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1 Ergebnisse
1
One for All, All for One: Learning and Transferring User Em..:
, In:
Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining
,
Li, Chenglin
;
Xie, Yuanzhen
;
Yu, Chenyun
... - p. 366-374 , 2023
Link:
https://dl.acm.org/doi/10.1145/3539597.3570379
RT T1 <cTitle>Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining</cTitle>: T1 <Title>One for All, All for One: Learning and Transferring User Embeddings for Cross-Domain Recommendation</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3570379&Exemplar=1&LAN=DE A1 Li, Chenglin A1 Xie, Yuanzhen A1 Yu, Chenyun A1 Hu, Bo A1 Li, Zang A1 Shu, Guoqiang A1 Qie, Xiaohu A1 Niu, Di PB ACM YR 2023 K1 autoencoder K1 contrastive learning K1 cross-domain recommendation K1 representation learning K1 user modeling K1 Computing methodologies K1 Machine learning K1 Machine learning approaches K1 Learning latent representations K1 Information systems K1 Information retrieval K1 Retrieval tasks and goals K1 Recommender systems SP 366 OP 374 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3539597.3570379 DO https://dl.acm.org/doi/10.1145/3539597.3570379 SF ELIB - SuUB Bremen
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