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