Efficient feature mining in music objects

Jia Ling Koh, William D.C. Yu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)


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.

Original languageEnglish
Title of host publicationDatabase and Expert Systems Applications - 12th International Conference, DEXA 2001, Proceedings
EditorsHeinrich C. Mayr, Jiri Lazansky, Gerald Quirchmayr, Pavel Vogel
PublisherSpringer Verlag
Number of pages11
ISBN (Print)3540425276, 9783540425274
Publication statusPublished - 2001
Event12th International Conference on Database and Expert Systems Applications, DEXA 2001 - Munich, Germany
Duration: 2001 Sept 32001 Sept 5

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other12th International Conference on Database and Expert Systems Applications, DEXA 2001

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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