Research Of Personalized Recommendation And Search Based On User Interest Model

The rapid development of the Internet brings lots of information to people, at the same time, it results in the inevitable problem of finding valid.message quickly for people. In order to solve this problem, Personalized Information Service is put forward. It serves different users with different information according to the user's interest it gets. There are two kinds of important applications of Personalized Information Services, personalized recommendations and personalized information retrieval. This paper designs a personalized information service system based on user interest model, after doing a lot of study and research work on relevant field. This system establishes user interest model by collecting user information and fuzzy cluster analysis; presents nearest neighbor recommendation algorithm combined of personalized recommendation and user interest model; Adopts a strategy of query expansion and personalized sort in personalized Search. Experiments prove that the algorithm and strategy presented in this paper has high practicability.