Abstract: The existing link prediction methods are mostly focused on structure link prediction like missing links,but few are about temporal link prediction according to unknown links in future,therefore a link prediction method based on association rules of frequent closed graphs was proposed.Dynamic networks are divided into training set and test test,and frequent closed subgraphs are extracted from training set based on Apriori algorithm,thus time-lag distribution matrix is built to represent the temporal association rules between frequent closed graphs,and then the structure in test set is predicted.The link prediction method was used in the dynamic networks of AS level Internet at different time scales,and experimental results show that this method can efficiently predict links in wavery dynamic networks with high precision.

Key words: Link prediction,Frequent closed graph,Temporal association,AS level Internet,Dynamic networks