File size: 6,350 Bytes
71e354e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 | #ifndef CPPJIEBA_TEXTRANK_EXTRACTOR_H
#define CPPJIEBA_TEXTRANK_EXTRACTOR_H
#include <cmath>
#include "Jieba.hpp"
namespace cppjieba {
using namespace limonp;
using namespace std;
class TextRankExtractor {
public:
typedef struct _Word {string word;vector<size_t> offsets;double weight;} Word; // struct Word
private:
typedef std::map<string,Word> WordMap;
class WordGraph{
private:
typedef double Score;
typedef string Node;
typedef std::set<Node> NodeSet;
typedef std::map<Node,double> Edges;
typedef std::map<Node,Edges> Graph;
//typedef std::unordered_map<Node,double> Edges;
//typedef std::unordered_map<Node,Edges> Graph;
double d;
Graph graph;
NodeSet nodeSet;
public:
WordGraph(): d(0.85) {};
WordGraph(double in_d): d(in_d) {};
void addEdge(Node start,Node end,double weight){
Edges temp;
Edges::iterator gotEdges;
nodeSet.insert(start);
nodeSet.insert(end);
graph[start][end]+=weight;
graph[end][start]+=weight;
}
void rank(WordMap &ws,size_t rankTime=10){
WordMap outSum;
Score wsdef, min_rank, max_rank;
if( graph.size() == 0)
return;
wsdef = 1.0 / graph.size();
for(Graph::iterator edges=graph.begin();edges!=graph.end();++edges){
// edges->first start节点；edge->first end节点；edge->second 权重
ws[edges->first].word=edges->first;
ws[edges->first].weight=wsdef;
outSum[edges->first].weight=0;
for(Edges::iterator edge=edges->second.begin();edge!=edges->second.end();++edge){
outSum[edges->first].weight+=edge->second;
}
}
//sort(nodeSet.begin(),nodeSet.end()); 是否需要排序?
for( size_t i=0; i<rankTime; i++ ){
for(NodeSet::iterator node = nodeSet.begin(); node != nodeSet.end(); node++ ){
double s = 0;
for( Edges::iterator edge= graph[*node].begin(); edge != graph[*node].end(); edge++ )
// edge->first end节点；edge->second 权重
s += edge->second / outSum[edge->first].weight * ws[edge->first].weight;
ws[*node].weight = (1 - d) + d * s;
}
}
min_rank=max_rank=ws.begin()->second.weight;
for(WordMap::iterator i = ws.begin(); i != ws.end(); i ++){
if( i->second.weight < min_rank ){
min_rank = i->second.weight;
}
if( i->second.weight > max_rank ){
max_rank = i->second.weight;
}
}
for(WordMap::iterator i = ws.begin(); i != ws.end(); i ++){
ws[i->first].weight = (i->second.weight - min_rank / 10.0) / (max_rank - min_rank / 10.0);
}
}
};
public:
TextRankExtractor(const string& dictPath,
const string& hmmFilePath,
const string& stopWordPath,
const string& userDict = "")
: segment_(dictPath, hmmFilePath, userDict) {
LoadStopWordDict(stopWordPath);
}
TextRankExtractor(const DictTrie* dictTrie,
const HMMModel* model,
const string& stopWordPath)
: segment_(dictTrie, model) {
LoadStopWordDict(stopWordPath);
}
TextRankExtractor(const Jieba& jieba, const string& stopWordPath) : segment_(jieba.GetDictTrie(), jieba.GetHMMModel()) {
LoadStopWordDict(stopWordPath);
}
~TextRankExtractor() {
}
void Extract(const string& sentence, vector<string>& keywords, size_t topN) const {
vector<Word> topWords;
Extract(sentence, topWords, topN);
for (size_t i = 0; i < topWords.size(); i++) {
keywords.push_back(topWords[i].word);
}
}
void Extract(const string& sentence, vector<pair<string, double> >& keywords, size_t topN) const {
vector<Word> topWords;
Extract(sentence, topWords, topN);
for (size_t i = 0; i < topWords.size(); i++) {
keywords.push_back(pair<string, double>(topWords[i].word, topWords[i].weight));
}
}
void Extract(const string& sentence, vector<Word>& keywords, size_t topN, size_t span=5,size_t rankTime=10) const {
vector<string> words;
segment_.Cut(sentence, words);
TextRankExtractor::WordGraph graph;
WordMap wordmap;
size_t offset = 0;
for(size_t i=0; i < words.size(); i++){
size_t t = offset;
offset += words[i].size();
if (IsSingleWord(words[i]) || stopWords_.find(words[i]) != stopWords_.end()) {
continue;
}
for(size_t j=i+1,skip=0;j<i+span+skip && j<words.size();j++){
if (IsSingleWord(words[j]) || stopWords_.find(words[j]) != stopWords_.end()) {
skip++;
continue;
}
graph.addEdge(words[i],words[j],1);
}
wordmap[words[i]].offsets.push_back(t);
}
if (offset != sentence.size()) {
XLOG(ERROR) << "words illegal";
return;
}
graph.rank(wordmap,rankTime);
keywords.clear();
keywords.reserve(wordmap.size());
for (WordMap::iterator itr = wordmap.begin(); itr != wordmap.end(); ++itr) {
keywords.push_back(itr->second);
}
topN = min(topN, keywords.size());
partial_sort(keywords.begin(), keywords.begin() + topN, keywords.end(), Compare);
keywords.resize(topN);
}
private:
void LoadStopWordDict(const string& filePath) {
ifstream ifs(filePath.c_str());
XCHECK(ifs.is_open()) << "open " << filePath << " failed";
string line ;
while (getline(ifs, line)) {
stopWords_.insert(line);
}
assert(stopWords_.size());
}
static bool Compare(const Word &x,const Word &y){
return x.weight > y.weight;
}
MixSegment segment_;
unordered_set<string> stopWords_;
}; // class TextRankExtractor
inline ostream& operator << (ostream& os, const TextRankExtractor::Word& word) {
return os << "{\"word\": \"" << word.word << "\", \"offset\": " << word.offsets << ", \"weight\": " << word.weight << "}";
}
} // namespace cppjieba
#endif
|