Organizers: Gediminas Adomavicius (University of Minnesota), Konstantin Bauman (Temple University), Bamshad Mobasher (De-Paul University Chicago), Alexander Tuzhilin (New York University) and Moshe Unger (Tel Aviv University)

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The primary goal of the CARS workshop is to reimagine the CARS topic and broadly discuss the main features of the next generation of CARS and application domains that may require the use of novel types of contextual information and cope with their dynamic properties in group recommendations and in online environments. In this respect, the main challenge of the next generation of CARS is to introduce more explainable, flexible, and comprehensive approaches to modeling and using contextual information. We also aim at discussing novel perspectives on how recommender systems can deal with the specific contextual situations that characterise the usage of RSs and bring together researchers with wide-ranging backgrounds to identify important research questions in that field, exchange ideas from different research disciplines, and, more generally, to facilitate discussion and innovation in the area of the next generation of context-aware recommender systems.This year we wish to emphasize novel applications and usages of context in recommender systems, such as context in group dynamics and group decision making, cognitive biases due to irrelevant contextual conditions in decision making, GUI strategies for increasing context awareness, and utilizing user personality and context interactions in CARS.