符号网络链接预测算法研究综述  

Survey of Link Prediction Algorithms in Signed Networks

作　　者：刘苗苗 扈庆翠 郭景峰[3] 陈晶[3] LIU Miao-miao;HU Qing-cui;GUO Jing-feng;CHEN Jing(School of Computer&Information Technology,Northeast Petroleum University,Daqing,Heilongjiang 163318,China;The Key Laboratory for Oil Big Data and Intelligent Analysis of Heilongjiang Province,Daqing,Heilongjiang 163318,China;School of Information Science and Engineering,Yanshan University,Qinhuangdao,Hebei 066004,China)

机构地区：[1]东北石油大学计算机与信息技术学院,黑龙江大庆163318 [2]黑龙江省石油大数据与智能分析重点实验室,黑龙江大庆163318 [3]燕山大学信息科学与工程学院,河北秦皇岛066004

出　　处：《计算机科学》2020年第2期21-30,共10页Computer Science

基　　金：国家自然科学基金项目(61602401,61871465);黑龙江省自然科学基金项目(LH2019F042);东北石油大学青年基金项目(2018QNQ-01)~~

摘　　要：符号网络链接预测包括网络结构上两个节点间未知链接的可能性预测与符号预测两方面,其相关研究对于分析和理解符号网络的拓扑结构、功能及演化行为具有十分重要的意义,在个性化推荐、态度预测、蛋白质交互作用研究等领域有着重大的应用价值。文中综述了符号网络链接预测问题的研究成果,介绍了相关概念、符号网络的理论基础、常用符号网络数据集以及预测精度评价标准;将目前主要的符号网络链接预测算法按照设计思路分为有监督学习与无监督学习两大类,详细阐述了每种算法的主要思想;归纳总结了符号网络链接预测问题的特点和规律,讨论了目前存在的问题并指出了面临的挑战和未来可能的发展方向。这能为信息学、生物学、社会学等领域的相关研究人员提供有益参考。Link prediction in signed networks includes the possibility prediction of link existence or establishment and the sign prediction of unknown links between two nodes in the network.Related research is of great significance for analyzing and understanding the topological structure,function and evolutionary behaviors of signed networks,and has great application value in the fields of personalized recommendation,attitude prediction and protein interaction research and other fields.This paper reviewed the research results of link prediction in signed networks,and introduced related concepts,theoretical basis,commonly used data sets and evaluation indexes of link prediction accuracy of signed networks.According to the design idea,link prediction algorithms in signed networks were mainly divided into two categories,namely supervised and unsupervised machine learning method.The main idea of each algorithm was elaborated in detail.The characteristics,rules and existing problems of link prediction in signed networks were discussed,and the challenges and possible directions in the future were also pointed out,which can provide useful reference for relevant researchers in the fields of informatics,biology and sociology and so on.

关 键 词：符号网络 链接预测 结构平衡理论 机器学习 符号预测 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]