A Quad Motifs Index for Directed Link Prediction

Network motif is a sub-graph pattern may reflect structure functions or reveal underneath mechanics. Some scholars have used triadic motifs for link prediction and achieve convincing results. But most of them ignore the effectiveness of quad motifs in calculating the similarity of two endpoints. In this article, a new method based on quad motifs is proposed. Two winner motifs are chosen among 199 sub-graphs. Local information of motifs is also taken into consideration. Experiments on nine real networks show that the index we proposed can improve prediction accuracy, compared with seven well-known measures.