A clustering method for spatio-temporal data and its application to soccer game records

Authors:
Shoji Hirano;Shusaku Tsumoto
Affiliations:
Department of Medical Informatics, Shimane University, School of Medicine, Izumo, Shimane, Japan;Department of Medical Informatics, Shimane University, School of Medicine, Izumo, Shimane, Japan
Venue:
RSFDGrC'05 Proceedings of the 10th international conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing - Volume Part I
Year:
2005

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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.