Revision as of 14:42, 2 April 2015

Louvain Clustering

The Louvain clustering tries to optimize modularity in a greedy fashion by randomly moving nodes from one cluster to another in multiple levels.

The algorithm is:

start with each node being a singleton cluster:
consider nodes in random order
repeat as long as cluster membership changes
- for each node : remove it from its current cluster and add it to the cluster with the highest modularity gain
aggregate the resulting clustering to a new graph and continue with step 1 (as long as modularity improves).

Practically, the algorithm seems to scale well for large graphs.

Fast unfolding of communities in large networks, Vincent D Blondel, Jean-Loup Guillaume, Renaud Lambiotte, Etienne Lefebvre, Journal of Statistical Mechanics: Theory and Experiment 2008 (10), P10008 (12pp) doi: 10.1088/1742-5468/2008/10/P10008. ArXiv: http://arxiv.org/abs/0803.0476
"The Louvain method for community detection in large networks" Vincent Blondel http://perso.uclouvain.be/vincent.blondel/research/louvain.html

@@ Line 7: / Line 7: @@
 # start with each node being a singleton cluster:
 # consider nodes in random order
-# repeat as long as cluster membership changes, consider nodes in a random order
+# repeat as long as cluster membership changes
 #* for each node : remove it from its current cluster and add it to the cluster with the highest modularity gain
 # aggregate the resulting clustering to a new graph and continue with step 1 (as long as modularity improves).