Research And Achievement Of Personalized Search Engine

With the rapid growth of web information, search engines have become the main tools of information retrieval. But the existing majority of search engines have the shortcomings of providing the same results to the different users' retrieval requisition, failing to reflect the users' true interest. Aiming at the existing problems in current search engine systems, this paper is expected to develop a personalized search engine based on learning user feedback.First, this paper introduces the main background knowledge of traditional search engines, meta search engine and personalized search engine. Also this paper proposes the trend of search engine in the future. Search engine will be more personal, intelligent and professional.Then, after learning some technical knowledge of developing personalized search engine, this paper proposes the frame and processes of search engine. And the system is divided into the four modules that are interface module, searching module, learning user feedback module and optimizing search results module. Learning user feedback module is the core of this system. This paper designs a new method of learning user feedback, that is, to get user's satisfaction feedback by adding scoring system into seach engine to generate interest of certain user. Then system optimizes the search results and returns the results that user is most interested in, which makes search results highly targeted at centain user. In addition, system will be able to tell users about other users' interested modes, in order to make users share search results with each other and improve the efficiency of searching.After implementing the personalized search engine based on user's feedback, this paper also proposes the idea that brings automatic clustering technology to this search engine. Finally, paper presents the improved algorithm and verifies the feasibility of the algorithm through experiments, which can further improve the efficiency of searching and determine the direction of my future research.