An Improved Algorithm for Time-Series Pattern Discovery
Gongde Guo · Journal of Zhangzhou Normal University · 2011
A significant topic of time series data mining is to discover time-series patterns in time series database effectively.An improved effective algorithm for time-series pattern discovery is proposed in this paper.It divides a given sequence into several subsequences of the same length,and then a key-point series is extracted from each subsequence by using a segmentation algorithm based on key points,only retaining the main key points which reflect its changing patterns.Separate each subsequence by its key-point series,and then distribute their key-point series into a set of boxes according to ups and downs,so that only those in the same box are possibly similar,while those in the different boxes are not.Finally all the time-series patterns will be discovered by computing Dynamic Time Warping distance between any two key-point series in each box.Experimental results show the effectiveness of the proposed algorithm.