Temporal‐aware and sparsity‐tolerant hybrid collaborative recommendation method with privacy preservation

Author:

Meng Shunmei12ORCID,Li Qianmu1,Zhang Jing1,Lin Wenmin3,Dou Wanchun2

Affiliation:

1. School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing China

2. State Key Laboratory for Novel Software Technology Nanjing University Nanjing China

3. Department of Computer Science Hangzhou Dianzi University Hangzhou China

Funder

National Basic Research Program of China

National Natural Science Foundation of China

State Key Laboratory of Novel Software Technology

Fundamental Research Funds for the Central Universities

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Theoretical Computer Science,Software

Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. An improved collaborative filtering model based on time weighted correlation coefficient and inter-cluster separation;International Journal of Machine Learning and Cybernetics;2023-05-18

2. LSH-based missing value prediction for abnormal traffic sensors with privacy protection in edge computing;Complex & Intelligent Systems;2023-03-02

3. Privacy-preserving quality prediction for edge-based IoT services;Future Generation Computer Systems;2021-01

4. Data Privacy Protection of Industrial Blockchain;Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering;2021

5. Security-Driven hybrid collaborative recommendation method for cloud-based iot services;Computers & Security;2020-10

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