Using jWebMiner 2.0 to Improve Music Classification Performance by Combining Different Types of Features Mined from the Web

This paper presents the jWebMiner 2.0 cultural feature extraction software and describes the results of several musical genre classification experiments performed with it. jWebMiner 2.0 is an easy-to-use and open-source tool that allows users to mine the Internet in order to extract features based on both Last.fm social tags and general web search string co-occurrences extracted using the Yahoo! API. The experiments performed found that the features based on social tags were more effective at classifying music into a small (5-genre) genre ontology, but the features based on general web co-occurrences were more effective at classifying a moderate (10-genre) ontology. It was also found that combining the two types of features resulted in improved performance overall.