CCS Concepts • Information systems → Personalization; Recommender systems; • Computing methodologies → Learning latent representations; • Applied computing → Media arts Recommendation; Personalization; Artwork; User Experience; Machine Learning
Résumé :
[en] Art Therapy (AT) is an established practice that facilitates emotional processing and recovery through creative expression. Recently, Visual Art Recommender Systems (VA RecSys) have emerged to support AT, demonstrating their potential by personalizing therapeutic artwork recommendations. Nonetheless, current VA RecSys rely on visual stimuli for user modeling, limiting their ability to capture the full spectrum of emotional responses during preference elicitation. Previous studies have shown that music stimuli elicit unique affective reflections, presenting an opportunity for cross-domain recommendation (CDR) to enhance personalization in AT. Since CDR has not yet been explored in this context, we propose a family of CDR methods for AT based on music-driven preference elicitation. A large-scale study with 200 users demonstrates the efficacy of music-driven preference elicitation, outperforming the classic visual-only elicitation approach. Our source code, data, and models are available at https://github.com/ArtAICare/Affect-aware-CDR.
Disciplines :
Sciences informatiques
Auteur, co-auteur :
YILMA, Bereket Abera ; University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS)
LEIVA, Luis A. ; University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS)
Co-auteurs externes :
yes
Langue du document :
Anglais
Titre :
Affect-aware Cross-Domain Recommendation for Art Therapy via Music Preference Elicitation
Titre traduit :
[en] Affect-aware Cross-Domain Recommendation for Art Therapy via Music Preference Elicitation
Titre original :
[en] Affect-aware Cross-Domain Recommendation for Art Therapy via Music Preference Elicitation
Date de publication/diffusion :
22 septembre 2025
Nom de la manifestation :
19th ACM Conference on Recommender Systems
Lieu de la manifestation :
Prague, République Tchèque
Date de la manifestation :
22nd–26th September 2025
Sur invitation :
Oui
Manifestation à portée :
International
Titre de l'ouvrage principal :
Proceedings of the Nineteenth ACM Conference on Recommender Systems (RecSys ’25)
Maison d'édition :
ACM, Prague, République Tchèque
Edition :
19th
ISBN/EAN :
9798400713644
Peer reviewed :
Peer reviewed
Focus Area :
Computational Sciences
Projet européen :
HE - 101071147 - SYMBIOTIK - Context-aware adaptive visualizations for critical decision making
Projet FnR :
FNR15722813 - BANANA - Brainsourcing For Affective Attention Estimation, 2021 (01/02/2022-31/01/2025) - Luis Leiva
Organisme subsidiant :
CE - Commission Européenne European Union
Subventionnement (détails) :
Research supported by the Pathfinder program of the European Innovation Council (grant 101071147) and the Horizon 2020 FET program of the European Union (grant CHIST-ERA-20-BCI-001).
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