A novel piecewise linear segmentation for time series

Author

Ding, Yongwei ; Yang, Xiaohu ; Kavs, Alexsander J. ; Li, Juefeng

Author_Institution

Coll. of Comput. Sci. & Technol., Zhejiang Univ., Hangzhou, China

Volume

4

fYear

2010

fDate

26-28 Feb. 2010

Firstpage

52

Lastpage

55

Abstract

Time series representation is one of the fundamental tasks in Time Series Data Mining (TSDM). Due to the advantage of easy understanding and implementation, Piecewise Linear Representation (PLR) has been widely used in compression, indexing, and similarity measurement of time series data. In this paper, we introduce a novel online PLR segmentation method. It is based on determining the cumulative radian error for each data point. The proposed method is demonstrated by applying to real stock market indices data and shows its effectiveness and superiority.

Keywords

data mining; stock markets; time series; cumulative radian error; online PLR segmentation method; piecewise linear representation; piecewise linear segmentation; stock market indices data; time series data mining; Computational efficiency; Computer science; Data mining; Discrete Fourier transforms; Discrete wavelet transforms; Educational institutions; Fluctuations; Piecewise linear techniques; Stock markets; Transaction databases; cumulative effect; piecewise linear representation; radian; segmentation; time series;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer and Automation Engineering (ICCAE), 2010 The 2nd International Conference on

Conference_Location

Singapore

Print_ISBN

978-1-4244-5585-0

Electronic_ISBN

978-1-4244-5586-7

Type

conf

DOI

10.1109/ICCAE.2010.5451780

Filename

5451780