As we wrap up the Latin American School on Recommender Systems, we take a long-term look at recommender systems as tools for assisting and influencing human decision-making. Starting from the early origins of these system through today’s commercial applications, we look at how recommender systems design relates to human perception, cognition, and tasks. We then look at how recommender systems can be evaluated and tuned to achieve human-focused objectives, and explore open questions that can inform a future research agenda.
Short Bio
Joseph A. Konstan is Distinguished McKnight University Professor and Distinguished University Teaching Professor in the Department of Computer Science and Engineering, and Associate Dean for Research in the College of Science and Engineering at the University of Minnesota, where he formerly led the GroupLens Center for Social and Human-Centered Computing. His research addresses a variety of human-computer interaction issues, including recommender systems and social computing. He is best known for his work in collaborative filtering recommenders (the GroupLens project won the ACM Software Systems Award and one of its papers was recognized with the Seoul Test of Time Award), and for the creation of the MovieLens recommender system and datasets. Dr. Konstan received his Ph.D. from the University of California, Berkeley in 1993. He is a Fellow of the ACM, IEEE, and AAAS and a member of the CHI Academy. He chaired the first ACM Conference on Recommender Systems in 2007, and has served on its steering committee since its inception.