New method for link prediction in directed networks based on triad patterns - Sheng CHANG; Hong MA; Shuxin LIU (网络与信息安全学报)
Almost all current studies on link prediction problem focus on undirected networks.Unfortunately,many complex networks in the real world are directed.Ignoring the direction of a link will overlook some important information or even make the prediction meaningless.Directly applying the methods for undirected networks to directed networks will reduce the accuracy of prediction.A new method for link prediction in directed networks based on triad patterns was proposed.The proposed metric compare the difference of triad structures between undirected and directed networks and use potential theory to filter the triad patterns.By statistics of triad closeness in various networks,new method calculate the similarity between nodes using the triad closeness index of a network as the weight for different triad patterns.Experiments on nine real networks show that accuracy of proposed method is 4.3% better than benchmark methods.