Recommendation under Constraints

Recommendation systems that help users navigate through information by delivering the right content at the right time, are a part of our every day lives. Although a lot of progress has happened regarding the development of recommendation systems for unconstrained offline settings, there are still challenges when deploying such systems in constrained interactive settings. This talk will begin by reviewing the state-of-the-art in offline unconstrained recommendation. Then it will discuss methods for the particular constrained settings of (i) limited screen size of the devices, and (ii) limited capacities of the candidate items for recommendation. The talk will continue with a benchmarking study comparing the proposed methods with the state-of-the-art.