{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,28]],"date-time":"2026-06-28T05:11:43Z","timestamp":1782623503991,"version":"3.54.5"},"reference-count":79,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"4","license":[{"start":{"date-parts":[[2023,8,1]],"date-time":"2023-08-01T00:00:00Z","timestamp":1690848000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,8,1]],"date-time":"2023-08-01T00:00:00Z","timestamp":1690848000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,8,1]],"date-time":"2023-08-01T00:00:00Z","timestamp":1690848000000},"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":["2021ZD0111902"],"award-info":[{"award-number":["2021ZD0111902"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62072015"],"award-info":[{"award-number":["62072015"]}],"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":["U21B2038"],"award-info":[{"award-number":["U21B2038"]}],"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":["U19B2039"],"award-info":[{"award-number":["U19B2039"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004826","name":"Beijing Natural Science Foundation","doi-asserted-by":"publisher","award":["4222021"],"award-info":[{"award-number":["4222021"]}],"id":[{"id":"10.13039\/501100004826","id-type":"DOI","asserted-by":"publisher"}]},{"name":"R&D Program of Beijing Municipal Education Commission","award":["KZ202210005008"],"award-info":[{"award-number":["KZ202210005008"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Big Data"],"published-print":{"date-parts":[[2023,8,1]]},"DOI":"10.1109\/tbdata.2023.3275374","type":"journal-article","created":{"date-parts":[[2023,5,11]],"date-time":"2023-05-11T17:37:25Z","timestamp":1683826645000},"page":"1210-1224","source":"Crossref","is-referenced-by-count":21,"title":["Self-Supervised Nodes-Hyperedges Embedding for Heterogeneous Information Network Learning"],"prefix":"10.1109","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7540-530X","authenticated-orcid":false,"given":"Mengran","family":"Li","sequence":"first","affiliation":[{"name":"Beijing Key Laboratory of multimedia and intelligent software technology, Beijing Institute of artificial intelligence, Department of information science, Beijing University of Technology, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6650-6790","authenticated-orcid":false,"given":"Yong","family":"Zhang","sequence":"additional","affiliation":[{"name":"Beijing Key Laboratory of multimedia and intelligent software technology, Beijing Institute of artificial intelligence, Department of information science, Beijing University of Technology, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8958-8506","authenticated-orcid":false,"given":"Wei","family":"Zhang","sequence":"additional","affiliation":[{"name":"China Agricultural University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-7536-9827","authenticated-orcid":false,"given":"Yi","family":"Chu","sequence":"additional","affiliation":[{"name":"China Electronics Technology Group Taiji Co. Ltd., Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0440-438X","authenticated-orcid":false,"given":"Yongli","family":"Hu","sequence":"additional","affiliation":[{"name":"Beijing Key Laboratory of multimedia and intelligent software technology, Beijing Institute of artificial intelligence, Department of information science, Beijing University of Technology, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3121-1823","authenticated-orcid":false,"given":"Baocai","family":"Yin","sequence":"additional","affiliation":[{"name":"Beijing Key Laboratory of multimedia and intelligent software technology, Beijing Institute of artificial intelligence, Department of information science, Beijing University of Technology, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijinfomgt.2014.10.007"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2016.2598561"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1145\/3336191.3371834"},{"key":"ref4","article-title":"Graph partition neural networks for semi-supervised classification","author":"Liao","year":"2018"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330836"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2020.3031329"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.14778\/3402707.3402736"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/3097983.3098036"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1017\/cbo9780511750854"},{"key":"ref10","first-page":"1222","article-title":"A closer look at skip-gram modelling","volume-title":"Proc. 5th Int. Conf. Lang. Resour. Eval.","author":"Guthrie"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2018.2833443"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1145\/2623330.2623732"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i5.16600"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/3357384.3357820"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219890"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1145\/3437963.3441835"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1145\/3447548.3467415"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2021.3090866"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2005.1555942"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2008.2005605"},{"key":"ref21","article-title":"Spectral networks and locally connected networks on graphs","volume-title":"Proc. 2nd Int. Conf. Learn. Representations","author":"Bruna"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1606.09375"},{"key":"ref23","article-title":"Semi-supervised classification with graph convolutional networks","author":"Kipf","year":"2016"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219947"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939754"},{"key":"ref26","article-title":"Graph attention networks","author":"Veli\u010dkovi\u0107"},{"key":"ref27","first-page":"1725","article-title":"Simple and deep graph convolutional networks","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Chen"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1145\/3132847.3132953"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1145\/3308558.3313562"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.5833"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1145\/3366423.3380027"},{"key":"ref32","article-title":"Graph attention networks","author":"Veli\u010dkovi\u0107","year":"2017"},{"key":"ref33","first-page":"11983","article-title":"Graph transformer networks","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Yun"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.7551\/mitpress\/7503.003.0205"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2015.2415497"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206795"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2010.5540012"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/439"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33013558"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/366"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1145\/3357384.3357871"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2020.2997869"},{"key":"ref43","article-title":"HNHN: Hypergraph networks with hyperedge neurons","author":"Dong","year":"2020"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2020.107637"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2021\/353"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.2992393"},{"issue":"3","key":"ref47","first-page":"4","article-title":"Deep graph infomax","volume-title":"Proc. Int. Conf. Learn. Representations (Poster)","volume":"2","author":"Velickovic"},{"key":"ref48","first-page":"4116","article-title":"Contrastive multi-view representation learning on graphs","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Hassani"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11604"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN52387.2021.9533748"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.6048"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2021\/473"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01264-9_9"},{"key":"ref54","article-title":"Deep graph contrastive representation learning","author":"Zhu","year":"2020"},{"key":"ref55","first-page":"5812","article-title":"Graph contrastive learning with augmentations","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"You"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.5985"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1214\/aoms\/1177729694"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.2307\/2331554"},{"key":"ref59","first-page":"478","article-title":"Unsupervised deep embedding for clustering analysis","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Xie"},{"key":"ref60","article-title":"VICReg: Variance-invariance-covariance regularization for self-supervised learning","author":"Bardes","year":"2021"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1145\/3565028"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2022.3185638"},{"key":"ref63","first-page":"315","article-title":"Deep sparse rectifier neural networks","volume-title":"Proc. 14th Int. Conf. Artif. Intell. Statist.","author":"Glorot"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330970"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1145\/2736277.2741093"},{"key":"ref66","first-page":"1025","article-title":"Inductive representation learning on large graphs","volume-title":"Proc. 31st Int. Conf. Neural Inf. Process. Syst.","author":"Hamilton"},{"key":"ref67","first-page":"1","article-title":"Variational graph auto-encoders","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Kipf"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330961"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1145\/3447548.3467350"},{"key":"ref70","article-title":"SHGNN: Structure-aware heterogeneous graph neural network","author":"Xu","year":"2021"},{"key":"ref71","article-title":"Heterogeneous graph neural networks using self-supervised reciprocally contrastive learning","author":"Jin","year":"2022"},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.1145\/3543507.3583493"},{"key":"ref73","article-title":"Adam: A method for stochastic optimization","author":"Kingma","year":"2014"},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.1007\/BF00994018"},{"key":"ref75","doi-asserted-by":"publisher","DOI":"10.21136\/CMJ.1973.101168"},{"key":"ref76","first-page":"7793","article-title":"Beyond homophily in graph neural networks: Current limitations and effective designs","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Zhu"},{"key":"ref77","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevE.67.026126"},{"key":"ref78","article-title":"An empirical study of graph contrastive learning","author":"Zhu","year":"2021"},{"key":"ref79","first-page":"2579","article-title":"Visualizing data using t-SNE","volume":"9","author":"Van der Maaten","year":"2008","journal-title":"J. Mach. Learn. Res."}],"container-title":["IEEE Transactions on Big Data"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6687317\/10177823\/10123057.pdf?arnumber=10123057","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,1]],"date-time":"2024-03-01T05:06:16Z","timestamp":1709269576000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10123057\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,8,1]]},"references-count":79,"journal-issue":{"issue":"4"},"URL":"https:\/\/doi.org\/10.1109\/tbdata.2023.3275374","relation":{},"ISSN":["2332-7790","2372-2096"],"issn-type":[{"value":"2332-7790","type":"electronic"},{"value":"2372-2096","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,8,1]]}}}