{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,26]],"date-time":"2026-04-26T09:14:46Z","timestamp":1777194886328,"version":"3.51.4"},"reference-count":52,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"1","license":[{"start":{"date-parts":[[2024,2,1]],"date-time":"2024-02-01T00:00:00Z","timestamp":1706745600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2024,2,1]],"date-time":"2024-02-01T00:00:00Z","timestamp":1706745600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,2,1]],"date-time":"2024-02-01T00:00:00Z","timestamp":1706745600000},"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":["61906219"],"award-info":[{"award-number":["61906219"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"MBZUAI"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Emerg. Top. Comput. Intell."],"published-print":{"date-parts":[[2024,2]]},"DOI":"10.1109\/tetci.2023.3322341","type":"journal-article","created":{"date-parts":[[2023,10,25]],"date-time":"2023-10-25T18:02:28Z","timestamp":1698256948000},"page":"1003-1014","source":"Crossref","is-referenced-by-count":19,"title":["Heterogeneous Graph Contrastive Learning With Metapath-Based Augmentations"],"prefix":"10.1109","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7673-0670","authenticated-orcid":false,"given":"Xiaoru","family":"Chen","sequence":"first","affiliation":[{"name":"School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3284-1464","authenticated-orcid":false,"given":"Yingxu","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Machine Learning, Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, UAE"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6886-5882","authenticated-orcid":false,"given":"Jinyuan","family":"Fang","sequence":"additional","affiliation":[{"name":"School of Computing Science, University of Glasgow, Glasgow, U.K."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5374-0318","authenticated-orcid":false,"given":"Zaiqiao","family":"Meng","sequence":"additional","affiliation":[{"name":"School of Computing Science, University of Glasgow, Glasgow, U.K."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1625-2168","authenticated-orcid":false,"given":"Shangsong","family":"Liang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1145\/2481244.2481248"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2008.2005605"},{"key":"ref3","first-page":"1","article-title":"Semi-supervised classification with graph convolutional networks","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Kipf","year":"2016"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1145\/3097983.3098036"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/3308558.3313562"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/3534678.3539482"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2018.2833443"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219965"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1145\/3534678.3539080"},{"key":"ref10","first-page":"5812","article-title":"Graph contrastive learning with augmentations","volume-title":"Proc. Annu. Conf. Neural Inf. Process. Syst.","author":"You","year":"2020"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1145\/3485447.3512156"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1145\/3447548.3467415"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.5985"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/3511808.3557490"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611977172.10"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611977653.ch16"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.14778\/3402707.3402736"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2020.3045924"},{"key":"ref19","first-page":"1","article-title":"HDGI: An unsupervised graph neural network for representation learning in heterogeneous graph","volume-title":"Proc. AAAI Conf. Artif. Intell. Workshop","author":"Ren","year":"2020"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3220006"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219986"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-93417-4_38"},{"key":"ref23","first-page":"2331","article-title":"MAGNN: Metapath aggregated graph neural network for heterogeneous graph embedding","volume-title":"Proc. World Wide Web Conf.","author":"Xinyu","year":"2020"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1145\/3132847.3132953"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1145\/3357384.3358061"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1145\/2783258.2783307"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2020.2992500"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2021.3074654"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2021.3079239"},{"key":"ref30","first-page":"15509","article-title":"Learning representations by maximizing mutual information across views","volume-title":"Proc. Annu. Conf. Neural Inf. Process. Syst.","author":"Bachman","year":"2019"},{"key":"ref31","first-page":"1597","article-title":"A simple framework for contrastive learning of visual representations","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Ting","year":"2020"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58621-8_45"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2021.3131584"},{"key":"ref34","first-page":"1","article-title":"Deep graph infomax","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Velickovic","year":"2019"},{"key":"ref35","first-page":"1","article-title":"Learning deep representations by mutual information estimation and maximization","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Hjelm","year":"2019"},{"key":"ref36","first-page":"4116","article-title":"Contrastive multi-view representation learning on graphs","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Hassani","year":"2020"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2022.3177295"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00393"},{"key":"ref39","article-title":"Deep graph contrastive representation learning","author":"Yanqiao","year":"2020"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3449802"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1145\/3534678.3539425"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1145\/3459637.3482332"},{"key":"ref43","first-page":"1","article-title":"Graph attention networks","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Velickovic","year":"2018"},{"key":"ref44","article-title":"Representation learning with contrastive predictive coding","author":"Oord","year":"2018"},{"key":"ref45","first-page":"11960","article-title":"Graph transformer networks","volume-title":"Proc. Annu. Conf. Neural Inf. Process. Syst.","author":"Yun","year":"2019"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i5.16544"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-86520-7_20"},{"key":"ref48","first-page":"249","article-title":"Understanding the difficulty of training deep feedforward neural networks","volume-title":"Proc. 13th Int. Conf. Artif. Intell. Statist.","author":"Glorot","year":"2010"},{"key":"ref49","first-page":"1","article-title":"Adam: A method for stochastic optimization","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Kingma","year":"2015"},{"key":"ref50","first-page":"2837","article-title":"Information theoretic measures for clusterings comparison: Variants, properties, normalization and correction for chance","volume":"11","author":"Nguyen","year":"2010","journal-title":"J. Mach. Learn. Res."},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.1982.1056489"},{"key":"ref52","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 Emerging Topics in Computational Intelligence"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/7433297\/10412693\/10296092.pdf?arnumber=10296092","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,26]],"date-time":"2024-11-26T18:56:55Z","timestamp":1732647415000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10296092\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,2]]},"references-count":52,"journal-issue":{"issue":"1"},"URL":"https:\/\/doi.org\/10.1109\/tetci.2023.3322341","relation":{},"ISSN":["2471-285X"],"issn-type":[{"value":"2471-285X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,2]]}}}