Beyond Relevance: Recommender Systems for Tourism with Users and Society in Mind
Adir Solomon, University of Haifa
Abstract
Recommender systems for tourism have traditionally focused on predicting where users are likely to go next. However, tourism decisions are shaped by broader human and societal considerations. In this lecture, we argue that tourism recommender systems should move beyond relevance and account for user experience, safety, and informed decision-making. Drawing on recent studies, we discuss how tourism recommender systems can incorporate richer notions of traveler value, consider real-world risks as part of the recommendation process, and provide users with more complete information to support their decisions. Building on these insights, we will conclude by discussing challenges and future directions for the next generation of tourism recommender systems, including how to balance multiple objectives, integrate contextual features, and design recommendation experiences that are more human-centered.
Biography
Dr. Adir Solomon is an Assistant Professor in the Department of Information Systems at the University of Haifa. His research focuses on recommender systems, user modeling, and machine learning, with an emphasis on developing human-centered and responsible systems. His work explores how recommender systems can move beyond traditional relevance and accuracy objectives by incorporating contextual factors and broader user and societal considerations. He has applied these ideas across several domains, including tourism and mobility, healthcare, and computational criminology. His research has been published in leading journals and conferences, including Computers, Environment and Urban Systems, Travel Behaviour and Society, ACM RecSys, and ACM IUI. Adir is also actively involved in the recommender systems research community through conference organization, program committee service, and reviewing for leading conferences and journals.