The Research And Design On Intelligence Meta Search Engines

With the development of Internet and Web technology, WWW has been a gigantic space of information exchange. Facing the gigantic information, People often lost their direction when they looked for their requisite information. How quickly searching for their requisite information from gigantic information resource has been a big problem of perplexing the user.The search engines are the main tools to help people searching information, however, the problem of the information overload becomes more severe and most returned results are irrelevant to user interest. That affects the retrieval quality and increases the user cost. According to the defect of current search engines, a model of intelligence Meta search engines is presented, which could realize the intelligent and personalized needs of the user. In the paper, the author researches and designs on intelligence Meta search engines and researched a series problem of theory and technology in intelligent search engines.Creating and updating the user interest model are the key technology of intelligent search. The paper suggests the update model of user interests and researches on the intelligent relevance feedback model. When setting up user interest model, it adopts the combination of active offering user interests, watching user action and user logs, which could discover user interest fast and exact.Result Merging is an important part of intelligent search engines too. The paper applies the user interest model in the study of information filtering. The compare of Web page with user interest model and search key words can be valued by similarity function. Then filter and order the result by the calculated value to apply the intelligent search faced user.Finally, the author presents a model of intelligence Meta search engines and gives the working principle. According Meta search engine, Intelligent and personalized service of search engines through application of user interest model is realized.