Proceedings of the Joint Workshop on Interfaces and Human Decision Making for Recommender Systems September 16, 2016 In conjunction with the 10th ACM Conference on Recommender Systems Boston, MA, USA Edited by Peter Brusilovsky, Alexander Felfernig, Pasquale Lops, John O’Donovan, Giovanni Semeraro, Nava Tintarev, Martijn C. Willemsen Copyright © 2016 for the individual papers by the papers’ authors. Copying permitted for private and academic purposes. This volume is published and copyrighted by its editors. Preface As an interactive intelligent system, recommender systems are developed to give recommendations that match users’ 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. This workshop will focus on the aspect of integrating different theories of human decision making into the construction of recommender systems. It will focus particularly on the impact of interfaces on decision support and overall satisfaction. The 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. This workshop aims at establishing an interdisciplinary community with a focus on the interface design issues for recommender systems and promoting the collaboration opportunities between researchers and practitioners. The workshop consists of a mix of nine presentations of papers in which results of ongoing research as reported in these proceedings are presented and one invited talk by Bart P. Knijnenburg on “User-Tailored Privacy for Interactive Recommender Systems”. The workshop is closed by a final discussion session. We thank all PC members, our keynote speakers, as well as authors of accepted papers for making IntRS 2016 possible. We hope you will enjoy the workshop! Peter Brusilovsky, Alexander Felfernig, Pasquale Lops, John O’Donovan, Giovanni Semeraro, Nava Tintarev, Martijn C. Willemsen September 2016 Organizing Committee Workshop Co-Chairs Peter Brusilovsky, School of Information Sciences, University of Pittsburgh, USA Alexander Felfernig, Institute for Software Technology, Graz University of Technology, Austria Pasquale Lops, Dept. of Computer Science, University of Bari “Aldo Moro”, Italy John O’Donovan, Dept. of Computer Science, University of California, Santa Barbara Giovanni Semeraro, Dept. of Computer Science, University of Bari “Aldo Moro”, Italy Nava Tintarev, Bournemouth University, UK Martijn C. Willemsen, Eindhoven University of Technology, The Netherlands Program Committee Robin Burke, DePaul University Li Chen, Hong Kong Baptist University Jaegul Choo, Korea University Marco de Gemmis, University of Bari “Aldo Moro” Michael Ekstrand, Dept. of Computer Science, Texas State University Gerhard Friedrich, Alpen-Adria-Universitaet Klagenfurt Franca Garzotto, Polimi Mouzhi Ge, Universitaet der Bundeswehr Munich Sergiu Gordea, AIT Dietmar Jannach, TU Dortmund Aigul Kaskina, University of Fribourg Bart Knijnenburg, Clemson University Fedelucio Narducci, University of Bari “Aldo Moro” Denis Parra, Pontificia Universidad Catolica de Chile Francesco Ricci, Free University of Bozen-Bolzano Olga C. Santos, aDeNu Research Group (UNED) Christin Seifert, Uni Passau Luis Terán, University of Fribourg Juha Tiihonen, University of Helsinki Marko Tkalcic, Free University of Bolzano Christoph Trattner, KMI, TU-Graz Katrien Verbert, KU Leuven Markus Zanker, Free University of Bolzano Table of Contents Invited presentation User-Tailored Privacy for Interactive Recommender Systems Bart P. Knijnenburg 1 Accepted papers Investigating Mere-Presence Effects of Recommendations on the Consumer Choice Process Sören Köcher, Dietmar Jannach, Michael Jugovac, Hartmut H. Holzmüller 2 Estimating Party-user Similarity in Voting Advice Applications using Hidden Markov Models Marilena Agathokleous, Nicolas Tsapatsoulis, Constantinos Djouvas 6 Understanding Effects of Personalized vs. Aggregate Ratings on User Preferences Gediminas Adomavicius, Jesse Bockstedt, Shawn Curley, Jingjing Zhang 14 Can Trailers Help to Alleviate Popularity Bias in Choice-Based Preference Elicitation? Mark Graus, Martijn C. Willemsen 22 Scalable Exploration of Relevance Prospects to Support Decision Making Katrien Verbert, Karsten Seipp, Chen He, Denis Parra, Chirayu Wongchokprasitti, Peter Brusilovsky 28 Complements and Substitutes in Product Recommendations: The Differential Effects on Consumers’ Willingness-to-pay Mingyue Zhang, Jesse Bockstedt 36 DiRec: A Distributed User Interface Video Recommender Wessam Abdrabo, Wolfgang Wörndl 44 Learning User’s Preferred Household Organization via Collaborative Filtering Methods Stephen Brawner, Michael L. Littman 48 A Cross-Cultural Analysis of Explanations for Product Reviews John O’Donovan, Shinsuke Nakajima, Tobias Höllerer, Mayumi Ueda, Yuuki Matsunami, Byungkyu Kang 55