Influence propagation based community detection in complex networks

被引：7

作者：

Verma, Parth ^{[1
]}

Goyal, Rinkaj ^{[1
]}

机构：

[1] Guru Gobind Singh GGS Indraprastha Univ, Univ Sch Informat Commun & Technol USIC&T, New Delhi 110078, India

来源：

MACHINE LEARNING WITH APPLICATIONS | 2021年 / 3卷

关键词：

Social network analysis; Community detection; Complex systems; ALGORITHM;

D O I：

10.1016/j.mlwa.2020.100019

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Interaction between nodes in a complex network showing the property of homophily tends to produce community structure in the network. The detection of these communities is of immense financial and informational value. For this purpose, we propose a semi -supervised community detection algorithm, inspired by genetic genealogy and based on Label Propagation Algorithm, that detects communities in the network by taking into account the propagation of influence from different community centers identified in the network. Analysis of our proposed algorithm showed improved performance in detecting communities in real social networks.

引用

页数：8

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