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UK Workshop on Computational Intelligence

UKCI 2019: Advances in Computational Intelligence Systems pp 235–247Cite as

An Immunological Algorithm for Graph Modularity Optimization

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1043))

Abstract

Complex networks constitute the backbone of complex systems. They represent a powerful interpretation tool for describing and analyzing many different kinds of systems from biology, economics, engineering and social networks. Uncovering the community structure exhibited by real networks is a crucial step towards a better understanding of complex systems, revealing the internal organization of nodes. However, existing algorithms in the literature up-to-date present several crucial issues, and the question of how good an algorithm is, with respect to others, is still open. Recently, Newman [18] suggested modularity as a natural measure of the goodness of network community decompositions. Here we propose an implementation of an Immunological Algorithm, a population based computational systems inspired by the immune system and its features, to perform community detection on the methods of modularity maximization. The reliability and efficiency of the proposed algorithm has been validating by comparing it with Louvain algorithm one of the fastest and the popular algorithm based on a multiscale modularity optimization scheme.

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Author information

Authors and Affiliations

  1. Department of Mathematics and Computer Science, University of Catania, V.le A. Doria 6, 95125, Catania, Italy

    A. G. Spampinato, R. A. Scollo, M. Pavone & V. Cutello

  2. Institute for Biomedical Reasearch and Innovation, Italian National Research Council, Via P. Gaifami 18, 95126, Catania, Italy

    A. G. Spampinato & S. Cavallaro

Authors
  1. A. G. Spampinato
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  2. R. A. Scollo
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  3. S. Cavallaro
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  4. M. Pavone
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  5. V. Cutello
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Corresponding author

Correspondence to M. Pavone .

Editor information

Editors and Affiliations

  1. School of Computing, University of Portsmouth, Portsmouth, UK

    Zhaojie Ju

  2. Department of Computer and Information Sciences, Northumbria University, Newcastle upon Tyne, UK

    Longzhi Yang

  3. Bristol Robotics Laboratory, University of the West of England, Bristol, UK

    Chenguang Yang

  4. School of Computing, University of Portsmouth, Portsmouth, Hampshire, UK

    Alexander Gegov

  5. School of Computing, University of Portsmouth, Portsmouth, UK

    Dalin Zhou

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Spampinato, A.G., Scollo, R.A., Cavallaro, S., Pavone, M., Cutello, V. (2020). An Immunological Algorithm for Graph Modularity Optimization. In: Ju, Z., Yang, L., Yang, C., Gegov, A., Zhou, D. (eds) Advances in Computational Intelligence Systems. UKCI 2019. Advances in Intelligent Systems and Computing, vol 1043. Springer, Cham. https://doi.org/10.1007/978-3-030-29933-0_20

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