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
WordNet: a lexical database for English
Communications of the ACM
Cross-Language Information Retrieval
Cross-Language Information Retrieval
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Word sense disambiguation using optimised combinations of knowledge sources
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
Word-sense disambiguation using decomposable models
ACL '94 Proceedings of the 32nd annual meeting on Association for Computational Linguistics
HLT '93 Proceedings of the workshop on Human Language Technology
A WordNet-based algorithm for word sense disambiguation
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
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The increasing problem of information overload can be reduced by the improvement of information access tasks like Information Retrieval. Relevance Feedback plays a key role in this task, and is typically based only on the information extracted from documents judged by the user for a given query. We propose to make use of a thesaurus to complement this information to improve RF. This must be done by means of a Word Sense Disambiguation process that correctly identifies the suitable information from the thesaurus WORDNET. The results of our experiments show that the utilisation of a thesaurus requires Word Sense Disambiguation, and that with this process, Relevance Feedback is substantially improved.