Proceedings of the 1992 ACM/IEEE conference on Supercomputing
A simple rule-based part of speech tagger
ANLC '92 Proceedings of the third conference on Applied natural language processing
Word sense disambiguation using optimised combinations of knowledge sources
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
Contextual word similarity and estimation from sparse data
ACL '93 Proceedings of the 31st annual meeting on Association for Computational Linguistics
Statistical sense disambiguation with relatively small corpora using dictionary definitions
ACL '95 Proceedings of the 33rd annual meeting on Association for Computational Linguistics
Unsupervised word sense disambiguation rivaling supervised methods
ACL '95 Proceedings of the 33rd annual meeting on Association for Computational Linguistics
Word-sense disambiguation using decomposable models
ACL '94 Proceedings of the 32nd annual meeting on Association for Computational Linguistics
Integrating multiple knowledge sources to disambiguate word sense: an exemplar-based approach
ACL '96 Proceedings of the 34th annual meeting on Association for Computational Linguistics
Automatic recognition of verbal polysemy
COLING '94 Proceedings of the 15th conference on Computational linguistics - Volume 2
Co-occurrence vectors from corpora vs. distance vectors from dictionaries
COLING '94 Proceedings of the 15th conference on Computational linguistics - Volume 1
Word-sense disambiguation using statistical models of Roget's categories trained on large corpora
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 2
Using a semantic concordance for sense identification
HLT '94 Proceedings of the workshop on Human Language Technology
Discriminating among word senses using McQuitty's similarity analysis
NAACLstudent '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology: Proceedings of the HLT-NAACL 2003 student research workshop - Volume 3
Learning word senses with feature selection and order identification capabilities
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
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This paper describes unsupervised learning algorithm for disambiguating verbal word senses using term weight learning. In our method, collocations which characterise every sense are extracted using similarity-based estimation. For the results, term weight learning is performed. Parameters of term weighting are then estimated so as to maximise the collocations which characterise every sense and minimise the other collocations. The results of experiment demonstrate the effectiveness of the method.