Xu, S. and Wang, P. (2016) Coarse Graining of Complex Networks: A K-Means Clustering Approach. 2006 Chinese Control and Decision Conference (CCDC), Yinchuan, 28-30 May 2016.
https://doi.org/10.1109/CCDC.2016.7531703

has been cited by the following article:

• TITLE: Coarse Graining Method Based on Noded Similarity in Complex Network

  AUTHORS: Yingying Wang, Zhen Jia, Lang Zeng

  KEYWORDS: Complex Network, Coarse Graining, Node Similarity, Statistical Properties

  JOURNAL NAME: Communications and Network, Vol.10 No.3, July 18, 2018

  ABSTRACT: Coarse graining of complex networks is an important method to study large-scale complex networks, and is also in the focus of network science today. This paper tries to develop a new coarse-graining method for complex networks, which is based on the node similarity index. From the information structure of the network node similarity, the coarse-grained network is extracted by defining the local similarity and the global similarity index of nodes. A large number of simulation experiments show that the proposed method can effectively reduce the size of the network, while maintaining some statistical properties of the original network to some extent. Moreover, the proposed method has low computational complexity and allows people to freely choose the size of the reduced networks.