{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,16]],"date-time":"2025-10-16T06:58:41Z","timestamp":1760597921956,"version":"3.37.3"},"reference-count":45,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61902278"],"award-info":[{"award-number":["61902278"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Tianjin Science and Technology Development Strategic Research Project","award":["17ZLZDZF00430"],"award-info":[{"award-number":["17ZLZDZF00430"]}]},{"name":"Key Research and Development Program of Tianjin","award":["18YFZCSF01370"],"award-info":[{"award-number":["18YFZCSF01370"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2019]]},"DOI":"10.1109\/access.2019.2958326","type":"journal-article","created":{"date-parts":[[2019,12,16]],"date-time":"2019-12-16T15:23:57Z","timestamp":1576509837000},"page":"177484-177496","source":"Crossref","is-referenced-by-count":6,"title":["Deep Mutual Encode Model for Network Embedding From Structural Identity"],"prefix":"10.1109","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1174-7241","authenticated-orcid":false,"given":"Hongyao","family":"Ke","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7030-7046","authenticated-orcid":false,"given":"Yinghui","family":"Wang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8569-4192","authenticated-orcid":false,"given":"Xuan","family":"Guo","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5074-7661","authenticated-orcid":false,"given":"Lin","family":"Pan","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1049-1002","authenticated-orcid":false,"given":"Pengfei","family":"Jiao","sequence":"additional","affiliation":[]},{"given":"Wenjun","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Xiaoping","family":"Yang","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939751"},{"key":"ref38","first-page":"1137","article-title":"A neural probabilistic language model","volume":"3","author":"bengio","year":"2003","journal-title":"J Mach Learn Res"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1007\/BF02289694"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1198\/016214502388618906"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1016\/0022-2496(75)90028-0"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2839770"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1145\/2339530.2339723"},{"journal-title":"Applied network analysis A methodological introduction","year":"1983","author":"burt","key":"ref36"},{"key":"ref35","doi-asserted-by":"crossref","first-page":"788","DOI":"10.1038\/44565","article-title":"Learning the parts of objects by non-negative matrix factorization","volume":"401","author":"lee","year":"1999","journal-title":"Nature"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-662-39778-7_10"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2932396"},{"key":"ref40","article-title":"role2vec: Role-based network embeddings","author":"ahmed","year":"2019","journal-title":"Proc DLG KDD"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1177\/0268580907082260"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1145\/2871148"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611974348.9"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939807"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/0378-8733(78)90014-X"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1145\/324133.324140"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1198\/016214501753208735"},{"key":"ref18","first-page":"1981","article-title":"Mixed membership stochastic blockmodels","volume":"9","author":"airoldi","year":"2008","journal-title":"J Mach Learn Res"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2014.2349913"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1145\/2983323.2983754"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2018.2807452"},{"key":"ref27","first-page":"203","article-title":"Community preserving network embedding","author":"wang","year":"2017","journal-title":"Proc 31st AAAI Conf Artif Intell"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2018.2849727"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2018.03.022"},{"key":"ref29","first-page":"1145","article-title":"Deep neural networks for learning graph representations","author":"cao","year":"2016","journal-title":"Proc 13th AAAI Conf Artif Intell"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TBDATA.2018.2850013"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/2736277.2741093"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/2623330.2623732"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/2160718.2160738"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939753"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.aml.2007.01.006"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939754"},{"key":"ref45","article-title":"ADADELTA: An adaptive learning rate method","author":"zeiler","year":"2012","journal-title":"arXiv 1212 5701"},{"key":"ref22","article-title":"Learning role-based graph embeddings","author":"ahmed","year":"2018","journal-title":"arXiv 1802 02896"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1145\/3097983.3098061"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevE.73.026120"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P16-1095"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1016\/0378-8733(93)90012-A"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3220068"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3220025"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1126\/science.290.5500.2323"},{"key":"ref43","article-title":"Semi-supervised classification with graph convolutional networks","author":"kipf","year":"2016","journal-title":"arXiv 1609 02907"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1145\/2806416.2806512"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/8600701\/08928559.pdf?arnumber=8928559","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,12]],"date-time":"2022-01-12T11:31:43Z","timestamp":1641987103000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8928559\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"references-count":45,"URL":"https:\/\/doi.org\/10.1109\/access.2019.2958326","relation":{},"ISSN":["2169-3536"],"issn-type":[{"type":"electronic","value":"2169-3536"}],"subject":[],"published":{"date-parts":[[2019]]}}}