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).
Annemarie Abbing, Anne Ponstein, Susan van Hooren, Leo de Sonneville, Hanna Swaab, and Erik Baars. 2018. The effectiveness of art therapy for anxiety in adults: A systematic review of randomised and non-randomised controlled trials. PloS one 13, 12 (2018), e0208716.
Sinem Aslan, Giovanna Castellano, Vincenzo Digeno, Giuseppe Migailo, Raffaele Scaringi, and Gennaro Vessio. 2022. Recognizing the emotions evoked by artworks through visual features and knowledge graph-embeddings. In International Conference on Image Analysis and Processing. Springer, 129-140.
Kelly Sarah Barnett and Fabian Vasiu. 2024. How the arts heal: A review of the neural mechanisms behind the therapeutic effects of creative arts on mental and physical health. Frontiers in behavioral neuroscience 18 (2024), 1422361.
DavidMBlei, AndrewY Ng, and Michael I Jordan. 2003. Latent dirichlet allocation. Journal of machine Learning research 3, Jan (2003), 993-1022.
Rebecca Bokoch, Noah Hass-Cohen, April Espinoza, Tyler O'Reilly, and Elad Levi. 2025. A scoping review of integrated arts therapies and neuroscience research. Frontiers in Psychology 16 (2025), 1569609.
Olivia Brancatisano, Amee Baird, and William Forde Thompson. 2020. Why is music therapeutic for neurological disorders? The Therapeutic Music Capacities Model. Neuroscience & Biobehavioral Reviews 112 (2020), 600-615.
José J Campos-Bueno, Octavio DeJuan-Ayala, Pedro Montoya, and Niels Birbaumer. 2015. Emotional dimensions of music and painting and their interaction. The Spanish journal of psychology 18 (2015), E54.
Suvin Choi, Jong-Ik Park, Cheol-Ho Hong, Sang-Gue Park, and Sang-Cheol Park. 2024. Accelerated construction of stress relief music datasets using CNN and the Mel-scaled spectrogram. PloS one 19, 5 (2024), e0300607.
Shreyan Chowdhury, Andreu Vall, Verena Haunschmid, and Gerhard Widmer. 2019. Towards Explainable Music Emotion Recognition: The Route via Mid-level Features. In Proceedings of the 20th International Society for Music Information Retrieval Conference, ISMIR 2019, Delft, The Netherlands, November 4-8, 2019, Arthur Flexer, Geoffroy Peeters, Julián Urbano, and Anja Volk (Eds.). 237-243. http://archives. ismir. net/ismir2019/paper/000027. pdf
Pieter MA Desmet, Martijn H Vastenburg, and Natalia Romero. 2016. Mood measurement with Pick-A-Mood: review of current methods and design of a pictorial self-report scale. Journal of Design Research 14, 3 (2016), 241-279.
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018. Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv: 1810. 04805 (2018).
Antonella Di Vita, Mario Augusto Procacci, Martina Bellagamba, Maria Jacomini, Roberta Massicci, and Maria Paola Ciurli. 2022. Psychotherapy and Art Therapy: A pilot study of group treatment for patients with traumatic brain injury. Journal of health psychology 27, 4 (2022), 836-846.
Ali Mamdouh Elkahky, Yang Song, and Xiaodong He. 2015. A multi-view deep learning approach for cross domain user modeling in recommendation systems. In Proceedings of the 24th international conference on world wide web. 278-288.
Yingjie Feng and Mingda Wang. 2025. Effect of music therapy on emotional resilience, well-being, and employability: A quantitative investigation of mediation and moderation. BMC psychology 13, 1 (2025), 47.
Ignacio Fernández-Tobías, Matthias Braunhofer, Mehdi Elahi, Francesco Ricci, and Iván Cantador. 2016. Alleviating the new user problem in collaborative filtering by exploiting personality information. User Modeling and User-Adapted Interaction 26 (2016), 221-255.
Maarten Grootendorst. 2022. BERTopic: Neural topic modeling with a class-based TF-IDF procedure. arXiv preprint arXiv: 2203. 05794 (2022).
Suzanne Haeyen and Merel Staal. 2021. Imagery rehearsal based art therapy: Treatment of post-traumatic nightmares in art therapy. Frontiers in psychology 11 (2021), 628717.
Kathy Hathorn and Upali Nanda. 2008. A guide to evidence-based art. The Center for Health Design 1 (2008), 1-23.
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. 2016. Deep residual learning for image recognition. In Proceedings of the IEEE conference on computer vision and pattern recognition. 770-778.
Taisei Hirakawa, Keisuke Maeda, Takahiro Ogawa, Satoshi Asamizu, and Miki Haseyama. 2021. Cross-domain recommendation method based on multi-layer graph analysis with visual information. In 2021 IEEE International Conference on Image Processing (ICIP). IEEE, 2688-2692.
Jingxuan Hu, Jinhuan Zhang, Liyu Hu, Haibo Yu, and Jinping Xu. 2021. Art therapy: A complementary treatment for mental disorders. Frontiers in psychology 12 (2021), 686005.
Papadopoulos Stefanos Iordanis. 2021. Emotion-aware music recommendation systems. (2021).
Dian Jiao. 2025. Advancing personalized digital therapeutics: integrating music therapy, brainwave entrainment methods, and AI-driven biofeedback. Frontiers in Digital Health 7 (2025), 1552396.
Patrik N. Juslin and Daniel Västfjäll. 2008. Emotional responses to music: The need to consider underlying mechanisms. Behavioral and Brain Sciences 31, 5 (2008), 559-575. https://doi. org/10. 1017/S0140525X08005293
Stefan Koelsch. 2014. Brain correlates of music-evoked emotions. Nature reviews neuroscience 15, 3 (2014), 170-180.
AI Ladas, T Gravalas, C Katsoridou, and CA Frantzidis. 2024. Harmony in the brain: A narrative review on the shared neural substrates of emotion regulation and creativity. Brain Organoid and Systems Neuroscience Journal 2 (2024), 81-91.
Cheng-Che Lee, Wan-Yi Lin, Yen-Ting Shih, Pei-Yi Kuo, and Li Su. 2020. Crossing you in style: Cross-modal style transfer from music to visual arts. In Proceedings of the 28th ACM international conference on multimedia. 3219-3227.
Junnan Li, Dongxu Li, Caiming Xiong, and Steven Hoi. 2022. Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation. arXiv preprint arXiv: 2201. 12086 (2022).
Yizhi Li, Ruibin Yuan, Ge Zhang, Yinghao Ma, Xingran Chen, Hanzhi Yin, Chenghao Xiao, Chenghua Lin, Anton Ragni, Emmanouil Benetos, et al. 2023. Mert: Acoustic music understanding model with large-scale self-supervised training. arXiv preprint arXiv: 2306. 00107 (2023).
Bojun Liu and Bohong Liu. 2022. Human-Centric C ross-Domain T ransfer N etwork for M usic Recommendation. In International Advanced Computing Conference. Springer, 407-414.
Bernd Löwe, Inka Wahl, Matthias Rose, Carsten Spitzer, Heide Glaesmer, Katja Wingenfeld, Antonius Schneider, and Elmar Brähler. 2010. A 4-item measure of depression and anxiety: validation and standardization of the Patient Health Questionnaire-4 (PHQ-4) in the general population. Journal of affective disorders 122, 1-2 (2010), 86-95.
Cathy A Malchiodi. 2011. Handbook of art therapy. Guilford Press.
Tong Man, Huawei Shen, Xiaolong Jin, and Xueqi Cheng. 2017. Cross-domain recommendation: An embedding and mapping approach. In IJCAI, Vol. 17. 2464-2470.
Saif M Mohammad. 2025. NRC VAD Lexicon v2: Norms for valence, arousal, and dominance for over 55k English terms. arXiv preprint arXiv: 2503. 23547 (2025).
Sharaj Panwar, Paul Rad, Kim-Kwang Raymond Choo, and Mehdi Roopaei. 2019. Are you emotional or depressed? Learning about your emotional state from your music using machine learning. The Journal of Supercomputing 75 (2019), 2986-3009.
Varesh Patel and Khyati Mehta. 2024. Emotion-Aware Music Recommendations: Evaluating Custom CNN vs. VGG16 and InceptionV3. In 2024 IEEE International Conference on Future Machine Learning and Data Science (FMLDS). IEEE, 499-504.
Pearl Pu, Li Chen, and Rong Hu. 2011. A user-centric evaluation framework for recommender systems. In Proceedings of the fifth ACM conference on Recommender systems. 157-164.
Alfredo Raglio, Marcello Imbriani, Chiara Imbriani, Paola Baiardi, Sara Manzoni, Marta Gianotti, Mauro Castelli, Leonardo Vanneschi, Francisco Vico, and Luca Manzoni. 2020. Machine learning techniques to predict the effectiveness of music therapy: A randomized controlled trial. Computer Methods and Programs in Biomedicine 185 (2020), 105160. https://doi. org/10. 1016/j. cmpb. 2019. 105160
Yiren Ren, Sophia Kaltsouni Mehdizadeh, Grace Leslie, and Thackery Brown. 2024. Affective music during episodic memory recollection modulates subsequent false emotional memory traces: An fMRI study. Cognitive, Affective, & Behavioral Neuroscience 24, 5 (2024), 912-930.
Mathieu Roy, Isabelle Peretz, and Pierre Rainville. 2008. Emotional valence contributes to music-induced analgesia. Pain 134, 1-2 (2008), 140-147.
Gillian M Sandstrom and Frank A Russo. 2010. Music hath charms: The effects of valence and arousal on recovery following an acute stressor. Music and Medicine 2, 3 (2010), 137-143.
Susanne Schweizer, Ian H Gotlib, and Sarah-Jayne Blakemore. 2020. The role of affective control in emotion regulation during adolescence. Emotion 20, 1 (2020), 80.
Heather L Stuckey and Jeremy Nobel. 2010. The connection between art, healing, and public health: A review of current literature. American journal of public health 100, 2 (2010), 254-263.
J. Tan et al. 2024. Contrastive Learning Is Spectral Clustering On Similarity Graph. In Proceedings of CVPR 2024.
Michael Thaut. 2013. Rhythm, music, and the brain: Scientific foundations and clinical applications. Routledge.
Berit Marie Dykesteen Vik, Geir Olve Skeie, and Karsten Specht. 2019. Neuroplastic effects in patients with traumatic brain injury after music-supported therapy. Frontiers in human neuroscience 13 (2019), 177.
David Watson, Lee Anna Clark, and Auke Tellegen. 1988. Development and validation of brief measures of positive and negative affect: The PANAS scales. Journal of personality and social psychology 54, 6 (1988), 1063.
Barbara L Wheeler, Estate Sokhadze, Joshua Baruth, Gene Ann Behrens, and Carla F Quinn. 2011. Musically induced emotions: Subjective measures of arousal and valence. Music and Medicine (2011).
Bereket A. Yilma, Chan Mi Kim, Gerald C. Cupchik, and Luis A. Leiva. 2024. Artful Path to Healing: Using Machine Learning for Visual Art Recommendation to Prevent and Reduce Post-Intensive Care Syndrome (PICS). In Proceedings of the CHI Conference on Human Factors in Computing Systems (Honolulu, HI, USA) (CHI '24). Association for Computing Machinery, New York, NY, USA, Article 447, 19 pages. https://doi. org/10. 1145/3613904. 3642636
Bereket A Yilma, Chan Mi Kim, Geke Ludden, Thomas van Rompay, and Luis A Leiva. 2025. The AI-Therapist Duo: Exploring the Potential of Human-AI Collaboration in Personalized Art Therapy for PICS Intervention. arXiv preprint arXiv: 2502. 09757 (2025).
Saba Yousefian Jazi, Marjan Kaedi, and Afsaneh Fatemi. 2021. An emotionaware music recommender system: bridging the user's interaction and music recommendation. Multimedia Tools and Applications 80 (2021), 13559-13574.
Tianzi Zang, Yanmin Zhu, Haobing Liu, Ruohan Zhang, and Jiadi Yu. 2022. A survey on cross-domain recommendation: Taxonomies, methods, and future directions. ACM Transactions on Information Systems 41, 2 (2022), 1-39.
Qian Zhang, Wenhui Liao, Guangquan Zhang, Bo Yuan, and Jie Lu. 2021. A deep dual adversarial network for cross-domain recommendation. IEEE Transactions on Knowledge and Data Engineering 35, 4 (2021), 3266-3278.
Feng Zhu, Yan Wang, Chaochao Chen, Jun Zhou, Longfei Li, and Guanfeng Liu. 2021. Cross-domain recommendation: challenges, progress, and prospects. arXiv preprint arXiv: 2103. 01696 (2021).