Non-overlapping Subsequence Matching of Stream Synopses

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Abstract—In this paper, we propose SUbsequence Matching framework with cell MERgence (SUMMER) for online subsequence matching between histogram-based stream synopsis structures under the dynamic time warping distance. Given a query synopsis pattern, SUMMER continuously identi?es all the matching subsequences for a stream as the bins are generated. To effectively reduce the computation time, we design a Weighted Dynamic Time Warping (WDTW) algorithm, which computes the warping distance directly between two histogram-based synopses. Furthermore, a Stack-based Overlapping Filter Algorithm (SOFA) is provided to remove the overlapping subsequences to avoid the redundant information. Finally, we design an optional re?nement module to relax the subsequence range limit and improve the matching accuracy. Our experiments on real datasets show that the proposed method signi?cantly speeds up the pattern matching without compromising the accuracy required when compared with other approaches.

3 years ago


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