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A Model-Based Multivariate Time Series Clustering Algorithm

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Trends and Applications in Knowledge Discovery and Data Mining (PAKDD 2014)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8643))

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Abstract

Given a set of multivariate time series, the problem of clustering such data is concerned with the discovering of inherent groupings of the data according to how similar or dissimilar the time series are to each other. Existing time series clustering algorithms can divide into three types, raw-based, feature-based and model-based. In this paper, a model-based multivariate time series clustering algorithm is proposed and its tasks in several steps: (i)data transformation, (ii)discovering time series temporal patterns using confidence value to represent the relationship between different variables, (iii) clustering of multivariate time series based on the degree of patterns discovering in (ii). For evaluate performance of proposed algorithm, the proposed algorithm is tested with both synthetic data and real data. The result shows that it can be promising algorithm for multivariate time series clustering.

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Authors and Affiliations

  1. Department of Computing, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong

    Pei-Yuan Zhou & Keith C. C. Chan

Authors
  1. Pei-Yuan Zhou
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  2. Keith C. C. Chan
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Corresponding author

Correspondence to Pei-Yuan Zhou .

Editor information

Editors and Affiliations

  1. National Chiao Tung University, Hsinchu, Taiwan

    Wen-Chih Peng

  2. Google Research, Mountain View, California, USA

    Haixun Wang

  3. University of Melbourne, Melbourne, Victoria, Australia

    James Bailey

  4. National Cheng Kung University, Tainan, Taiwan

    Vincent S. Tseng

  5. Japan Advanced Institute of Science and Technology, Nomi City, Japan

    Tu Bao Ho

  6. Nanjing University, Nanjing, China

    Zhi-Hua Zhou

  7. National Chengchi University, Taipei, Taiwan

    Arbee L.P. Chen

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© 2014 Springer International Publishing Switzerland

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Zhou, PY., Chan, K.C.C. (2014). A Model-Based Multivariate Time Series Clustering Algorithm. In: Peng, WC., et al. Trends and Applications in Knowledge Discovery and Data Mining. PAKDD 2014. Lecture Notes in Computer Science(), vol 8643. Springer, Cham. https://doi.org/10.1007/978-3-319-13186-3_72

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  • DOI: https://doi.org/10.1007/978-3-319-13186-3_72

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-13185-6

  • Online ISBN: 978-3-319-13186-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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