A Classification Framework for Similar Music Search

Abstract

This paper has concentrated on how to retrieve a list of songs from music database similar to the specific one. Content-based retrieval of music is one of the most popular research subjects, which mostly focuses on querying the exactly one from database by humming a tune or submitting a recording of music. However, getting some songs similar to, but not exactly the given one could be also interested by people. In this paper, we propose a classification framework to solve this problem using string-based methods. Introducing string-based similarity measure, our framework has lower computational complexity and better effect. We also developed a new distributed clustering algorithm under MapReduce framework, which performed well for massive audio data. Experiments are performed and analyzed to show the efficiency and the effectiveness of our proposed framework.