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Conference Paper: Temporal Multi-view Graph Convolutional Networks for Citywide Traffic Volume Inference

TitleTemporal Multi-view Graph Convolutional Networks for Citywide Traffic Volume Inference
Authors
Dai, SWang, JHuang, CYu, YDong, J
Issue Date2021
PublisherIEEE.
Citation
2021 IEEE International Conference on Data Mining (ICDM), p. 1042-1047 How to Cite?
DOI: http://dx.doi.org/10.1109/ICDM51629.2021.00120
Persistent Identifierhttp://hdl.handle.net/10722/321064
ISI Accession Number ID
WOS:000780454100110

 

DC FieldValueLanguage
dc.contributor.authorDai, S-
dc.contributor.authorWang, J-
dc.contributor.authorHuang, C-
dc.contributor.authorYu, Y-
dc.contributor.authorDong, J-
dc.date.accessioned2022-11-01T04:46:18Z-
dc.date.available2022-11-01T04:46:18Z-
dc.date.issued2021-
dc.identifier.citation2021 IEEE International Conference on Data Mining (ICDM), p. 1042-1047-
dc.identifier.urihttp://hdl.handle.net/10722/321064-
dc.languageeng-
dc.publisherIEEE. -
dc.relation.ispartof2021 IEEE International Conference on Data Mining (ICDM)-
dc.rights2021 IEEE International Conference on Data Mining (ICDM). Copyright © IEEE.-
dc.rights©20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.-
dc.titleTemporal Multi-view Graph Convolutional Networks for Citywide Traffic Volume Inference-
dc.typeConference_Paper-
dc.identifier.emailHuang, C: chuang7@hku.hk-
dc.identifier.authorityHuang, C=rp02897-
dc.identifier.doi10.1109/ICDM51629.2021.00120-
dc.identifier.hkuros341114-
dc.identifier.spage1042-
dc.identifier.epage1047-
dc.identifier.isiWOS:000780454100110-

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