Design and Evaluation of Recommender Systems
Abstract: Recommender Systems (RSs) help users search large amounts of contents by allowing them to identify the items that are likely to be more attractive or useful. RSs play an important role in many domains (e.g., e-commerce, e-tourism, entertainment), as they can potentially augment the users’ trust towards an application and orient their decisions or actions towards specific directions. The goal of this lecture is to give participants a solid background of how to design and evaluate RSs, with a focus on user experience aspects, and to provide pragmatic guidelines to perform these activities more effectively. The lecture is structured into two parts. The first part will provide a general overview of recommender systems and their design issues. The second part will analyze “off-line” (system-centric) evaluation techniques.
Short Bio: Paolo Cremonesi is professor of Recommender Systems at the Computer Science Department of Politecnico di Milano. Paolo is also the co-founder of Moviri, the first and most successful start-up from Politecnico di Milano, now a holding company with more than 200 employees and offices in Europe, US and Asia. Paolo holds an MSc in Aerospace Engineering and a PhD in Computer Science. His research interests include high-performance computing and recommender systems. He has published more than 200 papers in refereed journals, conferences and book chapters, and holds 5 patents.