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Return to Session VIb: Disambiguation
Information retrieval using word senses is emerging as a good research challenge on semantic information retrieval. In this paper, we propose a new method using word senses in information retrieval: root sense tagging method. This method assigns coarse-grained word senses defined in WordNet to query terms and document terms by unsupervised way using co-occurrence information constructed automatically. Our sense tagger is crude, but performs consistent disambiguation by considering only the single most informative word as evidence to disambiguate the target word. We also allow multiple-sense assignment to alleviate the problem caused by incorrect disambiguation. Experimental results on a large-scale TREC collection show that our approach to improve retrieval effectiveness is successful, while most of the previous work failed to improve performances even on small text collection. Our method also shows promising results when is combined with pseudo elevance feedback and state-of-the-art retrieval function such as BM25.
@inproceedings{1009038, author = {Sang-Bum Kim and Hee-Cheol Seo and Hae-Chang Rim}, title = {Information retrieval using word senses: root sense tagging approach}, booktitle = {SIGIR '04: Proceedings of the 27th annual international conference on Research and development in information retrieval}, year = {2004}, isbn = {1-58113-881-4}, pages = {258--265}, location = {Sheffield, United Kingdom}, doi = {http://doi.acm.org/10.1145/1008992.1009038}, publisher = {ACM Press}, }  ©2005 Association for Computing Machinery |
