Coarse Graining Method Based on Noded Similarity in Complex Network

• 作者: Lang Zeng Yingying Wang Zhen Jia
• 来源期刊: 通讯与网络(英文)
• 学科: 数学
• 关键词: COMPLEX NETWORK Coarse GRAINING NODE SIMILARITY STATISTICAL Properties
• 年，卷（期）: 2018,（3）
• 页码范围: 51-64
• 页数: 14页
• 分类号: O1

摘要

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.