基于加权非负矩阵分解的链接预测算法

摘要

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.%本文针对在线微博，首先，基于带权动态链接预测特征集合，以用户社会关系因子约束目标函数，从用户概要和用户发布内容两个维度利用非负矩阵分解方法预测社会网络中链接的存在性和方向性。然后，在真实的数据集上验证了提出框架的有效性，并通过实验进一步证明了特征权重和时间信息在链接预测问题中的重要性。