a method for word sense disambiguation of unrestricted text
Báo cáo khoa học: "A Method for Word Sense Disambiguation of Unrestricted Text" potx
... lexical knowledge methods for word sense disambiguation. Computational Linguistics. J. Stetina, S. Kurohashi, and M. Nagao. 1998. General word sense disambiguation method based on a full ... for word sense disambiguation. Com- putational Linguistics, 18(1):1-30. R. Mihalcea and D.I. Moldovan. 1999. An au- tomatic method for generating sense tagged corpora. In Proceedings of ... semantically close. For appli- cations such as machine translation, fine grain disambiguation works well but for information extraction and some other applications this is an overkill, and...
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Báo cáo khoa học: "SenseRelate::TargetWord – A Generalized Framework for Word Sense Disambiguation" doc
... sense of a target word, using WordNet-based measures of seman-tic relatedness (Patwardhan et al., 2003).SenseRelate::TargetWord is a Perl pack-age that implements this algorithm. The disambiguation ... Sessions,pages 73–76, Ann Arbor, June 2005.c2005 Association for Computational LinguisticsSenseRelate::TargetWord – A Generalized Framework for Word Sense Disambiguation Siddharth PatwardhanSchool ... lexical sample format, which is anXML–based format that has been used for both theSENSEVAL-2 and SENSEVAL-3 exercises. A file inthis format includes a number of instances, each onemade up of...
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Tài liệu Báo cáo khoa học: "ParaSense or How to Use Parallel Corpora for Word Sense Disambiguation" pdf
... their aligned translations (and probabil-319 algorithm parameters in machine learning of language.Machine Learning, pages 84–95.I. Dagan and A. Itai. 1994. Word sense disambiguation using a second ... state -of- the-art systems for all languages, ex-cept for Spanish where the results are very similar.As all steps are run automatically, this multilingualapproach could be an answer for the acquisition ... SemEval systems as wellas the three flavors of the ParaSense system, weretrained on the same Europarl data, the scores illus-trate the potential advantages of using a multilingualapproach. Although...
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Báo cáo khoa học: "Estimating Class Priors in Domain Adaptation for Word Sense Disambiguation" pdf
... This gave a set of 6 nouns for SENSEVAL-2 and 9 nouns for SENSEVAL-3. For each noun, we gathered a maximum of 500parallel text examples as training data, similar towhat we had done in (Chan and ... 200 5a. Scalingup word sense disambiguation via parallel texts. InProc. of AAAI05.Yee Seng Chan and Hwee Tou Ng. 2005b. Word sense disambiguation with distribution estimation.In Proc. of IJCAI05.Pedro ... @comp.nus.edu.sgAbstractInstances of a word drawn from differentdomains may have different sense priors(the proportions of the different senses of a word) . This in turn affects the accuracy of word sense...
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Báo cáo khoa học: "Learning Expressive Models for Word Sense Disambiguation" pot
... be available for many examples. The problem of data sparse-ness increases as more knowledge is exploited and this can cause problems for the machine learning algorithms. A final disadvantage ... Machine Translation. Academic Press, Great Britain. Abolfazl K. Lamjiri, Osama El Demerdash, Leila Kos-seim. 2004. Simple features for statistical Word Sense Disambiguation. Proceedings of ... English Lexical Sample Task. Proceedings of Senseval-3: 3rd International Workshop on the Evaluation of Systems for Semantic Analysis of Text, Barcelona, pages 25-28. Saif Mohammad and Ted Pedersen....
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Báo cáo khoa học: "Domain Adaptation with Active Learning for Word Sense Disambiguation" pdf
... and accuracy improvement is less than1% after all the available WSJ adaptation examples are addedas additional training data. To obtain a clearer picture of theadaptation process, we discard ... in BC andWSJ, average MFS accuracy, average number of BCtraining, and WSJ adaptation examples per noun.data, and the rest of the WSJ examples are desig-nated as in-domain adaptation data. The ... 100WSD Accuracy (%)Percentage of adaptation examples added (%) a- c a r a- truePriorFigure 2: Adaptation process for all 21 nouns. of the BC training examples. At each adaptation iter-ation, WSJ adaptation...
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Báo cáo khoa học: "Exploiting Parallel Texts for Word Sense Disambiguation: An Empirical Study" potx
... the official training data so that we can do a fair comparison between the accuracy of the parallel text alignment approach versus the manual sense- tagging approach. After training a WSD classifier ... automobile races) could be found in the parallel corpora. To ensure a fairer comparison, for each of the 10-trial manually sense- tagged training data that gave rise to the ac-curacy figure M2 of a ... empirical study to evaluate an approach of automatically acquiring sense- tagged training data from English-Chinese parallel corpora, which were then used for disam-biguating the nouns in the SENSEVAL-2...
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Báo cáo khoa học: "Topic Models for Word Sense Disambiguation and Token-based Idiom Detection" pdf
... were discarded.tions caused by tagging or lemmatization errors,we manually corrected any bad tags and lemmas for the target instances.4 Sense Paraphrases For word sense disam-biguation tasks, ... muchbackground information is available, i.e., knowl-edge of the prior sense distribution available andtype of sense paraphrases used. In Model I andModel II, the sense paraphrases are obtained fromWordNet, ... Chang.2009. Plda: Parallel latent dirichlet allocation for large-scale applications. In Proc. of 5th Interna-tional Conference on Algorithmic Aspects in Infor-mation and Management. Software...
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Báo cáo khoa học: " Word Sense Disambiguation in Untagged Text based on Term Weight Learning" ppt
... value between vl and nj. We recall that wp and nq are semantically re- lated if w~i and nq are semantically related and (wv,n q) and (w'pi,nq) are semantically similar. (a) ' and ... These algorithms assign each instance of an ambiguous word to a known sense definition based solely on the values of automatically iden- tifiable features in text. Their methods are per- haps ... This algorithm requires a small number of training examples to serve as a seed. The result shows that the average percentage attained was 96.1% for 12 nouns when the training data was a 460...
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Báo cáo khoa học: "A Tool for Deep Semantic Encoding of Narrative Texts" docx
... (Kingsbury andPalmer, 2002) and Penn Treebank (Marcus et al.,1993). Such projects typically involve a formalmodel (such as a controlled vocabulary of thematicroles) and a corpus of text that has ... (equivalent toFigure 2) as configured for a particular Aesopfable.3. The procedure for reading a text for impor-tant named entities, and formally declaringthese named entities for the story graph.4. ... labeling of verbframes, thematic roles, temporal structure, modal-ity, causality and other features. This type of anno-tation allows for machine learning on the thematicdimension of narrative...
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Tài liệu Báo cáo khoa học: "A Kernel PCA Method for Superior Word Sense Disambiguation" ppt
... each word, training and test instances taggedwith WordNet senses are provided. There are an av-erage of 7.8 senses per target word type. On average109 training instances per target word are ... Special issue on SEN-SEVAL.Hoa Trang Dang and Martha Palmer. Combiningcontextual features for word sense disambigua-tion. In Proceedings of the SIGLEX/SENSEVALWorkshop on Word Sense Disambiguation: ... are available.Note that we used the set of sense classes from Sen-seval’s ”fine-grained” rather than ”coarse-grained”classification task.The KPCA-based model achieves the highest ac-curacy, as...
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