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2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) (2016)
San Francisco, CA, USA
Aug. 18, 2016 to Aug. 21, 2016
ISBN: 978-1-5090-2847-4
pp: 1384-1385
Yehonatan Cohen , Computer Science Department, Ben-Gurion University of the Negev, Be'er-Sheva, Israel
Danny Hendler , Computer Science Department, Ben-Gurion University of the Negev, Be'er-Sheva, Israel
Amir Rubin , Computer Science Department, Ben-Gurion University of the Negev, Be'er-Sheva, Israel
ABSTRACT
We present NECTAR, a community detection algorithm that generalizes Louvain method's local search heuristic for overlapping community structures. NECTAR chooses dynamically which objective function to optimize based on the network on which it is invoked. Our experimental evaluation on both synthetic benchmark graphs and real-world networks, based on ground-truth communities, shows that NECTAR provides excellent results as compared with state of the art community detection algorithms.
INDEX TERMS
Linear programming, Detection algorithms, Social network services, Complex networks, Clustering algorithms, Heuristic algorithms, Physics
CITATION

Y. Cohen, D. Hendler and A. Rubin, "Node-centric detection of overlapping communities in social networks," 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), San Francisco, CA, USA, 2016, pp. 1384-1385.
doi:10.1109/ASONAM.2016.7752423
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