Work place: Department of Computer Science and engineering, Thapar University Patiala-147004, Punjab, India
E-mail: manindersohal@thapar.edu
Website:
Research Interests: Autonomic Computing, Swarm Intelligence, Mathematics of Computing
Biography
Maninder Kaur is holding an academic position as Assistant Professor in Computer science and Engineering department, Thapar University, Patiala. She received her bachelor degree from SLIET and Master of Technology degree in Computer Science and Engineering from Punjabi University. She completed her Ph.D. in the field of Circuit partitioning using Evolutionary approach. Her major research interests include VLSI CAD, DNA computing, Soft computing. Currently she is working on the application of soft computing intelligence in various fields of VLSI physical design automation and Social networks. She is an associate member of The Institution of Engineers, India.
By Abhay Mahajan Maninder Kaur
DOI: https://doi.org/10.5815/ijitcs.2016.04.05, Pub. Date: 8 Apr. 2016
Identifying strongly associated clusters in large complex networks has received an increased amount of interest since the past decade. The problem of community detection in complex networks is an NP complete problem that necessitates the clustering of a network into communities of compactly linked nodes in such a manner that the interconnection between the nodes is found to be denser than the intra-connection between the communities. In this paper, different approaches given by the authors in the field of community detection have been described with each methodology being classified according to algorithm type, along with the comparative analysis of these approaches on the basis of NMI and Modularity for four real world networks.
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