Abstract

We propose methods for unsupervised learning of text profiles for music from unstructured text obtained from the web. The profiles can be used for classification, recommendation, and understanding, and may be used in conjunction with existing methods such as audio analysis and collaborative filtering to improve performance. A formal method for analyzing the quality of the learned profiles is given, and results indicate that they perform well when used to find similar artists. 1

Citations