Subsequence Matching of Stream Synopses under the Time Warping Distance

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.

• Type: Conference
• Year: 2010
• Where: PAKDD
• Authors: Su-Chen Lin, Mi-Yen Yeh, Ming-Syan Chen
• Keywords: Data Mining, Dynamic Time Warping, Dynamic Warping Distance, PAKDD 2010, Warping Distance