Mining the evolution of networks using Local-Cross-Communities-Paradigm
Department of Mathematics and Systems Science, College of Science, National University of Defense Technology Changsha, 410073, China
Received: 10 October 2013
Accepted: 2 December 2013
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.
PACS: 89.75.Hc – Networks and genealogical trees / 89.20.Ff – Computer science and technology / 89.65.-s – Social and economic systems
© EPLA, 2013