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International Conference on Bio-Inspired Computing: Theories and Applications

BIC-TA 2018: Bio-inspired Computing: Theories and Applications pp 338–350Cite as

A Decomposition Based Multiobjective Evolutionary Algorithm for Dynamic Overlapping Community Detection

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 952))

Abstract

Dynamic and overlapping are common features of community structures of many real world complex networks. There are few studies on detecting dynamic overlapping communities, but those studies consider only single optimization objective. In practice, it is necessary to evaluate the community detection by multiple metrics to reflect different aspects of a community structure. In this paper, we propose a multi-objective evolutionary algorithm based approach for the problem of dynamic overlapping community detection, with consideration of three optimization objectives: partition density (D), the extended modularity (EQ), and the community smoothing (NMILFK). The dynamic overlapping network is regarded as a set of network snapshots. The multi-objective evolutionary algorithm based on decomposition (MOEA/D) is used to detect the communities for each snapshot. Experiments show that our approach can find uniformly distributed Pareto solutions for the problem and outperforms those comparative approaches.

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Acknowledgments

This work was supported by National Natural Science Foundation of China under Grant 61873040 and 61374204.

Author information

Authors and Affiliations

  1. School of Computer Science, Beijing University of Posts and Telecommunications, Beijing, China

    Xing Wan, Xingquan Zuo & Feng Song

  2. Key Laboratory of Trustworthy Distributed Computing and Service, Ministry of Education, Beijing, China

    Xing Wan, Xingquan Zuo & Feng Song

Authors
  1. Xing Wan
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  2. Xingquan Zuo
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  3. Feng Song
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Corresponding author

Correspondence to Xingquan Zuo .

Editor information

Editors and Affiliations

  1. Beijing University of Posts and Telecommunications, Beijing, China

    Jianyong Qiao

  2. Beijing University of Posts and Telecommunications, Beijing, China

    Xinchao Zhao

  3. Huazhong University of Science and Technology, Wuhan, China

    Linqiang Pan

  4. Beijing University of Posts and Telecommunications, Beijing, China

    Xingquan Zuo

  5. Anhui University, Hefei, China

    Xingyi Zhang

  6. City University of Hong Kong, Kowloon, Hong Kong

    Qingfu Zhang

  7. Beijing University of Posts and Telecommunications, Beijing, China

    Shanguo Huang

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© 2018 Springer Nature Singapore Pte Ltd.

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Cite this paper

Wan, X., Zuo, X., Song, F. (2018). A Decomposition Based Multiobjective Evolutionary Algorithm for Dynamic Overlapping Community Detection. In: Qiao, J., et al. Bio-inspired Computing: Theories and Applications. BIC-TA 2018. Communications in Computer and Information Science, vol 952. Springer, Singapore. https://doi.org/10.1007/978-981-13-2829-9_31

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  • DOI: https://doi.org/10.1007/978-981-13-2829-9_31

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-2828-2

  • Online ISBN: 978-981-13-2829-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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