Elastic Partial Matching of Time Series

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Elastic Partial Matching of Time Series
We consider a problem of elastic matching of time series. We propose an algorithm that automatically determines a subsequence b of a target time series b that best matches a query series a. In the proposed algorithm we map the problem of the best matching subsequence to the problem of a cheapest path in a DAG (directed acyclic graph). Our experimental results demonstrate that the proposed algorithm outperforms the commonly used Dynamic Time Warping in retrieval accuracy. 1 Motivation For many datasets we can easily and accurately extract the beginning and ending of patterns of interest. However in some domains it is non-trivial to define the exact beginning and ending of a pattern within a longer sequence. This is a problem because if the endpoints are incorrectly specified they can swamp the distance calculation in otherwise similar objects. For concreteness we will consider an example of just such a domain and show that Minimal Variance Matching (MVM), proposed in this paper, can b...
Longin Jan Latecki, Vasilis Megalooikonomou, Qiang
Added 28 Jun 2010
Updated 28 Jun 2010
Type Conference
Year 2005
Where PKDD
Authors Longin Jan Latecki, Vasilis Megalooikonomou, Qiang Wang, Rolf Lakämper, Chotirat (Ann) Ratanamahatana, Eamonn J. Keogh
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