信息网络安全 ›› 2020, Vol. 20 ›› Issue (9): 97-101.doi: 10.3969/j.issn.1671-1122.2020.09.020

• 入选论文 • 上一篇    下一篇

一种基于改进DynamicTriad模型的动态链路预测方法

夏天雨, 顾益军()   

  1. 中国人民公安大学信息网络安全学院,北京 100038
  • 收稿日期:2020-07-16 出版日期:2020-09-10 发布日期:2020-10-15
  • 通讯作者: 顾益军 E-mail:guyijun@ppsuc.edu.cn
  • 作者简介:夏天雨(1998—),男,山东,硕士研究生,主要研究方向为网络空间安全|顾益军(1968—),男,江苏,教授,博士,主要研究方向为网络安全与执法
  • 基金资助:
    公安部技术研究计划竞争性遴选项目(2019JZX009)

A Dynamic Link Prediction Method Based on Improved Dynamic Triad Model

XIA Tianyu, GU Yijun()   

  1. College of Information and Cyber Security, People’s Public Security University of China, Beijing 100038, China
  • Received:2020-07-16 Online:2020-09-10 Published:2020-10-15
  • Contact: Yijun GU E-mail:guyijun@ppsuc.edu.cn

摘要:

针对动态社交网络的链路预测,文章提出了一种改进的DynamicTriad模型,该模型以动态三元闭环结构为载体,三个顶点组成一个基本网络单元,结合网络同质性和节点相似性指标,对动态网络进行建模,跨时间片对每个节点进行向量表示,从而实现社交网络个体行为的动态预测,并通过t+1时段的嵌入向量验证t时段的预测效果。实验表明,该模型在动态表示节点关系的同时,链路预测效果优于传统算法,支持对动态社交网络的建模和分析。

关键词: 社交网络, 动态网络, 链路预测

Abstract:

Concerning dynamic social network link prediction, the paper proposed an improved DynamicTriad model. The dynamic triadic closure structure was the carrier, and three vertices formd a basic network unit. Combined with the network homophily and similarity index, the dynamic network was represented dynamically and each node was represented in different time slices, as to realize the dynamic individual behavior prediction of social network. Moreover, the t+1 time embedding vector was used to validate t time prediction effect. Experiments show that the improved model represents the relationship between nodes dynamically, and the effect of link prediction is better than the traditional algorithms. Besides, the proposed method supports the modeling and analysis of dynamic social network.

Key words: social network, dynamic network, link prediction

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