Abstract

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

Citations