An effective selection of retrieval schemes for data fusion


  • Batri Krishnan


Data fusion, filter, information retrieval, overlap, precision, student-t test.


Merging the results from more retrieval systems/schemes may enhance the performance of the Information Retrieval system. The success of the fusion lies in the selection of the member schemes. This paper explores an effective selection algorithm, which is derived from the filter concept, by treating low-score returning schemes as noises. The proposed algorithm is tested over the three benchmark test collections namely, American Documentation Institute (ADI), Centre for Inventions and Scientific Information (CISI), and Medlars (MED). The consistency of the computed result is tested by paired student-t test. It is observed that the presented algorithm results in significant improvement over the existing combination functions. The improvement in performance of the projected method is due to the reduction in amplification chorus effect caused by the low score returning schemes.



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