METHOD OF CREATING CONTENT RECOMMENDATIONS BASED ON USER RATINGS OF CONTENT WITH IMPROVED USER PRIVACY

摘要

A recommendation system provides improved privacy under the local model, in which users store their data locally, and differential privacy is ensured through randomization of ratings under the control of the user before submitting data to the recommender system. The recommender system performs a clustering on the data collected from a plurality of users and returns the results to the users. The users' devices fine-tune the recommendation based on locally stored, non-randomized ratings. The recommendation system provides a user-adjustable degree of privacy while still allowing for generating recommendations with a decent accuracy.