An improved matrix factorization with local differential privacy based on piecewise mechanism for recommendation systems-Reference-Cited by-同舟云学术

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An improved matrix factorization with local differential privacy based on piecewise mechanism for recommendation systems

Published:2023-04 Issue: Volume:216 Page:119457
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Wang Yong^ORCID,Gao Mingxing^ORCID,Ran Xun,Ma Jun^ORCID,Zhang Leo Yu^ORCID

Funder

Natural Science Foundation of Chongqing

Chongqing Municipal Education Commission

National Natural Science Foundation of China

Chongqing University of Posts and Telecommunications

Ministry of Education of the People's Republic of China

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference34 articles.

1. Privacy-preserving collaborative filtering algorithm based on local differential privacy;Bao;China Communications,2021

2. “You might also like:” Privacy risks of collaborative filtering;Calandrino,2011

3. Collaborative filtering with privacy;Canny,2002

4. Differentially private user-based collaborative filtering recommendation based on K-means clustering;Chen;Expert Systems with Applications,2021

5. An improved matrix factorization based model for many-objective optimization recommendation;Cui;Information Sciences,2021

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