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1 Ergebnisse
1
Learning Joint Relational Co-evolution in Spatial-Temporal ..:
, In:
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
,
Li, Youru
;
Zhu, Zhenfeng
;
Guo, Xiaobo
... - p. 4426-4436 , 2023
Link:
https://dl.acm.org/doi/10.1145/3580305.3599855
RT T1 <cTitle>Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining</cTitle>: T1 <Title>Learning Joint Relational Co-evolution in Spatial-Temporal Knowledge Graph for SMEs Supply Chain Prediction</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3599855&Exemplar=1&LAN=DE A1 Li, Youru A1 Zhu, Zhenfeng A1 Guo, Xiaobo A1 Chen, Linxun A1 Wang, Zhouyin A1 Wang, Yinmeng A1 Han, Bing A1 Zhao, Yao PB ACM YR 2023 K1 deep learning K1 knowledge graph K1 supply chain prediction K1 Applied computing K1 Law, social and behavioral sciences K1 Economics K1 Computing methodologies K1 Artificial intelligence K1 Knowledge representation and reasoning K1 Information systems K1 Information systems applications K1 Spatial-temporal systems SP 4426 OP 4436 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3580305.3599855 DO https://dl.acm.org/doi/10.1145/3580305.3599855 SF ELIB - SuUB Bremen
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