Effect of Weight Assignment in Data Fusion Based Information Retrieval

Effect of Weight Assignment in Data Fusion Based Information Retrieval

 Krishnan Batri1, Veerasamy Murugesh2 and Nagammapudur Gopalan3
1Department of Computer Engineering, European University of Lefke, Turkey
2Department of Microsoft Information Technology, Keimyung University, Republic of Korea
3Department of Computer Applications, National Institute of Technology, India

 

Abstract: Variation in performances of an Information Retrieval system, which merges results from a number of retrieval schemes possessing equal and unequal weights, is studied in this paper. Weight of the retrieval schemes for a particular document is derived from the relevance scores of that corresponding document. Since, the relevance scores are varying from document to document and corpus to corpus, the method proposed is dynamic. A number of weight calculation methods, which are using the error value for computation purpose, are discussed in this paper. The effectiveness of the weight calculation is tested over three benchmark test collections viz., ADI, CISI and MED. It has been identified that the methods discussed in this paper retrieve articles effectively and they are independent of history or any training data.

Keywords:  Data fusion, information retrieval, relevance score, similarity measure, and weight assignment.

  Received September 16, 2008; accepted August 3, 2009

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