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Pattern discovery and change detection of online music query streams

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Abstract

Mining of music data is one of the most important problems in multimedia data mining. In this paper, two research issues of mining music data, i.e., online mining of music query streams and change detection of music query streams, are discussed. First, we proposed an efficient online algorithm, FTP-stream (Frequent Temporal Pattern mining of streams), to mine all frequent melody structures over sliding windows of music melody sequence streams. An effective bit-sequence representation is used in the proposed algorithm to reduce the time and memory needed to slide the windows. An effective list structure is developed in the FTP-stream algorithm to overcome the performance bottleneck of 2-candidate generation. Experiments show that the proposed algorithm FTP-stream only needs a half of memory requirement of original melody sequence data, and just scans the music query stream once. After mining frequent melody structures, we developed a simple online algorithm, MQS-change (changes of Music Query Streams), to detect the changes of frequent melody structures in current user-centered music query streams. Two music melody structures (set of chord-sets and string of chord-sets) are maintained and four melody structure changes (positive burst, negative burst, increasing change and decreasing change) are monitored in a new summary data structure, MSC-list (a list of Music Structure Changes). Experiments show that the MQS-change algorithm is an effective online method to detect the changes of music melody structures over continuous music query streams.

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Acknowledgements

The authors thank the reviewers’ precious comments for improving the quality of the paper. We would like to thank Dr. Yun Chi for contributing the source codes of Moment algorithm (MomentFP). The research is supported in part by the National Science Council, Project No. NSC 96-2218-E-424-001-, Taiwan, Republic of China.

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  1. Department of Computer Science, Kainan University, Taoyuan, Taiwan

    Hua-Fu Li

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  1. Hua-Fu Li
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Correspondence to Hua-Fu Li.

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Li, HF. Pattern discovery and change detection of online music query streams. Multimed Tools Appl 41, 287–304 (2009). https://doi.org/10.1007/s11042-008-0229-9

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  • DOI: https://doi.org/10.1007/s11042-008-0229-9

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