MetaFusion: An efficient metasearch engine using genetic algorithm

Abstract

World Wide Web is a dynamic source of information which is expanding its content at a staggering rate. Individual search engines are not able to handle the exponential nature of web. Hence meta-search engines are used to solve the problem of low web space information coverage rate of individual search engines. A meta-search engine is a kind of search tool that dynamically dispatches user query to the underlying search engines, hence providing parallel access to multiple search engines and then aggregate the results to present single consolidated result list to user. In this paper, a novel meta-search engine, MetaFusion, has been proposed. The proposed algorithm combines fuzzy AHP with genetic algorithm to get more comprehensive and optimized results. Experimental results shows that relevancy of results returned by MetaFusion is more than several existing research Metasearch engines. The precision of MetaFusion is more when compared with Dogpile and Infospace.