2009Unpublished venueRequires access

Dynamic selection method of the best search engine for a user's query

Kodai Mizuno, Kyoji Kawagoe

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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.

About this research paper

What this paper is about

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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Key contribution

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Method / approach

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Available 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.

Key concepts: Search engine, Computer science, Information retrieval, Metasearch engine, Query expansion, Search-oriented architecture, Focus (optics), Selection (genetic algorithm)

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