Fusion Knowledge Graph and Collaborative Filtering Recommendation Algorithm

Abstract

The influence of data sparse, the collaborative filtering recommendation algorithm has the problem of inaccurate recommendation.Therefore, this paper proposes a collaborative filtering algorithm that fuses knowledge graph.By introducing rich content information of items into the item-based collaborative filtering algorithm, this algorithm effectively makes up for the fact that the collaborative filtering algorithm ignores the content information of items.Experiments show that the algorithm is better than the original algorithm to some extent, so as to alleviate the problem of data sparse.