Abstract：Information retrieval model has been applied to the collaborative filtering algorithm now. The belief network model in information retrieval is used to describe user-based collaborative filtering and item-based collaborative filtering uniformly, and a recommendation algorithm of collaborative filtering graph model based on belief network is put forward. Due to the property that belief network is convenient to combine the information of additional sources, the expert information is added to the collaborative filtering model to provide decision support for the users, and consequently the data sparse problem of the recommendation system is solved. Experimental results show that the proposed algorithm improves the recommendation accuracy.
作者简介: 朱昆磊，男，1989年生，硕士研究生，主要研究方向为Web智能.E-mail:s201302176@emails.bjut.edu.cn. (ZHU Kunlei， born in 1989， master student. His research interests include web intelligence.) 黄佳进(通讯作者)，男，1977年生，博士，讲师，主要研究方向为Web智能.E-mail:hjj@emails.bjut.edu.cn. (HUANG Jiajin(Corresponding author)， born in 1977， Ph.D.， lecturer. His research interests include web intelligence.)
引用本文:
朱昆磊，黄佳进. 基于信念网络的协同过滤图模型的推荐算法*[J]. 模式识别与人工智能, 2016, 29(2): 171-176.
ZHU Kunlei, HUANG Jiajin. Recommendation Algorithm of Collaborative Filtering Graph Model Based on Belief Network. , 2016, 29(2): 171-176.
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