\\t\\r\\n\\t}\",\n \"@Override\\r\\n\\tprotected void initData() {\\n\\t\\t\\r\\n\\t}\",\n \"@Override\\r\\n\\tprotected void initData() {\\n\\t\\t\\r\\n\\t}\",\n \"@Override\\r\\n\\tprotected void initData() {\\n\\t\\t\\r\\n\\t}\",\n \"@Override\\r\\n\\tprotected void initData() {\\n\\t\\t\\r\\n\\t}\",\n \"private stendhal() {\\n\\t}\",\n \"@Override\\n\\tprotected void update() {\\n\\t\\t\\n\\t}\",\n \"@Override\\n\\t\\t\\tpublic void ic() {\\n\\t\\t\\t\\t\\n\\t\\t\\t}\",\n \"@Override\\n\\tprotected void initData() {\\n\\n\\t}\",\n \"@Override\\n\\tprotected void initData() {\\n\\n\\t}\",\n \"@Override\\n\\tpublic void init() {\\n\\t\\t\\n\\t}\",\n \"@Override\\n\\tpublic void init() {\\n\\t\\t\\n\\t}\",\n \"@Override\\n\\tpublic void init() {\\n\\t\\t\\n\\t}\",\n \"@Override\\n\\tpublic void init() {\\n\\t\\t\\n\\t}\",\n \"@Override\\n\\tpublic void init() {\\n\\t\\t\\n\\t}\",\n \"@Override\\n public void init() {\\n\\n }\",\n \"@Override\\n\\tprotected void initialize() {\\n\\t\\t\\n\\t}\",\n \"@Override\\n\\tprotected void initialize() {\\n\\t\\t\\n\\t}\",\n \"@Override\\r\\n\\tpublic void init() {\\n\\t\\t\\r\\n\\t}\",\n \"@Override\\r\\n\\tpublic void init() {\\n\\t\\t\\r\\n\\t}\",\n \"@Override\\r\\n\\tpublic void init() {\\n\\t\\t\\r\\n\\t}\",\n \"@Override\\n\\tpublic void debite() {\\n\\t\\t\\n\\t}\",\n \"@Override\\r\\n\\tpublic void init() {\\n\\r\\n\\t}\",\n \"@Override\\r\\n\\tpublic void init() {\\n\\r\\n\\t}\",\n \"@Override\\r\\n\\tpublic void init() {\\n\\r\\n\\t}\",\n \"public contrustor(){\\r\\n\\t}\",\n \"@Override\\n\\tprotected void initialize() {\\n\\n\\t}\",\n \"@Override\\r\\n\\tpublic void dispase() {\\n\\r\\n\\t}\",\n \"public void mo55254a() {\\n }\",\n \"public void mo55254a() {\\n }\",\n \"public void mo55254a() {\\n }\",\n \"public void mo55254a() {\\n }\",\n \"public void mo55254a() {\\n }\",\n \"public void mo55254a() {\\n }\",\n \"public void mo55254a() {\\n }\",\n \"@Override\\n\\tpublic void dtd() {\\n\\t\\t\\n\\t}\",\n \"@Override\\n\\tprotected void logic() {\\n\\n\\t}\",\n \"@Override\\n\\tprotected void lazyLoad() {\\n\\t\\t\\n\\t}\",\n \"public void mo4359a() {\\n }\",\n \"@Override\\r\\n\\tprotected void initialize() {\\n\\r\\n\\t}\",\n \"@Override\\n public void memoria() {\\n \\n }\",\n \"@Override\\n\\t\\tpublic void method() {\\n\\t\\t\\t\\n\\t\\t}\",\n \"private RepositorioAtendimentoPublicoHBM() {\\r\\t}\",\n \"@Override\\n protected void initialize() \\n {\\n \\n }\",\n \"@Override\\r\\n\\tpublic void getProposition() {\\n\\r\\n\\t}\",\n \"@Override\\n\\tpublic void particular1() {\\n\\t\\t\\n\\t}\",\n \"@Override\\n\\tpublic void init() {\\n\\n\\t}\",\n \"@Override\\n\\tpublic void init() {\\n\\n\\t}\",\n \"@Override\\n\\tpublic void init() {\\n\\n\\t}\",\n \"@Override\\n protected void prot() {\\n }\",\n \"@Override\\r\\n\\tpublic void init()\\r\\n\\t{\\n\\t}\",\n \"@Override\\n\\tprotected void initValue()\\n\\t{\\n\\n\\t}\",\n \"public void mo55254a() {\\n }\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6671074","0.6567672","0.6523024","0.6481211","0.6477082","0.64591026","0.64127725","0.63762105","0.6276059","0.6254286","0.623686","0.6223679","0.6201336","0.61950207","0.61950207","0.61922914","0.6186996","0.6173591","0.61327106","0.61285484","0.6080161","0.6077022","0.6041561","0.6024072","0.6020252","0.59984857","0.59672105","0.59672105","0.5965777","0.59485507","0.5940904","0.59239364","0.5910017","0.5902906","0.58946234","0.5886006","0.58839184","0.58691067","0.5857751","0.58503544","0.5847024","0.58239377","0.5810564","0.5810089","0.5806823","0.5806823","0.5800025","0.5792378","0.5792378","0.5792378","0.5792378","0.5792378","0.5792378","0.5790187","0.5789414","0.5787092","0.57844025","0.57844025","0.5774479","0.5774479","0.5774479","0.5774479","0.5774479","0.5761362","0.57596046","0.57596046","0.575025","0.575025","0.575025","0.5747959","0.57337177","0.57337177","0.57337177","0.5721452","0.5715831","0.57142824","0.57140535","0.57140535","0.57140535","0.57140535","0.57140535","0.57140535","0.57140535","0.5711723","0.57041645","0.56991017","0.5696783","0.56881124","0.56774884","0.56734604","0.56728","0.56696945","0.5661323","0.5657007","0.5655942","0.5655942","0.5655942","0.56549734","0.5654792","0.5652974","0.5650185"],"string":"[\n \"0.6671074\",\n \"0.6567672\",\n \"0.6523024\",\n \"0.6481211\",\n \"0.6477082\",\n \"0.64591026\",\n \"0.64127725\",\n \"0.63762105\",\n \"0.6276059\",\n \"0.6254286\",\n \"0.623686\",\n \"0.6223679\",\n \"0.6201336\",\n \"0.61950207\",\n \"0.61950207\",\n \"0.61922914\",\n \"0.6186996\",\n \"0.6173591\",\n \"0.61327106\",\n \"0.61285484\",\n \"0.6080161\",\n \"0.6077022\",\n \"0.6041561\",\n \"0.6024072\",\n \"0.6020252\",\n \"0.59984857\",\n \"0.59672105\",\n \"0.59672105\",\n \"0.5965777\",\n \"0.59485507\",\n \"0.5940904\",\n \"0.59239364\",\n \"0.5910017\",\n \"0.5902906\",\n \"0.58946234\",\n \"0.5886006\",\n \"0.58839184\",\n \"0.58691067\",\n \"0.5857751\",\n \"0.58503544\",\n \"0.5847024\",\n \"0.58239377\",\n \"0.5810564\",\n \"0.5810089\",\n \"0.5806823\",\n \"0.5806823\",\n \"0.5800025\",\n \"0.5792378\",\n \"0.5792378\",\n \"0.5792378\",\n \"0.5792378\",\n \"0.5792378\",\n \"0.5792378\",\n \"0.5790187\",\n \"0.5789414\",\n \"0.5787092\",\n \"0.57844025\",\n \"0.57844025\",\n \"0.5774479\",\n \"0.5774479\",\n \"0.5774479\",\n \"0.5774479\",\n \"0.5774479\",\n \"0.5761362\",\n \"0.57596046\",\n \"0.57596046\",\n \"0.575025\",\n \"0.575025\",\n \"0.575025\",\n \"0.5747959\",\n \"0.57337177\",\n \"0.57337177\",\n \"0.57337177\",\n \"0.5721452\",\n \"0.5715831\",\n \"0.57142824\",\n \"0.57140535\",\n \"0.57140535\",\n \"0.57140535\",\n \"0.57140535\",\n \"0.57140535\",\n \"0.57140535\",\n \"0.57140535\",\n \"0.5711723\",\n \"0.57041645\",\n \"0.56991017\",\n \"0.5696783\",\n \"0.56881124\",\n \"0.56774884\",\n \"0.56734604\",\n \"0.56728\",\n \"0.56696945\",\n \"0.5661323\",\n \"0.5657007\",\n \"0.5655942\",\n \"0.5655942\",\n \"0.5655942\",\n \"0.56549734\",\n \"0.5654792\",\n \"0.5652974\",\n \"0.5650185\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}}],"truncated":false,"partial":true},"paginationData":{"pageIndex":138,"numItemsPerPage":100,"numTotalItems":136513,"offset":13800,"length":100}},"jwt":"eyJhbGciOiJFZERTQSJ9.eyJyZWFkIjp0cnVlLCJwZXJtaXNzaW9ucyI6eyJyZXBvLmNvbnRlbnQucmVhZCI6dHJ1ZX0sImlhdCI6MTc3OTM3ODEyMiwic3ViIjoiL2RhdGFzZXRzL25vbWljLWFpL2Nvcm5zdGFjay1qYXZhLXYxIiwiZXhwIjoxNzc5MzgxNzIyLCJpc3MiOiJodHRwczovL2h1Z2dpbmdmYWNlLmNvIn0.m25B7g2JxhafrKr3cFgKReMofwC82F8ksIPox2pP0jr48WK6eThdTR6RzdrpxTKtaCp5veAhE132cn_MlVnKBA","displayUrls":true,"splitSizeSummaries":[{"config":"default","split":"train","numRows":136513,"numBytesParquet":1558040430}]},"discussionsStats":{"closed":0,"open":1,"total":1},"fullWidth":true,"hasGatedAccess":true,"hasFullAccess":true,"isEmbedded":false,"savedQueries":{"community":[],"user":[]}}">
query stringlengths 7 33.1k | document stringlengths 7 335k | metadata dict | negatives listlengths 3 101 | negative_scores listlengths 3 101 | document_score stringlengths 3 10 | document_rank stringclasses 102
values |
|---|---|---|---|---|---|---|
However, the type of reference of b is Baap so b.h will always refer to Baap's h | public static void main(String[] args) {
Baap b = new Beta(); //Here, b refers to an object of class Beta
//so b.getH() will always call the overridden (subclass's method)
System.out.println("Baap b = new Beta(): " + b.h/*2*/ + " " + b.getH())/*1*/;
// also 1) ... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"public void b(ahd paramahd) {}",
"public void b() {\n ((a) this.a).b();\n }",
"public t b() {\n return a(this.a);\n }",
"public abstract BoundType b();",
"MagReference getHvRef();",
"public void b(World paramaqu, BlockPosition paramdt, Block parambec)\r\n/* 27: */ {\r\n/* 28: 4... | [
"0.5760162",
"0.56714755",
"0.54906285",
"0.5480289",
"0.5438917",
"0.5430128",
"0.5428197",
"0.54005575",
"0.54005575",
"0.5400227",
"0.53536654",
"0.52887976",
"0.5283663",
"0.5281222",
"0.5277332",
"0.5268807",
"0.5264003",
"0.52555037",
"0.52462023",
"0.52306324",
"0.5228... | 0.5199437 | 23 |
lnd must be ready | @Override
public void work() {
if (!lnd_.isRpcReady())
return;
if (!started_) {
// NOTE: start protocol to recover in-flight payments' state:
// - get all payments w/ 'sending' state from db
// - get all payments from lnd
// - find 'sendin... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"public abstract void ready();",
"@Override\n public boolean isReady() {\n return true;\n }",
"@Override\n public boolean isReady() {\n return true;\n }",
"void isReady();",
"void isReady();",
"@Override\r\n\t\t\tpublic boolean isReady() {\n\t\t\t\treturn false;\r\n\t\t\t}",
"@Over... | [
"0.59829897",
"0.5862426",
"0.5836489",
"0.58303344",
"0.58303344",
"0.57747763",
"0.5713609",
"0.5713609",
"0.56896836",
"0.56695676",
"0.56695676",
"0.5667692",
"0.56576747",
"0.5655243",
"0.5630367",
"0.55788666",
"0.5569819",
"0.5565842",
"0.555607",
"0.55503523",
"0.5550... | 0.0 | -1 |
Compare values with largest number | public static void main(String[] args) {
Scanner val = new Scanner(System.in);
int num1 = val.nextInt();
int num2 = val.nextInt();
int num3 = val.nextInt();
val.close();
num1 = (num2 > num1)? num2:num1;
num3 = (num3 > num1)? num3:num1;
System.out.println(num3);
} | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"double largestNumber(double[] a) {\n\t\tdouble max = a[0];\n\t\tdouble no = 0;\n\t\tfor (int index = 1; index < a.length; index++) {\n\t\t\tif (max > a[index] && max > a[index + 1]) {\n\t\t\t\tno = max;\n\t\t\t\tbreak;\n\t\t\t} else if (a[index] > max && a[index] > a[index + 1]) {\n\t\t\t\tno = a[index];\n\t\t\t\t... | [
"0.6982909",
"0.6863735",
"0.67158955",
"0.6662198",
"0.66158956",
"0.6591017",
"0.6567861",
"0.6518906",
"0.6509642",
"0.65014374",
"0.64639837",
"0.64552444",
"0.6446018",
"0.64428425",
"0.6419264",
"0.6408566",
"0.6404517",
"0.63789874",
"0.6353375",
"0.63469666",
"0.63390... | 0.0 | -1 |
List list = new Vector(); List list = Collections.synchronizedList(new ArrayList()); | public static void main(String[] args) {
CopyOnWriteArrayList<String> list = new CopyOnWriteArrayList<>();
CopyOnWriteArraySet<String> set = new CopyOnWriteArraySet<>();
for (int i = 0; i < 30; i++) {
new Thread(()->{
set.add(UUID.randomUUID().toString());
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"@SuppressWarnings(\"unchecked\")\n \tpublic static <T> List<T> createConcurrentList() {\n \t\treturn (List<T>) Collections.synchronizedList(createArrayList());\n \t}",
"public static void main(String[] args) {\n\t\tList<Integer> list=Collections.synchronizedList(new ArrayList<>());\n\t\t\n\t\t\n\t}",
"private ... | [
"0.7255283",
"0.71889967",
"0.7147631",
"0.6872272",
"0.653382",
"0.6502858",
"0.6354238",
"0.6206271",
"0.6106977",
"0.6044963",
"0.6011033",
"0.595015",
"0.5949338",
"0.5938644",
"0.5907712",
"0.58640844",
"0.5856065",
"0.58477587",
"0.5832252",
"0.5735379",
"0.57306033",
... | 0.5937854 | 14 |
boolean returnValue = true; | private synchronized void print4() {
try {
int jNum = 0;
byte[] printText22 = new byte[10240];
byte[] oldText = setAlignCenter('0');
System.arraycopy(oldText, 0, printText22, jNum, oldText.length);
jNum += oldText.length;
oldText = setIn... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"public boolean getReturn();",
"public boolean get_return(){\n return local_return;\n }",
"boolean doSomething() {\n\t\treturn true;\n\t}",
"boolean getVarReturn();",
"boolean test();",
"boolean test();",
"boolean test();",
"boolean test() {\n ... | [
"0.7621053",
"0.76199734",
"0.73888505",
"0.7333712",
"0.7181328",
"0.7181328",
"0.7181328",
"0.71305335",
"0.708852",
"0.69825774",
"0.6982471",
"0.6982471",
"0.6982471",
"0.6982471",
"0.69568735",
"0.6927141",
"0.6872325",
"0.68402606",
"0.6830471",
"0.68129027",
"0.6812902... | 0.0 | -1 |
A constructor that adds a reference to the parent JDA instance | LavoisierListener(JDA jda) {
instance = jda;
} | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"public Parent() {\n super();\n }",
"Parent() {\n\t System.out.println(\"i am from Parent Class\");\n\t }",
"public ReferenceDatabaseSettingsGUI(AdminJavaGUI parent) {\n initComponents();\n windowMenu(); \n parentFrame = parent;\n getParentReferenceDatabase... | [
"0.6358775",
"0.6299422",
"0.59706277",
"0.59537953",
"0.5919605",
"0.581985",
"0.57945395",
"0.57553303",
"0.57457966",
"0.5745647",
"0.5720582",
"0.5698625",
"0.56379545",
"0.5595008",
"0.55935496",
"0.5574735",
"0.55375904",
"0.5523305",
"0.55084",
"0.5507268",
"0.5505589"... | 0.5978528 | 2 |
Load answer data into program | private void loadData() {
try {
URL source = new URL(CSV_URL);
URLConnection connect = source.openConnection();
BufferedReader f = new BufferedReader(new InputStreamReader(connect.getInputStream()));
header = f.readLine().split(",");
// Replace third ... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"public void readData() throws IOException {\n // as long as there are stuff left, keep reading by sets, which are\n // pairs of description + answer\n while (hasNext()) {\n counter++;\n readSet();\n }\n }",
"public void readQuestion()\n\t{\n\t\tnumLines = (int)numScan.nextDouble();\n\t\tqu... | [
"0.61766297",
"0.6150806",
"0.5977766",
"0.5976423",
"0.59274155",
"0.58778036",
"0.58778036",
"0.5844642",
"0.58321124",
"0.5796271",
"0.5782386",
"0.57492834",
"0.5722469",
"0.5642073",
"0.5641588",
"0.5635279",
"0.55793136",
"0.5528215",
"0.55194646",
"0.5514423",
"0.54881... | 0.5360267 | 31 |
A method to print out the help message | private void printHelpMessage(Message msg, String[] parameters) {
// No parameters
if(parameters.length == 1) {
MessageEmbed embed = new MessageEmbed(null, "*Current Commands*",
"**$help:** Display the help page for all commands." +
"\n\n**$que... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"void printHelp();",
"private void printHelp() \n {\n Logger.Log(\"You have somehow ended up in this strange, magical land. But really you just want to go home.\");\n Logger.Log(\"\");\n Logger.Log(\"Your command words are:\");\n parser.showCommands();\n Logger.Log(\"You may view... | [
"0.8836242",
"0.85331684",
"0.8478557",
"0.83347934",
"0.8316819",
"0.8307558",
"0.8243017",
"0.8239322",
"0.8224657",
"0.8204919",
"0.8184006",
"0.81792295",
"0.8172836",
"0.81561935",
"0.8114366",
"0.81087106",
"0.81049263",
"0.8079019",
"0.80702466",
"0.8050532",
"0.804858... | 0.0 | -1 |
A method to get a random value within a range | private int getValue(int lowerBound, int upperBound) {
int problemRange = upperBound - lowerBound + 1;
return lowerBound + rng.nextInt(problemRange);
} | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"public static int customRandom(int range)\n {\n \tint random = (int)(Math.random()*10)%range;\n\t\n\treturn random;\n }",
"private int _getRandomFromRange(int min, int max) {\n\t \n return min + random_.nextInt(max - min + 1);\n }",
"public int getRandomNumberInInterval() {\n\t\treturn getRandomN... | [
"0.75973296",
"0.73689204",
"0.7355706",
"0.73053247",
"0.7255473",
"0.71772355",
"0.71658367",
"0.70838153",
"0.70410717",
"0.70400995",
"0.70379484",
"0.70335454",
"0.6987245",
"0.6965747",
"0.6964726",
"0.69549984",
"0.694985",
"0.6938311",
"0.69274753",
"0.6925244",
"0.69... | 0.65674686 | 58 |
A method to query a USNCO problem | private void queryImage(Message msg, int actualYear, int actualProblem, int section) {
// Query from GitHub
String sectionVal;
String sectionDescription;
switch(section) {
case 0:
sectionVal = "locals";
sectionDescription = "Locals";
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"Query query();",
"public String susi(String query) throws Exception {\n\n \t\tthis.query = query;\n \t\tif (this.query != \"\") {\n \t\t\tString url = this.susiUrl + \"?q=\" +this.query;\n\n \t\t\tURL urlObj = new URL(url);\n HttpURLConnection con = (HttpURLConnection) urlObj.openConnection();\n\n ... | [
"0.55613244",
"0.5428159",
"0.541852",
"0.5391133",
"0.53482777",
"0.5298249",
"0.5256226",
"0.5215686",
"0.52028286",
"0.5165698",
"0.5151723",
"0.51313573",
"0.5103518",
"0.50899047",
"0.5059625",
"0.5040657",
"0.50326234",
"0.50304765",
"0.50262433",
"0.50065285",
"0.49816... | 0.48901302 | 31 |
A method to reset year, problem, and restriction parameters to their original value | private void resetParams() {
lowerYear = 1999;
upperYear = 2020;
yearRestriction = false;
lowerProblem = 1;
upperProblem = 60;
problemRestriction = false;
partTwo = false;
} | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"public void setYear(int _year) { year = _year; }",
"public void inputTempForYear() {\n\t\t\n\t\tfor (int i=0; i<12; i++)\n\t\t\tinputTempForMonth(i);\n\t}",
"public void setYear(int year){\r\n\t\ttry{\r\n\t\t\tif(year>=1900)\r\n\t\t\tthis.year = year;\r\n\t\t\telse\r\n\t\t\t\tthrow new cardYearException();\r\n... | [
"0.65275615",
"0.6162822",
"0.6144697",
"0.61259294",
"0.6055855",
"0.6013104",
"0.6007035",
"0.59928924",
"0.59585834",
"0.59047645",
"0.58721936",
"0.58694136",
"0.5855274",
"0.5848585",
"0.58383906",
"0.58254445",
"0.57638866",
"0.5758579",
"0.5756033",
"0.57522064",
"0.57... | 0.82811934 | 0 |
A method to restrict the year range problems are queried from | private int restrictYear(Message msg, String parameter, int section) {
int[] years = setYearRestriction(msg, parameter, section);
if (years[0] == ERROR_CODE[0]) {
return -1;
}
yearRestriction = true;
lowerYear = years[0];
upperYear = years[1];
return... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"private static String dateRangeRestriction(String startDate, String endDate){\r\n String restriction = \"\";\r\n String[] startDateParts = startDate.split(\"/\");\r\n String[] endDateParts = endDate.split(\"/\");\r\n int prevYear = Integer.parseInt(endDateParts[0]) - 1; //year previus t... | [
"0.6461501",
"0.64567184",
"0.6359415",
"0.6349753",
"0.63127935",
"0.61866397",
"0.6178176",
"0.60279995",
"0.6016391",
"0.5997309",
"0.5984758",
"0.5984758",
"0.5975242",
"0.5975242",
"0.5975242",
"0.5932926",
"0.58727413",
"0.5850893",
"0.5844806",
"0.5839853",
"0.5825709"... | 0.74214554 | 0 |
A method to restrict the problem range problems are queried from | private int restrictProblem(Message msg, String parameter) {
int[] problems = setProblemRestriction(msg, parameter);
if (problems[0] == ERROR_CODE[0]) {
return -1;
}
problemRestriction = true;
lowerProblem = problems[0];
upperProblem = problems[1];
r... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"Range controlLimits();",
"@Override\n public boolean isRange() {\n return false;\n }",
"private void setDefaultValidRange ()\r\n\t{\r\n\t\tm_lowerBounds = Integer.MIN_VALUE;\r\n\t\tm_upperBounds = Integer.MAX_VALUE;\r\n\t}",
"void calculateRange() {\n //TODO: See Rules\n }",
"Limits limits()... | [
"0.6051895",
"0.59386593",
"0.574081",
"0.5694922",
"0.5655285",
"0.56469244",
"0.5617134",
"0.5489708",
"0.5472333",
"0.5461008",
"0.5432687",
"0.54020053",
"0.5387173",
"0.5363844",
"0.53595334",
"0.5352464",
"0.53450567",
"0.5326257",
"0.5324107",
"0.5307986",
"0.528972",
... | 0.6296766 | 0 |
A method to restrict the test (local, part I, part II) our problems are queried from | private int restrictSection(Message msg, String parameter) {
int sec = Integer.parseInt(parameter);
if(sec > 2) {
MessageChannel ch = msg.getChannel();
ch.sendMessage("`Error: Invalid query [section not 0-2]. Query terminated.`").queue();
return -1;
}
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"public boolean needsProblem();",
"@Test\n public void testAircraftPartNoNotApplicable777() throws Exception {\n\n String lTaskApplSqlLdesc = \"rootpart.part_no_oem <> 777\";\n\n // verify on wing engine 777 is not applicable\n int lResult = execute( ON_WING_ENGINE_777, lTaskApplSqlLdesc );\n ... | [
"0.5759807",
"0.5632411",
"0.5592196",
"0.55807394",
"0.55704653",
"0.5568658",
"0.54862475",
"0.54737324",
"0.54440826",
"0.5433054",
"0.5429019",
"0.54279935",
"0.54256517",
"0.53538674",
"0.5329615",
"0.532692",
"0.53252614",
"0.53053427",
"0.5287198",
"0.52184004",
"0.520... | 0.5123393 | 25 |
A method to query a problem based on user input | private void queryProblems(Message msg, String[] parameters) {
if(data.isEmpty())
loadData();
// Bounds on the problem number and year number
resetParams();
int section = -1;
int currentOption = -1;
int success = 0;
for(int i = 1; i < parameters.len... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"String userInput(String question);",
"private static String getQuery(String query) {\n\t\tScanner reader = new Scanner(System.in);\n\t\tString state = \"\";\n\t\twhile (true) {\n\t\t\tSystem.out.println(\"Please Type in a \" + query + \":\");\n\t\t\ttry {\n\t\t\t\tstate = reader.nextLine();\n\t\t\t\treturn state... | [
"0.61423576",
"0.5864194",
"0.5753262",
"0.5723401",
"0.56442285",
"0.56279784",
"0.56262416",
"0.55856955",
"0.55575085",
"0.55325246",
"0.55118245",
"0.55029655",
"0.5493009",
"0.5487937",
"0.5478411",
"0.54781795",
"0.54720646",
"0.54460365",
"0.5435567",
"0.54047483",
"0.... | 0.6413918 | 0 |
A method to handle commands overall | private void handleCommand(Message msg, String commands) {
String[] tokens = commands.split(" ");
String command = tokens[0];
switch(command) {
case "query":
queryProblems(msg, tokens);
break;
case "help":
printHelpMessage(... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"private void handleCommands() {\n for (Command c : commands) {\n try {\n if (!game.isPaused()) {\n switch (c) {\n case INTERACT:\n game.interact();\n break;\n case... | [
"0.7654008",
"0.7396491",
"0.73099214",
"0.71171105",
"0.70430857",
"0.7041614",
"0.70197445",
"0.70138",
"0.69875056",
"0.69785947",
"0.69703794",
"0.6970316",
"0.69506824",
"0.690399",
"0.6879779",
"0.68422073",
"0.6832724",
"0.67766094",
"0.677409",
"0.6726003",
"0.6723890... | 0.68986565 | 14 |
Handle message sending and receiving | @Override
public void onMessageReceived(MessageReceivedEvent event) {
if(event.getAuthor().isBot())
return;
Message msg = event.getMessage();
String content = msg.getContentRaw();
if(content.charAt(0) == PREFIX) {
handleCommand(msg, content.substring(1));
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"private void messageHandler(String read){\n\n try {\n buffer.append(read);\n }catch (MalformedMessageException e){\n System.out.println(\"[CLIENT] The message received is not in XML format.\");\n }\n\n while(!buffer.isEmpty()) {\n if (buffer.getPong()) p... | [
"0.74563",
"0.7406282",
"0.73414356",
"0.7280701",
"0.7273313",
"0.7231558",
"0.7195365",
"0.7180781",
"0.69980264",
"0.69897616",
"0.6987571",
"0.69682205",
"0.69441956",
"0.69424266",
"0.69161946",
"0.69100785",
"0.6900865",
"0.6873043",
"0.68487865",
"0.6822763",
"0.681170... | 0.0 | -1 |
Add "." to start and end of pattern to fully match any string containing the pattern | @Override
public Stream<String> filter(Stream<String> stringStream, String pattern) {
String regex = ".*" + pattern + ".*";
return stringStream.filter(str -> {
return !Pattern.compile(regex).matcher(str).matches();
});
} | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"private String regex() {\n final List<String> keys = new LinkedList<>();\n for (final String key : this.template.split(\"\\\\.\")) {\n if (key.equals(\"*\")) {\n keys.add(\"\\\\w+\");\n } else {\n keys.add(key);\n ... | [
"0.5914358",
"0.52938",
"0.5281211",
"0.52144426",
"0.5166466",
"0.51592064",
"0.51315033",
"0.5123095",
"0.5097771",
"0.5090073",
"0.5039961",
"0.49998975",
"0.49818164",
"0.49716192",
"0.49581355",
"0.4957681",
"0.49394077",
"0.49049667",
"0.48970428",
"0.4896198",
"0.48935... | 0.0 | -1 |
/ checked out cust flush single rooms flush dob flush prm flush sut del cust | public static void main(String[] args) throws Exception, IOException {
DateTimeFormatter f = DateTimeFormatter.ofPattern("dd/MM/yyyy");
BufferedReader br = new BufferedReader(new InputStreamReader(System.in));
Map<String, Custo> c = null;
Map<String, Custo> sin = null;
Map<String, Custo> dobl = null;
Map<St... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"public void flush(){\r\n\t\tSystem.out.println(\"\\nCreating a customer by flush:\");\r\n\t\tEntityManager em = emf.createEntityManager();\r\n\t\tEntityTransaction tx = em.getTransaction();\r\n\t\tCustomer2 c1 = new Customer2(\"Selim\", \"Aslan\");\r\n\t\ttx.begin();\r\n\t\tem.persist(c1);\r\n\t\tlong id = c1.getC... | [
"0.63320124",
"0.557104",
"0.55518925",
"0.5459013",
"0.5418892",
"0.5370092",
"0.5326914",
"0.5319819",
"0.5300342",
"0.52911866",
"0.52776676",
"0.5275197",
"0.5236168",
"0.5233664",
"0.52224684",
"0.5213094",
"0.52072126",
"0.5191101",
"0.5190921",
"0.5186526",
"0.5179781"... | 0.0 | -1 |
Instantiate this function with an infinite width. | public AllDifferent()
{
this(0);
} | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"public Plain(int width) {\n this.width = width;\n }",
"public FixedWidthFunction(GroupingExpression exp, Number width) {\n this(null, null, exp,\n width instanceof Double ? new DoubleValue(width.doubleValue()) : new LongValue(width.longValue()));\n }",
"double getNewWidth();",
... | [
"0.64823556",
"0.5968908",
"0.5893348",
"0.58884764",
"0.5641955",
"0.5613188",
"0.5593008",
"0.5591713",
"0.55780673",
"0.5537561",
"0.5511492",
"0.54675525",
"0.54661113",
"0.54651093",
"0.54115677",
"0.5406519",
"0.5383397",
"0.5383397",
"0.5379138",
"0.5377192",
"0.537679... | 0.0 | -1 |
if a duplicate entry has been found and the width is infinite. | @Override
public Boolean getValue(Object x)
{
if (m_falseCount > 0 && m_width <= 0)
return false;
allDifferent = true;
// if duplicate entries were found in previous calls
if (m_falseCount > 0)
{
m_falseCount--;
allDifferent = false;
}
// compare this entry to every ... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"@Override\r\n\t\t\t\t\tprotected boolean removeEldestEntry(Map.Entry e)\r\n\t\t\t\t\t{\r\n\t\t\t\t\t\treturn size()>5;\r\n\t\t\t\t\t}",
"boolean hasWidth();",
"boolean hasWidth();",
"boolean hasWidth();",
"public boolean removeEldestEntry(Map.Entry entry){\n return size() > capacity;\n ... | [
"0.5627829",
"0.5563654",
"0.5563654",
"0.5563654",
"0.5423416",
"0.54012316",
"0.53828716",
"0.53736985",
"0.5370324",
"0.5356995",
"0.5322876",
"0.53048307",
"0.52965814",
"0.5267565",
"0.5233001",
"0.52117383",
"0.51820254",
"0.5158915",
"0.5151776",
"0.5139773",
"0.513675... | 0.0 | -1 |
this li1ne number is 0 base. | private int getLineNumber(@NonNull String contents, int offset) {
String preContents = contents.substring(0, offset);
String remContents = preContents.replaceAll("\n", "");
return preContents.length() - remContents.length();
} | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"private int getNumberBase(String n1){\n return Integer.parseUnsignedInt(n1, base);\n }",
"public void changeToBaseOne() {\r\n\t\tthis.numberBase = 1;\r\n\t}",
"public String negBase2(int n) throws Exception {\r\n\t\t String binaryStr=\"\";\r\n\r\n\t\t int minValue = -256;//allowed min decimal\r\n\... | [
"0.6643646",
"0.6513608",
"0.6176411",
"0.61259305",
"0.5929572",
"0.58271587",
"0.5821877",
"0.580789",
"0.57892466",
"0.5766924",
"0.57455724",
"0.57062405",
"0.56925964",
"0.5682736",
"0.5681638",
"0.56375444",
"0.5636765",
"0.5636586",
"0.5630927",
"0.5622785",
"0.5604633... | 0.0 | -1 |
this column number is 0 base. | private int getColumnNumber(@NonNull String contents, int offset) {
String preContents = contents.substring(0, offset);
String[] preLines = preContents.split("\n");
int lastIndex = preLines.length -1;
return preContents.endsWith("\n") ? 0 : preLines[lastIndex].length();
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"public int getIntialSortedColumn()\n { \n return 0; \n }",
"@Override\n\tpublic int getNumColumns() {\n\t\treturn 0;\n\t}",
"@Override\n\tpublic int getNumericCode() {\n\t\treturn 0;\n\t}",
"public Column(int num)\n {\n colNum = num;\n }",
"private int getColumn() {\n re... | [
"0.6459548",
"0.6433609",
"0.63993835",
"0.6370728",
"0.6113064",
"0.61004806",
"0.60702616",
"0.60422206",
"0.6034876",
"0.6025026",
"0.5995975",
"0.5980472",
"0.5980472",
"0.5978248",
"0.5962278",
"0.5929069",
"0.5922747",
"0.5909779",
"0.59080815",
"0.5898374",
"0.58811396... | 0.0 | -1 |
Source of biological unit. Mostly: SYNTHETIC | public StrColumn getSrcMethod() {
return delegate.getColumn("src_method", DelegatingStrColumn::new);
} | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"String getSource();",
"public abstract String getSource();",
"public String getSource ();",
"public String getSource();",
"public String getSource() {\n/* 312 */ return getValue(\"source\");\n/* */ }",
"public String get_source() {\n\t\treturn source;\n\t}",
"java.lang.String getSource();",
... | [
"0.6335917",
"0.6234252",
"0.62193584",
"0.6158671",
"0.6150574",
"0.6111239",
"0.6029425",
"0.6029425",
"0.5974726",
"0.5967423",
"0.59562695",
"0.59553146",
"0.5931785",
"0.59167606",
"0.5890848",
"0.58608466",
"0.58188987",
"0.5798793",
"0.5783144",
"0.57827646",
"0.575245... | 0.0 | -1 |
Spring Data ElasticSearch repository for the Pricing entity. | public interface PricingSearchRepository extends ElasticsearchRepository<Pricing, Long> {
} | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"public interface ServicePriceSearchRepository extends ElasticsearchRepository<ServicePrice, Long> {\n}",
"public interface ProductPricingRepository extends JpaRepository<ProductPricing, Long> {\n}",
"public interface GroupRateSearchRepository extends ElasticsearchRepository<GroupRate, Long> {\n}",
"@Suppress... | [
"0.7286061",
"0.702248",
"0.678128",
"0.6780915",
"0.6644016",
"0.6632004",
"0.6592339",
"0.65712065",
"0.6555739",
"0.6553429",
"0.65470034",
"0.6468063",
"0.6438855",
"0.643353",
"0.6415669",
"0.6399343",
"0.6388844",
"0.6373593",
"0.63693845",
"0.6359977",
"0.6359254",
"... | 0.780306 | 0 |
/ This endpoint creates a repository with an starter tag and an optional develop branch. | @RequestMapping(method = RequestMethod.POST, value = "/startRepo")
public String initializeRepo(@RequestBody CreateRepoRequestTemplate createRepoRequestTemplate) throws ResourceNotFoundException, BadRequestException {
return gitLabService.initializeRepo(createRepoRequestTemplate);
} | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"WithCreate withRepoUrl(String repoUrl);",
"@Override\n public CreateRepositoryResult createRepository(CreateRepositoryRequest request) {\n request = beforeClientExecution(request);\n return executeCreateRepository(request);\n }",
"TRepo createRepo();",
"public CompletableFuture<CreateRepo... | [
"0.64799607",
"0.61946714",
"0.5942678",
"0.5871605",
"0.58289343",
"0.58199525",
"0.5801379",
"0.5650184",
"0.5566602",
"0.54939413",
"0.54794806",
"0.54685163",
"0.5384734",
"0.5363201",
"0.53159964",
"0.5276887",
"0.5116236",
"0.51124275",
"0.502043",
"0.48835814",
"0.4875... | 0.5987682 | 2 |
TODO Autogenerated method stub | @Override
public void editPost(Integer postID, String message, String posterName,
String[] imageName, String[] imageID) {
} | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"@Override\r\n\tpublic void comer() \r\n\t{\n\t\t\r\n\t}",
"@Override\n\tpublic void comer() {\n\t\t\n\t}",
"@Override\n public void perish() {\n \n }",
"@Override\r\n\t\t\tpublic void annadir() {\n\r\n\t\t\t}",
"@Override\n\tpublic void anular() {\n\n\t}",
"@Override\n\tprotected void getExr... | [
"0.6671074",
"0.6567672",
"0.6523024",
"0.6481211",
"0.6477082",
"0.64591026",
"0.64127725",
"0.63762105",
"0.6276059",
"0.6254286",
"0.623686",
"0.6223679",
"0.6201336",
"0.61950207",
"0.61950207",
"0.61922914",
"0.6186996",
"0.6173591",
"0.61327106",
"0.61285484",
"0.608016... | 0.0 | -1 |
TODO Autogenerated method stub | @Override
public void editThread(Integer threadID, String topic, String message,
String posterName, String[] imageName, String[] imageID) {
} | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"@Override\r\n\tpublic void comer() \r\n\t{\n\t\t\r\n\t}",
"@Override\n\tpublic void comer() {\n\t\t\n\t}",
"@Override\n public void perish() {\n \n }",
"@Override\r\n\t\t\tpublic void annadir() {\n\r\n\t\t\t}",
"@Override\n\tpublic void anular() {\n\n\t}",
"@Override\n\tprotected void getExr... | [
"0.6671074",
"0.6567672",
"0.6523024",
"0.6481211",
"0.6477082",
"0.64591026",
"0.64127725",
"0.63762105",
"0.6276059",
"0.6254286",
"0.623686",
"0.6223679",
"0.6201336",
"0.61950207",
"0.61950207",
"0.61922914",
"0.6186996",
"0.6173591",
"0.61327106",
"0.61285484",
"0.608016... | 0.0 | -1 |
TODO Autogenerated method stub | @Override
public void createPost(Integer postID, Integer parentPostID,
String posterName, String message, String[] imageName,
String[] imageID) {
} | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"@Override\r\n\tpublic void comer() \r\n\t{\n\t\t\r\n\t}",
"@Override\n\tpublic void comer() {\n\t\t\n\t}",
"@Override\n public void perish() {\n \n }",
"@Override\r\n\t\t\tpublic void annadir() {\n\r\n\t\t\t}",
"@Override\n\tpublic void anular() {\n\n\t}",
"@Override\n\tprotected void getExr... | [
"0.6671074",
"0.6567672",
"0.6523024",
"0.6481211",
"0.6477082",
"0.64591026",
"0.64127725",
"0.63762105",
"0.6276059",
"0.6254286",
"0.623686",
"0.6223679",
"0.6201336",
"0.61950207",
"0.61950207",
"0.61922914",
"0.6186996",
"0.6173591",
"0.61327106",
"0.61285484",
"0.608016... | 0.0 | -1 |
Process the attack in the animal through the strategy and recalculates the available life power. | public final void receiveAttack(Weapon weapon) {
this.availableLifePower = damageStrategy.processAttack(this, weapon);
} | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"public void resolve(){\n logger.log(Level.FINE,attacker.getName()+\" withering attacked \"+defender.getName());\n AttackState state=new AttackState();\n state.weaponDamage=weapon.getDamage();\n state.initialAttackpool=baseAttackdice+baseAccuracy-woundpenalty;\n attacker.declareWi... | [
"0.67076623",
"0.66352063",
"0.6561955",
"0.63321954",
"0.63310575",
"0.63203114",
"0.62993586",
"0.6287019",
"0.62765193",
"0.614935",
"0.61477584",
"0.6080914",
"0.6074547",
"0.6058662",
"0.60457003",
"0.6042471",
"0.60414237",
"0.6028139",
"0.60210776",
"0.60148257",
"0.60... | 0.5603315 | 88 |
Creates an authorized Credential object. | public static Credential authorize() throws IOException
{
// Load client secrets.
InputStream in = YouTubeDownloader.class.getResourceAsStream("/youtube/downloader/resources/clients_secrets.json");
GoogleClientSecrets clientSecrets = GoogleClientSecrets.load(JSON_FACTORY, new InputStrea... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"AbstractCredentialModel createBasicCredential(String username, String password);",
"protected static Credentials getServiceCredentials() throws AnaplanAPIException {\n if (authType == AUTH_TYPE.CERT) {\n try {\n return new Credentials(getCertificate(), getPrivateKey());\n } catch (Exception e... | [
"0.66188663",
"0.6506624",
"0.638938",
"0.62834114",
"0.6251041",
"0.62424284",
"0.61427015",
"0.6054992",
"0.6031464",
"0.6030351",
"0.60015774",
"0.59658563",
"0.5901143",
"0.5878223",
"0.586457",
"0.5840592",
"0.5813233",
"0.5796609",
"0.5740635",
"0.57173693",
"0.5711749"... | 0.58576566 | 15 |
Build and return an authorized API client service, such as a YouTube Data API client service. | public static YouTube getYouTubeService() throws IOException {
Credential credential = authorize();
return new YouTube.Builder(
HTTP_TRANSPORT, JSON_FACTORY, credential)
.setApplicationName(APPLICATION_NAME)
.build();
} | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"private YouTube getService() throws GeneralSecurityException, IOException {\n final NetHttpTransport httpTransport = GoogleNetHttpTransport.newTrustedTransport();\n return new YouTube.Builder(httpTransport, JSON_FACTORY, null)\n .setApplicationName(APPLICATION_NAME)\n .build();\n }",
"public... | [
"0.63384336",
"0.6336757",
"0.6198538",
"0.6143181",
"0.6020759",
"0.5928088",
"0.58776295",
"0.58676696",
"0.5846059",
"0.5843613",
"0.58411926",
"0.58395433",
"0.5824829",
"0.580408",
"0.5759715",
"0.5748068",
"0.57446945",
"0.5728541",
"0.57241565",
"0.5689256",
"0.5688689... | 0.5493431 | 35 |
Use Comparator.comparing and thenComparing to sort the list by balance and then by ownerName Collect your stream into a list and print the sorted result to the console | public static void main(String[] args) {
List<Account> accounts = new ArrayList<Account>() {
{
add(new Account("Bob", 5000, 1001));
add(new Account("Jim", 10000, 1002));
add(new Account("Bruce", 5300, 1003));
add(new Account("Li", 12000, 1004));
add(new Account("Sam", 9000, 1005));
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"public static void main(String[] args) {\n ArrayList<BankAccount> accounts = makeBankingSystem();\n \n Collections.sort(accounts, BankAccount.createComparatorByBalance(false));\n for (BankAccount c: accounts){\n System.out.println(c.getName(c)+\", \"+c.getBalance(c));\n ... | [
"0.7342798",
"0.62204266",
"0.61799073",
"0.61594415",
"0.5991168",
"0.5972254",
"0.59635943",
"0.5947595",
"0.5941119",
"0.5855189",
"0.5837831",
"0.5768275",
"0.57673025",
"0.5755676",
"0.57053995",
"0.569247",
"0.56918305",
"0.5656489",
"0.5646564",
"0.56400543",
"0.559406... | 0.68962926 | 1 |
Runs when the job is started | @Override
public boolean onStartJob(JobParameters job) {
Log.d(LOG_TAG, "Sync job started...");
new Thread(new SyncRunnable(job)).start();
return true;
} | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"protected void beforeJobExecution() {\n\t}",
"private void scheduleJob() {\n\n }",
"@Override\n\t\t\tpublic void onStart() {\n\t\t\t\tSystem.out.println(\"onStart\");\n\t\t\t\tif(listener!=null) listener.onMessage(\"onStart\");\n\t\t\t\tisRun = true;\n\t\t\t}",
"private void startJobs() {\n List<Jo... | [
"0.7282081",
"0.708519",
"0.7032158",
"0.6967531",
"0.6950059",
"0.6950059",
"0.69261444",
"0.6897287",
"0.688294",
"0.68201",
"0.6818587",
"0.67837304",
"0.67837304",
"0.6782441",
"0.6774908",
"0.6769945",
"0.67609227",
"0.67575425",
"0.6755716",
"0.67514807",
"0.6741714",
... | 0.6722545 | 30 |
Runs when the job is stopped | @Override
public boolean onStopJob(JobParameters job) {
Log.d(LOG_TAG, "Sync job stopped");
return true;
} | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"public void stop() {\n \t\t\tif (isJobRunning) cancel();\n \t\t}",
"@Override\n public boolean onStopJob(JobParameters job) {\n return true;\n }",
"@Override\n protected void onStop() {\n stopService(new Intent(this, MyJobScheduler.class));\n super.onStop();\n }",
"@Override\... | [
"0.7679481",
"0.7384585",
"0.7330686",
"0.73277533",
"0.73160166",
"0.7285944",
"0.727875",
"0.72000724",
"0.72000724",
"0.7185586",
"0.71746755",
"0.7173771",
"0.7158877",
"0.71486473",
"0.7144053",
"0.71437716",
"0.71392363",
"0.70970917",
"0.70948863",
"0.70948863",
"0.706... | 0.70090365 | 46 |
When the sync has completed in a background thread, calls jobFinished() | private void onSyncFinished(JobParameters job) {
jobFinished(job, false); // Is a reschedule needed?
Log.d(LOG_TAG, "Sync job finished");
} | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"protected void jobFinished(Progress job) {\n }",
"protected void finished(){\n if (doFilterUpdate) {\n //runFilterUpdates();\n }\n \n double groupTotalTimeSecs = (System.currentTimeMillis() - (double) groupStartTime) / 1000;\n log.info(\"Job \"+id+\" finished \" /... | [
"0.7151507",
"0.7034199",
"0.69863266",
"0.6974351",
"0.68917555",
"0.6668809",
"0.65870774",
"0.6490893",
"0.6362296",
"0.6340109",
"0.6321839",
"0.6309747",
"0.6287309",
"0.6278736",
"0.6278736",
"0.62505555",
"0.6249185",
"0.620791",
"0.6179291",
"0.6169736",
"0.6156029",
... | 0.79219 | 0 |
Dispatches a sync for as soon as the network is available | public static void dispatchSyncNow(Context context) {
FirebaseJobDispatcher dispatcher = new FirebaseJobDispatcher(new GooglePlayDriver(context));
Job syncJob = dispatcher.newJobBuilder()
.setTag(SYNC_TAG)
.setService(FirebaseSyncJobService.class)
.setTrigger(Trigger.... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"@Override\n public void callSync() {\n\n }",
"public void requestExtraSync()\n {\n executor.requestExtraSync();\n }",
"private void invokeSync()\n \t{\n if (iDeviceList.size() == 0)\n {\n System.out.println(\"No devices found, so nothing to test\");\n ... | [
"0.66346747",
"0.643447",
"0.61977726",
"0.61440086",
"0.61266696",
"0.5971272",
"0.5899578",
"0.5873551",
"0.57837105",
"0.5738586",
"0.5730113",
"0.5719214",
"0.57124233",
"0.5709851",
"0.5683954",
"0.5662162",
"0.56315243",
"0.5574711",
"0.5574383",
"0.55683446",
"0.554105... | 0.5435903 | 33 |
Dispatches a sync for midnight on the day it was triggered; The sync will run as soon as the network is available after midnight | public static void dispatchScheduledSync(Context context) {
FirebaseJobDispatcher dispatcher = new FirebaseJobDispatcher(new GooglePlayDriver(context));
Job syncJob = dispatcher.newJobBuilder()
.setTag(SYNC_TAG_SCHEDULED)
.setService(FirebaseSyncJobService.class)
.set... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"public static void dispatchSyncNow(Context context) {\n FirebaseJobDispatcher dispatcher = new FirebaseJobDispatcher(new GooglePlayDriver(context));\n Job syncJob = dispatcher.newJobBuilder()\n .setTag(SYNC_TAG)\n .setService(FirebaseSyncJobService.class)\n .setTrigge... | [
"0.63342047",
"0.5996821",
"0.5919967",
"0.589004",
"0.5886641",
"0.58731973",
"0.58548844",
"0.58517325",
"0.58481634",
"0.5836042",
"0.5832729",
"0.5803721",
"0.5782976",
"0.5780491",
"0.5766398",
"0.5766398",
"0.5766398",
"0.5766398",
"0.5766398",
"0.5766398",
"0.5760471",... | 0.6004485 | 1 |
TODO Autogenerated method stub | @Override
protected JsonUtil getJsonUtil() {
return super.getJsonUtil();
} | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"@Override\r\n\tpublic void comer() \r\n\t{\n\t\t\r\n\t}",
"@Override\n\tpublic void comer() {\n\t\t\n\t}",
"@Override\n public void perish() {\n \n }",
"@Override\r\n\t\t\tpublic void annadir() {\n\r\n\t\t\t}",
"@Override\n\tpublic void anular() {\n\n\t}",
"@Override\n\tprotected void getExr... | [
"0.6671074",
"0.6567672",
"0.6523024",
"0.6481211",
"0.6477082",
"0.64591026",
"0.64127725",
"0.63762105",
"0.6276059",
"0.6254286",
"0.623686",
"0.6223679",
"0.6201336",
"0.61950207",
"0.61950207",
"0.61922914",
"0.6186996",
"0.6173591",
"0.61327106",
"0.61285484",
"0.608016... | 0.0 | -1 |
= new XStream(/new DomDriver()/); | public UE2_0_3Serializer(){
xstream = new XStream(/*new DomDriver()*/);
} | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"private static XStream createXStream(){\r\n\t\tXStream xstream = new XStream();\r\n\t\txstream.alias(\"configuration\", FilterConfig.class);\r\n\t\txstream.alias(\"filter\", FilterEnumeration.class);\r\n\t\txstream.alias(\"displayable\", DisplayableValue.class);\r\n\t\treturn xstream;\r\n\t}",
"private XStream b... | [
"0.6437617",
"0.61609674",
"0.6097178",
"0.6033878",
"0.5750813",
"0.56777906",
"0.56417257",
"0.56292987",
"0.5612706",
"0.5545476",
"0.5510748",
"0.54784656",
"0.54489815",
"0.5396621",
"0.53856915",
"0.53856915",
"0.53856915",
"0.5377515",
"0.5365683",
"0.5359267",
"0.5346... | 0.7016496 | 0 |
overridden in subclasses which handle StsObjects (DBStsClassType) and StsObject arrays (DBArrayType) | public void addToModel(Object object, StsModel model)
{
} | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"@Test public void getBaseTypeShouldReturnCorrectType() throws SQLException {\n\t\tList<Object> list = new ArrayList<>();\n\t\tArray array;\n\t\tfor (int type : Array.TYPES_SUPPORTED) {\n\t\t\tarray = new ListArray(list, type);\n\t\t\tassertEquals(type, array.getBaseType());\n\t\t}\n\t}",
"public Object[] getOrac... | [
"0.62701625",
"0.6001787",
"0.59190506",
"0.5896174",
"0.56076545",
"0.55986786",
"0.5593873",
"0.5554742",
"0.5491266",
"0.5434515",
"0.5389556",
"0.5347643",
"0.5283941",
"0.52790344",
"0.5270215",
"0.526104",
"0.52586496",
"0.5224994",
"0.52160054",
"0.5215911",
"0.5214756... | 0.0 | -1 |
initilize the MDP space | public MarkovDecisionProcess(int totalWorkloadLevel, int totalGreenEnergyLevel, int totalBatteryLevel, double prob[][][][], int maxTimeInterval) {
this.totalWorkloadLevel = totalWorkloadLevel;
this.totalGreenEnergyLevel = totalGreenEnergyLevel;
this.totalBatteryLevel = totalBatteryLevel;
this.prob = prob;
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"private void initialize()\n\t{\n\t\tfor(int i = 0 ; i < SOM.length; i++)\n\t\t{\n\t\t\tfor(int j=0; j < SOM[0].length; j++)\n\t\t\t{ \n\t\t\t\tSOM[i][j] = new Node(INPUT_DIMENSION,i,j);\n\t\t\t}\n\t\t}\n\t\t\n\t\tSOM_HORIZONTAL_LENGTH = SOM[0].length;\n\t\tSOM_VERTICAL_LENGTH = SOM.length;\n\t}",
"protected void... | [
"0.6601136",
"0.6157716",
"0.61171573",
"0.6083329",
"0.60725474",
"0.60689014",
"0.6026129",
"0.59705883",
"0.59691113",
"0.5969023",
"0.5964641",
"0.5938181",
"0.5920524",
"0.5860429",
"0.586032",
"0.5830627",
"0.58145696",
"0.5762541",
"0.57598805",
"0.57218087",
"0.570203... | 0.0 | -1 |
Identify the possible actions at a time interval | public void compileActions(int totalWorkloadLevel, int totalBatteryLevel) {
//possible actions
possibleActions = new Vector(totalWorkloadLevel * totalBatteryLevel);
for(int i = 0; i < totalWorkloadLevel; i++ ) {
for(int j = 0; j < totalBatteryLevel; j++) {
possibleActions.add(new Action(i ,j));
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"protected IntervalAction action() {\n CCSize s = Director.sharedDirector().winSize();\n return MoveBy.action(duration, s.width-ADJUST_FACTOR,0);\n }",
"public java.lang.String getTimeLimitAction();",
"private void getAllTotesCenterTimer()\r\n\t{\r\n\t\tswitch(autoStep)\r\n\t\t{\r\n\t\t\tcase 0... | [
"0.62615496",
"0.6211173",
"0.6034601",
"0.5910164",
"0.58662784",
"0.5834497",
"0.5767944",
"0.57226425",
"0.5710012",
"0.5602206",
"0.55739397",
"0.5552535",
"0.5488966",
"0.54438037",
"0.5385042",
"0.5383318",
"0.53721845",
"0.53507763",
"0.5339337",
"0.5339281",
"0.533384... | 0.0 | -1 |
Find the reachable states. The states with 0 probability are not considered. The following 4 methods are related to states | public void compileStates(int timeinterval) {
if(timeinterval == -1) {
//Add initial State
reachableStates.add(initialState);
this.numReachableState = 1;
}else{
State s;
int index = 0;
reachableStates.clear();
for(int i = 0; i < totalWorkloadLevel; i++) {
for(int j = 0; j < to... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"private Set<Integer> getStatesFromWichReachableAccepting(LabelledTransitionSystem ret) {\n\t\tMap<Integer, Set<Integer>> reversedReachable = this.computeInverseTransitionRelation(ret);\n\n\t\tSet<Integer> reachable = new HashSet<>();\n\n\t\tlogger.debug(\"Accepting states: \" + ret.getAccepting());\n\t\tSet<Integ... | [
"0.6960649",
"0.6578546",
"0.6324636",
"0.63120854",
"0.62913",
"0.6270745",
"0.6253968",
"0.62040216",
"0.6181632",
"0.6178198",
"0.61097604",
"0.59901774",
"0.5923785",
"0.59135926",
"0.5866732",
"0.5804204",
"0.5799127",
"0.5793137",
"0.5774621",
"0.5748617",
"0.5748397",
... | 0.614467 | 10 |
The following methods are related to actions. | public void setAction(State s, Action a) {
if(s.isTerminated())
return ;
s.action = a;
} | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"@Override\n public void action() {\n }",
"@Override\n public void action() {\n }",
"@Override\n public void action() {\n }",
"@Override\r\n\tpublic void action() {\n\t\t\r\n\t}",
"@Override\n\tpublic void action() {\n\n\t}",
"public void a... | [
"0.7511674",
"0.7511674",
"0.7511674",
"0.7497134",
"0.7301133",
"0.7022942",
"0.701082",
"0.701082",
"0.6969324",
"0.6966433",
"0.6960882",
"0.6960882",
"0.6960882",
"0.6960882",
"0.6960882",
"0.6960882",
"0.6960882",
"0.6960882",
"0.69602305",
"0.6944075",
"0.6889046",
"0... | 0.0 | -1 |
To validate the transit is possible, e.g. using some actions can reach out of boundary. The next state should belong to [0, maxLevel) | public boolean isPossibleTransit(State s, Action a) {
// int newWorkloadLevel = s.getWorkload() + a.getChangedWorkload();
int maxBatteryLevel = getNextBatteryLevel(s, a);
int maxActionLevel = s.getWorkload();
if((a.getChangedWorkload() <= maxActionLevel) && (a.getBatteryUsed() <= maxBatteryLevel))
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"private boolean isFeasibleState(int[] state){\n if((state[0] <= totalMissionaries && state[0] >= 0)&&(state[1] <= totalCannibals && state[1] >= 0)) {\n return true;\n }\n return false;\n }",
"private boolean isLegalState(int[] state){\n int[] stat... | [
"0.6315222",
"0.6267551",
"0.582121",
"0.57448274",
"0.56248367",
"0.55508405",
"0.54710585",
"0.5460037",
"0.5436863",
"0.543296",
"0.5431234",
"0.5420635",
"0.54013866",
"0.53622645",
"0.535507",
"0.53387207",
"0.53198844",
"0.5304792",
"0.5287709",
"0.5286305",
"0.5277106"... | 0.60037935 | 2 |
Handle when the module create | private void onModuleCreate(HTMLCanvasElement element, Display.Preference preference) {
Window.current().getDocument().addEventListener("visibilitychange", evt -> {
if (isHidden()) {
mLifecycle.onPause();
} else {
mLifecycle.onResume();
}
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"Module createModule();",
"private void onModuleCreate(Display.Preference preference) {\n //!\n //! Create display module.\n //!\n final GLFWFramebufferSizeCallback resize = GLFWFramebufferSizeCallback.create((window, width, height) ->\n {\n mLifecycle.onResize(width,... | [
"0.68034625",
"0.6711702",
"0.6527934",
"0.6393818",
"0.63243264",
"0.6164201",
"0.6121402",
"0.6116891",
"0.6078842",
"0.6066631",
"0.6059779",
"0.6052971",
"0.6052953",
"0.6026041",
"0.6000761",
"0.5979037",
"0.5970702",
"0.5948964",
"0.59469575",
"0.5939309",
"0.5925476",
... | 0.62566835 | 5 |
Handle when the module destroy | private void onModuleDestroy() {
//!
//! Handle the destroy notification.
//!
mLifecycle.onPause();
mLifecycle.onDispose();
//!
//! Unload resource module.
//!
mResources.onModuleDestroy();
mResources.unloadAll();
//!
//!... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"private void onModuleDestroy() {\n //!\n //! Handle the destroy notification.\n //!\n mLifecycle.onPause();\n mLifecycle.onDispose();\n\n //!\n //! Unload resource module.\n //!\n mResources.onModuleDestroy();\n mResources.unloadAll();\n\n ... | [
"0.8181511",
"0.75969905",
"0.7558324",
"0.7558324",
"0.7441234",
"0.7431554",
"0.74286646",
"0.74250126",
"0.7419767",
"0.74126613",
"0.73860735",
"0.7385367",
"0.73809224",
"0.7374312",
"0.7363231",
"0.7361256",
"0.73571324",
"0.73571324",
"0.73571324",
"0.73571324",
"0.735... | 0.81478137 | 1 |
Handle when the module update | private void onModuleUpdate() {
if (mTime == -1L) {
mTime = System.currentTimeMillis();
}
//!
//! Render until the display is not active.
//!
onModuleRender(System.currentTimeMillis());
//!
//! Request to render again.
//!
onA... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"@Override\n\t\t\t\t\tpublic void onUpdateFound(boolean newVersion, String whatsNew) {\n\t\t\t\t\t}",
"public void receivedUpdateFromServer();",
"protected void onUpdate() {\r\n\r\n\t}",
"private void checkForUpdates() {\n UpdateManager.register(this);\n }",
"private void checkForUpdates() {\n ... | [
"0.6469783",
"0.64249146",
"0.6423273",
"0.62885034",
"0.62885034",
"0.62644833",
"0.6256242",
"0.62548566",
"0.62518567",
"0.62348956",
"0.6197051",
"0.6189723",
"0.61573714",
"0.6141606",
"0.61268306",
"0.61223435",
"0.61118865",
"0.6096208",
"0.6074734",
"0.6072602",
"0.60... | 0.6269706 | 5 |
Handle when the module render | private void onModuleRender(long time) {
//!
//! Handle the render notification.
//!
mLifecycle.onRender((time - mTime) / 1000.0f);
//!
//! Update the new delta time.
//!
mTime = time;
//!
//! Update the render.
//!
//! NO... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"@Override\n public void onModuleLoad() {\n }",
"protected void render(){}",
"private void onModuleUpdate() {\n if (mTime == -1L) {\n mTime = System.currentTimeMillis();\n }\n\n //!\n //! Render until the display is not active.\n //!\n onModuleRender(Sy... | [
"0.66186696",
"0.6570539",
"0.65294087",
"0.6513774",
"0.6488292",
"0.6309487",
"0.6306284",
"0.62951434",
"0.6203096",
"0.6157021",
"0.612381",
"0.61110157",
"0.6097233",
"0.60969275",
"0.60931396",
"0.6078594",
"0.6070372",
"0.6069029",
"0.6024401",
"0.601679",
"0.59685624"... | 0.64993 | 4 |
Construct the conditional element from an XML node | public SCondition(Node node) {
super(node);
} | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"ConditionalExpression createConditionalExpression();",
"public Instruction startConditionalNode(final PsiElement element, final PsiElement condition, final boolean result) {\n final ConditionalInstruction instruction = new ConditionalInstructionImpl(this, element, condition, result);\n addNode(instruction)... | [
"0.6060902",
"0.59389997",
"0.5817393",
"0.5599313",
"0.5585734",
"0.543987",
"0.53712994",
"0.5344337",
"0.5213824",
"0.5054645",
"0.5044381",
"0.49947184",
"0.4972317",
"0.4969138",
"0.4935641",
"0.493025",
"0.48860538",
"0.4874012",
"0.48736987",
"0.48621866",
"0.4859078",... | 0.5184418 | 9 |
/ access modifiers changed from: protected | public void updateBackground(int i, int i2, int i3, int i4) {
if (this.mLauncher.getDeviceProfile().isVerticalBarLayout()) {
View revealView = getRevealView();
int i5 = i;
int i6 = i2;
int i7 = i3;
int i8 = i4;
InsetDrawable insetDrawable =... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"@Override\n protected void prot() {\n }",
"private stendhal() {\n\t}",
"@Override\n\tpublic void grabar() {\n\t\t\n\t}",
"@Override\n public void perish() {\n \n }",
"@Override\n\tpublic void comer() {\n\t\t\n\t}",
"@Override\r\n\tpublic void comer() \r\n\t{\n\t\t\r\n\t}",
"@Override... | [
"0.7375736",
"0.7042321",
"0.6922649",
"0.6909494",
"0.68470824",
"0.6830288",
"0.68062353",
"0.6583185",
"0.6539446",
"0.65011257",
"0.64917654",
"0.64917654",
"0.64733833",
"0.6438831",
"0.64330196",
"0.64330196",
"0.64295477",
"0.6426414",
"0.6420484",
"0.64083177",
"0.640... | 0.0 | -1 |
/ access modifiers changed from: protected | public void onFinishInflate() {
super.onFinishInflate();
getContentView().setOnFocusChangeListener(new OnFocusChangeListener() {
public void onFocusChange(View view, boolean z) {
if (z) {
AllAppsContainerView.this.mAppsRecyclerView.requestFocus();
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"@Override\n protected void prot() {\n }",
"private stendhal() {\n\t}",
"@Override\n\tpublic void grabar() {\n\t\t\n\t}",
"@Override\n public void perish() {\n \n }",
"@Override\n\tpublic void comer() {\n\t\t\n\t}",
"@Override\r\n\tpublic void comer() \r\n\t{\n\t\t\r\n\t}",
"@Override... | [
"0.7375736",
"0.7042321",
"0.6922649",
"0.6909494",
"0.68470824",
"0.6830288",
"0.68062353",
"0.6583185",
"0.6539446",
"0.65011257",
"0.64917654",
"0.64917654",
"0.64733833",
"0.6438831",
"0.64330196",
"0.64330196",
"0.64295477",
"0.6426414",
"0.6420484",
"0.64083177",
"0.640... | 0.0 | -1 |
/ access modifiers changed from: protected | public void onMeasure(int i, int i2) {
DeviceProfile deviceProfile = this.mLauncher.getDeviceProfile();
deviceProfile.updateAppsViewNumCols();
if (!(this.mNumAppsPerRow == deviceProfile.inv.numColumns && this.mNumPredictedAppsPerRow == deviceProfile.inv.numColumns)) {
this.mNumAppsPe... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"@Override\n protected void prot() {\n }",
"private stendhal() {\n\t}",
"@Override\n\tpublic void grabar() {\n\t\t\n\t}",
"@Override\n public void perish() {\n \n }",
"@Override\n\tpublic void comer() {\n\t\t\n\t}",
"@Override\r\n\tpublic void comer() \r\n\t{\n\t\t\r\n\t}",
"@Override... | [
"0.7375736",
"0.7042321",
"0.6922649",
"0.6909494",
"0.68470824",
"0.6830288",
"0.68062353",
"0.6583185",
"0.6539446",
"0.65011257",
"0.64917654",
"0.64917654",
"0.64733833",
"0.6438831",
"0.64330196",
"0.64330196",
"0.64295477",
"0.6426414",
"0.6420484",
"0.64083177",
"0.640... | 0.0 | -1 |
Creates new form UdpExample | public UdpExample() {
initComponents();
myInitComponents();
} | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"public void createClient() {\n client = new UdpClient(Util.semIp, Util.semPort, this);\n\n // Le paso true porque quiero que lo haga en un hilo nuevo\n client.connect(true);\n }",
"private void createThreadUdp(){\n System.out.println(\"dirport: \"+serverDirPort);\n System.ou... | [
"0.58957815",
"0.57204866",
"0.55944467",
"0.5585818",
"0.5500188",
"0.54953784",
"0.5358484",
"0.5327305",
"0.523669",
"0.5218695",
"0.518186",
"0.51683307",
"0.5143919",
"0.5135067",
"0.5125136",
"0.51148444",
"0.51035833",
"0.5090125",
"0.50848883",
"0.50686747",
"0.503856... | 0.6603273 | 0 |
This method is called from within the constructor to initialize the form. WARNING: Do NOT modify this code. The content of this method is always regenerated by the Form Editor. //GENBEGIN:initComponents | private void initComponents() {
udpServer = new UdpServer();
jLabel1 = new javax.swing.JLabel();
portField = new javax.swing.JFormattedTextField(0);
jLabel2 = new javax.swing.JLabel();
groupField = new javax.swing.JTextField();
jPanel1 = new javax.swing.JPanel();
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"public MainForm() {\n initComponents();\n }",
"public MainForm() {\n initComponents();\n }",
"public MainForm() {\n initComponents();\n }",
"public Form() {\n initComponents();\n }",
"public TorneoForm() {\n initComponents();\n }",
"public GUIForm() { \... | [
"0.7392436",
"0.7392436",
"0.7392436",
"0.73524207",
"0.7332867",
"0.73308986",
"0.729576",
"0.7267236",
"0.72270304",
"0.721562",
"0.7159843",
"0.71548635",
"0.715188",
"0.71416056",
"0.7137083",
"0.7133313",
"0.71205837",
"0.7119088",
"0.71151245",
"0.7110943",
"0.7088094",... | 0.0 | -1 |
Devuelve el siguiente elemento de la iteracion. | public T getNext()
{
T elem = handler.getTop();
handler.pop();
return elem;
} | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"public Object nextElement() {\n/* 75 */ return this.iterator.next();\n/* */ }",
"@Override public T next() {\n T elem = null;\n if (hasNext()) {\n Nodo<T> nodo = pila.pop();\n elem = nodo.elemento;\n nodo = nodo.derecho;\n while(nod... | [
"0.7192707",
"0.6767897",
"0.67309755",
"0.6702413",
"0.6571108",
"0.6538033",
"0.6536762",
"0.6527444",
"0.64980906",
"0.64886534",
"0.647263",
"0.64412105",
"0.6434362",
"0.6362155",
"0.63204587",
"0.6312327",
"0.63089746",
"0.6299254",
"0.62807673",
"0.6239724",
"0.6233277... | 0.0 | -1 |
Devuelve cierto si aun quedan elementos sin visitar en la iteracion. | public boolean hasNext()
{
return !handler.isEmpty();
} | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"@Override\n public boolean hasNext() {\n return numeroDiNodiAncoraVisitabili>0;\n }",
"@Override\n public boolean hasNext() {\n return nextElementSet || setNextElement();\n }",
"public boolean hasNext() {\n return neste.neste != null;\n }",
... | [
"0.7592424",
"0.6926388",
"0.6878384",
"0.6870281",
"0.68617177",
"0.68286926",
"0.67438436",
"0.6730197",
"0.67210704",
"0.6719351",
"0.6699117",
"0.6674327",
"0.66348255",
"0.6598542",
"0.6592435",
"0.6578686",
"0.6569268",
"0.65667766",
"0.65659076",
"0.65659076",
"0.65510... | 0.0 | -1 |
Restablece el iterador al comienzo. | public void reset()
{
handler = new StackDynamic<T>(restart);
} | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"@Override\n public Iterator<Piedra> iterator() {\n return piedras.iterator();\n \n //crear un iterator propio\n// return new Iterator<Piedra>(){\n// int index=0;\n// @Override\n// public boolean hasNext() {\n// return piedras.size()>index;\n//... | [
"0.692098",
"0.6857741",
"0.64886135",
"0.6363798",
"0.63234025",
"0.63232815",
"0.6194288",
"0.6186084",
"0.6163172",
"0.61521715",
"0.61305285",
"0.61029303",
"0.60938513",
"0.6057746",
"0.6014972",
"0.59946156",
"0.59726554",
"0.5968486",
"0.58997965",
"0.58735925",
"0.587... | 0.0 | -1 |
========================================================================== Misc. Method(s) ========================================================================== JBuilder init method. Constructs the Add Vehicle Dialog. Using XYLayout to allow rapid building, final version will use swing layout manager(s). | void jbInit() throws Exception {
//setup file dialog
filer1.setFrame(f);
filer1.setMode(FileDialog.LOAD);
filer1.setTitle("Select Vehicle Image");
panel1.setLayout(xYLayout1);
jLabel1.setFont(new java.awt.Font("Dialog", 1, 12));
jLabel1.setText("VIN");
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"public CarRentalGUI() {\n initComponents();\n this.setLocationRelativeTo(null);\n\n //set outer border\n Border globalBorder = BorderFactory.createMatteBorder(1, 1, 1, 1, Color.BLUE);\n jPanel6.setBorder(globalBorder);\n\n Border labelBorder = BorderFactory.createMatteBord... | [
"0.6469756",
"0.6445048",
"0.6428486",
"0.6292821",
"0.6272948",
"0.6254247",
"0.6250972",
"0.62066776",
"0.6204562",
"0.6202428",
"0.61703134",
"0.61426735",
"0.61191094",
"0.6111631",
"0.6110794",
"0.6087033",
"0.60704136",
"0.60688585",
"0.6065546",
"0.60648066",
"0.606238... | 0.61838967 | 10 |
Add ActionListener(s) to this object's components. | public void addActionlistener(ActionListener l) {
cancelButton.addActionListener(l);
addButton.addActionListener(l);
} | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"private void addActionListeners() {\n\t\tif(this.actionListener == null)\n\t\t\t\treturn; \n\t\t\n\t\t\n\t\t/**\n\t\t\tADD ACTION LISTENERS FOR BUTTONS HERE \n\t\t*/\n\t\tclearButton.addActionListener(this.actionListener);\n\t\tsinButton.addActionListener(this.actionListener);\n\t\tcosButton.addActionListener(thi... | [
"0.7544628",
"0.70504725",
"0.70274967",
"0.7007636",
"0.69900686",
"0.6946617",
"0.69072986",
"0.6870675",
"0.6811738",
"0.6727979",
"0.67126465",
"0.6658835",
"0.66560894",
"0.6621376",
"0.6617824",
"0.65839547",
"0.65759295",
"0.6573816",
"0.653521",
"0.65268123",
"0.65120... | 0.60643977 | 55 |
========================================================================== Accessor Method(s) ========================================================================== get VIN field | public String getVinField() {
return vinField.getText();
} | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"public String getVin() {\r\n return vin;\r\n }",
"public String getVin() {\r\n return vin;\r\n }",
"public String getVin() {\n\t\treturn vin;\n\t}",
"@java.lang.SuppressWarnings(\"all\")\n\t@javax.annotation.Generated(\"lombok\")\n\tpublic Integer getVout() {\n\t\treturn this.vout;\n\t}",... | [
"0.8019909",
"0.8019909",
"0.7904182",
"0.6519607",
"0.6426085",
"0.6360435",
"0.6318972",
"0.63120234",
"0.6292406",
"0.62828076",
"0.6263334",
"0.6227649",
"0.6151719",
"0.6117357",
"0.61125505",
"0.60916674",
"0.60594875",
"0.59920293",
"0.5984074",
"0.5974455",
"0.5945448... | 0.793292 | 2 |
Add a barge to the schedule. The schedule should be sorted on the latest starting time in order to construct waiting profiles. Because LinkedHashMap (in which schedule is stored) does not provide this functionality out of the box, we implemented that in this method as well. | public void addAppointment(Barge barge, int LAT, int LST, int PT) {
// determine position where the appointment should be inserted.
// the schedule should be sorted on the LST in order to create
// a right waiting profile
// to keep track of the position we use integer i.
int i = 0;
for (Barge b : thi... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"public void bargeArrives(Barge barge, int time) {\r\n\t\tthis.actualArrival.put(barge, time);\r\n\t\tthis.queue.add(barge);\r\n\t\t//System.out.println(barge+\" arrived to \"+this.name+\"// arraival list= \"+this.actualArrival);\r\n\r\n\t\tif (Port.terminalLogic.equals(\"Unreserved\")\r\n\t\t\t\t&& this.state == T... | [
"0.5888798",
"0.5256955",
"0.52559215",
"0.5074789",
"0.49696532",
"0.4933672",
"0.47966903",
"0.4784746",
"0.47363544",
"0.4670205",
"0.46597457",
"0.45890528",
"0.45849794",
"0.45724517",
"0.45602462",
"0.45258614",
"0.4513077",
"0.45021588",
"0.44744876",
"0.44405648",
"0.... | 0.64348143 | 0 |
Construct and send the waiting profile | public WaitingProfile constructWaitingProfile(Barge barge, int currentTime) {
/*if(Port.eventsToExcel.equals("Yes")){
Port.stats.addEvent(currentTime, barge.bargeNumber, (barge.toString()+ " asked Terminal " + this.toString()+
" for appoints "+
" ||appointements= " +this.appointmentsToString()));... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"public WaitMessage() {\n super(\"Wait for other player...\\n\");\n }",
"public WaitingScreen() {\r\n super(\"Please wait...\", new Item[0]);\r\n mWaitString = new StringItem(\"Network\", \"\\nServer contacting...\");\r\n append(mWaitString);\r\n }",
"public void takeABus() {\n... | [
"0.5978791",
"0.593957",
"0.57592046",
"0.57502234",
"0.5711542",
"0.56396985",
"0.54175526",
"0.54088545",
"0.53503424",
"0.5343656",
"0.5277495",
"0.5212677",
"0.51851505",
"0.51746285",
"0.51730317",
"0.51724344",
"0.5170638",
"0.5169571",
"0.5169422",
"0.51569474",
"0.514... | 0.6625135 | 0 |
[ISchedulableAction] Starts the handling of a barge | public void bargeArrives(Barge barge, int time) {
this.actualArrival.put(barge, time);
this.queue.add(barge);
//System.out.println(barge+" arrived to "+this.name+"// arraival list= "+this.actualArrival);
if (Port.terminalLogic.equals("Unreserved")
&& this.state == Terminal.IDLE) {
// ////////////... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"@Override\n\tpublic void startAction() {\n\t if (!balls.isEmpty() && firingBall == null) {\n\t gb.addToActiveList(this);\n\t //fire next ball\n\t firingBall = (Ball)balls.remove(0);\n\t firingBall.setAbsorbed(false);\n\t firingBall.setVy(-50*25);\n\t //align balls that ... | [
"0.60295343",
"0.5606827",
"0.5590184",
"0.55576533",
"0.5528375",
"0.5524553",
"0.5486794",
"0.5465112",
"0.54485816",
"0.5447672",
"0.54170245",
"0.54109377",
"0.54080003",
"0.53897685",
"0.53719693",
"0.5360487",
"0.5346576",
"0.53193474",
"0.5295799",
"0.526556",
"0.52616... | 0.5785605 | 1 |
/ returns a boolean array the cell 0 is if barge handled and cell 1 if rejected | private boolean[] checkIfHandleBarge(Barge barge, int time) {
boolean [] result={false, false};
// if there is no other barge in the appointment list start handling
// directly
if (this.appointments.size() == 1) {
Port.schedule.schedule(ScheduleParameters.createOneTime(time,
ScheduleParameters.L... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"boolean arrCompleted(Boolean[] boolarray) {\n for (int i=0; i < boolarray.length; i++) {\n if (boolarray[i] == false) {\n return false;\n }\n }\n return true;\n }",
"public abstract boolean[] calculate();",
"public boolean[] binaryRep() {\r\n\t\tint ... | [
"0.6177478",
"0.58768654",
"0.5826917",
"0.57497036",
"0.57344043",
"0.5653771",
"0.55440766",
"0.55113983",
"0.5510413",
"0.5458107",
"0.5432543",
"0.5430274",
"0.54228544",
"0.5409766",
"0.5367916",
"0.5297036",
"0.52512187",
"0.5243054",
"0.5242889",
"0.5239475",
"0.523783... | 0.55202043 | 7 |
[ISchedulableAction] Finish handling of a barge | public void finishHandling(Barge barge, int time) {
// remove the barge from appointments of terminal
this.appointments.remove(barge);
this.numHandling--;
//this.state = Terminal.IDLE;
// let the barge decide what to do after it finished handling
barge.afterFinish(time, this);
if (Port.ev... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"public void finish() {\n if ( actor.hasActions() )\r\n actor.getActions().first().act(100000);\r\n // remove any remaining actions\r\n actor.clearActions();\r\n }",
"public void bargeArrives(Barge barge, int time) {\r\n\t\tthis.actualArrival.put(barge, time);\r\n\t\tthis.queue.... | [
"0.6180914",
"0.6005668",
"0.59980047",
"0.5964356",
"0.59331924",
"0.58989424",
"0.58989424",
"0.583515",
"0.58235973",
"0.5820916",
"0.58036083",
"0.58036083",
"0.58036083",
"0.5775158",
"0.57534784",
"0.5750173",
"0.5719388",
"0.5704176",
"0.5671254",
"0.56403315",
"0.5607... | 0.6209253 | 0 |
used to display the queue size in the chart in the GUI | public int getQueueSize() {
return this.queue.size();
} | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"public void refreshQueueCount(){\n queueCountLabel.setText(\"Count: \" + String.valueOf(builder.size()));\n }",
"public static void setSizeOfQueue(Label sizeOfQueueValue) {\n \tsizeOfQueueValue.setText(String.valueOf(Capture.getInspectionQueue().size()));\n }",
"private void updateQueueSize() {... | [
"0.7117305",
"0.7057366",
"0.63759696",
"0.6305131",
"0.6222833",
"0.6218054",
"0.61677057",
"0.61127317",
"0.6040652",
"0.59914076",
"0.59774333",
"0.5955932",
"0.59541416",
"0.59411484",
"0.59391844",
"0.5908418",
"0.58950377",
"0.5893207",
"0.5882426",
"0.58606815",
"0.583... | 0.5706392 | 35 |
used to display the number of busy terminals in the GUI | public int getNumhandling() {
return this.numHandling;
} | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"public int getNumIdle();",
"protected void printNumberSelectedPicturesOnStatusLine( ) {\n\t\tSwingUtilities.invokeLater(new Runnable() {\n\t\t\t \n\t\t\tpublic void run() {\n\t\t\t\tString text;\n\t\t\t\tint count = indexData.pictureSelected.cardinality();\n\t\t\t\tif (count == 1) {\n\t\t\t\t\ttext = \"1 picture... | [
"0.61746365",
"0.594273",
"0.5871741",
"0.58549523",
"0.58340186",
"0.5815044",
"0.58114344",
"0.5793308",
"0.5776639",
"0.5737697",
"0.57220066",
"0.57064086",
"0.5644291",
"0.56392187",
"0.56334",
"0.56326735",
"0.5588907",
"0.55809414",
"0.55712754",
"0.5569568",
"0.552272... | 0.0 | -1 |
Initializes the controller class. | @Override
public void initialize(URL url, ResourceBundle rb) {
model=DomainController.getInstance();
addDataToChoiceBox();
} | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"private void initialize() {\n\t\tcontroller = Controller.getInstance();\n\t}",
"public MainController() {\n\t\tcontroller = new Controller(this);\n\t}",
"public abstract void initController();",
"public Controller() {\n super();\n }",
"public Controller() {\n super();\n }",
"public Co... | [
"0.8125658",
"0.78537387",
"0.78320265",
"0.776199",
"0.776199",
"0.76010174",
"0.74497247",
"0.7437837",
"0.7430714",
"0.742303",
"0.74057597",
"0.7341963",
"0.7327749",
"0.72634363",
"0.72230434",
"0.7102504",
"0.70575505",
"0.69873077",
"0.69721675",
"0.6944077",
"0.691256... | 0.0 | -1 |
nastavenie komponentov ktore sa zobrazia v scene | public void setUpEditStage(){
solvableCircle = solvableCircleComponents();
Circle wCircle = whiteButtonComponents();
whiteCellButton = new Button("", wCircle);
whiteCellButton.getStyleClass().add("edit-buttons");
whiteCellButton.setOnAction(e-> whiteCellButtonAction());
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"public void openGamePane() {\n\t\tParent root;\n\t\ttry {\n\t\t\tFXMLLoader loader = new FXMLLoader(getClass().getResource(GAMEPANELOCATION));\n\t\t\tloader.setController(this);\n\t\t\troot = loader.load();\n\t\t\tScene scene = new Scene(root);\n\t\t\tStage stage = new Stage();\n\t\t\tstage.setScene(scene);\n\t\t\... | [
"0.6433536",
"0.6386917",
"0.63868225",
"0.6306565",
"0.62969285",
"0.6271738",
"0.62116677",
"0.61733717",
"0.6113407",
"0.6103242",
"0.60831636",
"0.6067678",
"0.60670996",
"0.6039509",
"0.60127896",
"0.60028297",
"0.6002209",
"0.5993976",
"0.5989704",
"0.5987455",
"0.59620... | 0.0 | -1 |
metoda nastavi tlacitko na clicked | public void setClickedStyle(Button button){
whiteCellButton.getStyleClass().clear();
blackCellButton.getStyleClass().clear();
removeCellButton.getStyleClass().clear();
if (button == whiteCellButton) {
whiteCellButton.getStyleClass().add("edit-buttons-selected");
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"@Override\n\t\t\tpublic void mouseClicked(MouseEvent e) {\n\t\t\t\tSystem.out.println(\"vai ficar clikando ai a toa? PATETA\");\n\t\t\t\t\n\t\t\t}",
"@Override\n public void mouseClicked(MouseEvent e) {\n System.out.println(\"MouseClicked\");\n //kwadrat.clicked();\n trojkat.clicked();\n ... | [
"0.7876019",
"0.778278",
"0.7736392",
"0.7692161",
"0.76845366",
"0.76845366",
"0.76845366",
"0.76845366",
"0.76845366",
"0.76845366",
"0.76845366",
"0.76845366",
"0.76845366",
"0.76845366",
"0.76845366",
"0.7661894",
"0.76599073",
"0.7659045",
"0.7659045",
"0.76515555",
"0.7... | 0.0 | -1 |
zmenenie stredneho kruhu cervena = naeditovany level sa neda ulozit (neriesitelne/neskotrolovane) zelena = naeditovany level sa moze ulozit | public void setCenterCircleFill(){
if(solvable){
solvableCircle.setFill(Color.GREEN);
}
else{
solvableCircle.setFill(Color.RED);
}
} | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"private String vylozZvieraZVozidla() {\r\n if (zoo.getPracovneVozidlo() == null) {\r\n return \"Pracovne vozidlo nie je pristavene\";\r\n }\r\n\r\n Integer pozicia = MojeMetody.vlozInt(\"Vloz index zvierata\");\r\n if (pozicia == null) return \"\";\r\n\r\n try {\r\n ... | [
"0.6767371",
"0.6633183",
"0.64145553",
"0.62401587",
"0.6121189",
"0.61192626",
"0.6100647",
"0.60957485",
"0.6095744",
"0.60916644",
"0.60828686",
"0.60758895",
"0.6063912",
"0.60594857",
"0.6058851",
"0.6058851",
"0.60219103",
"0.6021792",
"0.6021792",
"0.60154843",
"0.600... | 0.0 | -1 |
associate deeplinks with activity | public Intent parseAndGetIntent(Uri uri) {
Log.d(TAG, uri.toString());
List<String> pathSegments = uri.getPathSegments();
Intent intent = null;
String tagKey = pathSegments.get(0).toLowerCase();
Log.d(TAG, "tagKey:" + tagKey);
if (AppIndexApplication.getInstance().ca... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"private void deepLinkingFlow() {\n\n if (getActivity().getIntent().hasExtra(\"deeplink\")) {\n destination = getActivity().getIntent().getParcelableExtra(\"deeplink\");\n hotelSearchPresenter.checkDeepLinking(destination, getActivity().getSupportFragmentManager().beginTransaction());\n... | [
"0.72185796",
"0.7126579",
"0.6626288",
"0.65022343",
"0.6062156",
"0.59453773",
"0.5880377",
"0.57237476",
"0.57166815",
"0.5701771",
"0.55898273",
"0.55171055",
"0.5362321",
"0.5286225",
"0.52378446",
"0.52260053",
"0.51831055",
"0.5182679",
"0.51498914",
"0.5131103",
"0.51... | 0.0 | -1 |
end main Takes the input count and generates that number of random double precision floating point numbers. Counts how many times the first decimal place occurs in the sequence. Prints out each digit and the number of times it occurred in ascending order of the number of times it occurred. | public static void printEachInstance(int count) {
List<RandGeneratedValue> list = new ArrayList<RandGeneratedValue>();
for(int i = 0; i < count; i++) {
Double rand = Math.random();
RandGeneratedValue rdv = new RandGeneratedValue();
//Store the randomly generated value
rdv.setRandValue(rand);
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"public static void main(String args[])\n {\n Scanner sc=new Scanner(System.in);\n String s=sc.next();\n double n=0;\n int dcount=0;\n int pointer=0;\n for(int i=0;i<s.length();i++)\n {\n if(s.charAt(i)!='.')\n {\n n=n*10+(s.charAt(i)-'0');\n if(pointer==1)\n d... | [
"0.6357716",
"0.6274294",
"0.6172699",
"0.6132539",
"0.6061748",
"0.602409",
"0.60066456",
"0.5984489",
"0.5982982",
"0.5876075",
"0.58709735",
"0.5817232",
"0.5802197",
"0.57959926",
"0.5793088",
"0.5787493",
"0.5783517",
"0.5776166",
"0.5747733",
"0.57294",
"0.5724716",
"... | 0.6398065 | 0 |
Creates a new instance of AcuityTest | public AcuityTest() {
} | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"public ClimbingClubTest()\n {\n \n }",
"public AuthorityFactoriesTest() {\n }",
"public AllLaboTest() {\n }",
"public PerezosoTest()\n {\n }",
"public ActivitiTestCase() {\n }",
"private AccuracyTestHelper() {\n // empty\n }",
"public UnitTests()\n {\n }",
"... | [
"0.671001",
"0.66987014",
"0.65943927",
"0.65567654",
"0.6551962",
"0.6513047",
"0.64711994",
"0.6424128",
"0.6409134",
"0.6346423",
"0.6339013",
"0.6308003",
"0.6306722",
"0.6261673",
"0.6260099",
"0.6229242",
"0.61984223",
"0.6176624",
"0.6161638",
"0.6157369",
"0.6154755",... | 0.849121 | 0 |
add the patient answer to the answer list | public void saveAnswer(long answerTime, Element element, boolean patientAnswer, String patientAnswerStr){
getTestAnswers().add( new TestAnswer(answerTime, patientAnswer, element, patientAnswerStr) );
} | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"void addQuestionAnswer(Answer answer);",
"void addAnswer(Answer answer);",
"@Override\r\n public void addAnswer(String answer) {\r\n this.answers.add(answer);\r\n }",
"public void addAnswer(Answer ans) {\n // TODO implement here\n }",
"public void addAnswer(Answer answer) {\n \t\tans... | [
"0.7742983",
"0.7580539",
"0.74334913",
"0.74326485",
"0.71915084",
"0.6991407",
"0.69699365",
"0.6904292",
"0.68483573",
"0.6835915",
"0.67260784",
"0.6725295",
"0.66842264",
"0.65206254",
"0.63380796",
"0.6259477",
"0.6219937",
"0.6208152",
"0.61172754",
"0.6098837",
"0.607... | 0.62877834 | 15 |
add the patient answer to the answer list | public void saveAnswer(Element element, boolean patientAnswer, String patientAnswerStr){
getTestAnswers().add( new TestAnswer(patientAnswer, element, patientAnswerStr) );
} | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"void addQuestionAnswer(Answer answer);",
"void addAnswer(Answer answer);",
"@Override\r\n public void addAnswer(String answer) {\r\n this.answers.add(answer);\r\n }",
"public void addAnswer(Answer ans) {\n // TODO implement here\n }",
"public void addAnswer(Answer answer) {\n \t\tans... | [
"0.7742983",
"0.7580539",
"0.74334913",
"0.74326485",
"0.71915084",
"0.6991407",
"0.69699365",
"0.6904292",
"0.68483573",
"0.6835915",
"0.67260784",
"0.6725295",
"0.66842264",
"0.63380796",
"0.62877834",
"0.6259477",
"0.6219937",
"0.6208152",
"0.61172754",
"0.6098837",
"0.607... | 0.65206254 | 13 |
You can call method from the class name with className.method if that method is defined with static | public static String placePostData()
{
String res="/maps/api/place/add/json";
return res;
} | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"MethodName getMethod();",
"public static void staticMethod() {\n Log.e(\"LOG_TAG\", \"Company: STATIC Instance method\");\n }",
"static void method1() {\r\n\t\r\n}",
"static void staticShow() {\n System.out.println(\"In a static class static method\");\n }",
"static void method2(){\n... | [
"0.6563972",
"0.6557888",
"0.6542901",
"0.64990366",
"0.6412168",
"0.63668305",
"0.6343916",
"0.6343916",
"0.6322235",
"0.6314092",
"0.631077",
"0.6288914",
"0.6238323",
"0.6209906",
"0.6209906",
"0.6204279",
"0.6168336",
"0.6167555",
"0.61606055",
"0.6139141",
"0.6139141",
... | 0.0 | -1 |
get loan amount from the textView and convert it to double | @Override
public void onClick(View view) {
double loan = Double.parseDouble(binding.loanAmount.getText().toString());
// get tenure amount from the textView and convert it to double
double tenure = Double.parseDouble(binding.loanTenure.getText().toString());
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"public void getMonthlyPayment(View view) {\n //Get all the EditText ids\n EditText principal = findViewById(R.id.principal);\n EditText interestRate = findViewById(R.id.interestRate);\n EditText loanTerm = findViewById(R.id.loanTerm);\n\n //Get the values for principal, MIR and t... | [
"0.68901944",
"0.6743956",
"0.6568079",
"0.65575397",
"0.6494578",
"0.6481042",
"0.6464636",
"0.63911104",
"0.6341193",
"0.63255805",
"0.631663",
"0.62941325",
"0.6275098",
"0.6236251",
"0.6236251",
"0.6207866",
"0.61204135",
"0.611987",
"0.6101559",
"0.6098905",
"0.6091936",... | 0.68577594 | 1 |
choose the video encoder by name. | @TargetApi(Build.VERSION_CODES.JELLY_BEAN)
private static MediaCodecInfo chooseVideoEncoder(String name) {
int nbCodecs = MediaCodecList.getCodecCount();
for (int i = 0; i < nbCodecs; i++) {
MediaCodecInfo mci = MediaCodecList.getCodecInfoAt(i);
if (!mci.isEncoder()) {
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"public String getVideoPreset();",
"private void configureEncoder() throws IOException\n {\n encoder = MediaCodec.createByCodecName(encoderName);\n MediaFormat mediaFormat = MediaFormat.createVideoFormat(MIME_TYPE, width, height);\n mediaFormat.setInteger(MediaFormat.KEY_BIT_RATE, BITRATE)... | [
"0.60611564",
"0.60441685",
"0.5655714",
"0.56289583",
"0.5604947",
"0.55679303",
"0.5521886",
"0.5517504",
"0.5512166",
"0.5490423",
"0.5457824",
"0.5401785",
"0.53775036",
"0.5355942",
"0.5340001",
"0.52557766",
"0.52379006",
"0.5225033",
"0.51944387",
"0.519398",
"0.513101... | 0.82752746 | 0 |
INDEXING MANAGEMENT [MODIFIED] Inserts new information provided by new occurence of token in docID at offset. | public void insert( String token, int docID, int offset ) {
// Add to map of postingslist
//if (docID % 100 == 0)
//System.err.println("Trying to insert ''" + token + "'' found in doc "+docID);
if (this.index.containsKey(token)){
//System.err.println(token+" already in me... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"public void insert( String token, int docID, int offset ) {\r\n PostingsList posting = this.getPostings(token);\r\n if(posting != null){\r\n posting.insertElement(docID, (double)0, offset);\r\n index.put(token, posting);\r\n }\r\n else{\r\n PostingsList ... | [
"0.6344753",
"0.63235545",
"0.60032284",
"0.59595346",
"0.59330505",
"0.578764",
"0.5781231",
"0.5760061",
"0.5738502",
"0.5733359",
"0.57019573",
"0.569972",
"0.5683141",
"0.5683141",
"0.5674248",
"0.562783",
"0.5595195",
"0.55493456",
"0.5527176",
"0.55203867",
"0.5482442",... | 0.6843133 | 0 |
DISK/MEMORY MANAGEMENT [NEW] Recovers the essential files required to retrieve information in memory. This includes hashmap mapping tokens with respective terms and list of names of the retrieved documents. | public void load(){
// Recover docIDs
try(Reader reader = new FileReader("postings/docIDs.json")){
this.docIDs = (new Gson()).fromJson(reader,
new TypeToken<Map<String, String>>(){}.getType());
} catch (IOException e) {
e.printStackTrace();
}
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"private void scanDocuments()\n{\n document_counts = new HashMap<>();\n kgram_counts = new HashMap<>();\n for (File f : root_files) {\n addDocuments(f);\n }\n}",
"public static void main(String[] args) throws IOException{\n\t\tint termIndex = 1;\n\t\t\n\t\t// startOffset holds the start offset for e... | [
"0.5995485",
"0.5839277",
"0.57960045",
"0.55711436",
"0.5396472",
"0.5236064",
"0.52118707",
"0.51939565",
"0.5157785",
"0.5112572",
"0.51100713",
"0.5089438",
"0.5079131",
"0.50780505",
"0.50760406",
"0.5066933",
"0.5057492",
"0.50543725",
"0.50523096",
"0.5043695",
"0.5038... | 0.0 | -1 |
[NEW] Saves the tokentermIDs map and list with document names | public void saveAll(){
// Store postings
for (Map.Entry<String, PostingsList> entry : this.index.entrySet()) {
saveJSON("postings/t"+hash(entry.getKey())+".json", entry.getValue());
System.err.println("postings/t"+hash(entry.getKey())+".json");
count++;
if... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"private void saveToken() throws IOException {\n\t\t\n\t\tFileWriter termIdx = new FileWriter(StoragePath+Path.termIdxDir);\n\t\t\n\t\tfor(Entry<String, Integer> term: termDic.entrySet()){\n\t\t\ttermIdx.append(term.getKey() + \"\\n\" + term.getValue() + \"\\n\");\n\t\t}\n\t\t\n\t\ttermIdx.close();\n\t\t\n\t}",
"... | [
"0.61611456",
"0.588707",
"0.5825966",
"0.5631039",
"0.56064516",
"0.5588778",
"0.5588274",
"0.5588257",
"0.5482481",
"0.54597014",
"0.53377825",
"0.53221774",
"0.5288427",
"0.5280946",
"0.5271845",
"0.526328",
"0.52533746",
"0.5247164",
"0.5237755",
"0.52139837",
"0.5147063"... | 0.55061305 | 8 |
[NEW] Saves object "o" as a JSON file called fileName | public void saveJSON(String fileName, Object o){
// System.err.println("accessing disk");
Gson gson = new Gson();
try(FileWriter writer = new FileWriter(fileName)){
gson.toJson(o, writer);
//System.err.println("\n Token stored");
}catch (IOException e) {
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"public static void writeJsonObjectFile(JsonEntity objectToWrite, String filePath) \n\t{\n\t\tGson gsonParser = new Gson();\n\t\t\n\t\ttry \n\t\t{\n\t\t\tFiles.write(gsonParser.toJson(objectToWrite).getBytes(), new File(filePath));\n\t\t}\n\t\tcatch (IOException e) \n\t\t{\n\t\t\tSystem.err.println(\"Can't write to... | [
"0.7685922",
"0.7182024",
"0.7159729",
"0.7137173",
"0.7057812",
"0.70540637",
"0.7053874",
"0.7003681",
"0.6954736",
"0.6898823",
"0.6881606",
"0.6876142",
"0.6826735",
"0.6755188",
"0.67119867",
"0.6710243",
"0.66534215",
"0.66483724",
"0.6613342",
"0.6548435",
"0.65134025"... | 0.86886233 | 0 |
No need for cleanup in a HashedIndex. | public void cleanup() {
this.index = new TreeMap<String, PostingsList>();
this.count = 0;
} | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"@AfterClass\n\tpublic static void cleanIndex() {\n\t\tEntityTest et = new EntityTest(id, \"EntityTest\");\n\t\tRedisQuery.remove(et, id);\n\t}",
"void indexReset();",
"public void clear() {\n index.clear();\n }",
"private Reindex() {}",
"private Reindex() {}",
"void clearAllIndexes();",
"publ... | [
"0.6721599",
"0.6681743",
"0.66589624",
"0.65445966",
"0.65445966",
"0.6508383",
"0.63637435",
"0.6360245",
"0.63154876",
"0.62771064",
"0.62437534",
"0.6216059",
"0.6196626",
"0.61939406",
"0.61733735",
"0.61713153",
"0.6138556",
"0.61282516",
"0.61186033",
"0.6097255",
"0.6... | 0.6162504 | 16 |
SEARCH MANAGEMENT (USER) [MODIFIED] Returns the postings for a specific term, or null if the term is not in the index. | public PostingsList getPostings( String token ) {
PostingsList post = new PostingsList();
if(this.index.containsKey(token))
post = (this.index.get(token)).clone();
/*System.err.println("start search...");
// Read JSON file associated to token and return it as a postingslist
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"@Override\r\n\tpublic List<Post> searchInfResult(String word) {\n\t\tpostDao=new PostDaoImpl(TransactionManager.connection);\r\n\t\treturn postDao.selectPosts(word);\r\n\t}",
"private void termQuerySearch(String[] terms) {\n for (String term : terms) {\n LinkedList<TermPositions> postingLists =... | [
"0.5979783",
"0.59439623",
"0.5828963",
"0.5720514",
"0.5714142",
"0.56416255",
"0.563343",
"0.5438755",
"0.5398442",
"0.53896147",
"0.5354768",
"0.5341725",
"0.531625",
"0.5312132",
"0.53009015",
"0.5274076",
"0.5270938",
"0.52231854",
"0.5207723",
"0.5195788",
"0.51900214",... | 0.5259476 | 17 |
QUERIES MANAGEMENT Searches the index for postings matching the query. | public PostingsList search( Query query, int queryType, int rankingType,
int structureType ) {
double idf_threshold = new Double(0);
double index_elimination = new Double(0.008);
// System.err.println(pageRank[docNumber.get("121")]);
if (query.size()>0){
switch (quer... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"private void queryPosts() {\n ParseQuery<OutfitPost> query = ParseQuery.getQuery(OutfitPost.class);\n // only include data referred by user key\n query.include(OutfitPost.KEY_USER);\n query.whereEqualTo(OutfitPost.KEY_USER, ParseUser.getCurrentUser());\n // limit query to latest ... | [
"0.5320133",
"0.52384716",
"0.51909447",
"0.51793134",
"0.51689667",
"0.5166202",
"0.51531994",
"0.511496",
"0.51019454",
"0.50839907",
"0.5083817",
"0.5078615",
"0.5059571",
"0.5005355",
"0.5002798",
"0.49850202",
"0.49844736",
"0.49838942",
"0.49333358",
"0.4925261",
"0.489... | 0.4517407 | 70 |
query: Query inserted by the user w: Weight the tfidf score, usually very small to account for scale difference with pagerank idf_threshold: Threshold to perform index elimination / 1) Obtain union of results containing the considered query terms | public PostingsList ranked_query(Query query, double w, double idf_threshold){
long startTime = System.nanoTime();
PostingsList result = new PostingsList();
// Obtain union of terms above idf threshold if indexElimination is true
// (Set idf_threshold to zero to disable this feature)
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"public Set<String> queryTermsConsidered(Query query, double idf_threshold){\n double idf, nDocs = this.docIDs.size();\n String term;\n\n Set<String> termsToConsider = new HashSet<String>();\n\n Iterator<String> it = query.terms.iterator();\n while(it.hasNext()){\n term... | [
"0.713265",
"0.67490345",
"0.6708787",
"0.6570831",
"0.65290445",
"0.65091664",
"0.6301124",
"0.62564147",
"0.62462723",
"0.62303966",
"0.6121615",
"0.6092577",
"0.60881495",
"0.6067615",
"0.6061933",
"0.60572237",
"0.6025526",
"0.59403056",
"0.5899081",
"0.58948946",
"0.5887... | 0.7497625 | 0 |
Which terms should be considered? Based on Index elimination theory, idfthresholding! | public Set<String> queryTermsConsidered(Query query, double idf_threshold){
double idf, nDocs = this.docIDs.size();
String term;
Set<String> termsToConsider = new HashSet<String>();
Iterator<String> it = query.terms.iterator();
while(it.hasNext()){
term = it.next();... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"public abstract int numberOfTerms();",
"int DF(String term) {\n for (int i = 0; i < count1; i++) {\n if (economydocument[i].contains(term)) {\n df++;\n }\n }\n for (int i = 0; i < count2; i++) {\n if (educationdocument[i].contains(term)) {\n ... | [
"0.60107577",
"0.5797017",
"0.5660234",
"0.5633843",
"0.5564556",
"0.5551654",
"0.554559",
"0.5543597",
"0.5539202",
"0.55127895",
"0.54864407",
"0.54860085",
"0.54856205",
"0.54337925",
"0.5350816",
"0.5343665",
"0.5324684",
"0.53126794",
"0.5291859",
"0.5283408",
"0.5283391... | 0.6349889 | 0 |
[NEW] Finds documents containing the query as a phrase TODO: Skip pointer | public PostingsList phrase_query(Query query){
LinkedList<PostingsList> listQueriedPostings = new LinkedList<PostingsList>();
// List with postings corresponding to the queries
for (int i = 0; i<query.size(); i++){
// If any query has zero matches, return 0 results
//if(... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"@Test\n public void testPhrase() {\n assertQ(req(\"q\",\"text:now-cow\", \"indent\",\"true\")\n ,\"//*[@numFound='1']\"\n );\n // should generate a query of (now OR cow) and match both docs\n assertQ(req(\"q\",\"text_np:now-cow\", \"indent\",\"true\")\n ,\"//*[@numFound='2']\"\n );\n ... | [
"0.7247035",
"0.6326672",
"0.61507344",
"0.614432",
"0.6127424",
"0.61083686",
"0.60629725",
"0.60173154",
"0.5970413",
"0.59642434",
"0.595486",
"0.59493905",
"0.5948072",
"0.5947946",
"0.5944434",
"0.5918083",
"0.59072393",
"0.5887826",
"0.58828676",
"0.58804107",
"0.587460... | 0.60083085 | 8 |
[NEW] Finds documents containing a twowords phrase | public PostingsList phrase_query(PostingsList l1, PostingsList l2){
PostingsList phrase = new PostingsList();
// Counters to iterate docIDs
int count1 = 0;
int count2 = 0;
// Counters to iterate positional indices
int subcount1 = 0;
int subcount2 = 0;
/... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"@Test\n public void testPhrase() {\n assertQ(req(\"q\",\"text:now-cow\", \"indent\",\"true\")\n ,\"//*[@numFound='1']\"\n );\n // should generate a query of (now OR cow) and match both docs\n assertQ(req(\"q\",\"text_np:now-cow\", \"indent\",\"true\")\n ,\"//*[@numFound='2']\"\n );\n ... | [
"0.68965036",
"0.60956764",
"0.59332526",
"0.5928022",
"0.58062935",
"0.57813257",
"0.57707757",
"0.5745215",
"0.5720394",
"0.5696968",
"0.5672093",
"0.5598769",
"0.55674994",
"0.5545627",
"0.551981",
"0.5488837",
"0.5467346",
"0.5463441",
"0.5459747",
"0.54115915",
"0.540834... | 0.56311864 | 11 |
[NEW] Intersects a set of queries TODO: Skip pointer | public PostingsList intersect(Query query){
LinkedList<PostingsList> listQueriedPostings = new LinkedList<PostingsList>();
// List with postings corresponding to the queries
for (int i = 0; i<query.size(); i++){
// If any query has zero matches, return 0 results
//if(!(n... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"@Test\r\n\t\tpublic void testIntersection() {\n\t\t\ttestingSet = new IntegerSet(list1);\r\n\t\t\ttestingSet2= new IntegerSet(list2);\r\n\t\t\t// create 3rdset = to the intersection list \r\n\t\t\ttestingSet3= new IntegerSet(intersection);\r\n\t\t\t// create 4th set =to the intersection of set1 and set2\r\n\t\t\tt... | [
"0.601857",
"0.5893896",
"0.575646",
"0.56862754",
"0.5679482",
"0.5663984",
"0.56257683",
"0.5607326",
"0.5603596",
"0.5601509",
"0.5576574",
"0.55470616",
"0.55435514",
"0.5515671",
"0.55070364",
"0.5502553",
"0.5489338",
"0.54770523",
"0.5475129",
"0.5470427",
"0.5450035",... | 0.6197183 | 0 |
[NEW] Intersects two queries (represented by the postingslist) | public PostingsList intersect(PostingsList l1, PostingsList l2){
PostingsList intersection = new PostingsList();
// Counters to iterate docIDs
int count1 = 0;
int count2 = 0;
// First posting
PostingsEntry p1 = l1.get(0);
PostingsEntry p2 = l2.get(0);
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"public PostingsList intersect(Query query){\n\n LinkedList<PostingsList> listQueriedPostings = new LinkedList<PostingsList>();\n // List with postings corresponding to the queries\n for (int i = 0; i<query.size(); i++){\n // If any query has zero matches, return 0 results\n ... | [
"0.69769245",
"0.6333911",
"0.5428158",
"0.5357878",
"0.530351",
"0.5271801",
"0.51897854",
"0.51882815",
"0.51229084",
"0.50980556",
"0.5068206",
"0.50642776",
"0.506333",
"0.5041754",
"0.502724",
"0.5019483",
"0.5001322",
"0.49797273",
"0.49742696",
"0.4948692",
"0.49297482... | 0.6708024 | 1 |
[NEW] Sorts a set of postings list according to the document frequency | public LinkedList<PostingsList> sortByIncreasingFrequency(LinkedList<PostingsList> l){
Collections.sort(l, new Comparator<PostingsList>(){
@Override
public int compare(PostingsList p1, PostingsList p2){
if(p1.size() < p2.size()){
return -1;
}
if... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"public void sort() {\n documents.sort();\n }",
"public void sortDocumentsByDocnos() {\n order = new int[mDocSet.length];\n mDocSet_tmp = new double[mDocSet.length];\n accumulated_scores_tmp = new float[mDocSet.length];\n\n for (int i = 0; i < order.length; i++) {\n order[i] = i;\n mDocS... | [
"0.67374855",
"0.63989174",
"0.6172652",
"0.5989494",
"0.59094334",
"0.5851778",
"0.57968163",
"0.57893056",
"0.5646224",
"0.5625188",
"0.5610343",
"0.56095076",
"0.559386",
"0.55909723",
"0.5517896",
"0.5515005",
"0.5512062",
"0.5501602",
"0.54893845",
"0.54655427",
"0.54344... | 0.6929145 | 0 |
OTHERS [MODIFIED] Returns all the words in the index. | public Set<String> keySet() {
return this.index.keySet();
} | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"public Set<String> getWords() {\n\t\treturn Collections.unmodifiableSet(this.invertedIndex.keySet());\n\t}",
"public Iterator words() {\n return index.keySet().iterator();\n }",
"public void showAllWords() {//out\n System.out.println(\"No\\t|English\\t|Vietnamese\");\n ArrayList<Word> f... | [
"0.6683834",
"0.63288605",
"0.60075307",
"0.5970147",
"0.5862826",
"0.5859984",
"0.58519155",
"0.5818616",
"0.57877696",
"0.57772887",
"0.57062596",
"0.5672519",
"0.5668082",
"0.56145406",
"0.5612684",
"0.5563824",
"0.55119944",
"0.550613",
"0.54892987",
"0.5488961",
"0.54867... | 0.0 | -1 |
[NEW] Hashes the string to unique int representation | public static String hash(String token){
return Integer.toString( token.hashCode() );
} | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"int toHashKey(String s)\n\t{\n\t\tint A = 1952786893;\n\t\tint B = 367257;\n\t\tint v = B;\n\t\tfor (int j = 0; j < s.length(); j++)\n\t\t{\n\t\t\tchar c = s.charAt(j);\n\t\t\tv = A * (v + (int) c + j) + B;\n\t\t}\n\n\t\tif (v < 0) v = -v;\n\t\treturn v;\n\t}",
"private int hash(String string) {\n\t\tint hash = ... | [
"0.7137949",
"0.6897674",
"0.6708983",
"0.6634139",
"0.6602896",
"0.6580906",
"0.6529667",
"0.6447881",
"0.64134866",
"0.64026445",
"0.6386157",
"0.6376087",
"0.6344094",
"0.6320488",
"0.6314912",
"0.6302626",
"0.62619746",
"0.62537754",
"0.62481886",
"0.62098116",
"0.6183987... | 0.5671831 | 78 |
[NEW] Strings the map containing all postingslist and tokens | public String toString(){
String s = " ";
for (Map.Entry<String, PostingsList> entry : this.index.entrySet()) {
s += entry.getKey()+" - " + entry.getValue().toString() + "\n";
}
return s;//this.indexInMemory.toString();
} | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"Map<String, String> getTokens();",
"@Override\r\n public String toString() {\r\n String s = new String();\r\n for (String t : tokenList)\r\n s = s + \"~\" + t;\r\n return s;\r\n }",
"@Override\n public String toString() {\n StringJoiner sj = new StringJoiner(\", \", \"{\", \"}\\n\");\... | [
"0.6758433",
"0.58897084",
"0.5630534",
"0.5508794",
"0.5503969",
"0.54728544",
"0.5447173",
"0.53018135",
"0.5263845",
"0.5251088",
"0.5191312",
"0.51761514",
"0.51590157",
"0.51570046",
"0.5153402",
"0.5152076",
"0.51318806",
"0.5107668",
"0.51008123",
"0.51008123",
"0.5100... | 0.5571595 | 3 |
This method is called from within the constructor to initialize the form. WARNING: Do NOT modify this code. The content of this method is always regenerated by the Form Editor. | @SuppressWarnings("unchecked")
// <editor-fold defaultstate="collapsed" desc="Generated Code">//GEN-BEGIN:initComponents
private void initComponents() {
jLabel1 = new javax.swing.JLabel();
jLabel2 = new javax.swing.JLabel();
jLabel3 = new javax.swing.JLabel();
txtNombre = new ja... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"public Form() {\n initComponents();\n }",
"public MainForm() {\n initComponents();\n }",
"public MainForm() {\n initComponents();\n }",
"public MainForm() {\n initComponents();\n }",
"public frmRectangulo() {\n initComponents();\n }",
"public form() {\n ... | [
"0.73206544",
"0.7291311",
"0.7291311",
"0.7291311",
"0.7286492",
"0.7249181",
"0.7213362",
"0.72085494",
"0.71965617",
"0.7190475",
"0.7184897",
"0.7159234",
"0.71483016",
"0.7094075",
"0.7081491",
"0.70579433",
"0.6987627",
"0.69776064",
"0.69552463",
"0.69549114",
"0.69453... | 0.0 | -1 |
TODO Autogenerated method stub | public void addUser(User user) {
userMapper.insert(user);
} | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"@Override\r\n\tpublic void comer() \r\n\t{\n\t\t\r\n\t}",
"@Override\n\tpublic void comer() {\n\t\t\n\t}",
"@Override\n public void perish() {\n \n }",
"@Override\r\n\t\t\tpublic void annadir() {\n\r\n\t\t\t}",
"@Override\n\tpublic void anular() {\n\n\t}",
"@Override\n\tprotected void getExr... | [
"0.6671074",
"0.6567672",
"0.6523024",
"0.6481211",
"0.6477082",
"0.64591026",
"0.64127725",
"0.63762105",
"0.6276059",
"0.6254286",
"0.623686",
"0.6223679",
"0.6201336",
"0.61950207",
"0.61950207",
"0.61922914",
"0.6186996",
"0.6173591",
"0.61327106",
"0.61285484",
"0.608016... | 0.0 | -1 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.