计算机科学 ›› 2018, Vol. 45 ›› Issue (6): 41-45.doi: 10.11896/j.issn.1002-137X.2018.06.007

• 第十四届全国Web信息系统及其应用学术会议 • 上一篇    下一篇

一种融合节点属性信息的社会网络链接预测方法

张昱, 高克宁, 于戈   

  1. 东北大学计算机科学与工程学院 沈阳110819
  • 收稿日期:2017-03-11 出版日期:2018-06-15 发布日期:2018-07-24
  • 作者简介:张 昱(1980-),男,博士生,讲师,CCF会员,主要研究方向为社会网络,E-mail:zhangyu@mail.neu.edu.cn;高克宁 教授,主要研究方向为Web信息处理、社会网络;于 戈 教授,博士生导师,主要研究方向为数据库理论与技术等,E-mail:yuge@mail.neu.edu.cn(通信作者)
  • 基金资助:
    本文受教育部基本科研业务费项目青年教师科研启动基金(N151603001),辽宁省科技攻关项目博士启动基金(201601026)资助

Method of Link Prediction in Social Networks Using Node Attribute Information

ZHANG Yu, GAO Ke-ning, YU Ge   

  1. School of Computer Science and Engineering,Northeastern University,Shenyang 110819,China
  • Received:2017-03-11 Online:2018-06-15 Published:2018-07-24

摘要: 随着大规模社会网络的发展,链接预测成为了一个重要的研究课题。研究了在社会网络中融合节点属性信息进行链接预测,在传统的社会-属性网络图模型的基础上,将节点属性的类别这一重要参量加入到网络构建中。基于此,提出了一系列为网络中不同类型的连边分配边权重的方法,最后通过随机游走的方法进行网络链接的预测。实验表明,所提链接预测方法相比同类方法有明显的效果提升。

关键词: 链接预测, 社会节点, 社会网络, 社会-属性网络, 属性节点

Abstract: With the development of large social networks,link prediction has become an important research subject.The link prediction problem in social networks using rich node attribute information was studied in this paper.Based on attribute-augmented social network model,which means rebuilding an augmented network by adding additional nodes with each node corresponding to an attribute,called social-attribute network,the classification of node attributes was added to the model as an important parameter.Several methods of assigning weights for different kinds of links were proposed.Then a random walk method was used for link prediction in the network.Experimental results reveal that this method has better performance compared with other similar methods.

Key words: Attribute node, Link prediction, Social network, Social node, Social-attribute network

中图分类号: 

  • TP311
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