A Graph-Based Method for Playlist Generation

Abstract. The advance of online music libraries has increased the im-portance of recommendation systems. The task of automatic playlist generation naturally arises as an interesting approach to this problem. Most of existing applications use some similarity criterion between the songs or are based on manual user interaction. In this work, we pro-pose a novel algorithm for automatic playlist generation based on paths in Minimum Spanning Trees (MST’s) of music networks. A motivation is to incorporate the relationship between music genres and expression of emotions by capturing the presence of temporal rhythmic patterns. One of the major advantages of the proposed method is the use of edge weights in the searching process (maximizing the similarity between sub-sequent songs), while Breadth-First (BF) and Depth-First (DF) search algorithms assume the hypothesis that all the songs are equidistant