计算机工程与应用2016，Vol.52Issue(19)：12-18,7.DOI:10.3778/j.issn.1002-8331.1603-0331
基于互相关的二阶段时间序列聚类方法
Two-step clustering method of time series clustering based on cross-correlation
摘要
Abstract
Based on cross-correlation, an efficient, fast method is proposed for time series clustering and the time series clustering is realized by a two steps measure. The first step is based on symbolic of time series and extracts the characteristic time period by designing a characteristic extraction algorithm. The second step is based on cross-correlation, which realizes a faster time series clustering by adjusting the cross-correlation step. The experiments show that this method can fit sparse and dense time series data extraction. Comparing with traditional clustering distance measure, this method has high pro-cessing speed and can perform better on the stretch of time series shape. Meanwhile, this method keeps the accuracy in a high degree.关键词
时间序列聚类/特征时间段抽取/互相关函数Key words
time series clustering/characteristic period extraction/cross-correlation分类
信息技术与安全科学引用本文复制引用
高启航,杨卫东..基于互相关的二阶段时间序列聚类方法[J].计算机工程与应用,2016,52(19):12-18,7.基金项目
国家行业专项（No.CHINARE2015-04-07）；海洋公益项目（No.201405031-04）。 （）
