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A Clustering Method for Spatio-temporal Data and Its Application to Soccer Game Records

  • Conference paper
Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing (RSFDGrC 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3641))

Abstract

This paper presents a novel method for finding interesting patterns from spatio-temporal data. First, we perform a pairwise comparison of spatio-temporal sequences using the multiscale matching, taking into account the requirements for multiscale observation. Next, we construct the clusters of sequences using rough-set based clustering technique. Experimental results on real soccer game records demonstrated that the method could discover some interesting pass patterns that may be associated with successful goals.

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Author information

Authors and Affiliations

  1. Department of Medical Informatics, Shimane University, School of Medicine, 89-1 Enya-cho, Izumo, Shimane, 693-8501, Japan

    Shoji Hirano & Shusaku Tsumoto

Authors
  1. Shoji Hirano
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  2. Shusaku Tsumoto
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Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Regina, Regina, SK, S4S 0A2 Canada, Polish-Japanese Institute of Information Technology, Koszykowa 86, 02-008 Warsaw, P.O. Box, Poland

    Dominik Ślęzak

  2. School of Information Science and Technology, Southwest Jiaotong University, 610031, Chengdu, P.R. China

    Guoyin Wang

  3. Institute of Mathematics, Warsaw University, Banacha 2, 02-097, Warsaw, Poland

    Marcin Szczuka

  4. Department of Computer Science, Brock University, St. Catharines, L2S 3A1, Ontario, Canada

    Ivo Düntsch

  5. Department of Computer Science, University of Regina, S4S 0A2, Regina, Saskatchewan, Canada

    Yiyu Yao

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© 2005 Springer-Verlag Berlin Heidelberg

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Hirano, S., Tsumoto, S. (2005). A Clustering Method for Spatio-temporal Data and Its Application to Soccer Game Records. In: Ślęzak, D., Wang, G., Szczuka, M., Düntsch, I., Yao, Y. (eds) Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing. RSFDGrC 2005. Lecture Notes in Computer Science(), vol 3641. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11548669_63

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  • DOI: https://doi.org/10.1007/11548669_63

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28653-0

  • Online ISBN: 978-3-540-31825-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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