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A robust approach to subsequence matching

A robust approach to subsequence matching

Zheng, Aihua, Ma, Jixin, Petridis, Miltos, Tang, Jin and Luo, Bin (2009) A robust approach to subsequence matching. In: Lee, Roger and Ishii, Naohiro, (eds.) Software Engineering Research, Management and Applications 2009. Studies in Computational Intelligence (253). Springer-Verlag, Berlin / Heidelberg, Germany, pp. 39-49. ISBN 9783642054402 (doi:10.1007/978-3-642-05441-9_4)

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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.

Item Type: Book Section
Additional Information: [1] This paper was presented at the 7th ACIS International Conference on Software Engineering Research, Management and Applications (SERA 2009), held 2-4 December 2009, in Haikou, China. Subsequently, the best 25 papers - including this paper - were selected and published in the book, "Software Engineering Research, Management and Applications 2009." [2] ISBN: 978-3-642-05440-2 (Hardcover), 978-3-642-26110-7 (Softcover), 978-3-642-05441-9 (eBook). Book Series ISSN: 1860-949X (Print) 1860-9503 (Online).
Uncontrolled Keywords: time theory, time-series, state-sequences, subsequence matching, similarity model
Subjects: Q Science > QA Mathematics
Faculty / Department / Research Group: Faculty of Architecture, Computing & Humanities
Related URLs:
Last Modified: 14 Oct 2016 09:05
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
URI: http://gala.gre.ac.uk/id/eprint/1865

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