Exploring the Potential of Generative AI for Augmenting Choice-Based Preference Elicitation in Recommender Systems
In: Adjunct Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization (UMAP Adjunct '24) / The Association for Computing Machinery (ACM) (Eds.). - 32nd ACM Conference on User Modeling, Adaptation and Personalization (UMAP Adjunct '24): Cagliari, Italy; July 1 - 4, 2024 - New York: ACM, 2024, pp. 114 - 119
2024book article/chapter in ProceedingsClosed access
Computer ScienceFaculty of Computer Science » Human-centered Computing and Cognitive Science (HCCS) » Interactive Systems
Title in English:
Exploring the Potential of Generative AI for Augmenting Choice-Based Preference Elicitation in Recommender Systems
Author:
Loepp, BenediktUDE
- GND
- 1232038113
- LSF ID
- 54109
- ORCID
-
0000-0001-9059-5324
- Other
- connected with university
- GND
- 1015876811
- LSF ID
- 3881
- ORCID
-
0000-0001-9603-5272
- Other
- connected with university
Open Access?:
Closed access
Scopus ID
Language of text:
English
Keyword, Topic:
Large language models ; Preference elicitation ; Recommender systems ; User experience
Type of resource:
Text
Access Rights:
restricted access