A robust approach to subsequence matching
Zheng, Aihua, Ma, Jixin, Petridis, Miltos, Tang, Jin and Luo, Bin (2010) A robust approach to subsequence matching. In: Software Engineering Research, Management and Applications 2009. Studies in Computational Intelligence (253). Springer-Verlag, Berlin / Heidelberg, Germany, pp. 39-49. ISBN 9783642054402 ISSN 1860-949X (Print) 1860-9503 (Online) (doi:10.1007/978-3-642-05441-9_4)Full text not available from this repository.
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:|| 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."  ISBN: 978-3-642-05440-2 (Hardcover), 978-3-642-26110-7 (Softcover), 978-3-642-05441-9 (eBook).|
|Uncontrolled Keywords:||time theory, time-series, state-sequences, subsequence matching, similarity model|
|Subjects:||Q Science > QA Mathematics|
|School / Department / Research Groups:||School of Computing & Mathematical Sciences|
School of Computing & Mathematical Sciences > Computer & Computational Science Research Group
School of Computing & Mathematical Sciences > Department of Computer Science
|Last Modified:||27 Mar 2013 11:42|
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