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A new algorithm CNM-Centrality of detecting communities based on node centrality

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成果类型:
期刊论文
作者:
Hu, Fang;Liu, Yuhua*
通讯作者:
Liu, Yuhua
作者机构:
[Hu, Fang; Liu, Yuhua] Cent China Normal Univ, Sch Comp Sci, Wuhan 430079, Peoples R China.
[Hu, Fang] Hubei Univ Chinese Med, Coll Informat Engn, Wuhan 430065, Peoples R China.
通讯机构:
[Liu, Yuhua] C
Cent China Normal Univ, Sch Comp Sci, Wuhan 430079, Peoples R China.
语种:
英文
关键词:
CNM-Centrality algorithm;Community structure detection;Modularity;Normalized mutual information;Simulation test
期刊:
Physica A-Statistical Mechanics and its Applications
ISSN:
0378-4371
年:
2016
卷:
446
页码:
138-151
机构署名:
本校为第一且通讯机构
院系归属:
计算机学院
摘要:
The discovery and analysis of community structure in complex networks is a hot issue in recent years. In this paper, based on the fast greedy clustering algorithm CNM with the thought of local search, the introduction of the idea of node centrality and the optimal division of the central nodes and their neighbor nodes into correct communities, a new algorithm CNM-Centrality of detecting communities in complex networks is proposed. In order to verify the accuracy and efficiency of this algorithm, the performance of this algorithm is tested on several representative real-world networks and a set...

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