The Research And Implementation Of Personalized Search Engin Base On Lucene

With the rapid development of Internet technology the network can provide people more and more information. Search engine has been widely used in many fields, which is treated as a tool that people can get information on World Wide Web. In order to provide personalized search service for users, personalized search engine comes forth. Because of many researchers contribution, people have made great progress in personalized search engine. This thesis points out the shortage of current search engine and user's requirements of personalized search, does some research on interest learning methods and its technology, a new user interest model is proposed. It mainly takes charge of information collection of user interest and user feedback technology. The research is of value in both theory and application. The main work in the thesis is showed as follow:The research tells basic theory of personalized search engine, and the method, contents and storage of collection of user information based on making user model. According to the theory above, it presents the ways of making user model based on user profile.Through collecting user information, the thesis presents a kind of method about renewing user model based on this technology. Further, to get united to the characters of user model, a personalized query expansion method and a new sort of personalized page ranking are proposed.An experimental system base on Lucene is established and proves the feasibility of architecture about personalized search engine. Besides, through collecting user information, a new user model is set up, in some percents, and it improves query precision of search engine.