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1 Ergebnisse
1
Learning Dynamic Graphs from All Contextual Information for..:
, In:
Proceedings of the 31st ACM International Conference on Advances in Geographic Information Systems
,
Hajisafi, Arash
;
Lin, Haowen
;
Shaham, Sina
... - p. 1-12 , 2023
Link:
https://dl.acm.org/doi/10.1145/3589132.3625567
RT T1 <cTitle>Proceedings of the 31st ACM International Conference on Advances in Geographic Information Systems</cTitle>: T1 <Title>Learning Dynamic Graphs from All Contextual Information for Accurate Point-of-Interest Visit Forecasting</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3625567&Exemplar=1&LAN=DE A1 Hajisafi, Arash A1 Lin, Haowen A1 Shaham, Sina A1 Hu, Haoji A1 Siampou, Maria Despoina A1 Chiang, Yao-Yi A1 Shahabi, Cyrus PB ACM YR 2023 K1 graph neural networks K1 time-series forecasting K1 POI visiting patterns K1 multi-context correlations K1 Computing methodologies K1 Machine learning K1 Learning paradigms K1 Supervised learning K1 Supervised learning by regression K1 Machine learning approaches K1 Neural networks K1 Learning latent representations SP 1 OP 12 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3589132.3625567 DO https://dl.acm.org/doi/10.1145/3589132.3625567 SF ELIB - SuUB Bremen
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