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.
National Natural Science Foundation of China under Grant No.61170007; National Major Research Plan of Chinese Infrastructure Software under Grant No.2010ZX01042-002-003-004.
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Zeng, J., He, Z., Wang, W., Huang, H. (2012). A Classification Framework for Similar Music Search. In: Bao, Z., et al. Web-Age Information Management. WAIM 2012. Lecture Notes in Computer Science, vol 7419. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33050-6_24
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DOI: https://doi.org/10.1007/978-3-642-33050-6_24
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