Agent-based Meta Search Engine

It is well known, the Web information increase exponentially with the rapid development of the Internet, and there are many ways of getting information from the Internet. In this case, how to retrieve information correctly and effectively is widely concerned by researchers and common users. Every independent search engine has its own strongpoint, and can get high precision in some specific field, but for common users, it is difficult to choose the appropriate search engine to meet their information querying requirement. Meta-search engine is an effective method to resolve this problem, which enlarges the scale of querying area by choosing different specific independent search engine. At the same times, meta-search engines have the same problem of getting much useless results and can't satisfy different users'interest. Besides, as the Web environment change dynamic, meta-search engine still can't adapt to the Web changing environment, so it is much possible to retrieve many useless information.In this paper, the agent technology is adopted to the meta-search engine, adapt the changes in the Web environment through the adaptability of agent , a agent based meta-search engine architecture(IMSA) is introduced, by modifying the relevant weight of the search engine in terms of the user's relevance feedback to guide the last query. At the same time, the query expansion algorithm based on AND/OR tree with weight is introduced to solve the problem that the uses usually can't express their own query need well and truly, it amend the user's query through the relevance feedback to make the query submitted by the user fit the user's need. Finally, an experiment is made to test the effect of the scheduler and the query expansion algorithm.