Automatic music style classification is an important, but challenging problem in music information retrieval. It has a number of applications, such as indexing of and searching in musical databases. Traditional music style classification approaches usually assume that each piece of music has a unique style and they make use of the music contents to construct a classifier for classifying each piece into its unique style. However, in reality, a piece may match more than one, even several different styles. Also, in this modern Web 2.0 era, it is easy to get a hold of additional, indirect information (e.g., music tags) about music. This paper proposes a multi-label music style classification approach, called Hypergraph integrated Support Vector Machine (HiSVM), which can integrate both music contents and music tags for automatic music style classification. Experimental results based on a real world data set are presented to demonstrate the effectiveness of the method.