时间序列数据挖掘中的特征表示与相似性度量方法研究分析  

Research and Analysis on Feature Representation and Similarity Measurement Methods in Time Series Data Mining

作　　者：王培屹 WANG Pei-yi(Zhengzhou Preschool Education College,Zhengzhou 450000,Henan)

机构地区：[1]郑州幼儿师范高等专科学校,河南郑州450000

出　　处：《电脑与电信》2018年第6期54-56,68,共4页Computer & Telecommunication

摘　　要：随着信息技术的快速发展,时间序列的数据量增长速度也逐步加快。与此同时,数据挖掘技术在时间序列数据库中的应用也越来越普遍。通过将把相同长度和不同长度的时间序列作为对象进行深入的研究,探讨各种表示方法的内涵与特征,使这些表示方法更加完善以及更好地应用于时间序列数据的挖掘工作中,从而能够更加方便有效地获取有价值的信息。With the rapid development of information technology,the data volume growth rate of time series has gradually accelerated.At the same time,the application of data mining technology in the time series database is also more and more common.Through in-depth study of time series of the same length and different lengths as objects,the connotation and characteristics of various representation methods are discussed,making these representation methods more perfect and better applied to time series data mining work.

关 键 词：时间序列 数据挖掘 特征表示 度量方法 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论]