Detecting local communities in complex network
Complex networks
Interaction relationship between nodes and community
Local centrality
Local community detection
Node similarity index
Journal
PeerJ. Computer science
ISSN: 2376-5992
Titre abrégé: PeerJ Comput Sci
Pays: United States
ID NLM: 101660598
Informations de publication
Date de publication:
2023
2023
Historique:
received:
05
12
2022
accepted:
17
04
2023
medline:
22
6
2023
pubmed:
22
6
2023
entrez:
22
6
2023
Statut:
epublish
Résumé
The goal of local community detection algorithms is to explore the optimal community with a reference to a given node. Such algorithms typically include two primary processes: seed selection and community expansion. This study develops and tests a novel local community detection algorithm called
Identifiants
pubmed: 37346543
doi: 10.7717/peerj-cs.1386
pii: cs-1386
pmc: PMC10280398
doi:
Types de publication
Journal Article
Langues
eng
Pagination
e1386Informations de copyright
© 2023 Wang et al.
Déclaration de conflit d'intérêts
The authors declare that they have no competing interests.
Références
Phys Rev E Stat Nonlin Soft Matter Phys. 2007 Sep;76(3 Pt 2):036106
pubmed: 17930305
Phys Rev E Stat Nonlin Soft Matter Phys. 2005 Aug;72(2 Pt 2):026132
pubmed: 16196669
Phys Rev E Stat Nonlin Soft Matter Phys. 2008 Oct;78(4 Pt 2):046110
pubmed: 18999496
Phys Rev E Stat Nonlin Soft Matter Phys. 2004 Feb;69(2 Pt 2):026113
pubmed: 14995526
PeerJ Comput Sci. 2022 May 18;8:e981
pubmed: 36091993
Proc Natl Acad Sci U S A. 2002 Jun 11;99(12):7821-6
pubmed: 12060727