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Personalized information service agents have emerged in the recent years to help users to cope with the increasing amount of information available on the Internet. The effectiveness of agents depends mainly on profile completeness and accuracy. In the existing agents, although the performance of these systems improves after learning a user profile, it is difficult to share user profile and adapt user profile to user interests. In order to solve these problems in agents, we present ontology based user profiling methods. The approaches in user profiling, such as representation, acquisition, learning, adaptation and re-ranking, are discussed. Moreover, a personalized information service agent is designed based on these approaches, and the performance of agent is evaluated.