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I-Louvain: An Attributed Graph Clustering Method

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Advances in Intelligent Data Analysis XIV (IDA 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9385))

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Abstract

Modularity allows to estimate the quality of a partition into communities of a graph composed of highly inter-connected vertices. In this article, we introduce a complementary measure, based on inertia, and specially conceived to evaluate the quality of a partition based on real attributes describing the vertices. We propose also I-Louvain, a graph nodes clustering method which uses our criterion, combined with Newman’s modularity, in order to detect communities in attributed graph where real attributes are associated with the vertices. Our experiments show that combining the relational information with the attributes allows to detect the communities more efficiently than using only one type of information. In addition, our method is more robust to data degradation.

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Notes

  1. 1.

    I-Louvain source code and dataset: http://bit.ly/ILouvain.

  2. 2.

    http://perso.crans.org/aynaud/communities/.

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Acknowledgments

The authors would like to thank P.N. Mougel for his help in building the bibliographic dataset.

Author information

Authors and Affiliations

  1. Université de Lyon, 42023, Saint-Étienne, France

    David Combe, Christine Largeron & Mathias Géry

  2. CNRS, UMR 5516, Laboratoire Hubert Curien, 42000, Saint-Étienne, France

    David Combe, Christine Largeron & Mathias Géry

  3. Université de Saint-Étienne, Jean-Monnet, 42000, Saint-Étienne, France

    David Combe, Christine Largeron & Mathias Géry

  4. Université de Lyon, UMR 5205 CNRS, LIRIS, 7 Av J. Capelle, 69100, Villeurbanne, France

    Előd Egyed-Zsigmond

Authors
  1. David Combe
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  2. Christine Largeron
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  3. Mathias Géry
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  4. Előd Egyed-Zsigmond
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Corresponding author

Correspondence to Christine Largeron .

Editor information

Editors and Affiliations

  1. Université de Saint-Etienne, Saint-Etienne, France

    Elisa Fromont

  2. Intelligent Systems Lab, University of Bristol Intelligent Systems Lab, Bristol, United Kingdom

    Tijl De Bie

  3. Informatics Section, Katholieke Universiteit Leuven, Leuven, Belgium

    Matthijs van Leeuwen

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Combe, D., Largeron, C., Géry, M., Egyed-Zsigmond, E. (2015). I-Louvain: An Attributed Graph Clustering Method. In: Fromont, E., De Bie, T., van Leeuwen, M. (eds) Advances in Intelligent Data Analysis XIV. IDA 2015. Lecture Notes in Computer Science(), vol 9385. Springer, Cham. https://doi.org/10.1007/978-3-319-24465-5_16

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  • DOI: https://doi.org/10.1007/978-3-319-24465-5_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-24464-8

  • Online ISBN: 978-3-319-24465-5

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