计算机科学 ›› 2012, Vol. 39 ›› Issue (3): 160-162.

• 数据库与数据挖掘 • 上一篇    下一篇

一种基于关键点的时间序列聚类算法

谢福鼎,李迎,孙岩,张永   

  1. (辽宁师范大学城市与环境学院 大连116029);(辽宁师范大学计算机与信息技术学院 大连116081)
  • 出版日期:2018-11-16 发布日期:2018-11-16

Cluster Algorithm for Time Series Based on Key Points

XIE Fu-ding,LI Ying,SUN Yan,ZHANG Yong   

  • Online:2018-11-16 Published:2018-11-16

摘要: 基于关键点技术,提出了一种新的时间序列聚类方法。算法首先寻找时间序列的关键点,将关键点序列进行等维处理后,通过计算关键点序列的相似性构造复杂网络,最后通过复杂网络的社团划分,实现时间序列的聚类。实验结果表明,在时间序列聚类过程中,本方法不仅可以有效降低时间序列的维数,加快聚类的速度,而且可以得到理想的聚类结果。

关键词: 时间序列,降维,关键点,复杂网络,聚类

Abstract: Based on key point technology, a new method for time series cluster was proposed. hhe key points for each time series were first found, and then the complex network was constructed by calculating the similarity between key point series after they were ectuidimensional. At last, the clustering time series were implemented by partitioning the complex network into communities. hhe experimental results show that the dimensions of time series and the consumplion of computing time can be effectively reduced by the proposal. Furthermore, the desired cluster result is obtained when applying this method to cluster some practical data.

Key words: Time series, Reduction dimension, Key point, Complex network, Cluster

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