Abstract
When a query is passed to multiple search engines, each search engine returns a ranked list of documents. The problem of result merging is to fuse these ranked lists such that optimal performance is achieved as a result of the combination. In this paper, our primary contribution is a result merging method, based on fuzzy set theory that adapts the quantifier-guided, Ordered Weighted Averaging (OWA) operators introduced by Yager. The proposed framework is more comprehensive than the existing OWA operator based method, as our investigation evaluates alternative heuristics for missing documents (those existing exist in some, but not all, ranked lists) in order to place such documents into the ranked lists before merging. It shows that the effectiveness of the merging process is improved over the based strategy known as Borda-fuse.
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Diaz, E.D., De, A., Raghavan, V. (2005). A Comprehensive OWA-Based Framework for Result Merging in Metasearch. In: Ślęzak, D., Yao, J., Peters, J.F., Ziarko, W., Hu, X. (eds) Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing. RSFDGrC 2005. Lecture Notes in Computer Science(), vol 3642. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11548706_21
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DOI: https://doi.org/10.1007/11548706_21
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28660-8
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