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1 Ergebnisse
1
Spatio-Temporal-Categorical Graph Neural Networks for Fine-..:
, In:
Proceedings of the 30th ACM International Conference on Information & Knowledge Management
,
Wang, Zhaonan
;
Jiang, Renhe
;
Cai, Zekun
... - p. 2060-2069 , 2021
Link:
https://dl.acm.org/doi/10.1145/3459637.3482482
RT T1 <cTitle>Proceedings of the 30th ACM International Conference on Information & Knowledge Management</cTitle>: T1 <Title>Spatio-Temporal-Categorical Graph Neural Networks for Fine-Grained Multi-Incident Co-Prediction</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3482482&Exemplar=1&LAN=DE A1 Wang, Zhaonan A1 Jiang, Renhe A1 Cai, Zekun A1 Fan, Zipei A1 Liu, Xin A1 Kim, Kyoung-Sook A1 Song, Xuan A1 Shibasaki, Ryosuke PB ACM YR 2021 K1 chain effect K1 data sparsity K1 emergency incidents K1 multi-graph convolutional recurrent neural networks K1 spatio-temporal prediction K1 Human-centered computing K1 Ubiquitous and mobile computing K1 Information systems K1 Information systems applications K1 Spatial-temporal systems K1 Computing methodologies K1 Artificial intelligence SP 2060 OP 2069 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3459637.3482482 DO https://dl.acm.org/doi/10.1145/3459637.3482482 SF ELIB - SuUB Bremen
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