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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...
Autores principales: | Müllner, Peter, Lex, Elisabeth, Schedl, Markus, Kowald, Dominik |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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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 |
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