%0 Journal Article
%T Research of New Similarity Measure Method on Time Series Data<br>新型时间序列相似性度量方法研究
%A LIU Yi
%A BAO De-pei
%A YANG Ze-hong
%A ZHAO Yan-nan
%A JIA Pei-fa
%A WANG Jia-qin
%A <br>刘懿
%A 鲍德沛
%A 杨泽红
%A 赵雁南
%A 贾培发
%A 王家钦
%J 计算机应用研究
%D 2007
%I 
%X Based on the feature of symbolic time series data,a new similarity measure method (SAX Statistical Vector Space,SSVS)was cleatively brought. The stock data from the Standard & Poor 500 index was obtained, and the behavior of kinds of similarity measure methods in clustering research was compared.The experiment results showed that the new method could efficiently measure the similarity according to the whole trend by comparing with the classic methods.
%K time series
%K similarity measure
%K data mining
%K symbolic method<br>时间序列
%K 相似性度量
%K 数据挖掘
%K 符号化
%K 时间序列符号化
%K 相似性度量方法
%K 研究
%K Data
%K Time
%K Series
%K Method
%K Similarity
%K Measure
%K 前景
%K 应用
%K 意义
%K 趋势
%K 结果
%K 比较
%K 类实验
%K 股票数据
%K 指数
%K Statistical
%K Vector
%K Space
%K 向量空间法
%K 统计
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=EF4AD2E7BFCF0B30FF0792DECD0FF0E5&yid=A732AF04DDA03BB3&vid=B91E8C6D6FE990DB&iid=94C357A881DFC066&sid=4BB057F167CF3A60&eid=DDD31293A7C7D057&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=7