Parallel overlapping community discovery based on grey relational analysis

Discovering social communities or social circles from social networks is interesting and important for many applications like business advertisement, social recommendation and collaborative office. In this paper, by integrating grey relational analysis with the label propagation algorithm and the parallel framework, a new parallel algorithm for detecting overlapping communities is proposed. The similarity of the vertices is measured by the grey relational degree and the parallel computation primitives are employed to propagate the labels in parallel. The experiments on both the artificial and realworld networks demonstrate that the new algorithm is effective in detecting overlapping social communities.