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An Uncertainty-Aware Imputation Framework for Alleviating t..:
, In:
Proceedings of the 31st ACM International Conference on Information & Knowledge Management
,
Hwang, Sunghyun
;
Chae, Dong-Kyu
- p. 802-811 , 2022
Link:
https://dl.acm.org/doi/10.1145/3511808.3557236
RT T1 <cTitle>Proceedings of the 31st ACM International Conference on Information & Knowledge Management</cTitle>: T1 <Title>An Uncertainty-Aware Imputation Framework for Alleviating the Sparsity Problem in Collaborative Filtering</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3557236&Exemplar=1&LAN=DE A1 Hwang, Sunghyun A1 Chae, Dong-Kyu PB ACM YR 2022 K1 collaborative filtering with implicit feedback K1 data imputation K1 data sparsity K1 uncertainty quantification K1 Information systems K1 Information systems applications K1 Data mining K1 Collaborative filtering K1 Information retrieval K1 Retrieval tasks and goals K1 Recommender systems SP 802 OP 811 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3511808.3557236 DO https://dl.acm.org/doi/10.1145/3511808.3557236 SF ELIB - SuUB Bremen
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