Abstract
Result merging of search engine results for metasearch is a well explored area. However most result merging models try to collate document rankings from the search engines whose results are being merged into a single ranking using some mathematical function. However, only a few models compare documents in pair wise comparisons during the process of result merging. In this paper, we propose a Weighted Hybrid Fuzzy Result Merging model that comprehensively compares search engines and documents in pairs before applying the result aggregation function. We compare and contrast the performance of our model with existing models for result merging.
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De, A., Diaz, E.D. (2009). A Weighted Hybrid Fuzzy Result Merging Model for Metasearch. In: Sakai, H., Chakraborty, M.K., Hassanien, A.E., Ślęzak, D., Zhu, W. (eds) Rough Sets, Fuzzy Sets, Data Mining and Granular Computing. RSFDGrC 2009. Lecture Notes in Computer Science(), vol 5908. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10646-0_60
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DOI: https://doi.org/10.1007/978-3-642-10646-0_60
Publisher Name: Springer, Berlin, Heidelberg
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