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。
Based on key point technology,a new method for time series cluster was proposed. The 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 equidimensional. At last, the clustering time series were implemented by partitioning the complex network into communities. The experimental results show that the dimensions of time series and the consumption 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.
出处
《计算机科学》
CSCD
北大核心
2012年第3期157-159,173,共4页
Computer Science
基金
国家自然科学基金(10771092)
辽宁省博士启动基金(20081079)资助
关键词
时间序列
降维
关键点
复杂网络
聚类
Time series,Reduction dimension,Key point,Complex network,Cluster
