Dynamic selection method of the best search engine for a user's query
Kodai Mizuno, Kyoji Kawagoe
Abstract
Kodai Mizuno, Kyoji Kawagoe
Abstract
In this paper, we propose a new dynamic selection method of the best search engine for a user's query. When users retrieve on the Internet, the expert users manually select the best search engine for their queries. However, the most important problem is that the novice users cannot understand features of all search engines. Consequently, because such users cannot select the best search engine, the users cannot obtain the best retrieval results. In this paper, we focus the number of retrieval results, and we calculate search engines' matching scores suitable for the user's query by using this focus point. As a result, novice users can select the best search engine using the scores calculated by our system.
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In this paper, we propose a new dynamic selection method of the best search engine for a user's query. When users retrieve on the Internet, the expert users manually select the best search engine for their queries. However, the most important problem is that the novice users cannot understand features of all search engines. Consequently, because such users cannot select the best search engine, the users cannot obtain the best retrieval results. In this paper, we focus the number of retrieval results, and we calculate search engines' matching scores suitable for the user's query by using this focus point. As a result, novice users can select the best search engine using the scores calculated by our system.
Key concepts: Search engine, Computer science, Information retrieval, Metasearch engine, Query expansion, Search-oriented architecture, Focus (optics), Selection (genetic algorithm)