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<s>in Table 1. Also note that the algorithm also calculating the frequencies of reduplicated words separately. To identify the partial reduplicated word is relatively complicated compared to proper reduplication and hence first we studied the features of partial reduplication to setup our algorithm. In earlier work som... |
<s>for Indian Languages (TDIL) corpus [12] has been used. The TDIL corpus is devel-oped by the Department of Electronics, Govt. of India for Bengali language (http://tdil.mit.gov.in/). This corpus contains texts from Literature (20%), Fine Arts (5%), Social Sciences (15%), Natural Sciences (15%), Commerce (10%), Mass m... |
<s>the corpus etc. Note that in our experiment we have defined Tf = 5 by applying the random sample tech-nique in the corpus. Using this technique many irrelevant entries has been eliminated. For example, িপ. িভ./p.v. (abbreviation of a name), বdৃ েবৗd /bridha boudha (irrelevant word) etc. structurally look like redupl... |
<s>0.63 0.85 0.72 After Tuning TDIL 0.93 0.84 0.88 9 Error Analysis In order to find the weakness of our algorithms the error analysis has been carried out. This analysis not only measures the error in terms of number of wrongly identified but also identified the major source of errors in different phases of the system... |
<s>of recall and it reflects the recall value shown in Table 5. The other type of error is the false positive i.e. the algorithm wrongly identify the reduplicated words. For exam-ples, consider the system generated output with their frequencies, দমদম/dumdum (Dum-dum, name of a place) [frequency 50], টাটা/tata (Tata, na... |
<s>in Kannada. In: All India Conference of Dravidian Linguistics(eds.) (1972) 5. Nongmeikapam, K.: Identification of Reduplication MWEs in Manipuri, a rule-based ap-proach. In: 23rd International Conference on the Computer Processing of Oriental Lan-guages, California, USA, pp. 49–54 (2010) 6. Chattopadhyay, S.K.: Bhas... |
<s>12046_2019_1149_44_7 1..13Word Sense Disambiguation in Bengali language using unsupervisedmethodology with modificationsALOK RANJAN PAL1,* and DIGANTA SAHA21Department of Computer Science and Engineering, College of Engineering and Management, Kolaghat, India2Department of Computer Science and Engineering, Jadavpur ... |
<s>similaritymeasuring technique is used to find the similarity of a newtest data with these sense-tagged inventories. The minimumdistance between a test data and a sense-tagged inventoryrepresents the sense of that test data.In this work, WSD is implemented in the following way:first, sentence clustering is performed ... |
<s>probably because of the moredifficult text. Senseval-3 also brought the complete domi-nation of supervised approaches over the pure knowledge-based approaches.2.2 WSD in Asian languages, as well as in IndianlanguagesVarious works in WSD are implemented in English andother European languages, but very few works are e... |
<s>sys-tem based on the Leacock–Chodorow semantic relatednessmeasure [20]. The algorithm is tested on the data set con-sisting of 20 Hindi polysemous nouns, obtaining the aver-age precision and recall of 60.65% and 57.11%,respectively.Yadav and Vishwarkarma [21] have proposed a WSDsystem for Hindi nouns based on mining... |
<s>on WSD in Bengalilanguage are in progress at different research organizationsin India and Bangladesh, only a few of them are availablein the web.Das and Sarkar [30] have presented one WSD system forBengali to get correct lexical choice for Bengali–Hindimachine translation. The authors used an unsupervisedgraph-based... |
<s>on the nature of the experiment. According toFigure 1. Flowchart of the baseline procedure.1The TDIL Bengali corpus is obtained from the Linguistic ResearchUnit Department, ISI, Kolkata.168 Page 4 of 13 Sådhanå (2019) 44:168theoretical linguistics, all the Bengali words carry relevantsenses in specific cases. Howeve... |
<s>corpus.Although theoretically almost every Bengali word carriesmultiple senses in different contexts [34, 35], in computa-tional field only those words are considered for experimentthat are present in the corpus with some needful numbers ofoccurrences.3.7 Selection of senses for the ambiguous wordsfor evaluationIn r... |
<s>sets, this length variesfrom 2000 to 3500 approximately) was out of the compu-tational power of the available system (system specificationis mentioned in section 3.5). Hence, reduction of length ofthe feature vector, while preserving the principalcomponents, became an obvious issue. To deal with thisproblem, PCA is ... |
<s>word is present in theWordNet:(a) meaning of the word,(b) example of use of the word,(c) synonyms (words with similar meanings),(d) part-of-speech,(e) ontology (hierarchical semantic representation) and(f) semantic and lexical relations.At present the Bengali WordNet contains 36534 wordscovering all major lexical ca... |
<s>a single sentencecarrying different senses: A few sentences are encounteredwhere multiple-sense-carrying keywords are present in asingle sentence to denote a single sense as a whole. Forexample:(pāndulipir dhoosar pātāy tnār ātmajeebanee ājo etotāijeebanta ye ekbār parte shuru karle cokher pātā prenā.)’’ ... |
<s>of thewords are not established (properly/not at all) in this onlinedictionary, such as hypernymy, hyponymy, holonymy,meronymy, antonymy, etc.5.7 Usefulness of function words in BengaliHandling the function words and the content words inBengali is one of the toughest jobs. To bring the size of thedata sets to some m... |
<s>In: Proceedings of the 17th Annual Inter-national ACM SIGIR Conference on Research andDevelopment in Information Retrieval, SIGIR’94, Dublin,Ireland, pp. 142–151[6] Banerjee S and Pedersen T 2002 An adapted Lesk algorithmfor word sense disambiguation using WordNet. In: Pro-ceedings of the Third International Confere... |
<s>in Hindi lan-guage using hyperspace analogue to language and fuzzy-C means clustering. In: Proceedings of the InternationalConference on Natural Language Processing (ICON)[25] Roy A, Sarkar S and Purkayastha B S 2014 Knowledge basedapproaches to Nepali word sense disambiguation. Interna-tional Journal on Natural Lan... |
<s>Proceedings Template - WORDLabeling of Query Words using Conditional Random FieldSatanu Ghosh West Bengal University of Technology +91-7278137003 satanu.ghosh.94@gmail.comSouvick Ghosh Jadavpur University +91-9007728924 souvick.gh@gmail.com Dipankar Das Jadavpur University +91-9432226464 dipankar.dipnil2005@gmail.co... |
<s>word or a transliterated L-language word. The words of a single query usually come from 1 or 2 languages and very rarely from 3 languages. In case of mixed language queries, one of the languages is either English or Hindi. Thus, queries are formed by mixing Tamil and English words, or Bengali and Hindi words, but no... |
<s>developed nine wordlists for nine different languages using training data. The wordlists contained few overlapping words. 4. SYSTEM DESCRIPTION Our primary task was word-level language classification. However, identification of Named Entities was also necessary. 4.1 Word-level Language Identification Features The fo... |
<s>If yes, then 1 else 0 CHR3: If the word starts with http? If yes, then 1 else 0 CHR4: If emoticon? If yes, then 1 else 0 4.1.4 Dictionary Feature A total of 9 different languages were there to be identified. We used 9 different lexical resources, one for each language. We used 9 different Boolean features to represe... |
<s>F-Measure 0.749833 Table 3: Confusion matrix between languages en X hi bn ml mr kn te gu ta 6 http://nlp.stanford.edu/software/CRF-NER.shtml 7 http://crfpp.googlecode.com/svn/trunk/doc/index.html 72 79 37 47 1 2 1 16 1 6 X 32 63 2 1 0 0 0 1 0 0 1 84 42 38 0 6 3 6 9 0 bn 84 71 50 12 0 7 2 4 9 8 ml 19 38 2 13 60 1 12 ... |
<s>window. In COLING, pages 383-389, 2000. [6] B. King and S. Abney. Labeling the languages of words in mixed-language documents using weakly supervised methods. In NAACL-HLT, pages 1110-1119, 2013. [7] H. Li, Z. Min, and J. Su. A joint source-channel model for machine transliteration. In ACL, page 159, 2004. [8] V. So... |
<s>See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/339655969A Bengali Text Generation Approach in Context of Abstractive TextSummarization Using RNNChapter · March 2020DOI: 10.1007/978-981-15-2043-3_55CITATIONSREADS1915 authors, including:Some of the authors... |
<s>in now a days, is to develop machines to understand the context of any information given and be able to produce the summary based on its understanding. This type of summarization are in a stage of making comparison with human generated summaries, and it’s called abstractive summarization. Now a days, information in ... |
<s>sentence generation, abstractive methods will be more accurate and machines will be able to predict and be able to complete writing the whole sentence considering the predicted contextual tokens. Text generation is significant for the arrangement to grouping word order. This paper we attempted to clarify a technique... |
<s>use n-gram sequence as given word and the predicted word as next word. Example given in table 2. Finally, we can do acquire the input X and the next word Y which is used for training model N-GRAM TEXT TOKEN SEQUENCE হাইশেক পাকক [103,45] হাইশেক পাকক বির্ কাণ [103,45,10] হাইশেক পাকক বির্ কাণ কাজ [103,45,10,24] হাইশেক ... |
<s>the probability and keep only the correct next sequence. Figure4: View of Proposed Model. i. Long Short Term Memory: Long Short Term Memory is a part of the Recurrent Neural Network. It's used to disappearance of gradient and abolishes gradient. Every LSTM cell has three gates such as Input Gate, Forget Gate, Output... |
<s>next words. In our future work, we will make an automatic text generator which provides a random length Bengali text without using any token or sequence. Acknowledgment We would like to give thanks to our DIU-NLP and Machine Learning Research Lab for providing all research facility and guidance. We would also give s... |
<s>International Conference on Bangla Speech and Language Processing(ICBSLP), 21-22 September, 2018Pipilika N-gram Viewer: An Efficient Large ScaleN-gram Model for BengaliAdnan Ahmad∗, Mahbubur Rub Talha∗, Md. Ruhul Amin∗, Farida Chowdhury∗∗Search Engine Pipilika∗Department of Computer Science & Engineering∗Shahjalal U... |
<s>a standard evaluation method for language models.We also use it to perform multiple NLP tasks, namely context-aware spell checker and Trending topic detection. We include theperformance results of these tasks and show the efficiency of themodel. This model can be used in many farther NLP tasks byresearchers, so we d... |
<s>spectrum is often charac-terized by very high values corresponding to the lowest frequencyclasses, and a very long tail of frequency classes with only onemember. Thus, a full spectrum plot on a non-logarithmic scale willalways have the rather uninformative L-shaped profile. So, we plotit on a log-log scale. The same... |
<s>test set with a corpus of 36556 sentencescontaining 399271 words. For Unigram probability calculation, wemultiply the factor|vocabulary|with each probability as described here [6]. To deal with the probabil-ity of unknown words p(unk), we used Laplace smoothing [7]. Theresults of perplexities from different year fro... |
<s>places and organizations which are notpresent in the traditional dictionaries.There are two main steps for a successful spell checker. The firststep is spell checking and the second step is spell suggestion. Thespell checking process is straightforward; we consider a sentence andcheck each word of the sentence wheth... |
<s>calledChi-square test [12]. Chi-square test is a statistical hypothesis testassessing the goodness of fit between a set of observed values andthose expected theoretically. The formula for the chi-square statisticused in the chi square test is:χ̃2 =k=1(Ok − Ek)Where O is observed value and E is expected value. Now co... |
<s>Chelba and J. Schalkwyk, 2013. Empirical Exploration of LanguageModeling for the google.com Query Stream as Applied to Mobile VoiceSearch, pages 197229. Springer, New York.[3] D. Guthrie and M. Hepple. 2010. Storing the web in memory: Spaceefficient language models with constant time retrieval. In Proceedingsof EMNL... |
<s>Microsoft Word - 11 Mumin CSESee discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/332318483SUMono: A Representative Modern Bengali CorpusArticle · January 2014CITATIONSREADS2995 authors, including:Some of the authors of this publication are also working on the... |
<s>model has been followed in the construction of the American National Corpus, the Korean National Corpus, the Polish National Corpus, and the Russian Reference Corpus [2]. In this paper, we introduce a large-scale representative Bengali corpus, the SUMono corpus. The format and contents of the SUMono corpus follows t... |
<s>for Bengali language. Table 1 depicts a comparison in size between SUMono corpus and the other Bengali corpora whose corpus statistics are available. Table 1: Comparison in Size Between SUMono and other Bengali Corpora SUMono ‘Prothom-alo’ CIIL Corpus size (in words) 27,118,025 18,100,378 3,044,573 Vocabulary size (... |
<s>Since the individual sources of collected texts differ in many aspects, a lot of effort was required to integrate them into a common framework. The following steps have been applied as preprocessing on the documents. Cleaning: We start by cleaning up the original material that we collected from the different sources... |
<s>, 00.664 - 00.163 . 00.002 / 02.983 0 01.179 1 00.629 2 00.094 3 02.954 4 01.146 ◌5 00.465 6◌ 00.088 7 02.868 8 01.138 9 00.444 : 00.086 ; 02.356 < 01.110 = 00.401 > 00.079 ‘�‘ (reph) and ‘ ‘ (ro-phola). Surprising to our intuition, the next most frequently used letter is ‘◌� ’ (hoshonto). While writing Bengali text... |
<s>� ◊ 214613 ◊ % ◌� � ◊ 135278 / 4166883 ◌� � 1580520 � �◌ ◊ 529583 � �◌ ◊ 209045 % �◌ ◊ ; ◌� 126155 Word Level Analysis 82 Md. Abdullah Al Mumin, Abu Awal Md. Shoeb, Mohammad Reza Selim and M. Zafar Iqbal 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20Number of Let t ers1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18... |
<s>words (types) (b) The umber of total n-letter words (tokens) Figure 1: Distribution of Usage of n-Letter Words in SUMono Corpus SUMono: A Representative Modern Bengali Corpus 83 The above statistics may have different applications in different contexts. For example, post processing in Bengali OCR, Speech-to-Text, sp... |
<s>The law states that: r.f = c, where r is the rank of a word, f is the frequency of occurrence of the word, and c is a constant that depends on the text being analyzed. Word frequencies have been counted for all the domains separately, and for the whole dataset. In all, seven lists of word frequencies were created. E... |
<s>%�� 0.45 �� 0.50 �3 0.51 SUMono: A Representative Modern Bengali Corpus 85 5.3 Vocabulary Growth The statistical models of Baayen [17] link the degree of productivity of a morphological process to the rate of vocabulary growth, i.e., to how frequently new word types that are formed by the process are encountered whe... |
<s>various levels up to deep syntactic layer. We hope that the SUMono corpus will function as the basic source of reference for both national and international researchers who are willing to do their computational research on Bengali language processing. 86 Md. Abdullah Al Mumin, Abu Awal Md. Shoeb, Mohammad Reza Selim... |
<s>Automatic Keyword Extraction from Bengali Text Using Improved RAKE Approach2018 21st International Conference of Computer and Information Technology (ICCIT), 21-23 December, 2018 978-1-5386-9242-4/18/$31.00 ©2018 IEEE Automatic Keyword Extraction from Bengali Text using Improved RAKE Approach Mozammel Haque Dept. of... |
<s>the word scores of its constituent words to calculate the candidate keyword score. 5. Take the first one-third top scoring candidates from the list of candidates as the final list of keywords. A. Candidate keyword Scoring using RAKE A candidate keyword of RAKE may have multiple words and summation of each word score... |
<s>them consists of same words but not in the same order. For instance, “X Y Z”, “Y X Z” and “Z X Y” are the candidate keywords that found from the same text. They all are not equally important as keywords but RAKE generates the same score for all of the above candidate keywords [3]. Table I shows the top ten extracted... |
<s>8 2 1 16 বাংলার 15 4 3.75 4 1 15 সািহতয্ 14 3 4.67 3 1 14 মানষু 7 2 3.5 4 1 14 B. Potency of RAKEB RAKE produces high degree score for a multi-word keyword. The RAKEB normalizes this length issue and finds the more frequent and significant keywords using proposed (1). RAKEB solves both limitations of RAKE, as we hav... |
<s>কিরেব, কােজর বণর্নার মধয্ িদেয় শহীদlুাh সmেকর্ পুেরাপুির, মসুলমান হoয়ার কারেণ ঢাকা িব িবদয্ালেয়র িশkেকর চাকিরেত [Note: comma separates the keywords] িতিমরিবনাশী-সংgাহক ভাষা, আবদলু কিরম, পঁুিথর, সংsৃিত, চ gাম, বাংলা সািহতয্, মাতৃভাষা, জাতীয় ভাষা, gােমর, মাdাসা aসংখয্ কািহিন েকcা গীত গাথা পালার মলূয্ সািহেতয্র iিতহােস... |
<s>2 37 বলেছন 3.25 9 1 29.25 TABLE VI. EXTRACTED KEYWORDS FROM বাঙািল সংsৃিতর pকৃত সাধক Keyword (K) O N KS(K) সংsৃত 4.5 11 1 49.5 বাংলার 5.13 8 1 41 িহn ু 5.67 4 1 22.67 বাংলা সািহেতয্র 10.45 4 2 20.9 পূবর্ব 3.33 6 1 20 বাংলা ভাষা 8.7 4 2 17.4 aনরুােগর 7.5 2 1 15 kিমlা 5.5 2 1 11 ভাষার 2.33 4 1 9.33 V. LIMITATIONS AND ... |
<s>(sRGB IEC61966-2.1) /CalCMYKProfile (U.S. Web Coated \050SWOP\051 v2) /sRGBProfile (sRGB IEC61966-2.1) /CannotEmbedFontPolicy /Error /CompatibilityLevel 1.7 /CompressObjects /Off /CompressPages true /ConvertImagesToIndexed true /PassThroughJPEGImages true /CreateJobTicket false /DefaultRenderingIntent /Default /Dete... |
<s>/CordiaNew-BoldItalic /CordiaNew-Italic /CordiaUPC /CordiaUPC-Bold /CordiaUPC-BoldItalic /CordiaUPC-Italic /Courier /Courier-Bold /Courier-BoldOblique /CourierNewPS-BoldItalicMT /CourierNewPS-BoldMT /CourierNewPS-ItalicMT /CourierNewPSMT /Courier-Oblique /CourierStd /CourierStd-Bold /CourierStd-BoldOblique /CourierS... |
<s>/NimbusMonL-BoldObli /NimbusMonL-Regu /NimbusMonL-ReguObli /NimbusRomNo9L-Medi /NimbusRomNo9L-MediItal /NimbusRomNo9L-Regu /NimbusRomNo9L-ReguItal /NimbusSanL-Bold /NimbusSanL-BoldCond /NimbusSanL-BoldCondItal /NimbusSanL-BoldItal /NimbusSanL-Regu /NimbusSanL-ReguCond /NimbusSanL-ReguCondItal /NimbusSanL-ReguItal /N... |
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<s>Author GuidelineICERIE_ MIE_XYZ Proceedings of the International Conference on Engineering Research, Innovation and Education 2017 ICERIE 2017, 13 15 January, SUST, Sylhet, Bangladesh Bangla Word Clustering Based on Tri-gram, 4-gram and 5-gram Language Model Dipaloke Saha1,*, Md Saddam Hossain, MD. Saiful Islamand S... |
<s>work on Bangla word clustering exists in which an unsupervised machine learning technique is used to implement the bigram model by Sabir Ismail and M. Shahidur Rahman. In many other languages different types of techniques are used for word clustering. Finch and Chater (1992) implemented bigram model for the calculat... |
<s>are determined as follows, For tri-gram, P(Wi,Wj)=(Count(match(list(Wi+3,Wi+2,Wi+1),list(Wj+3,Wj+2,Wj+1)))/((Count(list(Wi+3,Wi+2,Wi+1)) +Count(list(Wj+3, Wj+2, Wj+1))) Similarly, calculation for the 4-gram model is: P(Wi,Wj)=(Count(match(list(Wi+4,Wi+3,Wi+2,Wi+1),list(Wj+4,Wj+3,Wj+2,Wj+1)))/((Count(list(Wi+4,Wi+3 ,... |
<s>efficiency among the three mentioned models for word clustering. On the basis of the observation, it can be said that better efficiency is in the higher orders than the preceding orders of the N-gram model. REFERENCES Top 10 most spoken languages in the world, http://listverse.com/2008/06/26/top-10-most-spoken-langu... |
<s>2019 22nd International Conference on Computer and InformationTechnology (ICCIT), 18-20 December, 2019Authorship Attribution in Bangla literature usingCharacter-level CNNAisha KhatunDepartment of ComputerScience and EngineeringShahjalal University ofScience and TechnologySylhet, BangladeshEmail: aysha.kamal7@gmail.c... |
<s>differentforms. Moreover, there are some words with the same meaningbut slightly different spelling. These inconsistencies are notrecognized by word-level models but character-level modelscan capture and relate words of this kind, making suchmodels more appropriate for Bangla language. Comparisonof character embeddi... |
<s>morphologicalmeaning of the entities. These meanings are leveraged bymachine learning techniques to find patterns in texts and thusperform various tasks such as classification.1) Word Embedding: Representing words in continuousvector spaces is considered as one of the breakthroughsof NLP. Word embeddings are learned... |
<s>CNN was usedin this paper to perform the task of author attribution. Anelaborate set of experiments were performed on 3 differentdatasets to conclude with an architecture that successfullyextracts the character level features of any sample text. Thesame architecture was used to prepare the pre-trained characterembed... |
<s>separate model was used [28] to learn theembeddings. Instead, already available classification task ona marginally large dataset learns character embeddings forits purposes. These embeddings can be used as initializationfor the author attribution task, which has a smaller datasetcompared to the former, giving it an ... |
<s>10 12 14samples/author 350 1100 931 849 562 469Char-CNN 83 96 92 86 75 69W2V(CBOW) 65.3 97 82.8 83.3 76.4 71.8fastText(CBOW) 65 73 58 35.7 37.31 40.3W2V(Skip) 79 94 91.1 85.4 82.2 78.6fastText(Skip) 86 98 95.2 86.35 80.9 81.2Accuracy comparison(in percents) of the proposed modelwith and without pre-trained character... |
<s>a form of transfer learning, given the alphabet remainsthe same.VII. CONCLUSIONSo far no work has been done to evaluate the usefulnessof character embeddings for classification task in Banglalanguage. We attempt to fill this gap and compare characterembeddings with word embeddings showing that character em-beddings ... |
<s>learning approach forauthorship attribution for bengali blogs,” 2016.[18] I. Santos, N. Nedjah, and L. de Macedo Mourelle, “Sentiment analysisusing convolutional neural network with fasttext embeddings,” 2017.[19] E. Rudkowsky, M. Haselmayer, M. Wastian, M. Jenny, Š. Emrich, andM. Sedlmair, “More than bags of words... |
<s>untitledSee discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/339676286Developing the Bangladeshi National Corpus-a Balanced and RepresentativeBangla CorpusConference Paper · December 2019DOI: 10.1109/STI47673.2019.9068005CITATIONSREADS4 authors, including:Some... |
<s>document, we’ll be discussing our approaches to build the corpus and methods that we’ll be using in the course of corpus creation. Bangladesh is often considered as one of the fastest emerging nations in the world in terms of economic growth. Besides, the country has a reputation in utilizing IT in the most creative... |
<s>the flow-chart showing the principal steps that we have considered while developing our corpus (mono-lingual) in the first phase. Fig. 1. The development process of Bangla corpus B. Second & Third Phase (Multilingual Parallel Corpora) In the second and third phase of the Corpus development task, we will be using the... |
<s>though it is a labour-intensive and resource-hungry option. Still, this method is better for leaflets, hand-written items, and recorded speech. • Existing electronic texts: There are many texts already exist in electronic form in Bengali which is a great source of text- such as Wikipedia, Baglapedia, Newspapers, Mag... |
<s>of lines: 1. Word lines containing the annotation of a word/token in 10 fields separated by single tab characters. The fields are namely- ID, FORM, LEMMA, UPOSTAG, XPOSTAG, FEATS, HEAD, DEPREL, DEPS, MISC 2. Blank lines marking sentence boundaries. 3. Comment lines starting with a hash (#). Example of annotating a B... |
<s>(token) in a document to the number of unique words (types) in the document is called Type-Token Ratio. Highest: mini (0.101) kilo (0.082) Lowest: giga (0.043) mega (0.059) A lower vocabulary usually density indicates complex text with a pool of unique words, and a higher ratio indicates simpler text with words reus... |
<s>the comparative frequency of some of ‘অব য়’ (which is a part of speech or grammatical category name in Bangla grammar). In comparison to English grammar, ‘অব য়’ can be used as both prepositions, conjunction and interjection in a sentence of Bangla language. ‘ও’ and ‘এবং’ are a somewhat similar type of POS in Bangla ... |
<s>design. [14] M. A. Al Mumin, A. A. M. Shoeb, M. R. Selim, and M. Z. Iqbal, “Sumono: A representative modern bengali corpus,” SUST Journal of Science and Technology, vol. 21, pp. 78–86, 2014. [15] S. Khan, A. Ferdousi, and M. A. Sobhan, “Creation and analysis of a new bangla text corpus bdnc01,” International Journal... |
<s>Uchida, H., Zhu, M., & Khan, M. A. S. (2012, December). UNL explorer. In Proceedings of COLING 2012: Demonstration Papers (pp. 453-458). [31] Salam, K. M. A., Uchida, H., Yamada, S., & Nishino, T. (2013). Web Based UNL Ontology Visualization. Journal of Convergence Information Technology, 8(13), 69. [32] Salam, K. M... |
<s>/Barmeno-ExtraBold /Barmeno-Medium /Barmeno-Regular /Baskerville /BaskervilleBE-Italic /BaskervilleBE-Medium /BaskervilleBE-MediumItalic /BaskervilleBE-Regular /Baskerville-Bold /Baskerville-BoldItalic /Baskerville-Italic /BaskOldFace /Batang /BatangChe /Bauhaus93 /Bellevue /BellMT /BellMTBold /BellMTItalic /Berling... |
<s>/FuturaBT-Medium /FuturaBT-MediumItalic /Futura-Light /Futura-LightOblique /GalliardITCbyBT-Bold /GalliardITCbyBT-BoldItalic /GalliardITCbyBT-Italic /GalliardITCbyBT-Roman /Garamond /Garamond-Bold /Garamond-BoldCondensed /Garamond-BoldCondensedItalic /Garamond-BoldItalic /Garamond-BookCondensed /Garamond-BookCondens... |
<s>/TimesNewRomanPSMT /Times-Roman /Times-RomanSC /Trajan-Bold /Trebuchet-BoldItalic /TrebuchetMS /TrebuchetMS-Bold /TrebuchetMS-Italic /Tunga-Regular /TwCenMT-Bold /TwCenMT-BoldItalic /TwCenMT-Condensed /TwCenMT-CondensedBold /TwCenMT-CondensedExtraBold /TwCenMT-CondensedMedium /TwCenMT-Italic /TwCenMT-Regular /Univer... |
<s>[600 600] /PageSize [612.000 792.000]>> setpagedevice</s> |
<s>Word Sense Disambiguation in Bangla Language Using Supervised Methodology with Necessary ModificationsORIGINAL CONTRIBUTIONWord Sense Disambiguation in Bangla Language Using SupervisedMethodology with Necessary ModificationsAlok Ranjan Pal · Diganta Saha · Niladri Sekhar Dash ·Antara PalReceived: 10 July 2017 / Acce... |
<s>find the closeness of a test data with thesense-tagged clusters. The minimum distance from a sensetagged cluster assigns the sense to that new test data.The present work is based on Naı̈ve Bayes probabilisticmodel which is used as a baseline method for sense clas-sification. This baseline method generates 81% accura... |
<s>feature space. When a new datapoint comes to be categorized, any distance based simi-larity measuring technique is used to find the closeness ofthe data point w.r.t. all the other classifiers. The minimumdistance w.r.t. a particular classifier represents the sense ofthe test data.Support Vector MachineIn Support Vec... |
<s>text corpus used in this work consists of35,89,220 inflected and non-inflected words, among which199,245 words may be treated as distinct lexical units.These words are first arranged in decreasing orderaccording to their term frequency in the corpus. The mostfrequently used words are then selected for experimentThe ... |
<s>of correctly evaluated instances according to human decisionð Þ= total number of data instancesð Þ; andF - Measure ¼ 2 � P � R= Pþ Rð Þ:J. Inst. Eng. India Ser. B123Through the work, the systems evaluated all the testinstances either correctly or wrongly which result the samePrecision and the Recall value for each d... |
<s>the same strategy as inthe baseline method in addition to the words derived fromlemmatization. Words are represented in the followingformat: “word-in-surface-level/stem-form/POS”.This expansion approach uses the same standard outputfiles used in the baseline experiment. Though the inputshave been prepared in lemmati... |
<s>exact to ourexpectation, may be accepted for the time being on theground that this is the first attempt of this kind and thismethod may help us to devise new strategies for achievingour goals. In reality the complex linguistic natures of theSouth Asian languages like Hindi, Bangla, Tamil, Telugu,Punjabi, Malayalam a... |
<s>83neeche 51 74 80māthā 30 83 84Total 892 81.5 83J. Inst. Eng. India Ser. B123Support Concept Map Construction. In: String Processing andInformation Retrieval, eds. by M.A. Nascimento, E.S. de Moura,A.L. Oliveira. SPIRE 2003. Lecture Notes in Computer Science,vol 2857 (Springer, Berlin, Heidelberg, 2003) pp. 350–35... |
<s>for unsu-pervised WSD, in Proceedings of the 21st International Confer-ence on Computational Linguistics and 44th Annual Meeting ofthe ACL (Sydney, 2006), pp. 97–10453. http://arxiv.org/pdf/cs/0007010.pdf. 14 May 201554. http://www.aclweb.org/anthology/S01-1017. 14 May 2015J. Inst. Eng. India Ser. B123http://www.lin... |
<s>See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/334331114Developing A Bangla WordNet: The Word Clustering ApproachThesis · September 2018CITATIONSREADS1033 authors:Some of the authors of this publication are also working on these related projects:NLP/ML p... |
<s>word cluster, word2vec.-I-AcknowledgementsWe would like to thank the Department of Computer Science and Engineering, Shahjalal Uni-versity of Science and Technology, Sylhet 3114, Bangladesh, for supporting this research. We arealso grateful to numerous authors of previous works for their cooperation and support.We w... |
<s>. . . . . . 52 Background Study 62.1 Literature Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62.2 WordNets In Other Languages . . . . . . . . . . . . . . . . . . . . . . . . . . . 112.3 Uses of WordNet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133 Methodology 1... |
<s>. . . . 314.4 Experiment III: FastText Skip-gram model . . . . . . . . . . . . . . . . . . . . . 324.5 Experiment III: FastText CBOW model . . . . . . . . . . . . . . . . . . . . . . 334.6 Training Time . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 344.7 Comparing The Word Embedding Models ... |
<s>. . . . . . . . . . . . . . . . . . . . 21.2 Sample structure of a Bangla WordNet . . . . . . . . . . . . . . . . . . . . . . . 32.1 Block diagram of WordNet system[2] . . . . . . . . . . . . . . . . . . . . . . . 72.2 Proposed method for BanglaNet[3] . . . . . . . . . . . . . . . . . . . . . . . . . 82.3 Linked Ind... |
<s>development of these resources.A WordNet can be a very powerful resource for any language. The concept of WordNet wasfirst introduced by Princeton University. They developed the WordNet for the English language,which is now known as the Princeton WordNet[6]. WordNet is a large lexical database of En-glish language. ... |
<s>and important resource for any language. But its importance doesnot end there. As a WordNet features word relations and their connections, a lot of information-3-can be utilized from aWordNet regarding any language. This makes it a powerful tool for researchworks. WordNet has use in various sectors of NLP research w... |
<s>process followed and the steps implementedto complete our work.• Chapter 4 deals with the results we have gotten for our implementations, their comparisonand the decisions we have reached from them.• Discussions based on the construction of Bangla WordNet will be found in chapter 5.• We concluded in Chapter 6.-5-Cha... |
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