Privacy-Preserving Collaborative Filtering Schemes

The privacy-preserving recommendation system enables us to evaluate the recommended value without leaking the private information of users to service providers. The large overhead in performing cryptographical operations in proportion to the number of users and the number of items is the current issue. In this article, we propose some efficient schemes reducing the preference matrix of the sets of items and users.