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International Workshop on Graph-Based Representations in Pattern Recognition

GbRPR 2003: Graph Based Representations in Pattern Recognition pp 235–246Cite as

Graph Clustering Using the Weighted Minimum Common Supergraph

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2726))

Abstract

Graphs are a powerful and versatile tool useful for representing patterns in various subfields of science and engineering. In many applications, for example, in pattern recognition and computer vision, it is required to measure the similarity of objects for clustering similar patterns. In this paper a new structural method, the Weighted Minimum Common Supergraph (WMCS), for representing a cluster of patterns is proposed. Using this method it becomes easy to extract the common information shared in the patterns of a cluster and separate this information from noise and distortions that usually affect graphs representing real objects. Moreover, experimental results show that WMCS is suitable for performing graph clustering.

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Author information

Authors and Affiliations

  1. Institut für Informatik und angwandte Mathematik, Universität Bern, Neubrückstrasse 10, CH-3012, Bern, Switzerland

    Horst Bunke

  2. Dipartimento di Informatica e Sistemistica, Università di Napoli “Federico II”, Via Claudio, 21, I-80125, Napoli, Italy

    P. Foggia & C. Guidobaldi

  3. Dipartimento di Ingegneria dell’Informazione ed Ingegneria Elettrica, Università di Salerno, via P.te Don Melillo, I-84084, Fisciano (SA), Italy

    M. Vento

Authors
  1. Horst Bunke
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  2. P. Foggia
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  3. C. Guidobaldi
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  4. M. Vento
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Editor information

Editors and Affiliations

  1. Department of Computer Science, University of York, York, YO1 5DD, UK

    Edwin Hancock

  2. D.I.I.I.E., Università degli Studi di Salerno, Via Ponte don Melillo, 1, 84084, Fisciano (SA), Italy

    Mario Vento

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© 2003 Springer-Verlag Berlin Heidelberg

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Cite this paper

Bunke, H., Foggia, P., Guidobaldi, C., Vento, M. (2003). Graph Clustering Using the Weighted Minimum Common Supergraph. In: Hancock, E., Vento, M. (eds) Graph Based Representations in Pattern Recognition. GbRPR 2003. Lecture Notes in Computer Science, vol 2726. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45028-9_21

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  • DOI: https://doi.org/10.1007/3-540-45028-9_21

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40452-1

  • Online ISBN: 978-3-540-45028-3

  • eBook Packages: Springer Book Archive

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