An Autonomous Clustering Technique

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


The basic idea of this paper is that it will be possible to construct clusters by moving each pair of objects closer or farther according to their relative similarity to all of the objects. For this purpose, regarding a set of objects as a set of autonomous agents, each agent decides its action to the other agents by taking account of the similarity between its self and others. And consequently, we get the clusters autonomously.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. BOCK, H.H.(1996): Probability Models and Hypotheses Testing in Partitioning Cluster Analysis. In: P. Arabie, L.J. Hubert and G. De Soete (Eds.): Clustering and Classification. World Scientific Pbul., 377–453.Google Scholar
  2. HARTIGAN, J.A.(1975): Clustering Algorithms.John Wiley & Sons, New York.Google Scholar
  3. LANCE, G.N. and WILLIAMS, W.T.(1967): A General Theory of Classificatory Sorting Strategies I, Hierarchical Systems. Computer Journal, 9, 373–380.Google Scholar

Copyright information

© Springer-Verlag Berlin · Heidelberg 2000

Authors and Affiliations

  • Yoshiharu Sato
    • 1
  1. 1.Division of Systems and InformationHokkaido UniversityKita-ku, SapporoJapan

Personalised recommendations