计算机工程与应用2012，Vol.48Issue(33)：162-166,202,6.DOI:10.3778/j.issn.1002-8331.1206-0440
基于特征点分段的多元时间序列相似性搜索
Similarity search algorithm for multivariate time series based on feature points
摘要
Abstract
A variety of methods for matching multivariate time series can not measure similarity accurately and efficiently at the same time. This paper proposes a similarity search algorithm by segmentation based on special points of multivariate time series. It extracts the feature points, by which it segments the multivariate time series, and then transforms them into pattern sequences, thus the global shape characteristics of the original sequences can be retained. It makes the similarity search with the hierarchical matching method. The experimental results show that this method can effectively portray the global shape features of the sequences, retain local similarity matching by hierarchical matching, and improve the accuracy of the search at the same time.关键词
多元时间序列/分段/相似性搜索/特征点/分层Key words
multivariate time series/ segment/ similarity search/ feature points/ hierarchy分类
信息技术与安全科学引用本文复制引用
王燕,马倩倩,韩萌..基于特征点分段的多元时间序列相似性搜索[J].计算机工程与应用,2012,48(33):162-166,202,6.基金项目
甘肃省自然科学基金(No.1014RJZA009,No.1112RJZA029) （No.1014RJZA009,No.1112RJZA029）
甘肃省高等学校基本科研业务费项目(No.1114ZTC144). （No.1114ZTC144）
