基于时间序列相似性聚类的应用研究综述

Summaly of application research based on clustering of time series similarity

在综合分析近年来时间序列数据挖掘相关文献的基础上从时间序列分割、相似性度量、时间序列聚类等方面对时间序列数据挖掘进行了综述,简要分析了基于时间序列相似性聚类的研究现状,对比较流行的算法进行了比较分析,对当前一些未解决的问题进行了简要介绍,并在此基础上对未来的发展趋势进行了展望,为研究者了解最新的基于时间序列相似性聚类研究动态、新技术及发展趋势提供了参考。

On the basis of a comprehensive analysis of the recent years relevant literature of time series data mining,time-series data mining such as the division of time series,similarity measure,clustering are reviewed.The current state of research of cluster based on time series similarity are analyzed briefly a brief analysis.Current research topics are briefly described.The popular algorithms have been a comparative analysis.Based on a brief introduction of some unresolved issues,the future development trend is outlook.The aim is to put forward reference for scholars who research development,new techniques and trends of time series data mining.