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Applying statistical principles to data fusion in information retrieval

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3 Author(s)
Shengli Wu ; Univ. of Ulster, Coleraine ; Yaxin Bi ; McClean, S.

Data fusion in information retrieval has been investigated by many researchers and quite a few data fusion methods have been proposed. However, their impact on effectiveness has not been well understood. In this paper, we apply statistical principles to data fusion and present a statistical data fusion model, which specifies the algorithm for fusion and conditions to be satisfied. The statistical model can be used as a guideline for data fusion methods. Based on this analysis, we compare CombSum and CombMNZ, which are the two best-known data fusion methods. We explain why sometimes CombMNZ does outperform Comb- Sum and what can be done to make CombSum more effective. Experimental results with TREC data are reported to support the conclusion that our enhancements to the algorithm improve effectiveness.

Published in:

Systems, Man and Cybernetics, 2007. ISIC. IEEE International Conference on

Date of Conference:

7-10 Oct. 2007