Personalized music recommendation algorithm based on tag information

With the development of the mobile Internet and streaming media technology, digital music has been accepted by many people. However, in the face of the massive music data on the Internet, users want to find favorite music is like looking for a needle in a haystack via traditional music indexing techniques. In this paper, an improved algorithm for personalized music recommendation based on tag information is proposed. Firstly, we use the improved user-based collaborative filtering algorithm to deal with the user's long-term preferences. Secondly, according to the user-tag-music relationships, getting the music that associated with the user via recommendation algorithm based on bipartite graph. Experiments on real dataset demonstrate the efficiency and effectiveness of the improved algorithm, getting better results and have practical significance.