Bicocca Open Archive

Logo unimib boa

Marconi, L., Matamoros Aragon, R., Epifania, F. (2023). Discovering the Unknown Suggestion: a Short Review on Explainability for Recommender Systems. In Proceedings of the 2nd Italian Workshop on Artificial Intelligence and Applications for Business and Industries (AIABI 2022) co-located with 21st International Conference of the Italian Association for Artificial Intelligence (AI*IA 2022). Online, originally held in Milan, Italy, December 2nd, 2022 (pp.1-15). Aachen : CEUR-WS.

Discovering the Unknown Suggestion: a Short Review on Explainability for Recommender Systems

Marconi, L;Matamoros Aragon, R;Epifania, F
2023
paper
Machine Learning; Recommender Systems; Artificial Intelligence; eXplainable Artificial Intelligence; eXplainable Recommender Systems
English
2nd Italian Workshop on Artificial Intelligence and Applications for Business and Industries (AIABI 2022), co-located with 21st International Conference of the Italian Association for Artificial Intelligence (AI*IA 2022)
2022
Epifania, F; Marconi, L; Matamoros, R; Rosati, R; Frontoni, E; Romeo, L
Proceedings of the 2nd Italian Workshop on Artificial Intelligence and Applications for Business and Industries (AIABI 2022) co-located with 21st International Conference of the Italian Association for Artificial Intelligence (AI*IA 2022). Online, originally held in Milan, Italy, December 2nd, 2022
CEUR WORKSHOP PROCEEDINGS
2023
3463
1
15
https://ceur-ws.org/Vol-3463/paper3.pdf
open
Marconi, L., Matamoros Aragon, R., Epifania, F. (2023). Discovering the Unknown Suggestion: a Short Review on Explainability for Recommender Systems. In Proceedings of the 2nd Italian Workshop on Artificial Intelligence and Applications for Business and Industries (AIABI 2022) co-located with 21st International Conference of the Italian Association for Artificial Intelligence (AI*IA 2022). Online, originally held in Milan, Italy, December 2nd, 2022 (pp.1-15). Aachen : CEUR-WS.
02 - Intervento a convegno
File in questo prodotto:
File Dimensione Formato  
Marconi-2023-CEUR-VoR.pdf

accesso aperto

Tipologia di allegato: Publisher’s Version (Version of Record, VoR)
Licenza: Creative Commons
Dimensione 807.49 kB
Formato Adobe PDF
Visualizza/Apri
807.49 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/466854
Citazioni
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
Social impact