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131574 - A community merger of optimization algorithm to extract overlapping communities in networks.pdf (5.65 MB)

A community merger of optimization algorithm to extract overlapping communities in networks

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journal contribution
posted on 2023-05-20, 02:10 authored by Li, Q, Zhong, J, Wang, C, Cao, Z
A community in networks is a subset of vertices primarily connecting internal components, yet less connecting to the external vertices. The existing algorithms aim to extract communities of the topological features in networks. However, the edges of practical complex networks involving a weight that represents the tightness degree of connection and robustness, which leads a significant influence on the accuracy of community detection. In our study, we propose an overlapping community detection method based on the seed expansion strategy applying to both the unweighted and the weighted networks, called OCSE. First, it redefines the edge weight and the vertex weight depending on the influence of the network topology and the original edge weight, and then selects the seed vertices and updates the edges weight. Comparisons between OCSE approach and existing community detection methods on synthetic and real-world networks, the results of the experiment show that our proposed approach has the significantly better performance in terms of the accuracy.


Publication title

IEEE Access








School of Information and Communication Technology


Institute of Electrical and Electronics Engineers

Place of publication

United States

Rights statement

Copyright 2018 IEEE.

Repository Status

  • Open

Socio-economic Objectives

Intelligence, surveillance and space

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