Journal on Communications ›› 2014, Vol. 35 ›› Issue (3): 116-123.doi: 10.3969/j.issn.1000-436x.2014.03.013

• Academic paper • Previous Articles     Next Articles

Modified link prediction algorithm based on AdaBoost

Zu-feng WU,Qi LIANG,Qiao LIU,Zhi-guang QIN   

  1. School of Computer Science and Engineering,University of Electronic Science and Technology of China,Chengdu 610054,China
  • Online:2014-03-25 Published:2017-08-17
  • Supported by:
    The National Natural Science Foundation of China;The National High Technology Research and Development Program of China (863 Program)

Abstract:

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.

Key words: link prediction, social network analysis, AdaBoost algorithm, recommended system, machine learning

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