Link Prediction Model Based on Weighted Nonnegative Matrix Factorization

WANG Meng-meng; ZUO Wan-li; WANG Ying

doi:10.3969/j.issn.0372-2112.2016.10.016

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Link Prediction Model Based on Weighted Nonnegative Matrix Factorization

更新时间：2025-07-16

- Link Prediction Model Based on Weighted Nonnegative Matrix Factorization
- Acta Electronica Sinica Vol. 44, Issue 10, Pages: 2391-2397(2016)
- 作者机构：
  
  1. 吉林大学计算机科学与技术学院,吉林,长春,130012
  2. 符号计算与知识工程教育部重点实验室(吉林大学),吉林,长春,130012
  3. 吉林大学计算机科学与技术学院,吉林,长春,130012
  4. 符号计算与知识工程教育部重点实验室(吉林大学),吉林,长春,130012
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China (No.61300148);Science and Technology Development Project of Jilin Province (No.20130206051GX);Science and Technology Program of Jilin Province (No.20130522112JH);Fundamental Fund for Science Frontier and Cross Project of Jilin University (No.201103129)
- DOI：10.3969/j.issn.0372-2112.2016.10.016
  CLC： TP393.03
- Published Online：25 October 2016，
  
  Published：2016
- 稿件说明：
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WANG Meng-meng, ZUO Wan-li, WANG Ying. Link Prediction Model Based on Weighted Nonnegative Matrix Factorization[J]. Acta Electronica Sinica, 2016, 44(10): 2391-2397.
DOI：

WANG Meng-meng, ZUO Wan-li, WANG Ying. Link Prediction Model Based on Weighted Nonnegative Matrix Factorization[J]. Acta Electronica Sinica, 2016, 44(10): 2391-2397. DOI： 10.3969/j.issn.0372-2112.2016.10.016.

摘要

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.

Abstract

Targeted at on-line microbloggings

on the basis of weighted and dynamic link prediction features

we utilize 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 effectiveness of the proposed framework.Further experiments are conducted to understand the importance of features' weights and temporal information in link prediction.

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