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Differential privacy in collaborative filtering recommender systems: a review

State-of-the-art recommender systems produce high-quality recommendations to support users in finding relevant content. However, through the utilization of users' data for generating recommendations, recommender systems threaten users' privacy. To alleviate this threat, often, differential...

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Detalles Bibliográficos
Autores principales: Müllner, Peter, Lex, Elisabeth, Schedl, Markus, Kowald, Dominik
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10601453/
https://www.ncbi.nlm.nih.gov/pubmed/37901117
http://dx.doi.org/10.3389/fdata.2023.1249997