Proceedings of the 2016 International Conference on Applied Mathematics, Simulation and Modelling

A Graph Clustering Algorithm Based on the Intra Vertex Adjacent Ratio

Authors
Haili Guo, Deqiang Wang
Corresponding Author
Haili Guo
Available Online May 2016.
DOI
https://doi.org/10.2991/amsm-16.2016.30How to use a DOI?
Keywords
component; graph; clustering algorithm; intra vertex connection ratio
Abstract

This paper proposes a new clustering coefficient based on the number of connecting vertices within a cluster (called inter vertex adjacent ratio, IVAR) and proposes a new clustering algorithm based on IVAR. Finally, the analysis of algorithm applicability shows that the algorithm is more applicative and effective for regular graphs than the vertex-clustering algorithm based on intra connection ratio [L. Moussiades and A. Vakali, Clustering dense graph: A web site graph paradigm. Information Processing and Management, vol. 46, pp.247-267, 2010].

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 Applied Mathematics, Simulation and Modelling
Series
Advances in Computer Science Research
Publication Date
May 2016
ISBN
978-94-6252-198-8
ISSN
2352-538X
DOI
https://doi.org/10.2991/amsm-16.2016.30How 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  - Haili Guo
AU  - Deqiang Wang
PY  - 2016/05
DA  - 2016/05
TI  - A Graph Clustering Algorithm Based on the Intra Vertex Adjacent Ratio
BT  - Proceedings of the 2016 International Conference on Applied Mathematics, Simulation and Modelling
PB  - Atlantis Press
SP  - 129
EP  - 132
SN  - 2352-538X
UR  - https://doi.org/10.2991/amsm-16.2016.30
DO  - https://doi.org/10.2991/amsm-16.2016.30
ID  - Guo2016/05
ER  -