A music recommendation algorithm based on hybrid collaborative filtering technique

Abstract

With the rapid development of e-commerce, the recommendation system is becoming increasingly important. The collaborative filtering algorithm is one of the most successful algorithms in recommendation system. However, users’ preference and application scenarios play a significant role in determining the effect of these algorithms. Therefore, we propose a method to fusion itembased and user-based collaborative filtering algorithms into a hybrid one, we also consider time as a property and design a method to evaluate the rank of items. Last, the Movielens and real-world data-set are used to evaluate the recall and efficient of the algorithm in this paper.