基于信念网络的协同过滤图模型的推荐算法

摘要

信息检索模型现已应用于协同过滤算法。文中使用信息检索中的信念网络模型统一描述基于用户的协同过滤和基于项目的协同过滤，提出基于信念网络的协同过滤图模型的推荐算法。针对信念网络便于结合附加信息源的特性，将专家信息添加到协同过滤图模型中，为用户提供决策支持，以此解决推荐系统数据稀疏的问题。实验表明文中算法能提高推荐精度。%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.