在线分割时间序列数据

Vol.15, No.11 1000-9825/2004/15(11)1671

?2004 Journal of Software 软件学报

在线分割时间序列数据?

李爱国1,2+, 覃征2

1(西安科技大学计算机科学技术系,陕西西安 710054)

2(西安交通大学计算机科学技术系,陕西西安 710049)

On-Line Segmentation of Time-Series Data

LI Ai-Guo1,2+, QIN Zheng2

1(Department of Computer Science and Technology, Xi’an University of Science and Technology, Xi’an 710054, China)

2(Department of Computer Science and Technology, Xi’an Jiaotong University, Xi’an 710049, China)

+ Corresponding author: Phn: +86-29-82663979, E-mail: liag@https://www.wendangku.net/doc/d5238949.html,

Received 2003-07-02; Accepted 2004-02-05

Li AG, Qin Z. On-Line segmentation time-series data. Journal of Software, 2004,15(11):1671~1679.

https://www.wendangku.net/doc/d5238949.html,/1000-9825/15/1671.htm

Abstract: Segmentation of time series is one of the important tasks in time series data mining. Segmentation has two major uses: It may be performed either to detect when the system that creates the time series has changed or to create a high level representation of the time series for indexing, clustering, and classification. Approaches to on-line segmentation of time series are necessary when identifying and predicting temporal patterns in real-time time series databases are needed, and this is the focus of this paper. A formal description of segmenting time series problem and a criterion for the evolution of segmentation algorithms are presented. An on-line iterative algorithm of segmenting time series, called OLS (on-line segmentation), is then proposed. OLS is independent of a priori knowledge about the segmented time series. Experimental results demonstrate that OLS can on-line detect the critical change points of time series with less ‘over fit’ than that of competitive algorithms.

Key words: data mining; knowledge acquisition; time series; segmentation

摘 要: 时间序列分割是时间序列数据挖掘研究的重要任务之一.它主要有两个应用:检测生成时间序列的系统何时发生变化;创建时间序列的高级数据表示,从而对时间序列进行索引

），男,甘肃张掖人,博士,副教授,主要研究领域为机器学习,数据挖掘,信息融合;覃征(1956