On the role of t-norms on hybrid fuzzy result merging for metasearch

Metasearch engines provide a mechanism to carry out parallel searches on a number of vertical search systems in parallel. A metasearch engine accepts a user query and passes it to multiple search engines, which in turn return results in the form of ranked result lists. An important task of metasearch is to aggregate results returned by multiple search engines into one composite ranked result list. In this paper we explore the effect of applying algebraic Fuzzy t-norms in result aggregation within a Fuzzy MCDM model which uses Analytic Hierarchy Process (AHP) to do pair wise comparison of search engines and documents prior to result merging using Yager´s Ordered Weighted Average OWA. Our proposed model that uses t-norms in aggregation outperforms the OWA model proposed earlier by Diaz et.all and the Hybrid Fuzzy model proposed by De et.all.