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Brazilian Conference on Intelligent Systems

BRACIS 2020: Intelligent Systems pp 322–336Cite as

Particle Competition for Unbalanced Community Detection in Complex Networks

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12320))

Abstract

Unbalanced community structures is a common phenomenon when representing real-world systems using Complex Networks; however, not all community detection model can correctly identify communities of different sizes. In this paper, we propose a community detection technique focusing on the detection of unbalanced communities. The method augments the Particle Competition model: a bio-inspired technique that employs a set of particles (random walkers) into the network to compete for its nodes. However, the detection of unbalanced communities in the original Particle Competition is impossible because every particle shares the same ability to defend and attack nodes. The proposed model introduces a second stage into the system, named Regularization, which explicitly handles the detection of unbalanced communities. This mechanism uses the neighborhood of the nodes to create a custom preference guide for each particle, specifically tailored to the community of the particle. As a result, the model can precisely detect unbalanced community structures. Furthermore, the model achieves higher accuracy and faster computational speed compared to the original Particle Competition model.

This work is supported in part by the São Paulo State Research Foundation (FAPESP) under grant numbers 2015/50122-0 and 2013/07375-0, the Brazilian Coordination for Higher Education Development (CAPES), the Pro-Rectory of Research (PRP) of University of São Paulo under grant number 2018.1.1702.59.8, and the Brazilian National Council for Scientific and Technological Development (CNPq) under grant number 303199/2019-9.

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Author information

Authors and Affiliations

  1. Institute of Mathematics and Computer Science, University of São Paulo (USP), São Paulo, Brazil

    Luan V. C. Martins

  2. Faculty of Philosophy, Science, and Letters at Ribeirão Preto, University of São Paulo (USP), São Paulo, Brazil

    Liang Zhao

Authors
  1. Luan V. C. Martins
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  2. Liang Zhao
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Correspondence to Luan V. C. Martins .

Editor information

Editors and Affiliations

  1. Federal University of São Carlos, São Carlos, Brazil

    Ricardo Cerri

  2. Federal University of ABC, Santo Andre, Brazil

    Ronaldo C. Prati

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Martins, L.V.C., Zhao, L. (2020). Particle Competition for Unbalanced Community Detection in Complex Networks. In: Cerri, R., Prati, R.C. (eds) Intelligent Systems. BRACIS 2020. Lecture Notes in Computer Science(), vol 12320. Springer, Cham. https://doi.org/10.1007/978-3-030-61380-8_22

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  • DOI: https://doi.org/10.1007/978-3-030-61380-8_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-61379-2

  • Online ISBN: 978-3-030-61380-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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