关键词: 协同过滤, 推荐算法, 意象标签, 双矩阵模型, 点赞行为

Abstract: The low accuracy problem for recommendation is a great challenge in traditional Collaborative Filtering（CF） algorithm. And there is difficulty to recommend new items for this method. So this paper introduces Kansei tags which is different from the existing tags in other platforms as a bridge between users and items and proposes a double-matrix model based on CF algorithm. Then using the praise pointing activity of users to complete this method. As a result, the experimental result shows that these two methods can significantly expand the recommending range and the completed method which contains the praise pointing behaviors can effectively improve the accuracy of recommendation.

Key words: Collaborative Filtering（CF）, recommendation algorithm, Kansei tags, double-matrix model, praise pointing