Abstract
We investigate the effect of paraphrase generation on document retrieval performance. Specifically, we describe experiments where three information sources are used to generate lexical paraphrases of queries posed to the Internet. These information sources are: WordNet, a Webster-based thesaurus, and a combination of Webster and WordNet. Corpus-based information and wordsimilarity information are then used to rank the paraphrases. We evaluated our mechanism using 404 queries whose answers reside in the LA Times subset of the TREC-9 corpus. Our experiments show that query paraphrasing improves retrieval performance, and that performance is influenced both by the number of paraphrases generated for a query and by their quality. Specifically, the best performance was obtained usingWordNet, which improves document recall by 14% and increases the number of questions that can be answered by 8%.
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Zukerman, I., Raskutti, B., Wen, Y. (2002). Experiments in Query Paraphrasing for Information Retrieval. In: McKay, B., Slaney, J. (eds) AI 2002: Advances in Artificial Intelligence. AI 2002. Lecture Notes in Computer Science(), vol 2557. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36187-1_3
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DOI: https://doi.org/10.1007/3-540-36187-1_3
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