A Distributed Agent Based Web Search using a Genetic Algorithm


In this paper, the problems of current web search engines are analyzed, and the need for a new design is justified. Some ideas on how to improve current web search engines are presented, and then an adaptive method for web meta-search engines with a multi-agent specially the mobile agents is presented to make search engines work more efficiently. In the method, the cooperation between stationary and mobile agents is used to make more efficiency. The meta-search engine gives the user needed documents based on the multi-stage mechanism. The merge of the results obtained from the search engines in the network is done in parallel. Using a reduction parallel algorithm, the efficiency of this method is increased. Furthermore, a feedback mechanism gives the meta-search engine the user’s suggestions about the found documents, which leads to a new query using a genetic algorithm. In the new search stage, more relevant documents are given to the user. The practical experiments were performed in Aglets programming environment. The results achieved from these experiments confirm the efficiency and adaptability of the method.

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@inproceedings{Koorangi2007ADA, title={A Distributed Agent Based Web Search using a Genetic Algorithm}, author={M. Koorangi and Kamran Zamanifar}, year={2007} }