An Algorithm based on piecewise slope transformation distance for short time series similarity measure

Author

Huimin Li ; Liying Fang ; Pu Wang ; Jingwei Liu

Author_Institution

Coll. of Electron. Inf. & Control Eng., Beijing Univ. of Technol., Beijing, China

fYear

2012

fDate

6-8 July 2012

Firstpage

691

Lastpage

695

Abstract

Aiming at the irregular and uneven feature of medical time series data, a novel algorithm based on piecewise slope transformation distance for short time series similarity measure is propose. We firstly do some preprocess based on algorithm for key points selected, make the data curve to zigzag shape, then, we measure the distance between two curves based on piecewise slope transformation algorithm. By experiments, conclusion can be draw that this new approach can measure distance rapidly and correctly, especially appropriate to short time series data.

Keywords

data mining; medical information systems; time series; data curve; medical time series data; piecewise slope transformation distance; short time series data; short time series similarity measure; uneven feature; zigzag shape; Data mining; Euclidean distance; Market research; Shape; Shape measurement; Time measurement; Time series analysis; Data Mining; Piecewise Slope Transformation Distance; Short Time Series; Similarity Measure;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation (WCICA), 2012 10th World Congress on

Conference_Location

Beijing

Print_ISBN

978-1-4673-1397-1

Type

conf

DOI

10.1109/WCICA.2012.6357966

Filename

6357966