{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T16:33:37Z","timestamp":1775838817747,"version":"3.50.1"},"reference-count":40,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"9","license":[{"start":{"date-parts":[[2023,9,1]],"date-time":"2023-09-01T00:00:00Z","timestamp":1693526400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,9,1]],"date-time":"2023-09-01T00:00:00Z","timestamp":1693526400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,9,1]],"date-time":"2023-09-01T00:00:00Z","timestamp":1693526400000},"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":["2019YFB1600700"],"award-info":[{"award-number":["2019YFB1600700"]}]},{"name":"Starry Night Science Fund of Zhejiang University Shanghai Institute for Advanced Study","award":["SN-ZJU-SIAS-001"],"award-info":[{"award-number":["SN-ZJU-SIAS-001"]}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["226-2022-00064"],"award-info":[{"award-number":["226-2022-00064"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Open Research Projects of Zhejiang Lab","award":["2019KD0AD01\/018"],"award-info":[{"award-number":["2019KD0AD01\/018"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Knowl. Data Eng."],"published-print":{"date-parts":[[2023,9,1]]},"DOI":"10.1109\/tkde.2022.3208604","type":"journal-article","created":{"date-parts":[[2022,9,22]],"date-time":"2022-09-22T23:07:30Z","timestamp":1663888050000},"page":"8742-8756","source":"Crossref","is-referenced-by-count":2,"title":["HSDN: A High-Order Structural Semantic Disentangled Neural Network"],"prefix":"10.1109","volume":"35","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2556-9239","authenticated-orcid":false,"given":"Bingde","family":"Hu","sequence":"first","affiliation":[{"name":"College of Computer Science, Zhejiang University, Hangzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0507-5020","authenticated-orcid":false,"given":"Xingen","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Computer Science, Zhejiang University, Hangzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8640-8434","authenticated-orcid":false,"given":"Zunlei","family":"Feng","sequence":"additional","affiliation":[{"name":"College of Software Technology, Zhejiang University, Hangzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3671-6521","authenticated-orcid":false,"given":"Jie","family":"Song","sequence":"additional","affiliation":[{"name":"College of Software Technology, Zhejiang University, Hangzhou, China"}]},{"given":"Ji","family":"Zhao","sequence":"additional","affiliation":[{"name":"Shanghai Pudong Development Bank Co., Ltd., Shanghai, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2621-6048","authenticated-orcid":false,"given":"Mingli","family":"Song","sequence":"additional","affiliation":[{"name":"College of Computer Science, Zhejiang University, Hangzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5507-6569","authenticated-orcid":false,"given":"Xinyu","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Computer Science, Zhejiang University, Hangzhou, China"}]}],"member":"263","reference":[{"key":"ref13","article-title":"Learning disentangled representations for recommendation","author":"ma","year":"2019"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1093\/comnet\/cnaa031"},{"key":"ref12","article-title":"Adversarial graph disentanglement","author":"zheng","year":"2021"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3449822"},{"key":"ref15","first-page":"1287","article-title":"Image-to-image translation for cross-domain disentanglement","author":"gonzalez-garcia","year":"2018","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2015.141"},{"key":"ref14","first-page":"5894","article-title":"Dual swap disentangling","author":"feng","year":"2018","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1145\/3038912.3052597"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/366"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/439"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2015.2513406"},{"key":"ref33","article-title":"Representation learning with contrastive predictive coding","author":"oord","year":"2018"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10590-1_2"},{"key":"ref32","first-page":"1511","article-title":"HyperGCN: A new method for training graph convolutional networks on hypergraphs","author":"yadati","year":"2019","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref2","first-page":"1","article-title":"Auto-encoding variational bayes","author":"kingma","year":"2014","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref1","first-page":"1","article-title":"Beta-VAE: Learning basic visual concepts with a constrained variational framework","author":"higgins","year":"2017","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403221"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1145\/2783258.2783417"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.3034267"},{"key":"ref38","article-title":"Benchmarking graph neural networks","author":"dwivedi","year":"2020"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1145\/3065386"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1145\/3447548.3467394"},{"key":"ref24","first-page":"1024","article-title":"Inductive representation learning on large graphs","author":"hamilton","year":"2017","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33013558"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.576"},{"key":"ref25","article-title":"Graph attention networks","author":"veli?kovi?","year":"2017"},{"key":"ref20","article-title":"Spectral networks and locally connected networks on graphs","author":"bruna","year":"2013"},{"key":"ref22","first-page":"3844","article-title":"Convolutional neural networks on graphs with fast localized spectral filtering","author":"defferrard","year":"2016","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref21","article-title":"Semi-supervised classification with graph convolutional networks","author":"kipf","year":"2016"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2010.5540012"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403253"},{"key":"ref29","article-title":"Uncovering hypergraphs of cell-cell interaction from single cell rna-sequencing data","volume":"1","author":"tsuyuzaki","year":"2019","journal-title":"BioRxiv"},{"key":"ref8","article-title":"Factorizable graph convolutional networks","author":"yang","year":"2020"},{"key":"ref7","article-title":"LGD-GCN: Local and global disentangled graph convolutional networks","author":"guo","year":"2021"},{"key":"ref9","article-title":"How powerful are graph neural networks?","author":"xu","year":"2018"},{"key":"ref4","first-page":"2180","article-title":"InfoGAN: Interpretable representation learning by information maximizing generative adversarial nets","author":"chen","year":"2016","journal-title":"Proc 30th Int Conf Neural Inf Process Syst"},{"key":"ref3","first-page":"1","article-title":"Deep variational information bottleneck","author":"alemi","year":"2017","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.5929"},{"key":"ref5","first-page":"4212","article-title":"Disentangled graph convolutional networks","author":"ma","year":"2019","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref40","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"2014"}],"container-title":["IEEE Transactions on Knowledge and Data Engineering"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/69\/10210449\/09899756.pdf?arnumber=9899756","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,8,28]],"date-time":"2023-08-28T18:07:22Z","timestamp":1693246042000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9899756\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,9,1]]},"references-count":40,"journal-issue":{"issue":"9"},"URL":"https:\/\/doi.org\/10.1109\/tkde.2022.3208604","relation":{},"ISSN":["1041-4347","1558-2191","2326-3865"],"issn-type":[{"value":"1041-4347","type":"print"},{"value":"1558-2191","type":"electronic"},{"value":"2326-3865","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,9,1]]}}}