A two-stage calibration approach for mitigating bias and fairness in recommender systems (2024)
Source: Proceedings. Conference titles: ACM/SIGAPP Symposium on Applied Computing - SAC. Unidade: ICMC
Assunto: SISTEMAS DE RECOMENDAÇÃO
ABNT
SOUZA, Rodrigo Ferrari de e MANZATO, Marcelo Garcia. A two-stage calibration approach for mitigating bias and fairness in recommender systems. 2024, Anais.. New York: ACM, 2024. Disponível em: https://doi.org/10.1145/3605098.3636092. Acesso em: 24 ago. 2024.APA
Souza, R. F. de, & Manzato, M. G. (2024). A two-stage calibration approach for mitigating bias and fairness in recommender systems. In Proceedings. New York: ACM. doi:10.1145/3605098.3636092NLM
Souza RF de, Manzato MG. A two-stage calibration approach for mitigating bias and fairness in recommender systems [Internet]. Proceedings. 2024 ;[citado 2024 ago. 24 ] Available from: https://doi.org/10.1145/3605098.3636092Vancouver
Souza RF de, Manzato MG. A two-stage calibration approach for mitigating bias and fairness in recommender systems [Internet]. Proceedings. 2024 ;[citado 2024 ago. 24 ] Available from: https://doi.org/10.1145/3605098.3636092