Clustering time series with Granular Dynamic Time Warping method

被引：17
|
作者：
Yu, Fusheng [1 ]
Dong, Keqiang [1 ]
Chen, Fei [1 ]
Jiang, Yongke [1 ]
Zeng, Wenyi [2 ]
机构：
[1] Beijing Normal Univ, Sch Math Sci, Beijing 100875, Peoples R China
[2] Beijing Normal Univ, Dept Math, Beijing 100875, Peoples R China
来源：
GRC: 2007 IEEE INTERNATIONAL CONFERENCE ON GRANULAR COMPUTING, PROCEEDINGS | 2007年
关键词：
D O I：
10.1109/GrC.2007.34
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, a new method, named Granular Dynamic Time Warping is proposed. This method is based on the granular approach of information granulation and has the characteristics of Dynamic Time Warping approach. Thus it can be used to cluster time series with different lengths on the granular level. To cluster time series, this method first builds the corresponding granular time series, and then does the clustering on the granular time series. With this method, higher efficiency will be achieved in clustering time series, which is a goal pursued in clustering of large amount of time series. We also illustrate the prior performance of the new method with experiments.
引用
收藏
页码：393 / +
页数：2
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