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Number 3

An Analysis for the Detection of Network Communities in Dynamic Environments

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  • K. Sendil Kumar and K. S. Suganthi and C. Suchitra and S. Sharmili 2013. An Analysis for the Detection of Network Communities in Dynamic Environments. International Journal of Applied Information Systems. 5, 3 (February 2013), 53-57. DOI=http://dx.doi.org/10.5120/ijais450877 
  • @article{10.5120/ijais2017451568,
author = {K. Sendil Kumar and K. S. Suganthi and C. Suchitra and S. Sharmili},
title = {An Analysis for the Detection of Network Communities in Dynamic Environments},
journal = {International Journal of Applied Information Systems},
issue_date = {February 2013},
volume = {5},
number = {},
month = {February},
year = {2013},
issn = {},
pages = {53-57},
numpages = {},
url = {/archives/volume5/number3/431-0877},
doi = { 10.5120/ijais12-450877},
publisher = { xA9 2012 by IJAIS Journal},
address = {}
}

  • %1 450877
%A K.  Sendil Kumar
%A K.  S.  Suganthi
%A C.  Suchitra
%A S.  Sharmili
%T An Analysis for the Detection of Network Communities in Dynamic Environments
%J International Journal of Applied Information Systems
%@ 
%V 5
%N 
%P 53-57
%D 2013
%I  xA9 2012 by IJAIS Journal

Abstract

Community Detection basically refers to the discovery of the naturally occurring associations between vertices in a given network. Initial algorithms involved detecting communities in static networks. This slowly evolved into detecting communities in dynamic environments as the nature of the network itself, in general, is dynamic. This paper on community detection is based on the analysis of existing algorithms present for the detection in dynamic environments and we have proposed an idea involving the combination of two techniques: local community measurement of multi resolution applied in multi – objective immune algorithm.

References

  1. Mao – Guo Gong, Ling – Jun Zhang, Jing Jing – Ma and Li – Cheng Jiao, "Community Detection in Dynamic Social Networks based on Multiobjective Immune Algorithm", Journal of Computer Science and Technology, May 2012.
  2. Jianbin Huang, Heli Sun, Yaguang Liu, Qinbao Song and Tim Weninger, "Towards Online Multiresolution Community Detection in Large – Scale Networks", August 2011.
  3. Keehyung Kim, Ri (Bob) McKay and Byung – Ro Moon, "Multiobjective Evolutionary Algorithms for Dynamic Social Netowork Clustering", ACM 2010.
  4. Tinbao Yang, Yun Chi, Shenghuo Zhu, Yihong Gong and Rong Jin, "Detecting Communities and their evolutions in dynamic social netoworks – a Bayesian approach", Springer 2011.
  5. Andrea Lancichinetti, Santo Fortunato and Janos Kertesz, "Detecting the overlapping and hierarchical community structure in complex networks",March 2009.
  6. M. E. J. Newman and M. Girvan, "Finding and evaluating community structure in networks", August 2003.
  7. M. E. J. Newman, "Fast algorithm for detecting community structure in networks", September 2003.
  8. C. O. Dorso and A. D. Menus, "Community Detection in Networks", International Journal of Bifurcation and Chaos, 2010.
  9. Wenye Li and Dale Schuurmans, "Modular Community Detection in Networks", Internaltional Journal of Computer Applications, 2011.
  10. Chengying Mao, "A heuristic algorithm for Bipartite Community Detection in Social Networks", Journal of Software, January 2012.

Keywords

Community detection, dynamic environment, Similarity factor

Index Terms

Computer Science
Information Sciences