Musto, Cataldo; Delic, Amra; Inel, Oana; Polignano, Marco; Rapp, Amon; Semeraro, Giovanni; Ziegler, Jürgen:
5th Workshop on Explainable User Models and Personalised Systems (ExUM)
ExUM 2023 ; 5th Workshop on Explainable User Models and Personalised Systems
In: UMAP 2023 : Adjunct Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization ; 26-30 June, 2023, Limassol, Cyprus / The Association for Computing Machinery (Eds.). - 31st ACM Conference on User Modeling, Adaptation and Personalization ; UMAP 2023 ; 26.-30.06.2023, Limassol, Cyprus - New York: Association for Computing Machinery, 2023 - (ACM Conferences) (ACM Digital Library), pp. 196 - 198
2023book article/chapter in ProceedingsClosed access
Computer ScienceFaculty of Engineering » Computer Science and Applied Cognitive Science » Computer Science » Interactive Systems
Related: 1 publication(s)
Title in English:
5th Workshop on Explainable User Models and Personalised Systems (ExUM)
Conference
ExUM 2023 ; 5th Workshop on Explainable User Models and Personalised Systems
Author:
Musto, Cataldo
;Delic, Amra
;Inel, Oana
;Polignano, Marco
;Rapp, Amon
;Semeraro, Giovanni
;Ziegler, JürgenUDE
GND
1015876811
LSF ID
3881
ORCID
0000-0001-9603-5272ORCID iD
Other
connected with university
Open Access?:
Closed access
DOI
10.1145/3563359.3595629
Scopus ID
85163702919
Language of text:
English
Appears in
UMAP 2023 : Adjunct Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization ; 26-30 June, 2023, Limassol, Cyprus
Conference
31st ACM Conference on User Modeling, Adaptation and Personalization ; UMAP 2023 ; 26.-30.06.2023, Limassol, Cyprus
Editor:
The Association for Computing Machinery
Place of publication:
New York
Publisher:
Association for Computing Machinery
Year of publication:
2023
Open Access?:
Closed access
in:
pp. 196 - 198
DOI
10.1145/3563359
ISBN
978-1-4503-9891-6
PPN:
1852091975
Language of text:
English
In Series
ACM Conferences
In Series
ACM Digital Library
Keyword, Topic:
Explainability ; Interpretability ; Personalization ; Recommender Systems ; Transparency ; User Modeling