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A challenge for rounded evaluation of recommender systems

Nature Machine Intelligence volume 5, pages 181–182 (2023)Cite this article

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An Author Correction to this article was published on 11 March 2024

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The organizers of the EvalRS recommender systems competition argue that accuracy should not be the only goal and explain how they took robustness and fairness into account.

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Fig. 1: A radar chart showcasing performance across the main metric types.

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References

  1. Tagliabue, J. et al. Preprint at https://arxiv.org/abs/2104.09423 (2021).

  2. Baigorria Alonso, M. Preprint at https://arxiv.org/abs/2108.09858 (2021).

  3. Ribeiro, M. T., Wu, T., Guestrin, C. & Singh, S. in Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics 4902–4912 https://doi.org/10.18653/v1/2020.acl-main.442 (2020).

  4. Chia, P. J., Tagliabue, J., Bianchi, F., He, C. & Ko, B. In Companion Proc. Web Conference 2022 99–104 https://doi.org/10.1145/3487553.3524215 (2022).

  5. Tagliabue, J. et al. Proceedings of the CIKM 2022 Workshops co-located with 31st ACM International Conference on Information and Knowledge Management Vol. 3318 CEUR-WS (2022).

  6. Schedl, M. In Proc. 2016 ACM on International Conference on Multimedia Retrieval 103–110 https://doi.org/10.1145/2911996.2912004 (2016).

  7. Ke Yang, J. S. In Proc. 29th International Conference on Scientific and Statistical Database Management 1–6 https://doi.org/10.1145/3085504.3085526 (2017).

  8. Dixon, L., Li, J., Sorensen, J., Thain, N. & Vasserman, L. In Proc. 2018 AAAI/ACM Conference on AI, Ethics, and Society 67–73 https://doi.org/10.1145/3278721.3278729 (2018).

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Acknowledgements

EvalRS is based on RecList, an open source library whose development is supported by Comet, Neptune and Gantry.

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Authors and Affiliations

  1. Tandon School of Engineering, New York University, Brooklyn, NY, USA

    Jacopo Tagliabue

  2. South Park Commons, New York, NY, USA

    Jacopo Tagliabue & Ciro Greco

  3. Computer Science Dept., Stanford University, Stanford, CA, USA

    Federico Bianchi

  4. Microsoft, Redmond, WA, USA

    Tobias Schnabel

  5. Department of Computing Sciences, Bocconi University, Via Roberto Sarfatti, Milano, Italy

    Giuseppe Attanasio

  6. NVIDIA, Santa Clara, CA, USA

    Gabriel de Souza Moreira

  7. Coveo, Montreal, Quebec, Canada

    Patrick John Chia

Authors
  1. Jacopo Tagliabue
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  2. Federico Bianchi
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  3. Tobias Schnabel
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  4. Giuseppe Attanasio
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  5. Ciro Greco
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  6. Gabriel de Souza Moreira
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  7. Patrick John Chia
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Correspondence to Jacopo Tagliabue.

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Tagliabue, J., Bianchi, F., Schnabel, T. et al. A challenge for rounded evaluation of recommender systems. Nat Mach Intell 5, 181–182 (2023). https://doi.org/10.1038/s42256-022-00606-0

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