Parallel Multi-label Propagation for Overlapping Community Detection in Large-Scale Networks

摘要

In recent years, with the rapid growth of network scale, it becomes difficult to detect communities in large-scale networks for many existing algorithms. In this paper, a novel Parallel Multi-Label Propagation Algorithm (PMLPA) is proposed to detect the overlapping communities in networks. PMLPA employs a new label updating strategy using ankle-value in the label propagation procedure during each iteration. The new algorithm is implemented in the Spark framework for its power in distributed parallel computation. Experiments on artificial and real networks show that PMLPA is effective and efficient in community detection in large-scale networks.