"Serving Each User": Supporting different eating goals through a multi-list recommender interface

Alain Starke, Edis Asotic, Christoph Trattner

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

9 Citations (Scopus)


Food recommender systems optimize towards a user's current preferences. However, appetites may vary, in the sense that users might seek healthy recipes today and look for unhealthy meals tomorrow. In this paper, we propose a novel approach in the food domain to diversify recommendations across different lists to 'serve' different users goals, compiled in a multi-list food recommender interface. We evaluated our interface in a 2 (single list vs multiple lists) x 2 (without or with explanations) between-subject user study (N = 366), linking choice behavior and evaluation aspects through the user experience framework. Our multi-list interface was evaluated more favorably than a single-list interface, in terms of diversity and choice satisfaction. Moreover, it triggered changes in food choices, even though these choices were less healthy than those made in the single-list interface.

Original languageEnglish
Title of host publicationRecSys 2021 - 15th ACM Conference on Recommender Systems
PublisherAssociation for Computing Machinery, Inc
Number of pages9
ISBN (Electronic)978-1-4503-8458-2
Publication statusPublished - Sep 2021
Externally publishedYes
Event15th ACM Conference on Recommender Systems, RecSys 2021 - Virtual, Online Beurs van Berlage, Amsterdam, Netherlands
Duration: 27 Sep 20211 Oct 2021
Conference number: 15


Conference15th ACM Conference on Recommender Systems, RecSys 2021
Abbreviated titleRecSys 2021
Internet address


  • Food
  • Goals
  • Health
  • Nudges
  • Recommender Systems
  • User Experience


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