2025
Authors
Vinagre, J; Porcaro, L; Merisio, S; Purificato, E; Gómez, E;
Publication
Proceedings of the Nineteenth ACM Conference on Recommender Systems, RecSys 2025, Prague, Czech Republic, September 22-26, 2025
Abstract
2025
Authors
Purificato, E; Boratto, L; Vinagre, J;
Publication
Adjunct Proceedings of the 33rd ACM Conference on User Modeling, Adaptation and Personalization, UMAP Adjunct 2025, New York City, NY, USA, June 16-19, 2025
Abstract
2025
Authors
Eriksson, M; Purificato, E; Noroozian, A; Vinagre, J; Chaslot, G; Gómez, E; Llorca, DF;
Publication
CoRR
Abstract
2025
Authors
Gonçalves, C; Bessa, RJ; Teixeira, T; Vinagre, J;
Publication
CoRR
Abstract
2023
Authors
Porcaro, L; Castillo, C; Gómez, E; Vinagre, J;
Publication
Proceedings of the 2nd European Workshop on Algorithmic Fairness, Winterthur, Switzerland, June 7th to 9th, 2023.
Abstract
Among the seven key requirements to achieve trustworthy AI proposed by the High-Level Expert Group on Artificial Intelligence (AI-HLEG) established by the European Commission, the fifth requirement (“Diversity, non-discrimination and fairness”) declares: “In order to achieve Trustworthy AI, we must enable inclusion and diversity throughout the entire AI system’s life cycle. [...] This requirement is closely linked with the principle of fairness”. In this paper, we try to shed light on how closely these two distinct concepts, diversity and fairness, may be treated by focusing on information access systems and ranking literature. © 2023 Copyright for this paper by its authors.
2023
Authors
Porcaro, L; Vinagre, J; Frau, P; Hupont, I; Gómez, E;
Publication
CoRR
Abstract
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