Vol-2682
urn:nbn:de:0074-2682-7

Copyright © 2020 for the individual papers by the papers' authors. Copyright © 2020 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 2020
Interfaces and Human Decision Making for Recommender Systems 2020

Proceedings of the 7th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems
co-located with 14th ACM Conference on Recommender Systems (RecSys 2020)

Online Event, September 26, 2020.

Edited by

Peter Brusilovsky *
Marco de Gemmis
Alexander Felfernig *
Pasquale Lops
John O'Donovan
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
**** University of California Santa Barbara, Department of Computer Science, Santa Barbara, USA
***** Eindhoven University of Technology, Department of Industrial Engineering and Innovation Sciences, Eindhoven, The Netherlands

Table of Contents

Preface

Long Papers

User Feedback in Controllable and Explainable Social Recommender Systems: a Linguistic Analysis 1-13
Chun-Hua Tsai, Peter Brusilovsky
Featuristic: An interactive hybrid system for generating explainable recommendations - beyond system accuracy 14-25
Sidra Naveed, Jürgen Ziegler
Post-hoc Explanations for Complex Model Recommendations using Simple Methods 26-36
Dorin Shmaryahu, Guy Shani, Bracha Shapira
A Comparison of Services for Intent and Entity Recognition for Conversational Recommender Systems 37-47
Andrea Iovine, Fedelucio Narducci, Marco de Gemmis, Marco Polignano, Pierpaolo Basile, Giovanni Semeraro
The Effect of Personality Traits on Persuading Recommender System Users 48-56
Alaa Alslaity, Thomas Tran
Diversity Exposure in Social Recommender Systems: A Social Capital Theory Perspective 57-64
Chun-Hua Tsai, Jukka Huhtamäki, Thomas Olsson, Peter Brusilovsky
Exploiting Distributional Semantics Models for Natural Language Context-aware Justifications for Recommender Systems 65-71
Cataldo Musto, Giuseppe Spillo, Marco de Gemmis, Pasquale Lops, Giovanni Semeraro

Short Papers

End-to-End Learning for Conversational Recommendation: A Long Way to Go? 72-76
Dietmar Jannach, Ahtsham Manzoor
Recommending Interesting Writing using a Controllable, Explanation-Aware Visual Interface 77-80
Rohan Bansal, Jordan Olmstead, Uri Bram, Robert Cottrell, Gabriel Reder, Jaan Altosaar

2020-09-16: submitted by Marco de Gemmis, metadata incl. bibliographic data published under Creative Commons CC0
2020-09-23: published on CEUR Workshop Proceedings (CEUR-WS.org, ISSN 1613-0073) |valid HTML5|