Local community detection in complex networks based on maximum cliques extension
type: Item
instance of: scholarly article
title: Local community detection in complex networks based on maximum cliques extension
zbMATH Open document ID: 1407.91199
DOI: 10.1155/2014/653670
author: Meng Fanrong
author: Zhu Mu
author: Zhou Yong
author: Zhou Ranran
published in: Mathematical Problems in Engineering
publication date: 2019-02-08T00:00:00Z
review text: Summary: Detecting local community structure in complex networks is an appealing problem that has attracted increasing attention in various domains. However, most of the current local community detection algorithms, on one hand, are influenced by the state of the source node and, on the other hand, cannot effectively identify the multiple communities linked with the overlapping nodes. We proposed a novel local community detection algorithm based on maximum clique extension called LCD-MC. The proposed method firstly finds the set of all the maximum cliques containing the source node and initializes them as the starting local communities; then, it extends each unclassified local community by greedy optimization until a certain objective is satisfied; finally, the expected local communities will be obtained until all maximum cliques are assigned into a community. An empirical evaluation using both synthetic and real datasets demonstrates that our algorithm has a superior performance to some of the state-of-the-art approaches.
Mathematics Subject Classification ID: 91D30
Mathematics Subject Classification ID: 05C85
zbMATH DE Number: 7016956
describes a project that uses: Algorithm 457
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2014/653670
OpenAlex ID: W1985497632
Wikidata QID: Q59068667
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description: scientific article; zbMATH DE number 7016956