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Modularity Based Community Detection in Hypergraphs

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Algorithms and Models for the Web Graph (WAW 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13894))

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Abstract

In this paper, we make a significant step toward designing a scalable community detection algorithm using hypergraph modularity function. The main obstacle with adjusting the initial stage of the classical Louvain algorithm is dealt via carefully adjusted linear combination of the graph modularity function of the corresponding two-section graph and the desired hypergraph modularity function. It remains to properly tune the algorithm and design a mechanism to adjust the weights in the modularity function (in an unsupervised way), depending on how often nodes in one community share hyperedges with nodes from other communities. It will be done in the journal version of this paper.

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Notes

  1. 1.

    https://github.com/bkamins/ABCDGraphGenerator.jl/.

  2. 2.

    https://github.com/tolcz/ABCDeGraphGenerator.jl/.

  3. 3.

    https://math.torontomu.ca/~pralat/research.html.

  4. 4.

    https://math.torontomu.ca/~pralat/research.html.

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Author information

Authors and Affiliations

  1. Decision Analysis and Support Unit, SGH Warsaw School of Economics, Warsaw, Poland

    Bogumił Kamiński

  2. Institute of Computer Sciences, Poznan University of Technology, Poznan, Poland

    Paweł Misiorek

  3. Department of Mathematics, Toronto Metropolitan University, Toronto, ON, Canada

    Paweł Prałat

  4. Tutte Institute for Mathematics and Computing, Ottawa, ON, Canada

    François Théberge

Authors
  1. Bogumił Kamiński
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  2. Paweł Misiorek
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  3. Paweł Prałat
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  4. François Théberge
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Corresponding author

Correspondence to Paweł Prałat .

Editor information

Editors and Affiliations

  1. Tutte Institute for Mathematics and Computing, Ottawa, ON, Canada

    Megan Dewar

  2. Toronto Metropolitan University, Toronto, ON, Canada

    Paweł Prałat

  3. SGH Warsaw School of Economics, Warsaw, Poland

    Przemysław Szufel

  4. Tutte Institute for Mathematics and Computing, Ottawa, ON, Canada

    François Théberge

  5. SGH Warsaw School of Economics, Warsaw, Poland

    Małgorzata Wrzosek

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Kamiński, B., Misiorek, P., Prałat, P., Théberge, F. (2023). Modularity Based Community Detection in Hypergraphs. In: Dewar, M., Prałat, P., Szufel, P., Théberge, F., Wrzosek, M. (eds) Algorithms and Models for the Web Graph. WAW 2023. Lecture Notes in Computer Science, vol 13894. Springer, Cham. https://doi.org/10.1007/978-3-031-32296-9_4

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  • DOI: https://doi.org/10.1007/978-3-031-32296-9_4

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