Before revision:  This entails not only predicting accurate preference estimates  as classical recommenders do, but also defining adequate fusion processes for aggregating user-to-user preferential information.
After revision:  This entails not only predicting accurate preference estimates upon user interaction data as classical recommenders do, but also defining adequate fusion processes for aggregating user-to-user preferential information.