Adaptive User Profiling for Personalized Information Retrieval

Many search engines such as Yahoo, Google, MSN, and AltaVista, are developed to meet users' needs, but they not satisfy the various users' needs in real world. In general, because of the lack of the personal information such as hobby, preference, and interest, these existing information retrieval systems are unsuitable to provide personalized search results to users. In this paper, we propose an adaptive user profile method using dynamic updating policy considering the change of the users' preferences over time and domain. Moreover, we will employ collaborative filtering method to apply the situation that users' preferences are frequently or continuously changed. The purpose of this paper is improvement of personalized search performance for each user through automatic creation, maintenance, and personalization of user preference profiles that include search pattern for each user. By using this user profile, our system can provide more personalized search results to users.