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Missing link prediction in indirected and un-weighted network is an open andchallenge problem which has been studied intensively in recent years. In thispaper, we studied the relationships between community structure and linkformation and proposed a Fast Block probabilistic Model(FBM). In accordancewith the experiments on four real world networks, we have yielded very goodaccuracy of missing link prediction and huge improvement in computingefficiency compared to conventional methods. By analyzing the mechanism of linkformation, we also discovered that clique structure plays a significant role tohelp us understand how links grow in communities. Therefore, we summarizedthree principles which are proved to be able to well explain the mechanism oflink formation and network evolution from the theory of graph topology.

Cliques in complex networks reveal link formation and community evolution