点击次数：

论文类型：会议论文

发表时间：2011-07-29

收录刊物：EI、CPCI-S、Scopus

卷号：255-260

页面范围：2267-2271

关键字：Data Mining; Time Series; Dynamic Time Wrapping; Lower Bounding Distance

摘要：Dynamic time warping(DTW) distance is the most effective similarity measurement methods in time-series data mining area. Because of the high computational complexity of DTW, it is not suitable for huge amounts of data. Thus, some DTW distance lower bound methods are proposed, which can improve the efficiency of DTW distance calculation. In this paper, we summarized the existing lower bound of DTW method and then proposed a closely related field with the application and exacted Lower Bounding distance measure with Segmentation(eLBS). Experiment results show that this method meet the need of non-omission.