A Comprehensive Survey on Privacy-Preserving Techniques in Federated Recommendation Systems

A Comprehensive Survey on Privacy-Preserving Techniques in Federated Recommendation Systems

Big data is a rapidly growing field, and new developments are constantly emerging to address various challenges. One such development is the use of federated learning for recommendation systems (FRSs). An FRS provides a way to protect user privacy by training recommendation models using intermediate...

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Bibliographic Details
Main Authors: Muhammad Asad, Saima Shaukat, Ehsan Javanmardi, Jin Nakazato, Manabu Tsukada
Format: Article
Language:English
Published: MDPI AG 2023-05-01
Series:Applied Sciences
Subjects:
federated recommendation systems
privacy preserving
big data
data sharing
Online Access:https://www.mdpi.com/2076-3417/13/10/6201

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