@inproceedings{54fcc47395d6424caeea784c63356609,
title = "Detecting Highly Overlapping Community Structure by Model-based Maximal Clique Expansion",
abstract = "In this paper, we propose an efficient overlapping community detection method using a seed set expansion approach. In particular, we make an original use of a particular concept of graph theory, called chordal graph, to discover densely connected structures in social interactions based on maximal cliques. Indeed, a chordal graph possesses a number of interesting and useful properties that can help us to efficiently recover all maximal cliques of a given graph. Then, we develop new seeding strategies based on different fitness functions for discovering meaningful communities. Experimental results demonstrate the effectiveness and the efficiency of our overlapping community model in a variety of real graphs.",
keywords = "Chordal graphs, Community Detection, Maximal cliques, Social Networks",
author = "Said Jabbour and Nizar Mhadhbi and Badran Radaoui and Lakhdar Sais",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 IEEE International Conference on Big Data, Big Data 2018 ; Conference date: 10-12-2018 Through 13-12-2018",
year = "2018",
month = jul,
day = "2",
doi = "10.1109/BigData.2018.8621868",
language = "English",
series = "Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1031--1036",
editor = "Naoki Abe and Huan Liu and Calton Pu and Xiaohua Hu and Nesreen Ahmed and Mu Qiao and Yang Song and Donald Kossmann and Bing Liu and Kisung Lee and Jiliang Tang and Jingrui He and Jeffrey Saltz",
booktitle = "Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018",
}