中国科学技术大学学报 ›› 2020, Vol. 50 ›› Issue (1): 57-63.DOI: 10.3969/j.issn.0253-2778.2020.01.007

• 科研论文 • 上一篇    下一篇

基于互信息的复杂网络链路预测

齐方鹏   

  1. 中国科学技术大学电子科学与技术系,安徽合肥 230027
  • 收稿日期:2018-03-31 修回日期:2018-12-21 出版日期:2020-01-31 发布日期:2020-01-31
  • 通讯作者: 傅忠谦
  • 作者简介:齐方鹏,男,1992年生,硕士生. 研究方向:链路预测. E-mail:fpqi@mail.ustc.edu.cn

Link prediction in complex networks based on mutual information

QI Fangpeng   

  1. Department of Electronic Science and Technology, University of Science and Technology of China, Hefei 230027, China
  • Received:2018-03-31 Revised:2018-12-21 Online:2020-01-31 Published:2020-01-31

摘要: 互信息在复杂网络中的应用为解决链路预测问题提供了一个新的思路.传统的互信息方法(MI)不仅考虑了节点的邻居信息,还加入了共同邻居之间的结构信息,这种方法比传统的基于共同邻居的方法预测精度更高;但是该方法没有对共同邻居进行有效的区分,即没有考虑到共同邻居之间的差异性.为此进行了相应的改进,提出了改进的互信息方法(MMI),实验结果表明,MMI方法可以在一定程度上提高链路预测的精度.

关键词: 复杂网络, 链路预测, 互信息

Abstract: A new perspective of dealing with link prediction problem was derived due to the application of mutual information in complex networks. Traditional mutual information algorithm (MI) not only considers the neighbor information of nodes, but also the structural information of common neighbors. Although MI has better performance compared with traditional methods which are based on common neighbors, it doesn’t effectively differentiate between different common neighbors. A new algorithm (MMI) was proposed by considering the influence of different common neighbors, which performs better than MI in precision.

Key words: complex network, link prediction, mutual information