| A framework for selective query expansion |
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Conference on Information and Knowledge Management
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Proceedings of the thirteenth ACM international conference on Information and knowledge management
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Washington, D.C., USA
POSTER SESSION: Posters P-2
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Pages: 236 - 237
Year of Publication: 2004
ISBN:1-58113-874-1
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Downloads (6 Weeks): 11, Downloads (12 Months): 64, Citation Count: 14
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ABSTRACT
Query expansion is a well-known technique that has been shown to improve <i>average</i> retrieval performance. This technique has not been used in many operational systems because of the fact that it can greatly degrade the performance of some individual queries. We show how comparison between language models of the unexpanded and expanded retrieval results can be used to predict when the expanded retrieval has strayed from the original sense of the query. In these cases, the unexpanded results are used while the expanded results are used in the remaining cases (where such straying is not detected). We evaluate this method on a wide variety of TREC collections.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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S. Cronen-Townsend, Y. Zhou, and W. B. Croft. A language modeling framework for selective query expansion. Technical Report IR-338, Center for Intelligent Information Retrieval, University of Massachusetts, 2004.
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H. C. Taneja and R. K. Tuteja. Characterization of a quantitative-qualitative measure of relative information. Information Sciences, 33:217--222, 1984.
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