A robust approach to subsequence matching

A. Zheng, J. Ma, Miltiadis Petridis, J. Tang, B. Luo

Research output: Chapter in Book/Conference proceeding with ISSN or ISBNChapter

Abstract

In terms of a general time theory which addresses time-elements as typed point-based intervals, a formal characterization of time-series and state-sequences is introduced. Based on this framework, the subsequence matching problem is specially tackled by means of being transferred into bipartite graph matching problem. Then a hybrid similarity model with high tolerance of inversion, crossover and noise is proposed for matching the corresponding bipartite graphs involving both temporal and non-temporal measurements. Experimental results on reconstructed time-series data from UCI KDD Archive demonstrate that such an approach is more effective comparing with the traditional similarity model based algorithms, promising robust techniques for lager time-series databases and real-life applications such as Content-based Video Retrieval (CBVR), etc.
Original languageEnglish
Title of host publicationSoftware Engineering Research, Management and Applications
EditorsR. Lee, N. Ishii
Place of PublicationBerlin Heidelberg
PublisherSpringer
Pages39-49
Number of pages11
Volume253
ISBN (Electronic)9783642054419
ISBN (Print)9783642054402
Publication statusPublished - 2009

Publication series

NameStudies in Computational Intelligence

Fingerprint Dive into the research topics of 'A robust approach to subsequence matching'. Together they form a unique fingerprint.

  • Cite this

    Zheng, A., Ma, J., Petridis, M., Tang, J., & Luo, B. (2009). A robust approach to subsequence matching. In R. Lee, & N. Ishii (Eds.), Software Engineering Research, Management and Applications (Vol. 253, pp. 39-49). (Studies in Computational Intelligence). Springer.