用基于移动均值的索引实现时间序列相似查询  

Similarity Search of Time Series with Moving Average Based Indexing

作　　者：林子雨[1] 杨冬青[1] 王腾蛟[1] 

机构地区：[1]北京大学高可信软件技术教育部重点实验室

出　　处：《软件学报》2008年第9期2349-2361,共13页Journal of Software

基　　金：国家自然科学基金;国家高技术研究与发展计划(863)~~

摘　　要：提出了基于移动均值的索引来解决子序列匹配中的“ε-查询”问题：提出并证明了基于移动均值的缩距定理和缩距比关系定理，后者具有很好的“裁减”能力，可以在相似查询时淘汰大部分不符合条件的候选时间序列，从而达到快速相似查找的目的引入了由Jagadish等人提出的BATON^＊-树，并在此基础上适当修改，建立了MABI索引，极大地加快了相似查询过程；最后，在一个股票交易数据集上进行了实验，证明了MABI索引的良好性能．In this paper, a method called MABI （moving average based indexing） is proposed to effectively deal with the issue of ε-search query in subsequence matching. Two important theorems, distance reduction theorem and DRR（distance reduction rate） relation theorem, are proposed here to be as the basis of MABL DRR relation theorem has strong capability in ＂pruning＂ those unqualified candidate sequences so as to achieve of fast similarity search. Furthermore, by modifying BATON＊ introduced by Jagadish, et aL, a multi-way balanced tree structure is introduced, to construct the index from time series, experiments over a stock exchange dataset show that which significantly speeds up the similarity search. Extensive MABI can achieve desirable performance

关 键 词：相似查询 子序列匹配 移动均值 时间序列数据库 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]