{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T07:13:25Z","timestamp":1784099605795,"version":"3.55.0"},"reference-count":49,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"10","license":[{"start":{"date-parts":[[2023,10,1]],"date-time":"2023-10-01T00:00:00Z","timestamp":1696118400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,10,1]],"date-time":"2023-10-01T00:00:00Z","timestamp":1696118400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,10,1]],"date-time":"2023-10-01T00:00:00Z","timestamp":1696118400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"National Key R&D Program of China","award":["2022YFB2703100"],"award-info":[{"award-number":["2022YFB2703100"]}]},{"name":"Starry Night Science Fund of Zhejiang University Shanghai Institute for Advanced Study","award":["SN-ZJU-SIAS-001"],"award-info":[{"award-number":["SN-ZJU-SIAS-001"]}]},{"DOI":"10.13039\/501100001381","name":"National Research Foundation Singapore","doi-asserted-by":"publisher","award":["AISG2-RP-2021-023"],"award-info":[{"award-number":["AISG2-RP-2021-023"]}],"id":[{"id":"10.13039\/501100001381","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Knowl. Data Eng."],"published-print":{"date-parts":[[2023,10,1]]},"DOI":"10.1109\/tkde.2023.3265271","type":"journal-article","created":{"date-parts":[[2023,4,6]],"date-time":"2023-04-06T17:42:52Z","timestamp":1680802972000},"page":"10151-10165","source":"Crossref","is-referenced-by-count":19,"title":["Temporal Aggregation and Propagation Graph Neural Networks for Dynamic Representation"],"prefix":"10.1109","volume":"35","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1190-9773","authenticated-orcid":false,"given":"Tongya","family":"Zheng","sequence":"first","affiliation":[{"name":"Big Graph Center, College of Computer Science, Hangzhou City University, and the College of Computer Science, Zhejiang University, Hangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0057-1404","authenticated-orcid":false,"given":"Xinchao","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Enigneering, National University of Singapore, Singapore"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8640-8434","authenticated-orcid":false,"given":"Zunlei","family":"Feng","sequence":"additional","affiliation":[{"name":"School of Software Technology, Zhejiang University, Hangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3671-6521","authenticated-orcid":false,"given":"Jie","family":"Song","sequence":"additional","affiliation":[{"name":"School of Software Technology, Zhejiang University, Hangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8780-5546","authenticated-orcid":false,"given":"Yunzhi","family":"Hao","sequence":"additional","affiliation":[{"name":"College of Computer Science, Zhejiang University, Hangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2621-6048","authenticated-orcid":false,"given":"Mingli","family":"Song","sequence":"additional","affiliation":[{"name":"Big Graph Center, College of Computer Science of Hangzhou City University, the ZJU-Bangsun Joint Research Center, and the Shanghai Institute for Advanced Study, Zhejiang University, Hangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0507-5020","authenticated-orcid":false,"given":"Xingen","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Computer Science, Zhejiang University, Hangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5507-6569","authenticated-orcid":false,"given":"Xinyu","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Computer Science, Zhejiang University, Hangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chun","family":"Chen","sequence":"additional","affiliation":[{"name":"College of Computer Science, Zhejiang University, Hangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","first-page":"35","article-title":"The netflix prize","volume-title":"Proc. KDD Cup Workshop","author":"Bennett"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/2487788.2488173"},{"key":"ref3","article-title":"SNAP Datasets: Stanford large network dataset collection","author":"Leskovec","year":"2014"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v29i1.9277"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/3184558.3191526"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3220054"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/640"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330895"},{"key":"ref9","first-page":"1","article-title":"Inductive representation learning on temporal graphs","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Xu"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1145\/3448016.3457564"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219890"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219869"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TNSM.2013.022713.120250"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/2623330.2623732"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939754"},{"key":"ref16","first-page":"1","article-title":"Semi-supervised classification with graph convolutional networks","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Kipf"},{"key":"ref17","first-page":"1024","article-title":"Inductive representation learning on large graphs","volume-title":"Proc. 31st Int. Conf. Neural Inf. Process. Syst.","author":"Hamilton"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2018.03.022"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.5984"},{"key":"ref20","first-page":"161","article-title":"The PageRank citation ranking: Bringing order to the web","volume-title":"Proc. ASIS","volume":"98","author":"Sergey","year":"1998"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1126\/science.290.5500.2323"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.7551\/mitpress\/1120.003.0080"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.14778\/3402707.3402736"},{"key":"ref24","first-page":"1097","article-title":"ImageNet classification with deep convolutional neural networks","volume-title":"Proc. 26th Int. Conf. Neural Inf. Process. Syst.","author":"Krizhevsky"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1310.4546"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.2978386"},{"key":"ref27","first-page":"3844","article-title":"Convolutional neural networks on graphs with fast localized spectral filtering","volume-title":"Proc. 30th Int. Conf. Neural Inf. Process. Syst.","author":"Defferrard"},{"key":"ref28","first-page":"1","article-title":"Graph attention networks","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Veli\u010dkovi\u0107"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1145\/2736277.2741093"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33015941"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1145\/3331184.3331267"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11257"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11747"},{"key":"ref34","first-page":"1603","article-title":"EPNE: Evolutionary pattern preserving network embedding","volume-title":"Proc. 24th Eur. Conf. Artif. Intell.","author":"Wang"},{"key":"ref35","first-page":"3462","article-title":"Know-evolve: Deep temporal reasoning for dynamic knowledge graphs","volume-title":"Proc. 34th Int. Conf. Mach. Learn.","author":"Trivedi"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.2019.2932913"},{"issue":"70","key":"ref37","first-page":"1","article-title":"Representation learning for dynamic graphs: A survey","volume":"21","author":"Kazemi","year":"2020","journal-title":"J. Mach. Learn. Res."},{"key":"ref38","first-page":"1","article-title":"DyRep: Learning representations over dynamic graphs","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Trivedi"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1145\/3366423.3380076"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403218"},{"key":"ref41","first-page":"1263","article-title":"Neural message passing for quantum chemistry","volume-title":"Proc. 34th Int. Conf. Mach. Learn.","author":"Gilmer"},{"key":"ref42","first-page":"1","article-title":"Deep graph library: Towards efficient and scalable deep learning on graphs","volume-title":"Proc. ICLR Workshop Representation Learn. Graphs Manifolds","author":"Wang"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1145\/3366423.3380073"},{"issue":"2001","key":"ref44","first-page":"2001","article-title":"Linguistic inquiry and word count: LIWC 2001","volume":"71","author":"Pennebaker","year":"2001","journal-title":"Mahway: Lawrence Erlbaum Associates"},{"key":"ref45","article-title":"Temporal graph networks for deep learning on dynamic graphs","author":"Rossi","year":"2020"},{"key":"ref46","first-page":"8026","article-title":"PyTorch: An imperative style, high-performance deep learning library","volume-title":"Proc. 33th Int. Conf. Neural Inf. Process. Syst.","author":"Paszke"},{"key":"ref47","first-page":"887","article-title":"On the dimensionality of word embedding","volume-title":"Proc. 32nd Int. Conf. Neural Inf. Process. Syst.","author":"Yin"},{"key":"ref48","article-title":"Improving neural networks by preventing co-adaptation of feature detectors","author":"Hinton","year":"2012"},{"key":"ref49","first-page":"2579","article-title":"Visualizing data using t-SNE","volume":"9","author":"Maaten","year":"2008","journal-title":"J. Mach. Learn. Res."}],"container-title":["IEEE Transactions on Knowledge and Data Engineering"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/69\/10251471\/10094005.pdf?arnumber=10094005","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,5,13]],"date-time":"2024-05-13T17:39:31Z","timestamp":1715621971000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10094005\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10,1]]},"references-count":49,"journal-issue":{"issue":"10"},"URL":"https:\/\/doi.org\/10.1109\/tkde.2023.3265271","relation":{},"ISSN":["1041-4347","1558-2191","2326-3865"],"issn-type":[{"value":"1041-4347","type":"print"},{"value":"1558-2191","type":"electronic"},{"value":"2326-3865","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,10,1]]}}}