Finding Time Series Discords Based on Haar Transform 1st Edition by Ada Wai chee Fu, Oscar Tat Wing Leung, Eamonn Keogh, Jessica Lin 9783540370253

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ISBN 13: 9783540370253

Author: Ada Wai chee Fu, Oscar Tat Wing Leung, Eamonn Keogh, Jessica Lin

The problem of finding anomaly has received much attention recently. However, most of the anomaly detection algorithms depend on an explicit definition of anomaly, which may be impossible to elicit from a domain expert. Using discords as anomaly detectors is useful since less parameter setting is required. Keogh et al proposed an efficient method for solving this problem. However, their algorithm requires users to choose the word size for the compression of subsequences. In this paper, we propose an algorithm which can dynamically determine the word size for compression. Our method is based on some properties of the Haar wavelet transformation. Our experiments show that this method is highly effective.

Finding Time Series Discords Based on Haar Transform 1st Table of contents:

1 Introduction
2 Background

3 The Proposed Algorithm

4 Empirical Evaluation

5 Conclusion and Future Work

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