loading...
 This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
15th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'03)
Query Expansion and Query Reduction in Document Retrieval
Sacramento, California, USA
November 03-November 05
ISBN: 0-7695-2038-3
Ingrid Zukerman, Monash University
Bhavani Raskutti, Telstra Research Laboratories
Yingying Wen, Monash University
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%.
Citation:
Ingrid Zukerman, Bhavani Raskutti, Yingying Wen, "Query Expansion and Query Reduction in Document Retrieval," ictai, pp.552, 15th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'03), 2003
Usage of this product signifies your acceptance of the Terms of Use.