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New Technology of Library and Information Service  2011, Vol. 27 Issue (1): 57-62    DOI: 10.11925/infotech.1003-3513.2011.01.09
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Study on Web Retrieval Query Fusion Based on Relevance Feedback
Jing Jing1, Hong Ying2, Jiang Yuanyuan3, Gao Xiaofeng4
1. Business School, Nankai University, Tianjin 300071, China;
2. Library of Tianjin Conservatory of Music, Tianjin 300071, China;
3. Editorial Office, Journal of Henan Agricultural University, Zhengzhou 450002, China;
4. Tangshan Railway Vehicles Co. Ltd., Tangshan 063035, China
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This paper introduces the combination of query fusion and relevance feedback methods.By analyzing previous TopN documents selection strategy, it puts forward a query fusion algorithm using correlation coefficient to select a variable number of TopN documents in order to extend query, which is called variable TopN feedback-based query fusion algorithm. Fixed and variable TopN query fusion experiments are analyzed separately, and the test results show that the variable TopN feedback method improves the retrieval performance to some extent.

Key wordsQuery fusion      Relevance feedback      Correlation coefficient      Meta-search engine     
Received: 11 November 2010      Published: 12 February 2011



Cite this article:

Jing Jing, Hong Ying, Jiang Yuanyuan, Gao Xiaofeng. Study on Web Retrieval Query Fusion Based on Relevance Feedback. New Technology of Library and Information Service, 2011, 27(1): 57-62.

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