Proceedings of the 2016 International Conference on Communications, Information Management and Network Security

An Improved Community Detection Algorithm Based on DCT and K-Means

Authors
Lin Li, Kefeng Fan, Jiezhong Gong, Hao Peng
Corresponding Author
Lin Li
Available Online September 2016.
DOI
10.2991/cimns-16.2016.73How to use a DOI?
Keywords
community structure; DCT; k-means; curse of dimensionality
Abstract

Detecting an overlapping and hierarchical community structure can give a significant insight into structural and functional properties in complex networks. In this paper, we propose an improved algorithm to detect communities in the complex network. The proposed algorithm use discrete cosine transform (DCT) to transfer the topology information into frequency domain, and reduce the dimension of frequency signal with a preliminary threshold, and at last cluster the nodes using K-means. Finally, we apply the proposed algorithm in the real and artificial networks. The simulation results show that the proposed algorithm can avoid curse of dimensionality and it is more accurate than some existing mechanisms.

Copyright
© 2016, 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 2016 International Conference on Communications, Information Management and Network Security
Series
Advances in Computer Science Research
Publication Date
September 2016
ISBN
10.2991/cimns-16.2016.73
ISSN
2352-538X
DOI
10.2991/cimns-16.2016.73How to use a DOI?
Copyright
© 2016, 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  - Lin Li
AU  - Kefeng Fan
AU  - Jiezhong Gong
AU  - Hao Peng
PY  - 2016/09
DA  - 2016/09
TI  - An Improved Community Detection Algorithm Based on DCT and K-Means
BT  - Proceedings of the 2016 International Conference on Communications, Information Management and Network Security
PB  - Atlantis Press
SP  - 293
EP  - 297
SN  - 2352-538X
UR  - https://doi.org/10.2991/cimns-16.2016.73
DO  - 10.2991/cimns-16.2016.73
ID  - Li2016/09
ER  -