Discovering Patterns from Large and Dynamic Sequential Data
Journal of Intelligent Information Systems
Efficiently mining long patterns from databases
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Efficient repeating pattern finding in music databases
Proceedings of the seventh international conference on Information and knowledge management
Data Mining: An Overview from a Database Perspective
IEEE Transactions on Knowledge and Data Engineering
Discovering Frequent Event Patterns with Multiple Granularities in Time Sequences
IEEE Transactions on Knowledge and Data Engineering
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Efficient Theme and Non-Trivial Repeating Pattern Discovering in Music Databases
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
An efficient approach for mining top-k fault-tolerant repeating patterns
DASFAA'06 Proceedings of the 11th international conference on Database Systems for Advanced Applications
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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.