Time series similarity measure based on the function of degree of disagreement

  • Authors:
  • Chonghui Guo;Yanchang Zhang

  • Affiliations:
  • Institute of Systems Engineering, Dalian University of Technology, Dalian, China;Institute of Systems Engineering, Dalian University of Technology, Dalian, China

  • Venue:
  • KSEM'11 Proceedings of the 5th international conference on Knowledge Science, Engineering and Management
  • Year:
  • 2011

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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.