电子学报2016，Vol.44Issue(10)：2391-2397,7.DOI:10.3969/j.issn.0372-2112.2016.10.016
基于加权非负矩阵分解的链接预测算法
Link Prediction ModeI Based on Weighted Nonnegative Matrix Factorization
摘要
Abstract
Targeted at on-line microbloggings,on the basis of weighted and dynamic link prediction features,we uti-lize nonnegative matrix factorization to predict existence and directivity of link from user-based and post-based dimension by employing relationship-based factor to constrain objective function.Experiments on real-world dataset demonstrate the effec-tiveness of the proposed framework.Further experiments are conducted to understand the importance of features’weights and temporal information in link prediction.关键词
有向链接预测/非负矩阵分解/特征权重/时间信息/动态社会网络Key words
directed link prediction/nonnegative matrix factorization/features’weights/temporal information/dy-namic social networks分类
信息技术与安全科学引用本文复制引用
王萌萌,左万利,王英..基于加权非负矩阵分解的链接预测算法[J].电子学报,2016,44(10):2391-2397,7.基金项目
国家自然科学基金（No．61300148）；吉林省科技发展计划（No．20130206051GX）；吉林省科技计划（No．20130522112JH）；吉林大学基本科研业务费科学前沿与交叉项目 （）
