knowledgerich word sense disambiguation rivaling supervised systems

Ngày tải lên: 17/03/2014, 00:20

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Ngày tải lên: 23/03/2014, 19:20

... Cross-Lingual Word Sense Disambiguation task for all five target languages. 1 Introduction Word Sense Disambiguation (WSD) is the NLP task that consists in selecting the correct sense of a polysemous word ... Machine- Learning of Word Sense Disambiguation. Natural Language Engineering, Special Issue on Word Sense Disambiguation Systems, 8:311–325. N. Ide, T. Erjavec, and D. Tufis¸. 2002. Sense discrimi- nation ... This system also differs from the Uvt-WSD and ParaSense systems in the sense that the word senses are derived from WordNet, whereas the other systems do not use any external resources. The results...

Ngày tải lên: 20/02/2014, 05:20

... two words. An ambiguous word has the same number of EPs as of senses. Each EP's sense maps to a sense of ambiguous word. The semantic equivalence demands further equivalence at each sense ... 2003. Word Sense Disambiguation Within a Multilingual Framework. PhD thesis, University of Maryland College Park. Mona Diab. 2004a. Relieving the Data Acquisition Bottleneck in Word Sense Disambiguation. ... morpheme words for every sense of the word in construction of the EP, rich semantic information can be acquired in the training step and is an advantage for sense disambiguation. 2) Senseval-3...

Ngày tải lên: 20/02/2014, 12:20

... describes SENSELEARNER – a minimally supervised word sense disam- biguation system that attempts to disam- biguate all content words in a text using WordNet senses. We evaluate the accu- racy of SENSELEARNER ... for minimally supervised word- sense dis- ambiguation that attempts to disambiguate all content words in a text using WordNet senses. The results ob- tained on both SENSEVAL-2 and SENSEVAL-3 data sets ... July. R. Mihalcea and E. Faruque. 2004. SenseLearner: Min- imally supervised word sense disambiguation for all words in open text. In Proceedings of ACL/SIGLEX Senseval-3, Barcelona, Spain, July. R....

Ngày tải lên: 20/02/2014, 15:20

... Jessica Stevens. Supervised sense tagging using support vector machines. In Proceedings of Senseval-2, Sec- ond International Workshop on Evaluating Word Sense Disambiguation Systems, pages 59–62, Toulouse, ... Wicentowski. The Johns Hopkins SENSEVAL2 system descrip- tions. In Proceedings of Senseval-2, Sec- ond International Workshop on Evaluating Word Sense Disambiguation Systems, pages 163–166, Toulouse, ... the Senseval 2 English lexical sample task. It includes 73 target words, among which nouns, adjectives, adverbs and verbs. For each word, training and test instances tagged with WordNet senses...

Ngày tải lên: 20/02/2014, 16:20

... @comp.nus.edu.sg Abstract Instances of a word drawn from different domains may have different sense priors (the proportions of the different senses of a word) . This in turn affects the accuracy of word sense disambiguation ... the domain dependence of supervised word sense disambiguation systems. In Proc. of EMNLP/VLC00. Adam Kilgarriff. 2001. English lexical sample task description. In Proc. of SENSEVAL-2. Yoong Keok ... Chan and Hwee Tou Ng. 2005a. Scaling up word sense disambiguation via parallel texts. In Proc. of AAAI05. Yee Seng Chan and Hwee Tou Ng. 2005b. Word sense disambiguation with distribution estimation. In...

Ngày tải lên: 08/03/2014, 02:21

... Re- latedness to Perform Word Sense Disambiguation. Sinopalnikova, A. (2004). Word Association Thesau- rus as a Resource for Building Wordnet. In GWC 2004. Sussna, M. (1993). Word Sense Disambiguation ... provided, SENSEVAL roughly categorizes the participating systems into “unsupervised systems and supervised systems . Those that don’t use the training data are not usually truly unsupervised, ... its use for processing word sense disam- biguation, achieving results that are compara- tively better than most unsupervised systems of SENSEVAL-2 in the literature. Since WordNet only organizes...

Ngày tải lên: 08/03/2014, 02:21

... Introduction Many words have multiple meanings, depending on the context in which they are used. Word sense dis- ambiguation (WSD) is the task of determining the correct meaning or sense of a word in context. ... resolving sense ambiguity, a WSD system will be able to help an MT system to determine the correct translation for an ambiguous word. To determine the correct sense of a word, WSD systems typically ... presents conflicting evi- dence on whether word sense disambigua- tion (WSD) systems can help to improve the performance of statistical machine transla- tion (MT) systems. In this paper, we suc- cessfully...

Ngày tải lên: 08/03/2014, 02:21

... Ciaramita and Mark Johnson. 2004. Mul- ti-component Word Sense Disambiguation. Proceed- ings of Senseval-3: 3rd International Workshop on the Evaluation of Systems for the Semantic Analysis of Text, ... words to the right and left of the verb, identified using POS tags, represented by has_narrow(snt, word_ position, word) : has_narrow(snt 1 , 1st _word_ left, mind). has_narrow(snt 1 , 1st _word_ right, ... the positions of the words, represented by has_narrow_trns(snt, word_ position, portuguese _word) : has_narrow_trns(snt 1 , 1st _word_ right, como). has_narrow_trns(snt 1 , 2nd _word_ right, um). …...

Ngày tải lên: 08/03/2014, 02:21

... natural language, a word often assumes different meanings, and the task of determining the correct meaning, or sense, of a word in different contexts is known as word sense disambiguation (WSD). ... behavior of active learn- ing for word sense disambiguation. In Proc. of HLT/NAACL06. H. T. Dang. 2004. Investigations into the Role of Lex- ical Semantics in Word Sense Disambiguation. PhD dissertation, ... dependence of super- vised word sense disambiguation systems. In Proc. of EMNLP/VLC00. A. Fujii, K. Inui, T. Tokunaga, and H. Tanaka. 1998. Selective sampling for example-based word sense dis- ambiguation....

Ngày tải lên: 08/03/2014, 02:21

... method of word sense disambiguation that com- putes the intended sense of a target word, using WordNet-based measures of seman- tic relatedness (Patwardhan et al., 2003). SenseRelate::TargetWord is ... algorithm. The disambiguation process is carried out by selecting that sense of the target word which is most related to the context words. Relatedness between word senses is mea- sured using the WordNet::Similarity ... Measure Context Target Sense Preprocessing Format Filter Sense Inventory Context Selection Postprocessing Pick Sense Figure 1: A generalized framework for Word Sense Disambiguation. modules...

Ngày tải lên: 08/03/2014, 04:22

... our system. 1 Introduction Supervised Word Sense Disambiguation (WSD) systems perform better than unsupervised systems. But lack of training data is a severe bottleneck for supervised systems due to the ... SENSEVAL-2: Second International Workshop on Evaluating Word Sense Disambiguation Systems. ACL SIGLEX, Toulouse, France. Mona Diab. 2004. An Unsupervised Approach for Boot- strapping Arabic Word ... Jessica Stevens. 2002. Supervised Sense Tagging using Support Vector Machines. Proceedings of the Second International Workshop on Evaluating Word Sense Disambiguation Systems (SENSEVAL-2). Toulouse,...

Ngày tải lên: 08/03/2014, 04:22

... Word Sense Disambigua- tion Systems (SENSEVAL-2), pages 17-20. Yoong Keok Lee and Hwee Tou Ng. 2002. An empiri- cal evaluation of knowledge sources and learning al- gorithms for word sense disambiguation. ... active feature selection for word sense disambiguation. In Proceedings of the Second Inter- national Workshop on Evaluating Word Sense Dis- ambiguation Systems (SENSEVAL-2), pages 127-130. George ... Hopkins SENSEVAL2 system descrip- tions. In Proceedings of the Second International Workshop on Evaluating Word Sense Disambigua- tion Systems (SENSEVAL-2), pages 163-166. WordNet 1.7 sense...

Ngày tải lên: 08/03/2014, 04:22

... the Special Issue on Word Sense Disambiguation: The State of the Art. Computational Linguistics, 24(1):1- 40. Adam Kilgarriff. 1998. Senseval: An exercise in eval- uating word sense disambiguation ... proto- type paths prepared for each sense of the target word. Step 3. Find a summation of similarity between each prototype and input path for each sense. Step 4. Select the sense with the maximum valueof the ... similar context have the same sense (Charniak, 1993; Lin, 1997). That is, once we prepare the pro- totype sequences for each sense, we can determine the sense of the target word as one with the most similar...

Ngày tải lên: 08/03/2014, 04:22

... semantically untagged word1 - word2 pair (W1 - W2) OUTPUT: ranking the senses of one word PROCEDURE: STEP 1. Form a similarity list ]or each sense of one of the words. Pick one of the words, say ... Combining unsupervised lexical knowledge methods for word sense disambiguation. Computational Linguistics. J. Stetina, S. Kurohashi, and M. Nagao. 1998. General word sense disambiguation ... age of WordNet in Natural Language Process- ing, Proceedings of COLING-A CL Workshop, Montreal, Canada, July. D. Yarowsky. 1995. Unsupervised word sense disambiguation rivaling supervised...

Ngày tải lên: 08/03/2014, 06:20

... 268 Word: cent Informant: Word to the left Information: .378 bits Sense 1 Sense 2 per 0 8 5 2 a one 4 7 Common informant values for each sense Pr(French I Sense 1) Pr(French [Sense ... each sense Sense 1 longtemps de UR quelques denx 1 plus trois Sense 2 le la l' ce les 1968 Comnmn informant values for each sense Pr(English [Sense 1) Pr(English [ Sense ... sense- disambiguation questions. FUTURE WORK Although our results are promising, this particular method of assigning senses to words is quite limited. It assigns at most two senses to a word, ...

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