Abstract
Music is to express emotions and interpreted by tags. Different emotion tags describe the same piece of music in different perspectives. This paper proposes a music retrieval algorithm which is based on the users’ emotion tags. First, we build a bi-partite graph, with tags on one side and music on the other, to compute the semantic similarity between the tags by T_SimRank. Second, we use the T_PageRank algorithm to get the music-popularity. Last, by taking the advantage of learning to rank, we combine many methods to get the final ranking results. Experimental results show that our method is better than the traditional cosine similarity and the Co_Tags similarity, and the fused method performs better than the single method.
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Li, J., Lin, H., Zhou, L. (2010). Emotion Tag Based Music Retrieval Algorithm. In: Cheng, PJ., Kan, MY., Lam, W., Nakov, P. (eds) Information Retrieval Technology. AIRS 2010. Lecture Notes in Computer Science, vol 6458. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17187-1_56
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DOI: https://doi.org/10.1007/978-3-642-17187-1_56
Publisher Name: Springer, Berlin, Heidelberg
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