{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T16:44:35Z","timestamp":1781628275626,"version":"3.54.5"},"reference-count":56,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"7","license":[{"start":{"date-parts":[[2025,4,1]],"date-time":"2025-04-01T00:00:00Z","timestamp":1743465600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,4,1]],"date-time":"2025-04-01T00:00:00Z","timestamp":1743465600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,4,1]],"date-time":"2025-04-01T00:00:00Z","timestamp":1743465600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["52071312"],"award-info":[{"award-number":["52071312"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Internet Things J."],"published-print":{"date-parts":[[2025,4,1]]},"DOI":"10.1109\/jiot.2024.3502517","type":"journal-article","created":{"date-parts":[[2024,11,19]],"date-time":"2024-11-19T13:46:09Z","timestamp":1732023969000},"page":"8638-8652","source":"Crossref","is-referenced-by-count":2,"title":["CLGSDN: Contrastive-Learning-Based Graph Structure Denoising Network for Traffic Prediction"],"prefix":"10.1109","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-9978-6872","authenticated-orcid":false,"given":"Peng","family":"Peng","sequence":"first","affiliation":[{"name":"School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-3688-7056","authenticated-orcid":false,"given":"Xuewen","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-0684-105X","authenticated-orcid":false,"given":"Xudong","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7150-0243","authenticated-orcid":false,"given":"Haina","family":"Tang","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hanji","family":"Shen","sequence":"additional","affiliation":[{"name":"Computer Network Information Center, Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jun","family":"Li","sequence":"additional","affiliation":[{"name":"Computer Network Information Center, Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"crossref","first-page":"4927","DOI":"10.1109\/TITS.2021.3054840","article-title":"Deep learning on traffic prediction: Methods, analysis, and future directions","volume":"23","author":"Yin","year":"2022","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2017.2716114"},{"key":"ref3","first-page":"1","article-title":"Diffusion convolutional recurrent neural network: Data-driven traffic forecasting","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Li"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP43922.2022.9746497"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2023.3243122"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2021.3093523"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2024.3362433"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/ICETCI57876.2023.10176584"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/ICCSI55536.2022.9970676"},{"key":"ref10","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1007\/s41019-020-00151-z","article-title":"A survey of traffic prediction: From spatio-temporal data to intelligent transportation","volume":"6","author":"Yuan","year":"2021","journal-title":"Data Sci. Eng."},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.2978386"},{"key":"ref12","doi-asserted-by":"crossref","first-page":"7796","DOI":"10.1109\/TVT.2023.3239054","article-title":"Semantics-aware dynamic graph convolutional network for traffic flow forecasting","volume":"72","author":"Liang","year":"2023","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref13","first-page":"1","article-title":"A survey on deep graph generation: Methods and applications","volume-title":"Proc. 1st Learn. Graphs Conf.","author":"Zhu"},{"key":"ref14","article-title":"Deep graph structure learning for robust representations: A survey","author":"Zhu","year":"2021","journal-title":"arXiv:2103.03036"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/264"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.3301922"},{"key":"ref17","first-page":"17804","article-title":"Adaptive graph convolutional recurrent network for traffic forecasting","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"33","author":"Bai"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/505"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1145\/3269206.3271692"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1007\/s10462-022-10351-w"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i01.5438"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403177"},{"key":"ref23","first-page":"1972","article-title":"Learning discrete structures for graph neural networks","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Franceschi"},{"key":"ref24","first-page":"11458","article-title":"Robust graph representation learning via neural sparsification","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Zheng"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/ICME46284.2020.9102726"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/563"},{"key":"ref27","first-page":"1","article-title":"Diffusion-convolutional neural networks","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"29","author":"Atwood"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11691"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.14778\/3551793.3551827"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN55064.2022.9892031"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1706.03762"},{"key":"ref32","article-title":"Graph attention networks","author":"Velickovic","year":"2017","journal-title":"arXiv:1710.10903"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3449952"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1145\/3437963.3441734"},{"key":"ref35","first-page":"19314","article-title":"Iterative deep graph learning for graph neural networks: Better and robust node embeddings","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"33","author":"Chen"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1145\/3534678.3539422"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i9.26336"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2023.3288135"},{"key":"ref39","first-page":"5812","article-title":"Graph contrastive learning with augmentations","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"33","author":"You"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403168"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1145\/3557915.3560939"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1145\/3543507.3583304"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1145\/2996913.2997016"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i5.16542"},{"key":"ref45","first-page":"1","article-title":"TESTAM: A time-enhanced spatio-temporal attention model with mixture of experts","volume-title":"Proc. 12th Int. Conf. Learn. Represent.","author":"Lee"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i7.25976"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i4.25547"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i8.26168"},{"key":"ref49","first-page":"1","article-title":"DropEdge: Towards deep graph convolutional networks on node classification","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Rong"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1406.1078"},{"key":"ref52","first-page":"11906","article-title":"DSTAGNN: Dynamic spatial-temporal aware graph neural network for traffic flow forecasting","volume-title":"Proc. 39th Int. Conf. Mach. Learn.","author":"Lan"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1145\/3589270"},{"key":"ref54","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2023.109670","article-title":"A decomposition dynamic graph convolutional recurrent network for traffic forecasting","volume":"142","author":"Weng","year":"2023","journal-title":"Pattern Recognit."},{"key":"ref55","first-page":"1","article-title":"Semi-supervised classification with graph convolutional networks","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Kipf"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v31i1.10735"}],"container-title":["IEEE Internet of Things Journal"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6488907\/10939020\/10757324.pdf?arnumber=10757324","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,20]],"date-time":"2026-05-20T19:53:44Z","timestamp":1779306824000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10757324\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,4,1]]},"references-count":56,"journal-issue":{"issue":"7"},"URL":"https:\/\/doi.org\/10.1109\/jiot.2024.3502517","relation":{},"ISSN":["2327-4662","2372-2541"],"issn-type":[{"value":"2327-4662","type":"electronic"},{"value":"2372-2541","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,4,1]]}}}