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1 Ergebnisse
1
EvalRS 2023: Well-Rounded Recommender Systems for Real-Worl..:
, In:
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
,
Bianchi, Federico
;
Chia, Patrick John
;
Tagliabue, Jacopo
... - p. 5851-5852 , 2023
Link:
https://dl.acm.org/doi/10.1145/3580305.3599222
RT T1 <cTitle>Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining</cTitle>: T1 <Title>EvalRS 2023: Well-Rounded Recommender Systems for Real-World Deployments</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3599222&Exemplar=1&LAN=DE A1 Bianchi, Federico A1 Chia, Patrick John A1 Tagliabue, Jacopo A1 Greco, Ciro A1 Moreira, Gabriel S P A1 Eynard, Davide A1 Husain, Fahd A1 Pomo, Claudio PB ACM YR 2023 K1 behavioural testing K1 multi-dimensional evaluation K1 recommender systems K1 Information systems K1 Information retrieval K1 Evaluation of retrieval results K1 Relevance assessment K1 Retrieval tasks and goals K1 Recommender systems SP 5851 OP 5852 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3580305.3599222 DO https://dl.acm.org/doi/10.1145/3580305.3599222 SF ELIB - SuUB Bremen
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