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Preference Aggregation Mechanisms for a Tourism-Oriented Bayesian Recommender

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PRIMA 2022: Principles and Practice of Multi-Agent Systems (PRIMA 2022)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13753))

Abstract

In this work, we employ various preference aggregation mechanisms from the social choice literature alongside with a multiwinner voting rule, namely the Reweighted Approval Voting (RAV), to the group recommendations problem. In more detail, we equip with such mechanisms a Bayesian recommender system for the tourism domain, allowing for the effective aggregation of elicited group members’ preferences while promoting fairness in the group recommendations. We conduct a systematic experimental evaluation of our approach by applying it on a real-world dataset. Our results clearly demonstrate that the use of multiwinner mechanisms allows for fair group recommendations with respect to the well-known m-proportionality and m-envy-freeness metrics.

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Notes

  1. 1.

    Of course, proportionality is only one notion of fairness provided by some multiwinner election mechanims. In other cases, one may want to define a notion of fairness based on the properties of shortlisting or diversity that other multiwinner election mechanisms satisfy.

  2. 2.

    Henceforth referred to as “multivariate Gaussians” or “Gaussians” for short.

  3. 3.

    Obviously the user model can and will also be updated following an actual visit to and rating of a particular POI, via the exact same process.

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Acknowledgments

This research has been co-financed by the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation, under the call RESEARCH-CREATE-INNOVATE B cycle (project code: T2EDK-03135). E. Streviniotis was also supported by the Onassis Foundation - Scholarship ID: G ZR 012-1/2021-2022.

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Authors and Affiliations

  1. Technical University of Crete, Chania, Greece

    Errikos Streviniotis & Georgios Chalkiadakis

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  1. Errikos Streviniotis
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Correspondence to Errikos Streviniotis .

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  1. Özyeğin University, Istanbul, Turkey

    Reyhan Aydoğan

  2. Universitat Politècnica de València, Valencia, Spain

    Natalia Criado

  3. Université Paris-Dauphine, Paris, France

    Jérôme Lang

  4. Universitat Politècnica de València, Valencia, Spain

    Victor Sanchez-Anguix

  5. King's College London, London, UK

    Marc Serramia

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Streviniotis, E., Chalkiadakis, G. (2023). Preference Aggregation Mechanisms for a Tourism-Oriented Bayesian Recommender. In: Aydoğan, R., Criado, N., Lang, J., Sanchez-Anguix, V., Serramia, M. (eds) PRIMA 2022: Principles and Practice of Multi-Agent Systems. PRIMA 2022. Lecture Notes in Computer Science(), vol 13753. Springer, Cham. https://doi.org/10.1007/978-3-031-21203-1_20

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  • DOI: https://doi.org/10.1007/978-3-031-21203-1_20

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