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Selected Contributions in Data Analysis and Classification pp 161–172Cite as

Clustering Methods: A History of k-Means Algorithms

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Abstract

This paper surveys some historical issues related to the well-known k-means algorithm in cluster analysis. It shows to which authors the different versions of this algorithm can be traced back, and which were the underlying applications. We sketch various generalizations (with references also to Diday’s work) and thereby underline the usefulness of the k-means approach in data analysis.

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Author information

Authors and Affiliations

  1. Institute of Statistics, RWTH Aachen University, D-52056, Aachen, Germany

    Hans-Hermann Bock

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  1. Hans-Hermann Bock
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Editor information

Editors and Affiliations

  1. Faculty of Economics, University of Porto, Rua Dr. Roberto Frias, 4200-464, Porto, Portugal

    Paula Brito

  2. ESG UQAM, 315 East, Sainte-Catherine Street, Montreal, Quebec, H2X 3X2, Canada

    Guy Cucumel

  3. Department Lussi, ENST Bretagne, 2 rue de la Châtaigneraie, CS 17607, 35576, Cesson-Sévigné Cedex, France

    Patrice Bertrand

  4. Centre of Computer Science (CIn), Federal University of Pernambuco (UFPE), Av. Prof. Luiz Freire s/n Cidade Universitária, CEP 50740-540, Recife-PE, Brazil

    Francisco de Carvalho

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Bock, HH. (2007). Clustering Methods: A History of k-Means Algorithms. In: Brito, P., Cucumel, G., Bertrand, P., de Carvalho, F. (eds) Selected Contributions in Data Analysis and Classification. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73560-1_15

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