Recommendations for the Recommenders: Reflections on Prioritizing Diversity in the RecSys Challenge

The RecSys Challenge 2024, co-organized by the Danish news outlet Ekstra Bladet, called for participants to develop a news recommender system that accurately predicts which news article a reader is most likely to select from a given list. In the context of this challenge, the organizers explicitly stated their interest in beyond-accuracy objectives. However, the setup of the challenge did not facilitate pursuing these more normative goals: a missed opportunity, given the quality of the dataset. In this paper, we highlight the issues encountered in a submission that prioritized normative diversity. We reflect on the responsibility of conferences, RecSys in particular, when it comes to promoting beyond-accuracy objectives and provide recommendations for future challenge iterations.

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Publication Details

Published
2024-10-11
DOI
https://doi.org/10.1145/3687151.3687155
Citations
4
Primary Topic
Recommender Systems and Techniques
Type
article
Field-Weighted Citation Impact
3.12

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article

Recommendations for the Recommenders: Reflections on Prioritizing Diversity in the RecSys Challenge

Lucien Heitz, Oana Inel, Sanne Vrijenhoek
4 citations
Recommender Systems and Techniques
3.12
article

Recommendations for the Recommenders: Reflections on Prioritizing Diversity in the RecSys Challenge

Lucien Heitz, Oana Inel, Sanne Vrijenhoek
article en
4 citations

Abstract

The RecSys Challenge 2024, co-organized by the Danish news outlet Ekstra Bladet, called for participants to develop a news recommender system that accurately predicts which news article a reader is most likely to select from a given list. In the context of this challenge, the organizers explicitly stated their interest in beyond-accuracy objectives. However, the setup of the challenge did not facilitate pursuing these more normative goals: a missed opportunity, given the quality of the dataset. In this paper, we highlight the issues encountered in a submission that prioritized normative diversity. We reflect on the responsibility of conferences, RecSys in particular, when it comes to promoting beyond-accuracy objectives and provide recommendations for future challenge iterations.

University of Zurich (CH), University of Amsterdam (NL)
Universität Zürich
Openalex Percentile: Top 7%
Recommender Systems and Techniques
3.12
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