Incrementally mining temporal patterns in interval-based databases

Yi Cheng Chen, Julia Tzu Ya Weng, Jun Zhe Wang, Chien Li Chou, Jiun-Long Huang, Suh Yin Lee

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

1 Scopus citations

Abstract

In several applications, sequence databases generally update incrementally with time. Obviously, it is impractical and inefficient to re-mine sequential patterns from scratch every time a number of new sequences are added into the database. Some recent studies have focused on mining sequential patterns in an incremental manner; however, most of them only considered patterns extracted from time point-based data. In this paper, we proposed an efficient algorithm, Inc-TPMiner, to incrementally mine sequential patterns from interval-based data. We also employ some optimization techniques to reduce the search space effectively. The experimental results indicate that Inc-TPMiner is efficient in execution time and possesses scalability. Finally, we show the practicability of incremental mining of interval-based sequential patterns on real datasets.

Original languageEnglish
Title of host publicationDSAA 2014 - Proceedings of the 2014 IEEE International Conference on Data Science and Advanced Analytics
EditorsGeorge Karypis, Longbing Cao, Wei Wang, Irwin King
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages304-311
Number of pages8
ISBN (Electronic)9781479969913
DOIs
StatePublished - 10 Mar 2014
Event2014 IEEE International Conference on Data Science and Advanced Analytics, DSAA 2014 - Shanghai, China
Duration: 30 Oct 20141 Nov 2014

Publication series

NameDSAA 2014 - Proceedings of the 2014 IEEE International Conference on Data Science and Advanced Analytics

Conference

Conference2014 IEEE International Conference on Data Science and Advanced Analytics, DSAA 2014
CountryChina
CityShanghai
Period30/10/141/11/14

Keywords

  • dynamic representation
  • incremental mining
  • interval-based pattern
  • sequential pattern mining

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  • Cite this

    Chen, Y. C., Weng, J. T. Y., Wang, J. Z., Chou, C. L., Huang, J-L., & Lee, S. Y. (2014). Incrementally mining temporal patterns in interval-based databases. In G. Karypis, L. Cao, W. Wang, & I. King (Eds.), DSAA 2014 - Proceedings of the 2014 IEEE International Conference on Data Science and Advanced Analytics (pp. 304-311). [7058089] (DSAA 2014 - Proceedings of the 2014 IEEE International Conference on Data Science and Advanced Analytics). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/DSAA.2014.7058089