RecSys '19 joint workshop on interfaces and human decision making for recommender systems

Peter Brusilovsky, Marco de Gemmis, Alexander Felfernig, Pasquale Lops, John O'Donovan, Giovanni Semeraro, Martijn C. Willemsen

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademic

Abstract

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 "human side" of recommender systems research. 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.
Original languageEnglish
Title of host publicationRecSys 2019 - 13th ACM Conference on Recommender Systems
Place of PublicationNew York
PublisherAssociation for Computing Machinery, Inc
Pages560-561
Number of pages2
ISBN (Electronic)9781450362436
ISBN (Print)978-1-4503-6243-6
DOIs
Publication statusPublished - 10 Sep 2019
Event 13th ACM Conference on Recommender Systems, RecSys 2019 - Copenhagen, Denmark
Duration: 16 Sep 201920 Sep 2019
Conference number: 13

Conference

Conference 13th ACM Conference on Recommender Systems, RecSys 2019
Abbreviated titleRecSys 2019
Country/TerritoryDenmark
CityCopenhagen
Period16/09/1920/09/19

Keywords

  • decision biases, evaluation methods, human computer interaction, human decision making, recommender systems, user interfaces
  • Recommender Systems
  • User Interfaces
  • Evaluation Methods
  • Human Decision Making
  • Decision Biases
  • Human Computer Interaction

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