{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,13]],"date-time":"2026-03-13T03:00:21Z","timestamp":1773370821475,"version":"3.50.1"},"reference-count":23,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"Beijing Municipal Natural Science Foundation Haidian","award":["L182037"],"award-info":[{"award-number":["L182037"]}]},{"DOI":"10.13039\/501100009592","name":"Beijing Municipal Science and Technology Commission","doi-asserted-by":"publisher","award":["Z181100003218015"],"award-info":[{"award-number":["Z181100003218015"]}],"id":[{"id":"10.13039\/501100009592","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Signal Process. Lett."],"published-print":{"date-parts":[[2021]]},"DOI":"10.1109\/lsp.2020.3048849","type":"journal-article","created":{"date-parts":[[2021,1,5]],"date-time":"2021-01-05T21:07:55Z","timestamp":1609880875000},"page":"239-243","source":"Crossref","is-referenced-by-count":24,"title":["GraphTTE: Travel Time Estimation Based on Attention-Spatiotemporal Graphs"],"prefix":"10.1109","volume":"28","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9392-475X","authenticated-orcid":false,"given":"Qiang","family":"Wang","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5306-2155","authenticated-orcid":false,"given":"Chen","family":"Xu","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4482-6715","authenticated-orcid":false,"given":"Wenqi","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Jingjing","family":"Li","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/ICTIS.2017.8047744"},{"key":"ref11","first-page":"1","article-title":"When will you arrive? estimating travel time based on deep neural networks","author":"wang","year":"0","journal-title":"Proc AAAI Conf Artif Intell"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1145\/3293317"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219900"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/3357384.3357870"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403320"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1007\/s10707-020-00422-x"},{"key":"ref17","first-page":"2135","article-title":"Effective travel time estimation: When historical trajectories over road networks matter","author":"yuan","year":"0","journal-title":"Proc ACM SIGMOD Int Conf Manage Data"},{"key":"ref18","article-title":"Semi-supervised classification with graph convolutional networks","author":"kipf","year":"2016"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/W14-4012"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3220033"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC.2017.8317783"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/2820783.2820836"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/234"},{"key":"ref8","article-title":"Real-time travel time estimation using matrix factorization","author":"badrestani","year":"2019","journal-title":"arXiv 1912 00455"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/3308558.3313418"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/LSP.2019.2896793"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/LSP.2018.2885511"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2019.2899906"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2019.2950416"},{"key":"ref22","first-page":"4800","article-title":"Hierarchical graph representation learning with differentiable pooling","author":"ying","year":"0","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref21","article-title":"Graph U-Nets","author":"gao","year":"2019"},{"key":"ref23","doi-asserted-by":"crossref","first-page":"1189","DOI":"10.1214\/aos\/1013203451","article-title":"Greedy function approximation: A gradient boosting machine","volume":"29","author":"friedman","year":"2001","journal-title":"Ann Statist"}],"container-title":["IEEE Signal Processing Letters"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/97\/9325893\/09314202.pdf?arnumber=9314202","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T14:50:31Z","timestamp":1652194231000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9314202\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"references-count":23,"URL":"https:\/\/doi.org\/10.1109\/lsp.2020.3048849","relation":{},"ISSN":["1070-9908","1558-2361"],"issn-type":[{"value":"1070-9908","type":"print"},{"value":"1558-2361","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]}}}