Research on recommendation system based on interest clustering
Yunfei Yu, Yinghua Zhou · AIP conference proceedings · 2017
Traditional collaborative filtering algorithm does not take into account the user’s interest factors, at the same time, it has the problem of sparse data, poor scalability and so on, which directly affects the quality of the recommendation. This paper proposes a collaborative filtering recommendation algorithm based on user interest clustering. Firstly, according to the user’s existing score, a method is used to compute the interest degree of the user. Secondly, a clustering algorithm is used to divide the users into clusters. Finally, a collaborative filtering algorithm is used to recommend movie, it effectively improves data sparsity and real-time of problem. The experimental results exhibit that the proposed algorithm shows a great improvement in the recommendation accuracy.