IntRS: Joint Workshop on Interfaces and Human Decision Making for Recommender Systems

Recommender systems help users in finding items that match their interests, needs, and preferences. Since the emergence of recommender systems, the majority of research in this area focused on improving predictive accuracy of recommendation. Much less attention has been paid to how users interact with the system and the efficacy of interface designs from users’ perspectives. The field has reached a point where it is necessary to look beyond algorithms, into users’ interactions, decision making processes, and overall end user experience.

The IntRS workshop series focuses on the “human side” or recommender systems. Its goal is to integrate modern HCI approaches and theories of human decision making into the construction of recommender systems. It focuses particularly on the impact of interfaces on decision support and overall satisfaction.

The aim of the IntRS workshop is to bring together researchers and practitioners exploring the topics of designing and evaluating novel intelligent interfaces for recommender systems in order to: (1) share research and techniques, including new design technologies and evaluation methodologies, (2) identify next key challenges in the area, and (3) identify emerging topics.

Demos and mock-ups of systems are encouraged to be used as a basis of a lively and interactive discussion.

  • Peter Brusilovsky, School of Information Sciences, University of Pittsburgh, USA
  • Marco de Gemmis, Dept. of Computer Science, University of Bari “Aldo Moro”, Italy
  • Alexander Felfernig, Institute for Software Technology, Graz University of Technology, Austria
  • Elisabeth Lex, Graz University of Technology, Austria
  • Pasquale Lops, Dept. of Computer Science, University of Bari “Aldo Moro”, Italy
  • Giovanni Semeraro, Dept. of Computer Science, University of Bari “Aldo Moro”, Italy
  • Martijn C. Willemsen, Eindhoven University of Technology, The Netherlands


Full day.

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