Generalized Louvain Method for Community Detection in Large Networks

De Meo, Pasquale and Ferrara, Emilio and Fiumara, Giacomo and Provetti, Alessandro (2011) Generalized Louvain Method for Community Detection in Large Networks. [Conference Paper]

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In this paper we present a novel strategy to discover the community structure of (possibly, large) networks. This approach is based on the well-know concept of network modularity optimization. To do so, our algorithm exploits a novel measure of edge centrality, based on the k-paths. This technique allows to efficiently compute a edge ranking in large networks in near linear time. Once the centrality ranking is calculated, the algorithm computes the pairwise proximity between nodes of the network. Finally, it discovers the community structure adopting a strategy inspired by the well-known state-of-the-art Louvain method (henceforth, LM), efficiently maximizing the network modularity. The experiments we carried out show that our algorithm outperforms other techniques and slightly improves results of the original LM, providing reliable results. Another advantage is that its adoption is naturally extended even to unweighted networks, differently with respect to the LM.

Item Type:Conference Paper
Additional Information:ISBN:
Subjects:Computer Science > Artificial Intelligence
Computer Science > Dynamical Systems
ID Code:7667
Deposited By: Ferrara, Dr. Emilio
Deposited On:27 Oct 2011 01:34
Last Modified:27 Oct 2011 01:34

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