DocumentCode
2358840
Title
Query expansion and query reduction in document retrieval
Author
Zukerman, Ingrid ; Raskutti, Bhavani ; Wen, Yingying
Author_Institution
Sch. of Comput. Sci. & Software Eng., Monash Univ., Clayton, Vic., Australia
fYear
2003
fDate
3-5 Nov. 2003
Firstpage
552
Lastpage
559
Abstract
We investigate two seemingly incompatible approaches for improving document retrieval performance in the context of question answering: query expansion and query reduction. Queries are expanded by generating lexical paraphrases. Syntactic, semantic and corpus-based frequency information is used in this process. Queries are reduced by removing words that may detract from retrieval performance. Features that identify these words were obtained from decision graphs. These approaches were evaluated using a subset of queries from TREC8, 9 and 10. Our evaluation shows that each approach in isolation improves retrieval performance, and both approaches together yield substantial improvements. Specifically, query expansion followed by reduction improved the average number of correct documents retrieved by 21.7% and the average number of queries that can be answered by 15%.
Keywords
query formulation; text analysis; TREC10; TREC8; TREC9; corpus-based frequency information; decision graphs; document retrieval; lexical paraphrases; query expansion; query reduction; question answering; retrieval performance; semantic-based frequency information; syntactic-based frequency information; Australia Council; Computer science; Dictionaries; Frequency; Internet; Laboratories; Performance analysis; Performance evaluation; Software engineering; Vocabulary;
fLanguage
English
Publisher
ieee
Conference_Titel
Tools with Artificial Intelligence, 2003. Proceedings. 15th IEEE International Conference on
ISSN
1082-3409
Print_ISBN
0-7695-2038-3
Type
conf
DOI
10.1109/TAI.2003.1250240
Filename
1250240
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