Privacy Preserving Recommender Systems

Author(s)	Akash Sharma, Niraj Kumar Goswami, Bardan Luitel
Country	India
Abstract	Privacy-preserving recommender systems are a growing area of research and development due to concerns about user privacy in digital environments. This review paper examines the existing methodologies and techniques used in designing and implementing these systems, focusing on their application in e-commerce, social media, and personalized content delivery platforms. The paper discusses the fundamental principles of privacy-preserving recommender systems and the motivations behind their need. The review also highlights the challenges and opportunities associated with existing privacy-preserving recommender systems, including scalability, efficiency, and usability. In this review, we focus on the challenges and opportunities that come with recommendation systems, and compare different systems to see how well they scale up, how fast they work, and how easy they are to use.
Keywords	Privacy Preserving, Recommender Systems, User privacy, Data Protection, Privacy-preserving recommender systems
Field	Computer
Published In	Volume 6, Issue 3, May-June 2024
Published On	2024-05-14
Cite This	Privacy Preserving Recommender Systems - Akash Sharma, Niraj Kumar Goswami, Bardan Luitel - IJFMR Volume 6, Issue 3, May-June 2024. DOI 10.36948/ijfmr.2024.v06i03.20301
DOI	https://doi.org/10.36948/ijfmr.2024.v06i03.20301
Short DOI	https://doi.org/gtt8sz

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International Journal For Multidisciplinary Research