SELF-ORGANIZING MAP OF COMPLEX NETWORKS FOR COMMUNITYDETECTION

Zhenping LI;Ruisheng WANG;Xiang-Sun ZHANG;Luonan CHEN

Journal of Systems Science & Complexity ›› 2010, Vol. 23 ›› Issue (5) : 931-941.

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中国科学院数学与系统科学研究院期刊网
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Journal of Systems Science & Complexity ›› 2010, Vol. 23 ›› Issue (5) : 931-941. DOI: 10.1007/s11424-010-0202-3
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SELF-ORGANIZING MAP OF COMPLEX NETWORKS FOR COMMUNITYDETECTION

  • Zhenping LI(1), Ruisheng WANG(2), Xiang-Sun ZHANG(3), Luonan CHEN(4)
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Abstract

Detecting communities from complex networks is an important
issue and has attracted attention of researchers in many fields. It
is relevant to social tasks, biological inquiries, and technological
problems since various networks exist in these systems. This paper
proposes a new self-organizing map (SOM) based approach to community
detection. By adopting a new operation and a new weight-updating
scheme, a complex network can be organized into dense subgraphs
according to the topological connection of each node by the SOM
algorithm. Extensive numerical experiments show that the performance
of the SOM algorithm is good. It can identify communities more
accurately than existing methods. This method can be used to detect
communities not only in undirected networks, but also in directed
networks and bipartite networks.

Key words

Community detection / complex network / neural networks / self-organizing map

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Zhenping LI , Ruisheng WANG , Xiang-Sun ZHANG , Luonan CHEN. SELF-ORGANIZING MAP OF COMPLEX NETWORKS FOR COMMUNITYDETECTION. Journal of Systems Science and Complexity, 2010, 23(5): 931-941 https://doi.org/10.1007/s11424-010-0202-3
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