An automatic music classification method based on users' comments is presented in view of the few categories and limited search content for the existing music platforms. First of all, a linear CRF statistic segmentation model, n-gram word extraction and affinity analysis method are used to obtain a dictionary which can be adapted to music corpus segmentation. Secondly, we use linear CRF model to segment comments with dictionary above, and then we correct the segmentation result via split-merge testing. Thirdly, the optimized TFIDF keyword extraction model is applied to extract candidate tags, and we merge tags after that. Fourthly, candidate tags with fewer frequency are filtered from a global perspective. Finally, a probability classification network is established between the music and filtered tags to classify music. As the result shows, our music classification method achieves high accuracy. Furthermore, it can ensure the personality of music retrieval for generating music tags automatically in multiple dimensions according to users' comments.