网络与信息安全学报 ›› 2020, Vol. 6 ›› Issue (5): 89-100.doi: 10.11959/j.issn.2096-109x.2020059

• 学术论文 • 上一篇    

基于广义共同邻居的有向网络链路预测方法

赵学磊(),季新生,刘树新,赵宇   

  1. 信息工程大学,河南 郑州 450001
  • 修回日期:2020-02-13 出版日期:2020-10-01 发布日期:2020-10-19
  • 作者简介:赵学磊(1996- ),男,河北石家庄人,信息工程大学硕士生,主要研究方向为复杂网络链路预测|季新生(1968- ),男,河南驻马店人,信息工程大学教授、博士生导师,主要研究方向为网络空间安全、移动通信网络安全、拟态安全|刘树新(1987- ),男,山东潍坊人,信息工程大学助理研究员,主要研究方向链路预测、通信网络安全|赵宇(1984- ),男,吉林辽源人,信息工程大学讲师,主要研究方向为移动通信网络、新型网络体系结构
  • 基金资助:
    国家自然科学基金(61803384)

Link prediction methods based on generalized common neighbor in directed network

Xuelei ZHAO(),Xinsheng JI,Shuxin LIU,Yu ZHAO   

  1. Information Engineering University,Zhengzhou 450001,China
  • Revised:2020-02-13 Online:2020-10-01 Published:2020-10-19
  • Supported by:
    The National Natural Science Foundation of China(61803384)

摘要:

链路预测利用已知网络节点及结构等信息预测网络未知连接或未来连接。现有主流方法多应用于无向网络,而且部分有向链路预测方法忽视了共同邻居在有向网络下的多样异构特征。针对上述问题,提出了一种广义共同邻居算法。该方法首先对有向网络定义了广义共同邻居,通过网络中有向邻居异构体的连边概率衡量不同结构对连边贡献程度,然后利用该定义对现有的局部相似性指标进行了优化,重定义8种基于广义共同邻居的有向相似性指标。在 12 个数据集上的实验表明,所提方法在两个衡量指标下普遍提升了现有预测指标性能。

关键词: 有向网络, 链路预测, 共同邻居, 异构融合

Abstract:

Link prediction aims to predict missing or future links through currently observed information of network.Existing mainstream methods are mostly applied to undirected network,and some methods designed for directed network ignored the diverse heterogeneous features of common neighbor.For this problem,a generalized common neighbor algorithm was proposed.Firstly,a generalized common neighbor was defined for the directed network.Then the degree of contribution of different structures was measured by the joint edge probability of the directed neighbor isomers,and the existing undirected local similarity index is improved by the new definition,redefining eight kinds of directed similarity indicators based on generalized common neighbor.Experiments on 12 datasets show that proposed method generally improves the performance of existing predictive indicators under two metrics.

Key words: directed network, link prediction, common neighbor, heterogeneous fusion

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