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. © 2011 Springer-Verlag.
CITATION STYLE
Guo, C., & Zhang, Y. (2011). Time series similarity measure based on the function of degree of disagreement. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7091 LNAI, pp. 103–111). https://doi.org/10.1007/978-3-642-25975-3_10
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