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Long Beach, CA, USA
Mar. 1, 2010 to Mar. 6, 2010
ISBN: 978-1-4244-5445-7
pp: 101-104
Machiko Toyoda , NTT Information Sharing Platform laboratories, Graduate School of Information Science, Nagoya University, Japan
Yasushi Sakurai , NTT Communication Science laboratories, Japan
ABSTRACT
In this paper, we focus on the problem of finding partial similarity between data streams. Our solution relies on dynamic time warping (DTW) as a similarity measure, which computes the distance between sequences whose lengths and/or sampling rates are different. Instead of straightforwardly using DTW that requires a high computation cost, we propose a streaming method that efficiently detects partial similarity between sequences. Our experiments demonstrate that our method detects pairs of optimal subsequences correctly and that it significantly reduces resources in terms of time and space.
CITATION
Machiko Toyoda, Yasushi Sakurai, "Discovery of cross-similarity in data streams", ICDE, 2010, 2013 IEEE 29th International Conference on Data Engineering (ICDE), 2013 IEEE 29th International Conference on Data Engineering (ICDE) 2010, pp. 101-104, doi:10.1109/ICDE.2010.5447927
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