Proceedings of the Joint Workshop on Interfaces and Human Decision Making for Recommender Systems September 19, 2015 In conjunction with the 9th ACM Conference on Recommender Systems Vienna, Austria Edited by John O’Donovan, Alexander Felfernig, Nava Tintarev, Peter Brusilovsky, Giovanni Semeraro, Pasquale Lops Copyright © 2015 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, and on ways to compare and evaluate novel techniques and applications in this area. 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 ten presentations of papers in which results of ongoing research as reported in these proceedings are presented and one invited talk by Anthony Jameson presenting “Recommender Systems Seen Through the Lens of Choice Architecture”. The workshop is closed by a final discussion session. John O’Donovan, Alexander Felfernig, Nava Tintarev, Peter Brusilovsky, Giovanni Semeraro and Pasquale Lops August 2015 Organizing Committee Workshop Co-Chairs John O’Donovan, University of California, Santa Barbara, USA Alexander Felfernig, Graz University of Technology, Austria Nava Tintarev, University of Aberdeen, UK Peter Brusilovsky, University of Pittsburgh, USA Giovanni Semeraro, University of Bari "Aldo Moro", Italy Pasquale Lops, University of Bari "Aldo Moro", Italy Program Committee Robin Burke, DePaul University, USA Jaegul Choo, College of Informatics, Korea University, South Korea Marco De Gemmis, Dipartimento di Informatica – University of Bari, Italy Jill Freyne, CSIRO, Australia Gerhard Friedrich, Alpen-Adria-Universitaet Klagenfurt, Austria Sergiu Gordea, AIT Austria Dietmar Jannach, TU Dortmund, Germany Bart Knijnenburg, University of California, Irvine, USA Henry Lieberman, MIT, USA Gerald Ninaus, TU Graz, Austria Denis Parra, Pontificia Universidad Catolica de Chile, Chile Christin Seifert, Uni Passau, Germany Christoph Trattner, Know Center, Austria and NTNU, Norway Jesse Vig, University of Minnesota, USA Martijn Willemsen, Eindhoven University of Technology, Netherlands Markus Zanker, Alpen-Adria-Universität Klagenfurt, Austria Table of Contents Invited presentation Recommender Systems Seen Through the Lens of Choice Architecture Anthony Jameson 1 Accepted papers Parsimonious and Adaptive Contextual Information Acquisition in Recommender Systems Matthias Braunhofer, Ignacio Fernández-Tobías, Francesco Ricci 2 Fostering Knowledge Exchange Using Group Recommendations Alexander Felfernig, Martin Stettinger, Gerhard Leitner 9 Explaining contextual recommendations: Interaction design study and prototype implementation Joanna Misztal, Bipin Indurkhya 13 Inspection Mechanisms for Community-based Content Discovery in Microblogs Nava Tintarev, Byungkyu Kang, Tobias Höllerer, John O’Donovan 21 uRank: Exploring Document Recommendations through an Interactive User-Driven Approach Cecilia di Sciascio, Vedran Sabol, Eduardo Veas 29 FutureView: Enhancing Exploratory Image Search Sayantan Hore, Dorota Glowacka, Ilkka Kosunen, Kumaripaba Athukorala, Giulio Jacucci 37 An Adaptive Electronic Menu System for Restaurants Paulo Henrique Azevedo Filho, Wolfgang Wörndl 41 User Controlled News Recommendations Jon Espen Ingvaldsen, Jon Atle Gulla, Özlem Özgöbek 45 Interaction Design in a Mobile Food Recommender System Mehdi Elahi, Mouzhi Ge, Francesco Ricci, Ignacio Fernández-Tobías, Shlomo Berkovski, Massimo David 49 Recommender Systems for the People — Enhancing Personalization in Web Augmentation Martin Wischenbart, Sergio Firmenich, Gustavo Rossi, Manuel Wimmer 53