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Outlier Mining on Multiple Time Series Data in Stock Market

  • Chao Luo
  • Yanchang Zhao
  • Longbing Cao
  • Yuming Ou
  • Li Liu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5351)

Abstract

With the dramatic increase of stock market data, traditional outlier mining technologies have shown their limitations in efficiency and precision. In this paper, an outlier mining model on stock market data is proposed, which aims to detect the anomalies from multiple complex stock market data. This model is able to improve the precision of outlier mining on individual time series. The experiments on real-world stock market data show that the proposed outlier mining model is effective and outperforms traditional technologies.

Keywords

Outlier mining time series stock market 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Chao Luo
    • 1
  • Yanchang Zhao
    • 1
  • Longbing Cao
    • 1
  • Yuming Ou
    • 1
  • Li Liu
    • 1
  1. 1.Faculty of Engineering & ITUniversity of TechnologySydneyAustralia

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