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Graph Partition for Matching

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Graph Based Representations in Pattern Recognition (GbRPR 2003)

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

Abstract

Although inexact graph-matching is a problem of potentially exponential complexity, the problem may be simplified by decomposing the graphs to be matched into smaller subgraphs. If this is done, then the process may cast into a hierarchical framework or cast in a way which is amenable to parallel computation. In this paper we demonstrate how the Fiedler-vector can be used to partition graphs for the purposes of decomposition. We show how the resulting subgraphs can be matched using a variety of algorithms. We demonstrate the utility of the resulting graph-matching method on both real work and synthetic data. Here it proves to provide results which are comparable with a number of state-of-the-art graph matching algorithms.

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of York Heslington, York, YO10 5DD, UK

    Huaijun Qiu & Edwin R. Hancock

Authors
  1. Huaijun Qiu
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  2. Edwin R. Hancock
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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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Qiu, H., Hancock, E.R. (2003). Graph Partition for Matching. 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_16

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  • DOI: https://doi.org/10.1007/3-540-45028-9_16

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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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