Modified link prediction algorithm based on AdaBoost - Zu-feng WU; Qi LIANG; Qiao LIU; Zhi-guang QIN (Tongxin xuebao)
The mainstream of current link prediction algorithm based on network topology structure generally have the problem of low efficiency of recalls.Study found that the correct results from some of the link prediction algorithms are complementary,accordingly,the Boosting method was considered to improve it.According to whether there is a link relationship between the nodes,the problem was divided into two categories,thus the link prediction algorithm as a two classification problem was defined.Furthermore,the algorithm complementary principle to select a number of representative link prediction algorithms as weak classifiers was followed,and a novel link prediction algorithm based on the AdaBoost algorithm was come up.The experimental results on the data from real dataset like the arXiv paper cooperation network and E-mail network show that,the novel algorithm has a better accuracy than the current mainstream algorithms.