Wu, Shengli, Bi, Yaxin and McClean, Sally (2007) Applying statistical principles to data fusion in information retrieval. In: IEEE International Conference on Systems, Man and Cybernetics, 2007, Montreal, Canada. IEEE. 7 pp. [Conference contribution]
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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.
|Item Type:||Conference contribution (Paper)|
|Faculties and Schools:||Faculty of Computing & Engineering|
Faculty of Computing & Engineering > School of Computing and Information Engineering
Faculty of Computing & Engineering > School of Computing and Mathematics
|Research Institutes and Groups:||Computer Science Research Institute|
Computer Science Research Institute > Artificial Intelligence and Applications
Computer Science Research Institute > Information and Communication Engineering
|Deposited By:||Professor Sally McClean|
|Deposited On:||11 Aug 2010 14:43|
|Last Modified:||09 May 2016 11:02|
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