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“Health Is the Real Wealth”: Unsupervised Approach to Improve Explainability in Health-Based Recommendation Systems

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Flexible Query Answering Systems (FQAS 2023)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 14113))

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Abstract

Nutritional recommendation systems are one of the major challenges in the field of recommendation systems. These systems can be based on various aspects such as individual preferences, group affiliations, or nutritional needs. The latter, known as healthy recommendation systems, aims to offer a menu tailored to the user and their vital needs, as well as having a positive impact on their health. However, although these systems allow for very precise multiple nutritional adjustments, users often do not understand what values are taken into account and why these values matter. This study proposes an unsupervised pipeline that generates nutrient-focused natural explanations, based on the nutritional data of the recommended recipes and nutritional textual guidelines made by experts.

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Acknowledgements

We would like to acknowledge support for this work from the Grants: Grant PID2021-123960OB-I00 funded by MCIN/AEI/ 10.13039/501100011033 and by ERDF A way of making Europe and Grant TED2021-129402B-C21 funded by MCIN/AEI/ 10.13039/501100011033 and, by the European Union NextGenerationEU/PRTR.

Funding

In addition, this research has been partially supported by the Ministry of Universities through the EU-funded Margarita Salas programme NextGenerationEU and the pre-competitive project of the Plan Propio of the “University of Granada”.

Author information

Authors and Affiliations

  1. Research Centre for Information and Communications Technologies (CITIC-UGR), University of Granada, 18014, Granada, Spain

    Bartolome Ortiz-Viso & Carlos Fernandez-Basso

  2. Causal Cognition Lab, Division of Psychology and Language Sciences, University College London, London, UK

    Carlos Fernandez-Basso & Jesica Gómez-Sánchez

  3. Department of Developmental and Educational Psychology, University of Granada, 18011, Granada, Spain

    Jesica Gómez-Sánchez

  4. Department of Computer Science and Artificial Intelligence, University of Granada, 18071, Granada, Spain

    Bartolome Ortiz-Viso & Maria J. Martin-Bautista

Authors
  1. Bartolome Ortiz-Viso
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  2. Carlos Fernandez-Basso
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  3. Jesica Gómez-Sánchez
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  4. Maria J. Martin-Bautista
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Corresponding author

Correspondence to Bartolome Ortiz-Viso .

Editor information

Editors and Affiliations

  1. Legind Technologies, Esbjerg V, Denmark

    Henrik Legind Larsen

  2. University of Granada, Granada, Spain

    Maria J. Martin-Bautista

  3. University of Granada, Granada, Spain

    M. Dolores Ruiz

  4. Roskilde University, Roskilde, Denmark

    Troels Andreasen

  5. Consiglio Nazionale delle Ricerche, Milano, Italy

    Gloria Bordogna

  6. Ghent University, Gent, Belgium

    Guy De Tré

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Ortiz-Viso, B., Fernandez-Basso, C., Gómez-Sánchez, J., Martin-Bautista, M.J. (2023). “Health Is the Real Wealth”: Unsupervised Approach to Improve Explainability in Health-Based Recommendation Systems. In: Larsen, H.L., Martin-Bautista, M.J., Ruiz, M.D., Andreasen, T., Bordogna, G., De Tré, G. (eds) Flexible Query Answering Systems. FQAS 2023. Lecture Notes in Computer Science(), vol 14113. Springer, Cham. https://doi.org/10.1007/978-3-031-42935-4_19

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  • DOI: https://doi.org/10.1007/978-3-031-42935-4_19

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