In this paper, we combine probabilistic model and classical content-based filtering recommendation algorithms to propose a new algorithm for recommendation system, which we call content-based filtering recommendation algorithm using HMM. We utilize the HMM of recommended items to match user model and recommend items using user data. According to experiment result, this new method is more effective on describing a user's interest compared with the VSM-based algorithm.
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