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A Dynamic Additive Fuzzy Clustering Model

  • Mika Sato-Ilic
  • Yoshiharu Sato
Part of the Studies in Classification, Data Analysis, and Knowledge Organization book series (STUDIES CLASS)

Abstract

This paper presents a dynamic clustering model in which clusters are constructed in order to find the features of the dynamical change.

If the similarity between the objects is observed depending on time or parameters which are satisfying the total order relation, then it is important to capture the change in the results of clustering according to the change in time. In this paper, we construct a model which can represent dynamically changing clusters by introducing the concepts of conventional dynamic MDS (Ambrosi, K. and Hansohm, J., 1987) or dynamic PCA (Baba, Y. and Nakamura, Y., 1997) into the additive clustering model (Sato, M. and Sato, Y., 1995).

Keywords

3-Way Data Dynamic MDS Clustering Model 

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References

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Copyright information

© Springer-Verlag Berlin · Heidelberg 1998

Authors and Affiliations

  • Mika Sato-Ilic
    • 1
  • Yoshiharu Sato
    • 2
  1. 1.University of TsukubaTsukuba 305Japan
  2. 2.Hokkaido UniversityKita-ku, Sapporo 060Japan

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