| 基于非负矩阵分解的隐私保护协同过滤算法 |
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| 引用本文： | 李涛,王建东.基于非负矩阵分解的隐私保护协同过滤算法[J].信息与控制,2008,37(6):1-1. |
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| 作者姓名： | 李涛 王建东 |
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| 作者单位： | 1. 南京航空航天大学信息科学与技术学院,江苏,南京,210016;南京信息工程大学电子与信息工程学院,江苏,南京,210044
2. 南京航空航天大学信息科学与技术学院,江苏,南京,210016 |
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| 摘 要： | 提出一种基于非负矩阵分解的隐私保护协同过滤推荐算法．该算法在用户数据收集过程中采用随机扰动技术，并使用非负矩阵分解对数据进行处理，从而形成隐私保护功能，并在此基础上产生推荐．理论分析和实验结果表明，该算法在保护用户个人隐私的基础上，能够产生具有一定精确性的推荐结果.
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| 关 键 词： | 非负矩阵分解 隐私保护 协同过滤 推荐系统 |
A Privacy-Preserving Collaborative Filtering Algorithm Based on Non-negative Matrix Factorization |
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| LI Tao,WANG Jian-dong.A Privacy-Preserving Collaborative Filtering Algorithm Based on Non-negative Matrix Factorization[J].Information and Control,2008,37(6):1-1. |
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| Authors: | LI Tao WANG Jian-dong |
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| Affiliation: | LI Tao~(1,2) WANG Jian-dong~1 (1.College of Information Science , Technology,Nanjing University of Aeronautics , Astronautics,Nanjing 210016,China,2.College of Electronic , Information Engineering,Nanjing University of Information Science , Technology,Nanjing 210044,China) |
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| Abstract: | A privacy-preserving collaborative filtering algorithm based on non-negative matrix factorization(NMF) is presented.The randomized perturbation techniques are used in the course of user data collection,and the collected data are processed by NMF,therefore,the users' privacy can be protected.The algorithm produces the recommendation based on the data of the privacy-preserving users.Theoretical analysis and experiment results show that the algorithm can not only protect the users' privacy,but also generate re... |
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| Keywords: | non-negative matrix factorization(NMF) privacy-preserving collaborative filtering recommendation system |
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