Mining the evolution of networks using Local-Cross-Communities-Paradigm

Abstract

Mining how network evolves is a crucial topic in extracting underlying information from networks. Among all the mechanisms, Common Neighbor (CN) and Preferential Attachment (PA) are basic and efficient. Recently, a new framework named Local-Community-Paradigm (LCP) provides a self-organized mechanism about the evolution of networks. Via using community mechanism instead, we propose a variant named Local-Cross-Communities-Paradigm (LCCP). We compare the four mechanisms and test them on link prediction problems. Empirical analysis on twelve real networks show that LCCP performs better than CN, PA and LCP.