Subsequence Matching of Stream Synopses under the Time Warping Distance

نویسندگان

  • Su-Chen Lin
  • Mi-Yen Yeh
  • Ming-Syan Chen
چکیده

In this paper, we propose a method for online subsequence matching between histogram-based stream synopsis structures under the dynamic warping distance. Given a query synopsis pattern, the work continuously identifies all the matching subsequences for a stream as the histograms 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. Our experiments on real datasets show that the proposed method significantly speeds up the pattern matching by sacrificing a little accuracy.

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تاریخ انتشار 2010