论文信息 - Content-Based Filtering Recommendation Algorithm Using HMM

Content-Based Filtering Recommendation Algorithm Using HMM

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.

Zhifang Liao | Fei Cai | Hui Li

[1] Joydeep Ghosh,et al. A Unified Framework for Model-based Clustering , 2003, J. Mach. Learn. Res..

[2] Lawrence R. Rabiner,et al. A tutorial on hidden Markov models and selected applications in speech recognition , 1989, Proc. IEEE.

[3] David Bawden,et al. Perspectives on information overload , 1999 .

[4] Gediminas Adomavicius,et al. Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions , 2005, IEEE Transactions on Knowledge and Data Engineering.