Mining Correlations between Multi-Streams Based on Haar Wavelet

Chen Anlong; Tang Changjie; Yuan Chang’an; Peng Jing; Hu Jianjun

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Mining Correlations between Multi-Streams Based on Haar Wavelet

Chen Anlong 1,Tang Changjie 1 *,Yuan Chang’an 2,Peng Jing 2,Hu Jianjun 2

1.College of Computer Science and Engineering, Sichuan University

2.College of Computer Science and Engineering- Sichuan University

*Correspondence author

#Submitted by

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Funding: 博士点基金（No.20020610007）

Opened online:13 September 2005

Accepted by: none

Citation: Chen Anlong,Tang Changjie,Yuan Chang’an.Mining Correlations between Multi-Streams Based on Haar Wavelet[OL]. [13 September 2005] http://en.paper.edu.cn/en_releasepaper/content/2859

In the application with multiple data streams, the correlation between data streams is very significant. The main contributions of this paper included: (1) Introduces the concept of total ordering with filter and compression by wavelets to describe streams. (2) Proposes the equivalence model to evaluate correlations between streams, including three theorems about the equivalence between wavelet coefficients and original data about computing correlation. (3) Designs anti-noise algorithm with sliding windows to compute correlation measure. (4) Gives extensive experiments on real data, which show that the local correlations are hardly affected by data with noise in the long windows, and that new algorithm has well filter on the streams with noise in the environment of short size windows.

Keywords:correlation coefficient; multi-streams data; Haar wavelet; double sliding windows.

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