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A Fuzzy-Interval Based Approach for Explicit Graph Embedding

  • Muhammad Muzzamil Luqman
  • Josep Lladós
  • Jean-Yves Ramel
  • Thierry Brouard
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6388)

Abstract

We present a new method for explicit graph embedding. Our algorithm extracts a feature vector for an undirected attributed graph. The proposed feature vector encodes details about the number of nodes, number of edges, node degrees, the attributes of nodes and the attributes of edges in the graph. The first two features are for the number of nodes and the number of edges. These are followed by w features for node degrees, m features for k node attributes and n features for l edge attributes — which represent the distribution of node degrees, node attribute values and edge attribute values, and are obtained by defining (in an unsupervised fashion), fuzzy-intervals over the list of node degrees, node attributes and edge attributes. Experimental results are provided for sample data of ICPR2010 contest GEPR.

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References

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    Colot, O., Olivier, C., Courtellemont, P., El-Matouat, A.: Information criteria and abrupt changes in probability laws. In: Signal Processing VII: Theories and Applications, pp. 1855–1858 (1994)Google Scholar
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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Muhammad Muzzamil Luqman
    • 1
    • 2
  • Josep Lladós
    • 2
  • Jean-Yves Ramel
    • 1
  • Thierry Brouard
    • 1
  1. 1.Laboratoire d’InformatiqueUniversité François Rabelais de ToursFrance
  2. 2.Computer Vision CenterUniversitat Autónoma de BarcelonaSpain

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