Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/9418
Title: Application areas of community detection: A review
Authors: Karataş, Arzum
Şahin, Serap
Keywords: Complex networks
Community detection
Application of community detection
Publisher: Institute of Electrical and Electronics Engineers Inc.
Abstract: In the realm of today's real world, information systems are represented by complex networks. Complex networks contain a community structure inherently. Community is a set of members strongly connected within members and loosely connected with the rest of the network. Community detection is the task of revealing inherent community structure. Since the networks can be either static or dynamic, community detection can be done on both static and dynamic networks as well. In this study, we have talked about taxonomy of community detection methods with their shortages. Then we examine and categorize application areas of community detection in the realm of nature of complex networks (i.e., static or dynamic) by including sub areas of criminology such as fraud detection, criminal identification, criminal activity detection and bot detection. This paper provides a hot review and quick start for researchers and developers in community detection area.
Description: International Congress on Big Data, Deep Learning and Fighting Cyber Terrorism (IBIGDELFT) ; 3-4 Dec. 2018; Ankara-Türkiye
URI: https://hdl.handle.net/11147/9418
ISBN: 978-1-7281-0472-0
Appears in Collections:Computer Engineering / Bilgisayar Mühendisliği
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

Files in This Item:
File SizeFormat 
Application_Areas.pdf202.06 kBAdobe PDFView/Open
Show full item record



CORE Recommender

SCOPUSTM   
Citations

34
checked on Mar 22, 2024

WEB OF SCIENCETM
Citations

23
checked on Mar 16, 2024

Page view(s)

172
checked on Mar 25, 2024

Download(s)

3,550
checked on Mar 25, 2024

Google ScholarTM

Check




Altmetric


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.