Indexing with WordNet synsets can improve Text Retrieval

Details Indexing with WordNet synsets can improve Text Retrieval Indexing with WordNet synsets can improve Text Retrieval

1998-08-05

arxiv.org/abs/cmp-lg/9808002v1

Proceedings of the COLING/ACL'98 Workshop on Usage of WordNet for NLP, Montreal, 1998

Computer Science

Computation and Language

7 pages, LaTeX2e, 3 eps figures, uses epsfig, colacl.sty

Scientific paper

The classical, vector space model for text retrieval is shown to give better results (up to 29% better in our experiments) if WordNet synsets are chosen as the indexing space, instead of word forms. This result is obtained for a manually disambiguated test collection (of queries and documents) derived from the Semcor semantic concordance. The sensitivity of retrieval performance to (automatic) disambiguation errors when indexing documents is also measured. Finally, it is observed that if queries are not disambiguated, indexing by synsets performs (at best) only as good as standard word indexing.

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