基于资源分配与偏好连接的局部路径链路预测算法  

Local Path Link Prediction Algorithm Based on Resource Allocation and Preferential Attachment

作　　者：陆圣宇 欧锋[1] 黄清元 刘宝 路振民 汤凌韬 LU Shengyu;OU Feng;HUANG Qingyuan;LIU Bao;LU Zhenmin;TANG Lingtao(Jiangnan Institute of Computing Technology,Wuxi,Jiangsu 214083,China)

机构地区：[1]江南计算技术研究所

出　　处：《计算机工程》2019年第9期316-320,共5页Computer Engineering

基　　金：国家重点研发计划“全球变化及应对”专项“大规模多模式多过程地球系统模式耦合平台开发”(2016YFA0602200)

摘　　要：针对复杂网络中基于结构相似性的链路预测问题,在对比现有链路预测算法相似性指标的基础上,结合资源分配算法中节点资源共享概念和偏好连接算法中节点度与连边概率关系,同时综合局部路径,定义一个相似性指标LRPA,并据此提出一种新的链路预测算法。在经典复杂网络数据集和真实比特币OCT交易网络中进行预测,实验结果表明,该算法能准确预测连边结构以及比特币用户的交易模式。To address the link prediction problem based on structural similarity in complex networks,based on the comparision of the similarity indexes of the existing link prediction algorithms,this paper defines a similarity index LRPA.LRPA is based on the node resource sharing concept in the resource allocation algorithm,the relationship between node degree and joint edge probability in the preferential attachment algorithm,and the local path. Based on LRPA,a new link prediction algorithm is proposed.The predictions are performed on the classical complex network datasets and the real bitcoin OCT trading network,experimental results show that,the proposed algorithm can accurately predict the edge structure and the trading mode of the bitcoin users.

关 键 词：复杂网络 链路预测 资源分配 偏好连接 局部路径 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]