{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,21]],"date-time":"2026-03-21T19:31:34Z","timestamp":1774121494324,"version":"3.50.1"},"reference-count":48,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"4","license":[{"start":{"date-parts":[[2022,7,1]],"date-time":"2022-07-01T00:00:00Z","timestamp":1656633600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2022,7,1]],"date-time":"2022-07-01T00:00:00Z","timestamp":1656633600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,7,1]],"date-time":"2022-07-01T00:00:00Z","timestamp":1656633600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"National Key R&amp;D Program of China","award":["2018AAA0102100"],"award-info":[{"award-number":["2018AAA0102100"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U1936206"],"award-info":[{"award-number":["U1936206"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61906190"],"award-info":[{"award-number":["61906190"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61906191"],"award-info":[{"award-number":["61906191"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62077031"],"award-info":[{"award-number":["62077031"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Netw. Sci. Eng."],"published-print":{"date-parts":[[2022,7,1]]},"DOI":"10.1109\/tnse.2022.3164659","type":"journal-article","created":{"date-parts":[[2022,4,5]],"date-time":"2022-04-05T19:31:40Z","timestamp":1649187100000},"page":"2495-2509","source":"Crossref","is-referenced-by-count":23,"title":["SE-GRU: Structure Embedded Gated Recurrent Unit Neural Networks for Temporal Link Prediction"],"prefix":"10.1109","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6638-405X","authenticated-orcid":false,"given":"Yanting","family":"Yin","sequence":"first","affiliation":[{"name":"Tianjin Key Laboratory of Network and Data Security Technology, College of Computer Science, Nankai University, Tianjin, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4735-0377","authenticated-orcid":false,"given":"Yajing","family":"Wu","sequence":"additional","affiliation":[{"name":"Institute of Automation, Chinese Academy of Sciences, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8343-125X","authenticated-orcid":false,"given":"Xuebing","family":"Yang","sequence":"additional","affiliation":[{"name":"Institute of Automation, Chinese Academy of Sciences, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0752-941X","authenticated-orcid":false,"given":"Wensheng","family":"Zhang","sequence":"additional","affiliation":[{"name":"Institute of Automation, Chinese Academy of Sciences, Beijing, China"}]},{"given":"Xiaojie","family":"Yuan","sequence":"additional","affiliation":[{"name":"Tianjin Key Laboratory of Network and Data Security Technology, College of Computer Science, Nankai University, Tianjin, China"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4419-6515-8_13"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.physa.2017.12.092"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-014-0631-0"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevE.91.052813"},{"key":"ref5","first-page":"2492","article-title":"Continuous-time regression models for longitudinal networks","author":"Vu","year":"2011","journal-title":"Proc. Adv. Neural Inf. Process. Syst."},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/S0378-8733(03)00009-1"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.21307\/ijssis-2017-592"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1093\/bfgp\/elr024"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0191939"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-10-3953-9_33"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1155\/2018\/1260860"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.23919\/ITC.2017.8064341"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3082932"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-021-02518-9"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.5984"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2019.06.024"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2019.2920268"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/BigData47090.2019.9005545"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.3233\/ida-205524"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i5.16586"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM.2019.8737631"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i07.6819"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1145\/3018661.3018669"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611973440.33"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1145\/3229543.3229546"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2017.06.025"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1145\/3269206.3271740"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-04167-0_33"},{"key":"ref29","first-page":"5171","article-title":"Link prediction based on graph neural networks","volume":"31","author":"Zhang","year":"2018","journal-title":"Proc. Adv. Neural Inf. Process. Syst."},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.2019.2932913"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1145\/3289600.3290998"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939753"},{"key":"ref33","article-title":"DynamicGEM: A library for dynamic graph embedding methods","author":"Goyal","year":"2018"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2017.2765202"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-18576-3_32"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2021.3084957"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2009.191"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330895"},{"key":"ref39","first-page":"1","article-title":"DyRep: Learning representations over dynamic graphs","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Trivedi","year":"2019"},{"key":"ref40","article-title":"Gaussian error linear units (GELUs","author":"Hendrycks","year":"2016"},{"key":"ref41","first-page":"1","article-title":"Empirical evaluation of gated recurrent neural networks on sequence modeling","author":"Chung","year":"2014"},{"key":"ref42","first-page":"51","article-title":"Estimation of simultaneously sparse and low rank matrices","volume-title":"Proc. 29th Int. Conf. Mach. Learn.","author":"Savalle","year":"2012"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1214\/11-AOS894"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1007\/s11192-007-1707-y"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1146\/annurev.soc.27.1.415"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v29i1.9277"},{"issue":"1","key":"ref47","first-page":"115","article-title":"Making a science of model search: Hyperparameter optimization in hundreds of dimensions for vision architectures","volume":"28","author":"Bergstra","year":"2013","journal-title":"Proc. 30th Int. Conf. Mach. Learn."},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1016\/S0031-3203(96)00142-2"}],"container-title":["IEEE Transactions on Network Science and Engineering"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6488902\/9808096\/09749946.pdf?arnumber=9749946","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,18]],"date-time":"2024-01-18T00:41:41Z","timestamp":1705538501000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9749946\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,7,1]]},"references-count":48,"journal-issue":{"issue":"4"},"URL":"https:\/\/doi.org\/10.1109\/tnse.2022.3164659","relation":{},"ISSN":["2327-4697","2334-329X"],"issn-type":[{"value":"2327-4697","type":"electronic"},{"value":"2334-329X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,7,1]]}}}