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Metasearch information fusion using linearprogramming

Published online by Cambridge University Press:  08 November 2012

Gholam R. Amin ,
Ali Emrouznejad  and
Hamid Sadeghi
Gholam R. Amin
Affiliation:
Postgraduate Engineering Centre, Islamic Azad University, South Tehran Branch, Tehran, Iran. gamin@azad.ac.ir
Ali Emrouznejad
Affiliation:
Aston Business School, Aston University, Birmingham, UK
Hamid Sadeghi
Affiliation:
Department of Computer Engineering, Hashtgerd Branch, Islamic Azad University, Alborz, Iran
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Abstract

For a specific query merging the returned results from multiple search engines, in theform of a metasearch aggregation, can provide significant improvement in the quality ofrelevant documents. This paper suggests a minimax linear programming (LP) formulation forfusion of multiple search engines results. The paper proposes a weighting method toinclude the importance weights of the underlying search engines. This is a two-phaseapproach which in the first phase a new method for computing the importance weights of thesearch engines is introduced and in the second stage a minimax LP model for findingrelevant search engines results is formulated. To evaluate the retrieval effectiveness ofthe suggested method, the 50 queries of the 2002 TREC Web track were utilized andsubmitted to three popular Web search engines called Ask, Bing and Google. The returnedresults were aggregated using two exiting approaches, three high-performance commercialWeb metasearch engines and our proposed technique. The efficiency of the generated listswas measured using TREC-Style Average Precision (TSAP). The new findings demonstrate thatthe suggested model improved the quality of merging considerably.

Keywords

Linear programmingsearch enginemetasearchinformation fusioninformation retrieval
Type
Research Article
Information
RAIRO - Operations Research , Volume 46 , Issue 4 , October 2012 , pp. 289 - 303
Copyright
© EDP Sciences, ROADEF, SMAI, 2012

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