6 th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems (IntRS) 2019 Proceedings PeterBrusilovsky AlexanderFelfernig JohnO' DonovanGiovanni SemeraroMartijn CWillemsen MarcoDe Gemmis PasqualeLops JohnO'donovan GiovanniSemeraro MartijnCWillemsen Marco de Gemmis School of Information Sciences University of Pittsburgh
USA
Marco de Gemmis Dept. of Computer Science University of Bari Aldo Moro
Italy
Institute for Software Technology Graz University of Technology
Austria
Dept. of Computer Science University of Bari Aldo Moro
Italy
Dept. of Computer Science Univ. of California
Santa Barbara USA
Dept. of Computer Science University of Bari Aldo Moro
Italy
Eindhoven University of Technology
The Netherlands
6 th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems (IntRS) 2019 BBE606C1A3BB17A8432EF75B7A9A66E3 GROBID - A machine learning software for extracting information from scholarly documents IntRS 2019 Workshop Organization
Preface

This volume contains the papers presented at the 6 th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems (IntRS), held as part of the 13 th ACM Conference on Recommender System (RecSys), in Copenhagen, Denmark.

RecSys is the premier international forum for the presentation of new research results, systems and techniques in the broad field of recommender systems. Recommendation is a particular form of information filtering, that exploits past behaviors and user similarities to generate a list of information items that is personally tailored to an end-user's preferences. Since the emergence of recommender systems, a large majority of research focuses on objective accuracy criteria and 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 ready to look beyond algorithms, into users' interactions, decision making processes, and overall experience.

The IntRS workshop focuses on human-centered recommender system design and application. The workshop goal is to improve users' overall experience with recommender systems by integrating different theories of human decision making into the construction of recommender systems and exploring better interfaces for recommender systems.

The workshop follows successful workshops on the same topic organized at RecSys conferences in 2014 -2018. The continuous aim of the workshop is to bring together researchers and practitioners around 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.

The 11 technical papers included in the proceedings were selected through a rigorous reviewing process, where each paper was reviewed by three PC members.

The IntRS chairs would like to thank the RecSys workshop chairs, Sandra Garcia and Christoph Trattner, for their guidance during the workshop organization. We also wish to thank all authors and all presenters, and the members of the program committee. All of them secured the workshop's high quality standards.