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Time Series Similarity Measure Based on the Function of Degree of Disagreement

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Part of the Lecture Notes in Computer Science book series (LNAI,volume 7091)

Abstract

Similarity measure is a basic task in time series data mining and attracts much attention in the last decade. This paper considers time series similarity measure from an information theoretic perspective. Based on the function of degree of disagreement (FDOD), a new time series similarity measure method is proposed. The empirical result indicates that the method of this paper can solve the unequal time series and has less time complexity. Meanwhile, it also can measure the similarity between multivariate time series.

Keywords

  • time series
  • data mining
  • similarity measure
  • function of degree of disagreement

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Guo, C., Zhang, Y. (2011). Time Series Similarity Measure Based on the Function of Degree of Disagreement. In: Xiong, H., Lee, W.B. (eds) Knowledge Science, Engineering and Management. KSEM 2011. Lecture Notes in Computer Science(), vol 7091. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25975-3_10

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  • DOI: https://doi.org/10.1007/978-3-642-25975-3_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-25974-6

  • Online ISBN: 978-3-642-25975-3

  • eBook Packages: Computer ScienceComputer Science (R0)