Abstract
Merging of search engine results is a key metasearch engine function. Most result merging models try to merge ranked lists of web documents returned by search engines in response to a user query using some linear combination approach. A few give more importance to one search engines as opposed to another based on some performance criteria. Other assign weights to documents ranks etc. However few models compare documents and search engines head to head during the process of result merging. In this paper we propose two models for result merging for metasearch, Fuzzy ANP and Weighted Fuzzy ANP that employ fuzzy linguistic quantifier guided approach to result merging using Saty’s Analytical Network Process. We compare our models to existing result merging models. Our results show significant improvements.
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De, A., Diaz, E. (2012). Fuzzy Analytical Network Models for Metasearch. In: Madani, K., Dourado Correia, A., Rosa, A., Filipe, J. (eds) Computational Intelligence. IJCCI 2010. Studies in Computational Intelligence, vol 399. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27534-0_13
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DOI: https://doi.org/10.1007/978-3-642-27534-0_13
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