Lexical ambiguity and information retrieval
ACM Transactions on Information Systems (TOIS)
Using WordNet to disambiguate word senses for text retrieval
SIGIR '93 Proceedings of the 16th annual international ACM SIGIR conference on Research and development in information retrieval
Word sense disambiguation using a second language monolingual corpus
Computational Linguistics
Word-sense disambiguation using statistical methods
ACL '91 Proceedings of the 29th 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
Estimating upper and lower bounds on the performance of word-sense disambiguation programs
ACL '92 Proceedings of the 30th annual meeting on Association for Computational Linguistics
Co-occurrence vectors from corpora vs. distance vectors from dictionaries
COLING '94 Proceedings of the 15th conference on Computational linguistics - Volume 1
Automatic thesaurus construction based on grammatical relations
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Selective sampling for example-based word sense disambiguation
Computational Linguistics
Word sense disambiguation using heterogeneous language resources
IJCNLP'04 Proceedings of the First international joint conference on Natural Language Processing
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Word sense disambugation has recently been utillized in corpus-based approaches, reflecting the growth in the number of machine readable texts. One category of approaches disambiguates an input verb sense based on the similarity between its governing case fillers and those in given examples. In this paper, we introduce the degree of contribution of case to verb sense disambiguation into this existing method. In this, greater diversity of semantic range of case filler examples will lead to that case contributing to verb sense disambiguation more. We also report the result of a comparative experiment, in which the performance of disambiguation is improved by considering this notion of semantic contribution.