DocumentCode :
381219
Title :
Adaptive parameter tuning for relevance feedback of information retrieval
Author :
Zhang, Jim ; Zhao, Yannan ; Yang, Zehong ; Wang, Jiaxin
Author_Institution :
Dept. of Comput. Sci. & Technol., Tsinghua Univ., Beijing, China
Volume :
3
fYear :
2002
fDate :
2002
Firstpage :
2132
Abstract :
Relevance feedback is an effective way to improve the performance of an information retrieval system. In practice, the parameters for feedback were usually determined manually without the consideration of the quality of the query. We propose a new concept (adaptiveness) to measure the quality of the query. We built two models to predict the adaptiveness of the query. The parameters for feedback were then determined by the quality of the query. Our experiments on TREC data showed that the performance was improved significantly when compared with blind relevance feedback.
Keywords :
information retrieval systems; relevance feedback; software performance evaluation; TREC data; adaptive parameter tuning; experiments; information retrieval; information retrieval system; performance; query adaptiveness; query quality; relevance feedback; Automation; Computer science; Information retrieval; Intelligent control; Intelligent systems; Laboratories; Predictive models; State feedback;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation, 2002. Proceedings of the 4th World Congress on
Print_ISBN :
0-7803-7268-9
Type :
conf
DOI :
10.1109/WCICA.2002.1021462
Filename :
1021462
Link To Document :
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