Recommender systems are developed to help users in finding items that match their interests, needs, and preferences. Since the emergence of recommender systems, the majority of research in this area focused on improving predictive accuracy of recommendation. Much less attention has been paid to how users interact with the system and the efficacy of interface designs from users’ perspectives. The field has reached a point where it is necesary to look beyond algorithms, into users’ interactions,
decision making processes, and overall end user experience.

The IntRS workshop series focuses on the “human side” or recommender systems. Its goal is to integrate modern HCI approaches and theories of human decision making into the construction of recommender systems. It focuses particularly on the impact of interfaces on decision support and overall satisfaction. IntRS workshops have been previously held at RecSys 2016, 2017, and 2018.

The aim of the IntRS’19 workshop is to bring together researchers and practitioners exploring the topics of designing and evaluating novel intelligent interfaces for recommender systems in order to: (1) share research and techniques, including new design technologies and evaluation methodologies, (2) identify next key challenges in the area, and (3) identify emerging topics.
This workshop aims at establishing an interdisciplinary community with a focus on the interface design issues for recommender systems and promoting the collaboration opportunities between researchers and practitioners. We particularly encourage demos and mock-ups of systems to be used as a basis of a lively and interactive discussion in the workshop. In our opinion, the workshop will complement the technical aspects mainly
discussed at the Conference with specific topics related to cognitive modeling and decision making.