Vol-3815
urn:nbn:de:0074-3815-4

Copyright © 2024 for the individual papers by the papers' authors. Copyright © 2024 for the volume as a collection by its editors. This volume and its papers are published under the Creative Commons License Attribution 4.0 International (CC BY 4.0).

IntRS 2024
Interfaces and Human Decision Making for Recommender Systems 2024

Proceedings of the 11th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems
co-located with 18th ACM Conference on Recommender Systems (RecSys 2024)

Hybrid Event, Bari, October 18, 2024.

Edited by

Peter Brusilovsky *
Marco de Gemmis
Alexander Felfernig *
Marco Polignano
Giovanni Semeraro
Martijn C. Willemsen ****

* University of Pittsburgh, School of Information Sciences, Pittsburgh, USA
** University of Bari Aldo Moro, Department of Computer Science, Bari, Italy
*** Graz University of Technology, Institute for Software Technology, Graz, Austria
**** Eindhoven University of Technology, Department of Industrial Engineering and Innovation Sciences, Eindhoven, The Netherlands

Preface
Summary: There were 15 papers submitted for peer-review to this workshop. Out of these, 11 papers were included in this volume, 4 as regular papers and 7 as short papers.

Regular Papers

Comparative Explanations for Recommendation: Research Directions 1-14
Meysam Varasteh, Elizabeth McKinnie, Amanda Aird, Daniel Acuña, Robin Burke
Comparing User Interfaces for Customizing Multi-Objective Recommender Systems 15-28
Patrik Dokoupil, Ludovico Boratto, Ladislav Peska
Designing and Evaluating an Educational Recommender System with Different Levels of User Control 29-45
Qurat Ul Ain, Mohamed Amine Chatti, William Kana Tsoplefack, Rawaa Alatrash, Shoeb Joarder
Bridging the Transparency Gap: Exploring Multi-Stakeholder Preferences for Targeted Advertisement Explanations 46-58
Dina Zilbershtein, Francesco Barile, Daan Odijk, Nava Tintarev

Short Papers

What Are We Optimizing For? A Human-centric Evaluation of Deep Learning-based Movie Recommenders 59-70
Ruixuan Sun, Xinyi Wu, Avinash Akella, Ruoyan Kong, Bart Knijnenburg, Joseph A. Konstan
Designing an Interpretable Interface for Contextual Bandits 71-80
Andrew Maher, Matia Gobbo, Lancelot Lachartre, Subash Prabanantham, Rowan Swiers, Puli Liyanagama
Social Circle-Enhanced Fashion Recommendations System 81-91
Aayesha Aayesha, Muhammad Afzaal, Julia Neidhardt
The Effect of Relational versus Anecdotal Explanations in Movie Domain Recommendations 92-102
Liam de la Cour, Derek Bridge
Intended Movie Experience: Linking Elicited Emotions to Eudaimonic and Hedonic Characteristics 103-112
Arsen Matej Golubovikj, Osnat Mokryn, Marko Tkalčič
The Importance of Cognitive Biases in the Recommendation Ecosystem: Evidence of Feature-Positive Effect, Ikea Effect, and Cultural Homophily 113-123
Markus Schedl, Oleg Lesota, Shahed Masoudian
Integrating the Mechanisms of Critiquing-based Recommendation into Constraint Solving 124-133
Pavle Knežević, Alexander Felfernig, Sebastian Lubos

2024-10-24: submitted by Marco de Gemmis, metadata incl. bibliographic data published under Creative Commons CC0
2024-10-31: published on CEUR Workshop Proceedings (CEUR-WS.org, ISSN 1613-0073) |valid HTML5|

IntRS 2024 Interfaces and Human Decision Making for Recommender Systems 2024

Proceedings of the 11th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems co-located with 18th ACM Conference on Recommender Systems (RecSys 2024)