Abstract
Joining two time series in their similar subsequences of arbitrary length provides useful information about the synchronization of the time series. In this work, we present an efficient method to subsequence join over time series based on segmentation and Dynamic Time Warping (DTW) measure. Our method consists of two steps: time series segmentation which employs important extreme points and subsequence matching which is a nested loop using sliding window and DTW measure to find all the matching subsequences in the two time series. Experimental results on ten benchmark datasets demonstrate the effectiveness and efficiency of our proposed method and also show that the method can approximately guarantee the commutative property of this join operation.
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Vinh, V.D., Anh, D.T. (2016). Efficient Subsequence Join Over Time Series Under Dynamic Time Warping. In: Król, D., Madeyski, L., Nguyen, N. (eds) Recent Developments in Intelligent Information and Database Systems. Studies in Computational Intelligence, vol 642. Springer, Cham. https://doi.org/10.1007/978-3-319-31277-4_4
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DOI: https://doi.org/10.1007/978-3-319-31277-4_4
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