Abstract
This paper proposes novel strategies for efficiently extracting repeating patterns and frequent note sequences in music objects. Based on bit stream representation, the bit index sequences are designed for representing the whole note sequence of a music object with little space requirement. Besides, the proposed algorithm counts the repeating frequency of a pattern efficiently to rapidly extracting repeating patterns in a music object. Moreover, with the assist of appearing bit sequences, another algorithm is proposed for verifying the frequent note sequences in a set of music objects efficiently. Experimental results demonstrate that the performance of the proposed approach is more efficient than the related works.
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© 2001 Springer-Verlag Berlin Heidelberg
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Koh, JL., Yu, W.D.C. (2001). Efficient Feature Mining in Music Objects. In: Mayr, H.C., Lazansky, J., Quirchmayr, G., Vogel, P. (eds) Database and Expert Systems Applications. DEXA 2001. Lecture Notes in Computer Science, vol 2113. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44759-8_23
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DOI: https://doi.org/10.1007/3-540-44759-8_23
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Online ISBN: 978-3-540-44759-7
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