2026-09-19T08:03:27Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/270832022-01-13T07:54:29Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Boris Katz.
Bilotti, Matthew W. (Matthew William), 1981-
Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2005-09-06T21:39:24Z
2005-09-06T21:39:24Z
2004
2004
http://hdl.handle.net/1721.1/27083
56820766
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2004.
Includes bibliographical references (p. 105-109).
Query expansion is a technique used to boost performance of a document retrieval engine, such as those commonly found in question answering (QA) systems. Common methods of query expansion for Boolean keyword-based document retrieval engines include inserting query terms, such as alternate inflectional or derivational forms generated from existing query terms, or dropping query terms that are, for example, deemed to be too restrictive. In this thesis, I present a quantitative evaluation against a test; collection of my own design of five query expansion techniques, two term expansion methods and three term-dropping strategies. I present results that show that there exist best-performing query expansion algorithms that can be ex- perimentally optimized for specific tasks. My findings pose questions that suggest interesting avenues for further study of query expansion algorithms.
by Matthew W. Bilotti.
M.Eng.
109 p.
5751699 bytes
5764839 bytes
application/pdf
application/pdf
en_US
Massachusetts Institute of Technology
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http://dspace.mit.edu/handle/1721.1/7582
Electrical Engineering and Computer Science.
Query expansion techniques for question answering
Thesis
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<Abstract>Query expansion is a technique used to boost performance of a document retrieval engine, such as those commonly found in question answering (QA) systems. Common methods of query expansion for Boolean keyword-based document retrieval engines include inserting query terms, such as alternate inflectional or derivational forms generated from existing query terms, or dropping query terms that are, for example, deemed to be too restrictive. In this thesis, I present a quantitative evaluation against a test; collection of my own design of five query expansion techniques, two term expansion methods and three term-dropping strategies. I present results that show that there exist best-performing query expansion algorithms that can be ex- perimentally optimized for specific tasks. My findings pose questions that suggest interesting avenues for further study of query expansion algorithms.</Abstract>
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