Adaptations of the k-Means Algorithm to Community Detection in Parallel Environments

In this paper we present preliminary results for a fast parallel adaptation of the well-known k-means clustering algorithm to graphs. We are going to use our method to detect communities in complex networks. For testing purposes we will use the graph generator of Lancichinetti et al., and we are going to compare our method with the OSLOM, CPM, and hub percolation overlapping community detection methods.