Clustering dynamics of complex discrete-time networks and its application in community detection.

@article{Wu2014ClusteringDO,
  title={Clustering dynamics of complex discrete-time networks and its application in community detection.},
  author={Jianshe Wu and Yang Jiao},
  journal={Chaos},
  year={2014},
  volume={24 3},
  pages={
          033104
        }
}
The clustering phenomenon is common in real world networks. A discrete-time network model is proposed firstly in this paper, and then the phase clustering dynamics of the networks are studied carefully. The proposed model acts as a bridge between the dynamic phenomenon and the topology of a modular network. On one hand, phase clustering phenomenon will occur for a modular network by the proposed model; on the other hand, the communities can be identified from the clustering phenomenon. Beyond… 
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27 Citations
Background Citations
6
Methods Citations
4

27 Citations

Citation Type

Citation Type

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TLDR
In this paper, intimacy evolutionary clustering algorithm is proposed to detect community structure in dynamic networks and achieves better detection performance compared with several better algorithms in terms of detection accuracy.
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