{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,28]],"date-time":"2026-10-28T16:56:21Z","timestamp":1793206581441,"version":"4.5.0"},"reference-count":45,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"11","license":[{"start":{"date-parts":[[2023,11,1]],"date-time":"2023-11-01T00:00:00Z","timestamp":1698796800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,11,1]],"date-time":"2023-11-01T00:00:00Z","timestamp":1698796800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,11,1]],"date-time":"2023-11-01T00:00:00Z","timestamp":1698796800000},"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":["61871470"],"award-info":[{"award-number":["61871470"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Neural Netw. Learning Syst."],"published-print":{"date-parts":[[2023,11]]},"DOI":"10.1109\/tnnls.2022.3158654","type":"journal-article","created":{"date-parts":[[2022,3,25]],"date-time":"2022-03-25T19:40:59Z","timestamp":1648237259000},"page":"9352-9362","source":"Crossref","is-referenced-by-count":98,"title":["Embedding Graph Auto-Encoder for Graph Clustering"],"prefix":"10.1109","volume":"34","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4274-7332","authenticated-orcid":false,"given":"Hongyuan","family":"Zhang","sequence":"first","affiliation":[{"name":"School of Computer Science and the School of Artificial Intelligence, OPtics and ElectroNics, Northwestern Polytechnical University, Xi&#x2019;an, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pei","family":"Li","sequence":"additional","affiliation":[{"name":"School of Computer Science and the School of Artificial Intelligence, OPtics and ElectroNics, Northwestern Polytechnical University, Xi&#x2019;an, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9418-0863","authenticated-orcid":false,"given":"Rui","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, OPtics and ElectroNics, Northwestern Polytechnical University, Xi&#x2019;an, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2924-946X","authenticated-orcid":false,"given":"Xuelong","family":"Li","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, OPtics and ElectroNics, Northwestern Polytechnical University, Xi&#x2019;an, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v28i1.8916"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00662"},{"key":"ref12","first-page":"1","article-title":"SpectralNet: Spectral clustering using deep neural networks","author":"shaham","year":"2018","journal-title":"Proc Int Conf Learn Represent"},{"key":"ref34","article-title":"Adaptive graph auto-encoder for general data clustering","author":"li","year":"2021","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.2978389"},{"key":"ref37","first-page":"21","article-title":"Mixhop: Higher-order graph convolutional architectures via sparsified neighborhood mixing","author":"abu-el-haija","year":"2019","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TFUZZ.2019.2945232"},{"key":"ref36","article-title":"AnchorGAE: General data clustering via O(n) bipartite graph convolution","author":"zhang","year":"2021","journal-title":"arXiv 2111 06586"},{"key":"ref31","article-title":"Graph attention networks","author":"veli?kovi?","year":"2017","journal-title":"arXiv 1710 10903"},{"key":"ref30","first-page":"2014","article-title":"Learning convolutional neural networks for graphs","author":"niepert","year":"2016","journal-title":"Proc Int Conf Mach Learn (ICML)"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1126\/science.1127647"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2012.2235192"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2018.2882925"},{"key":"ref32","article-title":"A comprehensive survey on graph neural networks","author":"wu","year":"2019","journal-title":"arXiv 1901 00596"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/2623330.2623726"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1080\/01969727308546046"},{"key":"ref17","first-page":"478","article-title":"Unsupervised deep embedding for clustering analysis","author":"xie","year":"2016","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/601"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2018.2848470"},{"key":"ref38","first-page":"6861","article-title":"Simplifying graph convolutional networks","author":"wu","year":"2019","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11872"},{"key":"ref18","article-title":"NetGAN: Generating graphs via random walks","author":"bojchevski","year":"2018","journal-title":"arXiv 1803 00816"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v31i1.10488"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2019.2910151"},{"key":"ref45","first-page":"1","article-title":"Query-driven active surveying for collective classification","volume":"8","author":"namata","year":"2012","journal-title":"Proc 10th Int Workshop Mining Learn With Graphs"},{"key":"ref26","first-page":"2111","article-title":"Network representation learning with rich text information","author":"yang","year":"2015","journal-title":"Proc 24th Int Joint Conf Artif Intell"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2015.105"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1145\/2623330.2623732"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v28i1.8916"},{"key":"ref41","first-page":"2579","article-title":"Visualizing data using t-SNE","volume":"9","author":"van der maaten","year":"2008","journal-title":"J Mach Learn Res"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2020.2988255"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1609\/aimag.v29i3.2157"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/MWC.2019.1800397"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v30i1.10179"},{"key":"ref28","first-page":"3844","article-title":"Convolutional neural networks on graphs with fast localized spectral filtering","author":"defferrard","year":"2016","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref27","article-title":"Spectral networks and locally connected networks on graphs","author":"bruna","year":"2013","journal-title":"arXiv 1312 6203"},{"key":"ref29","first-page":"1","article-title":"Semi-supervised classification with graph convolutional networks","author":"kipf","year":"2017","journal-title":"Proc ICLR"},{"key":"ref8","first-page":"226","article-title":"Density-based algorithm for discovering clusters in large spatial databases with noise","author":"ester","year":"1996","journal-title":"Proc KDD"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/3132847.3132967"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1126\/science.1136800"},{"key":"ref4","first-page":"849","article-title":"On spectral clustering: Analysis and an algorithm","author":"ng","year":"2002","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref3","doi-asserted-by":"crossref","first-page":"888","DOI":"10.1109\/34.868688","article-title":"Normalized cuts and image segmentation","volume":"22","author":"shi","year":"2000","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"ref6","article-title":"Variational graph auto-encoders","author":"kipf","year":"2016","journal-title":"arXiv 1611 07308"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.3007637"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/362"}],"container-title":["IEEE Transactions on Neural Networks and Learning Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/5962385\/10299535\/09741755.pdf?arnumber=9741755","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,20]],"date-time":"2023-11-20T19:26:17Z","timestamp":1700508377000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9741755\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,11]]},"references-count":45,"journal-issue":{"issue":"11"},"URL":"https:\/\/doi.org\/10.1109\/tnnls.2022.3158654","relation":{},"ISSN":["2162-237X","2162-2388"],"issn-type":[{"value":"2162-237X","type":"print"},{"value":"2162-2388","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,11]]}}}