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Study of Clique Based Community Detection Algorithms

A. Srivastava1 , A. Pillai2 , D. J. Gupta3

Section:Research Paper, Product Type: Journal Paper
Volume-6 , Issue-9 , Page no. 142-149, Sep-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i9.142149

Online published on Sep 30, 2018

Copyright © A. Srivastava, A. Pillai, D. J. Gupta . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: A. Srivastava, A. Pillai, D. J. Gupta, “Study of Clique Based Community Detection Algorithms,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.9, pp.142-149, 2018.

MLA Style Citation: A. Srivastava, A. Pillai, D. J. Gupta "Study of Clique Based Community Detection Algorithms." International Journal of Computer Sciences and Engineering 6.9 (2018): 142-149.

APA Style Citation: A. Srivastava, A. Pillai, D. J. Gupta, (2018). Study of Clique Based Community Detection Algorithms. International Journal of Computer Sciences and Engineering, 6(9), 142-149.

BibTex Style Citation:
@article{Srivastava_2018,
author = {A. Srivastava, A. Pillai, D. J. Gupta},
title = {Study of Clique Based Community Detection Algorithms},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {9 2018},
volume = {6},
Issue = {9},
month = {9},
year = {2018},
issn = {2347-2693},
pages = {142-149},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=2835},
doi = {https://doi.org/10.26438/ijcse/v6i9.142149}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i9.142149}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=2835
TI - Study of Clique Based Community Detection Algorithms
T2 - International Journal of Computer Sciences and Engineering
AU - A. Srivastava, A. Pillai, D. J. Gupta
PY - 2018
DA - 2018/09/30
PB - IJCSE, Indore, INDIA
SP - 142-149
IS - 9
VL - 6
SN - 2347-2693
ER -

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Abstract

Social networks are generally represented as graphs (nodes represent users and edges represent their associations). Community in a social network means group of people which are more closely connected to each other as compared to their connection with rest of the people in the network. Clique in a graph is a subgraph such that each node in the subgraph is connected to every other node of this subgraph (complete subgraph). In this way clique is strict version of community. Community detection in social networks has attracted researchers effectively due to its wide range of applications. Cliques, having similar characteristics, prove to be highly applicable in community detection process. There are several community detection techniques in the literature which are developed around cliques. Generally these techniques fall into category of clique percolation methods. Clique percolation is a prominent approach that is based on k-cliques in the graph. This paper represents a detailed discussion of significant k-clique based techniques existing in community detection literature.

Key-Words / Index Term

Social Graph; Clique, Community Detection, Social Network Analysis

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