Proceedings of the 3rd International Conference on Wireless Communication and Sensor Networks (WCSN 2016)

A survey of clustering algorithms in community detection of complex networks

Authors
Le Bo, Yang Shi, Hao Fang, Mei Wen
Corresponding Author
Le Bo
Available Online December 2016.
DOI
10.2991/icwcsn-16.2017.158How to use a DOI?
Keywords
Complex Networks; Clustering; Community Detection
Abstract

Complex network analysis begins in the 1930s, and the community structure in complex networks is a major characteristic that has been widely concerned. This paper introduces the basic and core ideas of several typical clustering algorithms in community detecting, and analyzes the advantages and disadvantages of each one. And it also reviews the background, the significance and the performance of these algorithms. Some algorithms may perform well in some specific areas but not in community detecting, while the newest algorithms still need to be tested in the future

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 3rd International Conference on Wireless Communication and Sensor Networks (WCSN 2016)
Series
Advances in Computer Science Research
Publication Date
December 2016
ISBN
10.2991/icwcsn-16.2017.158
ISSN
2352-538X
DOI
10.2991/icwcsn-16.2017.158How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Le Bo
AU  - Yang Shi
AU  - Hao Fang
AU  - Mei Wen
PY  - 2016/12
DA  - 2016/12
TI  - A survey of clustering algorithms in community detection of complex networks
BT  - Proceedings of the 3rd International Conference on Wireless Communication and Sensor Networks (WCSN 2016)
PB  - Atlantis Press
SP  - 783
EP  - 788
SN  - 2352-538X
UR  - https://doi.org/10.2991/icwcsn-16.2017.158
DO  - 10.2991/icwcsn-16.2017.158
ID  - Bo2016/12
ER  -