基于社区特征的平衡模块度最大化社交链接预测模型  

Community Features Based Balanced Modularity Maximization Social Link Prediction Model

作　　者：伍杰华[1,2] 沈静[1] 周蓓[1] WU Jie-hua;SHEN Jing;ZHOU Bei(Department of Computer Science,Guangdong Polytechnic of Industry and Commerce,Guangzhou 510510,China;College of Computer Science and Engineering,South China University of Technology,Guangzhou 510641,China)

机构地区：[1]广东工贸职业技术学院计算机工程系,广州510510 [2]华南理工大学计算机科学与工程学院,广州510641

出　　处：《计算机科学》2019年第3期253-259,共7页Computer Science

基　　金：广东省优秀青年教师培养计划项目(YQ2015177);广东省科技计划项目(2017ZC0348);广东高校重大科研项目与成果培育计划项目(2017GKTSCX009)资助

摘　　要：链接预测和社区发现是社交网络分析领域的两大研究方向。如何挖掘社区结构帮助提高链接预测效果具有十分重要的意义。在模块度最大化模型的基础上,提出一种基于社区结构特征提取与选择的链接预测方法。首先,在网络进化模型中引入基于社区结构的相似度指标建立局部特征,并利用影响力节点识别方法构建全局特征;然后,采用最小冗余最大相关度的特征选择算法度量特征之间的相互影响,并筛选出最有表示力的候选特征;最后,将基于经过上述步骤处理后的特征融入模块度最大化链接预测模型中。该算法在人工和真实两类数据集上与相关算法做了对比实验,结果证实了该算法的高效性,也表明了基于社区结构的特征提取与选择步骤的必要性。Link prediction and community detection are the two major research directions in the field of social network analysis.It is of great significance to explore the community structure and improve the link prediction effect.Based on the modularity maximization link prediction model,this paper proposed a link prediction method based on community structure feature extraction and selection.Firstly,the community structure based similarity index and influence node identification method are introduced into the network evolution model to obtain and link the local and global features respectively.Then,the feature selection algorithm with minimum redundancy and maximum correlation is used to measure the mutual influence,and the most expressive candidate features are filtered out.Finally,based on the above steps,the features are incorporated into the modularity maximization link prediction model.The algorithm was compared with related algorithms on both artificial and real datasets.The results verify the high efficiency of the algorithm and the necessity of feature extraction and selection based on community structure.

关 键 词：链接预测 社区特征 模块度 特征选择 社交网络 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]