{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,31]],"date-time":"2026-01-31T06:53:29Z","timestamp":1769842409594,"version":"3.49.0"},"reference-count":45,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61773392"],"award-info":[{"award-number":["61773392"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Knowl. Data Eng."],"published-print":{"date-parts":[[2020]]},"DOI":"10.1109\/tkde.2020.3025100","type":"journal-article","created":{"date-parts":[[2020,9,18]],"date-time":"2020-09-18T20:32:07Z","timestamp":1600461127000},"page":"1-1","source":"Crossref","is-referenced-by-count":51,"title":["Multi-View Spectral Clustering with High-Order Optimal Neighborhood Laplacian Matrix"],"prefix":"10.1109","author":[{"given":"Weixuan","family":"Liang","sequence":"first","affiliation":[]},{"given":"Sihang","family":"Zhou","sequence":"additional","affiliation":[]},{"given":"Jian","family":"Xiong","sequence":"additional","affiliation":[]},{"given":"Xinwang","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Siwei","family":"Wang","sequence":"additional","affiliation":[]},{"given":"En","family":"Zhu","sequence":"additional","affiliation":[]},{"given":"Zhiping","family":"Cai","sequence":"additional","affiliation":[]},{"given":"Xin","family":"Xu","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref1","first-page":"20","article-title":"Spectral clustering with two views","volume-title":"Proc. Int. Conf. Mach. Learn. Workshop Learning Multiple Views","author":"De Sa"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.26599\/BDMA.2018.9020003"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2019.2942029"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2017.2777489"},{"key":"ref5","first-page":"1413","article-title":"Co-regularized multi-view spectral clustering","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Kumar"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2015.03.027"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2015.2503743"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2017\/357"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2018.2877335"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2018.2889560"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2019.02.036"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TSMCB.2009.2039566"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.ipm.2015.05.007"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v29i1.9598"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v25i1.7900"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2014.2358564"},{"key":"ref17","first-page":"775","article-title":"Fast randomized kernel methods with statistical guarantees","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Alaoui"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2004.1262185"},{"key":"ref19","first-page":"631","article-title":"Making large-scale Nystr\u00f6m approximation possible","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Li"},{"key":"ref20","first-page":"105","article-title":"Exploring large feature spaces with hierarchical multiple kernel learning","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Bach"},{"key":"ref21","first-page":"396","article-title":"Learning non-linear combinations of kernels","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Cortes"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v31i1.10895"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2017.06.012"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2017\/396"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.2984814"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2879108"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/524"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.5555\/2980539.2980649"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1145\/2736277.2741093"},{"key":"ref30","first-page":"3844","article-title":"Convolutional neural networks on graphs with fast localized spectral filtering","volume-title":"Proc. Neural Inf. Process. Syst.","author":"Defferrard"},{"key":"ref31","first-page":"795","article-title":"Algorithms for learning kernels based on centered alignment","volume":"13","author":"Cortes","year":"2012","journal-title":"J. Mach. Learn. Res."},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v30i1.10249"},{"key":"ref33","first-page":"682","article-title":"Using the Nystr\u00f6m method to speed up kernel machines","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Williams"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1137\/090771806"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2011.5995425"},{"key":"ref36","first-page":"1881","article-title":"Parameter-free auto-weighted multiple graph learning: A framework for multiview clustering and semi-supervised classification","volume-title":"Proc. Int. Joint Conf. Artif. Intell.","author":"Nie"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v31i1.10909"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v28i1.8950"},{"key":"ref39","first-page":"3476","article-title":"Robust multiple kernel k-means using l21-norm","volume-title":"Proc. Int. Joint Conf. Artif. Intell.","author":"Du"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1007\/s10479-011-0841-3"},{"key":"ref41","article-title":"Very deep convolutional networks for large-scale image recognition","author":"Simonyan","year":"2015"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.243"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref44","first-page":"2598","article-title":"Multi-view K-means clustering on big data","volume-title":"Proc. 23rd Int. Joint Conf. Artif. Intell.","author":"Cai"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.5867"}],"container-title":["IEEE Transactions on Knowledge and Data Engineering"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/69\/4358933\/09200798.pdf?arnumber=9200798","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,9]],"date-time":"2024-01-09T23:42:41Z","timestamp":1704843761000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9200798\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"references-count":45,"URL":"https:\/\/doi.org\/10.1109\/tkde.2020.3025100","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":[[2020]]}}}