一种有向复杂网络生成模型的建立方法  

Link Formation Model for Directed Complex Networks

作　　者：刘大伟[1] 杨文峰 王海洋[1,3] 刘玮[1,3] LIU Da-wei;YANG Wen-feng;WANG Hai-yang;LIU Wei(Institute of Network Technology,Institute of Computing Technology（YANTAI）,Chinese Academy of Sciences,Yantai 264005,Chin;Suzhou Software Technology Co.Ltd.,China Mobile Communication Corp.,Suzhou 215000,China;Institute of Computing Technology,Chinese Academy of Sciences,Beijing 100090,China)

机构地区：[1]中国科学院计算技术研究所烟台分所烟台中科网络技术研究所,山东烟台264005 [2]中移(苏州)软件技术有限公司,江苏苏州215000 [3]中国科学院计算技术研究所网络数据科学与技术重点实验室,北京100090

出　　处：《小型微型计算机系统》2018年第10期2197-2201,共5页Journal of Chinese Computer Systems

基　　金：国家"八六三"高技术研究发展计划项目(2014AA015204)资助;山东省重点研发计划项目(2016GGX101020)资助;虚拟现实技术与系统国家重点实验室开放基金项目(BUAA-VR-17KF-13)资助

摘　　要：对于很多网络数据挖掘的应用,如链路预测、朋友推荐、社区发现和网络演化等,理解网络链路的生成模式是重要的基础性工作.随着复杂网络研究的发展,越来越多的网络应用可以抽象为有向网络的形式,但现有的研究大多关注于无向网络的范围,有向网络的生成机制亟待深入研究.通过分析有向网络的局部结构,基于微观组织模式,提出一种有向复杂网络生成模型的建立方法:局部相关位置方法.同时提出一种对应的链路预测算法来检验生成模型.在各种真实有向网络数据集中的实验结果证明了网络生成模型的有效性.Understanding the link patterns of networks is important for many tasks in link mining such as link prediction, friend recommendation, community detection and network evolution models. Recently,more and more models based on directed networks are present to formulate the underlying networks in various applications. However,most existing studies of link analysis are focused only in the undirected settings. In this paper, a theory of link formation named as Local Relative Position Theory is proposed by analyzing the local structures to reveal the microscopic organizing principles of directed networks. Then a corresponding link prediction algorithm is proposed combing with existing microscopic mechanisms. Extensive experiments were applied on real world directed networks and the results testified the effectiveness of our link formation theory.

关 键 词：链路生成 有向网络 网络挖掘 链路预测 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]