Dagstuhl-Seminar — Evaluation Perspectives of Recommender Systems: Driving Research and Education

While recommender systems is largely an applied field, their evaluation builds on and intersects theories from information retrieval, machine learning, and human-computer interaction. Historically, the theories and evaluation approaches in these fields are very different. Thoroughly evaluating recommender systems requires integrating all perspectives. Hence, this seminar will bring together experts from these fields and serve as a vehicle for discussing and developing the state-of-the-art and practice of evaluating recommender systems. The seminar will set the ground for developing recommender systems evaluation metrics, methods, and practices through collaborations and discussions between participants from diverse backgrounds, e.g., academic and industry researchers, industry practitioners, senior and junior. We emphasize the importance of getting and keeping the big picture of a recommender system’s performance in its context of use, for which it is ultimate to incorporate the technical and the human element. We will set the basis for the next generation of researchers, apt to evaluate and advance recommender systems thoroughly.