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Network Community Discovery with Evolutionary Multi-objective Optimization

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Computational Intelligence for Network Structure Analytics

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Abstract

As described in the previous chapters, the community discovery problems can be formulated as single-objective optimization problems. But it is difficult for single-objective optimization algorithms to reveal community structures at multiple resolution levels. The multi-resolution communities can effectively reflect the hierarchical structures of complex networks. In this chapter, we model the multi-resolution community detection problems as multi-objective optimization problems. And thereafter, we use four different evolutionary multi-objective algorithm for solving the multi-resolution community detection based multi-objective optimization problems. Among the four algorithms, three algorithms adopt the framework of MOEA/D, MODPSO, and NNIA to detect multi-resolution communities in undirected and static networks, and an algorithm uses the framework of MOEA/D to detect multi-resolution communities in dynamic networks.

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Notes

  1. 1.

    Acknowledgement: Reprinted from Physica A: Statistical Mechanics and its Applications, 391(15), Gong, M., Ma, L., Zhang, Q., Jiao, L., Community detection in networks by using multi-objective evolutionary algorithm with decomposition, 4050–4060, Copyright(2012), with permission from Elsevier.

  2. 2.

    Acknowledgement: Reprinted from Applied Soft Computing, 13(4), Gong, M., Chen, X., Ma, L., Zhang, Q., Jiao, L., Identification of multi-resolution network structures with multi-objective immune algorithm, 1705–1717, Copyright(2013), with permission from Elsevier.

  3. 3.

    Acknowledgement: Reprinted from Journal of Computer Science and Technology, 27(3), Gong, M.G., Zhang, L.J., Ma, J.J., Jiao, L.C., Community detection in dynamic social networks based on multi-objective immune algorithm, 455–467, Copyright (2012), with permission of Springer.

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Authors and Affiliations

  1. **dian University, **’an, Shaanxi, China

    Maoguo Gong & Shanfeng Wang

  2. Hong Kong Baptist University, Hong Kong, China

    Qing Cai & Lijia Ma

  3. Northwestern Polytechnical University, **’an, Shaanxi, China

    Yu Lei

Authors
  1. Maoguo Gong
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  2. Qing Cai
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  4. Shanfeng Wang
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  5. Yu Lei
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Correspondence to Maoguo Gong .

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Gong, M., Cai, Q., Ma, L., Wang, S., Lei, Y. (2017). Network Community Discovery with Evolutionary Multi-objective Optimization. In: Computational Intelligence for Network Structure Analytics. Springer, Singapore. https://doi.org/10.1007/978-981-10-4558-5_3

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  • DOI: https://doi.org/10.1007/978-981-10-4558-5_3

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