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A Multi-Agent Based Personalized Meta-Search Engine Using Automatic Fuzzy Concept Networks

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3 Author(s)
Arzanian, B. ; Dept. of Electr. Eng., Univ. of Kurdistan, Sanandaj, Iran ; Akhlaghian, F. ; Moradi, P.

As a result of the rapid growth and dynamic content of the web, the general purpose web search engines are becoming deficient. Although the meta-search engines can help by increasing the search coverage of the web, the large number of irrelevant results returned by a meta-search engine is still causing problems for the users. The personalization of meta-search engines overcomes this problem by filtering results respect to individual user's interests. In this paper, a multi-agent architecture is introduced for personalizing meta-search engine using the fuzzy concept networks. The main goal of this paper is to use automatic fuzzy concept networks to personalize results of a meta-search engine provided with a multi-agent architecture for searching and quickly retrieving. Experimental results indicate that the personalized meta-search results of the system are more relevant than the combined results of the search engines.

Published in:

Knowledge Discovery and Data Mining, 2010. WKDD '10. Third International Conference on

Date of Conference:

9-10 Jan. 2010