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arXiv · 1805.06757

Matching Consecutive Subpatterns Over Streaming Time Series

Rong Kang·Chen Wang·Peng Wang·Yuting Ding·Jianmin Wang
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Abstract

Pattern matching of streaming time series with lower latency under limited computing resource comes to a critical problem, especially as the growth of Industry 4.0 and Industry Internet of Things. However, against traditional single pattern matching model, a pattern may contain multiple subpatterns representing different physical meanings in the real world. Hence, we formulate a new problem, called "consecutive subpatterns matching", which allows users to specify a pattern containing several consecutive subpatterns with various specified thresholds. We propose a novel representation Equal-Length Block (ELB) together with two efficient implementations, which work very well under all Lp-Norms without false dismissals. Extensive experiments are performed on synthetic and real-world datasets to illustrate that our approach outperforms the brute-force method and MSM, a multi-step filter mechanism over the multi-scaled representation by orders of magnitude.

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Rong Kang, Chen Wang, Peng Wang, Yuting Ding, Jianmin Wang. 2018-05-17. Matching Consecutive Subpatterns Over Streaming Time Series. https://arxiv.org/abs/1805.06757

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