一种改进的Item-based协同过滤推荐算法

分析了协同过滤推荐系统中存在的用户多兴趣和项目多内容问题，提出了一种基于项的协同过滤改进算法，算法综合考虑了项目自身属性和用户评价的影响。试验表明该算法有效的解决了用户的多兴趣和项目的多内容问题，并且在用户评分数据比较稀疏的情况下也能有较好的推荐精度。

An Improved Item-Based Collaborative Filtering Algorithm

Based on an analysis of the problems of multiple interests of the user and multiple contents of the item existing in the collaborative filtering recommendation system, an improved item-based collaborative filtering algorithm is proposed. This new algorithm takes synthetically into account the influence of item attributes and user ratings. Experimental results indicate that the algorithm can satisfactorily solve the problems of multiple interests of the user and multiple contents of the item and provide better recommendation results even if the user ratings are very sparse.