EA_DTW: Early Abandon to Accelerate Exactly Warping Matching of Time Series

摘要：

Dynamic Time Warping (DTW) is one of the im- portant distance measures for time series, however,the exact calculation of DTW has become a bot-tleneck. We propose an approach, named Early Abandon DTW (EA DTW) to accelerate the cal-culation. We demonstrate the idea of early aban-don by theoretical analysis, and show the utili-ties of EA DTW by thorough experiments both on synthetic and real datasets. The results show,EA DTW outperforms the dynamic DTW calcula-tion in the light of process time, and is much bet-ter when the threshold is below the real DTW dis-tance.

关键词： Data mining Time series Similarity search Dynamic time warping Early abandon

作者: Junkui Li Yuanzhen Wang

作者单位: College of Computer Science and Technology, Huazhong University of Science and Technology Wuhan 430074, China

会议类型: 国际会议

会议名称: The 2007 International Conference on Intelligent Systems and Knowledge Engineering(第二届智能系统与知识工程国际会议)

会议地点: 成都

会议语种:英文

页码: 211-218

在线出版日期: 2007-10-15（万方平台首次上网日期，不代表论文的发表时间）