DocumentCode :
577620
Title :
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
Link To Document :
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