Enhancing Privacy in Recommender Systems through Differential Privacy Techniques

Recommender systems have become essential tools for addressing information overload in the digital age. However, the collection and usage of user data for personalized recommendations raise significant privacy concerns. This research focuses on enhancing privacy in recommender systems through the application of differential privacy techniques, particularly in the domain of privacy-preserving data publishing.