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Cooperative Game Theory Approaches for Network Partitioning

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Computing and Combinatorics (COCOON 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10392))

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Abstract

The paper is devoted to game-theoretic methods for community detection in networks. The traditional methods for detecting community structure are based on selecting denser subgraphs inside the network. Here we propose to use the methods of cooperative game theory that highlight not only the link density but also the mechanisms of cluster formation. Specifically, we suggest two approaches from cooperative game theory: the first approach is based on the Myerson value, whereas the second approach is based on hedonic games. Both approaches allow to detect clusters with various resolution. However, the tuning of the resolution parameter in the hedonic games approach is particularly intuitive. Furthermore, the modularity based approach and its generalizations can be viewed as particular cases of the hedonic games.

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Acknowledgements

This research is supported by Russian Humanitarian Science Foundation (project 15-02-00352), Russian Fund for Basic Research (projects 16-51-55006 and 17-11-01079), EU Project Congas FP7-ICT-2011-8-317672 and Campus France.

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Authors and Affiliations

  1. INRIA, 2004 Route des Lucioles, Sophia-Antipolis, France

    Konstantin E. Avrachenkov

  2. Karelian Research Center, Institute of Applied Mathematical Research, Russian Academy of Sciences, 11, Pushkinskaya Street, Petrozavodsk, 185910, Russia

    Aleksei Yu. Kondratev & Vladimir V. Mazalov

Authors
  1. Konstantin E. Avrachenkov
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  2. Aleksei Yu. Kondratev
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  3. Vladimir V. Mazalov
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Corresponding author

Correspondence to Konstantin E. Avrachenkov .

Editor information

Editors and Affiliations

  1. Department of Computing, Hong Kong Polytechnic University, Hong Kong, China

    Yixin Cao

  2. Texas A&M University, College Station, Texas, USA

    Jianer Chen

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Avrachenkov, K.E., Kondratev, A.Y., Mazalov, V.V. (2017). Cooperative Game Theory Approaches for Network Partitioning. In: Cao, Y., Chen, J. (eds) Computing and Combinatorics. COCOON 2017. Lecture Notes in Computer Science(), vol 10392. Springer, Cham. https://doi.org/10.1007/978-3-319-62389-4_49

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  • DOI: https://doi.org/10.1007/978-3-319-62389-4_49

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-62388-7

  • Online ISBN: 978-3-319-62389-4

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