{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,17]],"date-time":"2026-05-17T06:18:52Z","timestamp":1778998732336,"version":"3.51.4"},"reference-count":54,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2023,5,20]],"date-time":"2023-05-20T00:00:00Z","timestamp":1684540800000},"content-version":"vor","delay-in-days":139,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62203128"],"award-info":[{"award-number":["62203128"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["52171331"],"award-info":[{"award-number":["52171331"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100017369","name":"Scientific and Technological Planning Project of Guangzhou City","doi-asserted-by":"publisher","award":["202102010411"],"award-info":[{"award-number":["202102010411"]}],"id":[{"id":"10.13039\/100017369","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100017369","name":"Scientific and Technological Planning Project of Guangzhou City","doi-asserted-by":"publisher","award":["2023A04J1726"],"award-info":[{"award-number":["2023A04J1726"]}],"id":[{"id":"10.13039\/100017369","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100017369","name":"Scientific and Technological Planning Project of Guangzhou City","doi-asserted-by":"publisher","award":["2023A03J0124"],"award-info":[{"award-number":["2023A03J0124"]}],"id":[{"id":"10.13039\/100017369","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["International Journal of Intelligent Systems"],"published-print":{"date-parts":[[2023,1]]},"abstract":"<jats:p>Since real\u2010world multiview data frequently contains numerous samples that are not observed from some viewpoints, the incomplete multiview clustering (IMC) issue has received a great deal of attention recently. However, most existing IMC methods choose to zero\u2010fill the missing instances, which leads to the failure to exploit information hidden in the missing instances, and high\u2010order interactions between various views. To tackle these problems, we proposed an effective IMC method using low\u2010rank tensor ring completion, which was demonstrated to be powerful in exploiting high\u2010order correlation. Specifically, we first stack the incomplete similarity graphs of all views into a 3<jats:sup>rd<\/jats:sup>\u2010order incomplete tensor and then restore it via the tensor ring decomposition. Next, using an adaptive weighting technique, we apply multiview spectral clustering to all entire graphs in order to balance the contributions of different viewpoints and identify the consensus representation for grouping. Finally, we employ the alternating direction method of multipliers (ADMM) to optimize the suggested model. Numerous experimental findings on numerous different datasets show that the suggested approach is superior to other cutting\u2010edge approaches.<\/jats:p>","DOI":"10.1155\/2023\/7217818","type":"journal-article","created":{"date-parts":[[2023,5,20]],"date-time":"2023-05-20T21:05:07Z","timestamp":1684616707000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Incomplete Multiview Clustering via Low\u2010Rank Tensor Ring Completion"],"prefix":"10.1155","volume":"2023","author":[{"given":"Jinshi","family":"Yu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haonan","family":"Huang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qi","family":"Duan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9854-0528","authenticated-orcid":false,"given":"Yafei","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7328-5703","authenticated-orcid":false,"given":"Tao","family":"Zou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2023,5,20]]},"reference":[{"key":"e_1_2_9_1_2","doi-asserted-by":"publisher","DOI":"10.1002\/int.22319"},{"key":"e_1_2_9_2_2","doi-asserted-by":"publisher","DOI":"10.1002\/int.22409"},{"key":"e_1_2_9_3_2","doi-asserted-by":"crossref","unstructured":"SharmaA. KumarA. DaumeH. andJacobsD. W. Generalized multiview analysis: a discriminative latent space Proceedings of the 2012 IEEE conference on computer vision and pattern recognition June 2012 Providence RI USA IEEE 2160\u20132167.","DOI":"10.1109\/CVPR.2012.6247923"},{"key":"e_1_2_9_4_2","doi-asserted-by":"publisher","DOI":"10.1049\/cvi2.12152"},{"key":"e_1_2_9_5_2","doi-asserted-by":"crossref","unstructured":"NieF. LiJ. andLiX. Self-weighted multiview clustering with multiple graphs Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17) December 2017 Xi\u2019an China 2564\u20132570.","DOI":"10.24963\/ijcai.2017\/357"},{"key":"e_1_2_9_6_2","doi-asserted-by":"publisher","DOI":"10.1002\/int.22521"},{"key":"e_1_2_9_7_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2022.117728"},{"key":"e_1_2_9_8_2","doi-asserted-by":"publisher","DOI":"10.1002\/int.22901"},{"key":"e_1_2_9_9_2","doi-asserted-by":"crossref","unstructured":"ChaudhuriK. KakadeS. M. LivescuK. andSridharanK. Multi-view clustering via canonical correlation analysis Proceedings of the 26th annual international conference on machine learning December 2009 Xi\u2019an China 129\u2013136.","DOI":"10.1145\/1553374.1553391"},{"key":"e_1_2_9_10_2","first-page":"1413","article-title":"Co-regularized multi-view spectral clustering","volume":"24","author":"Kumar A.","year":"2011","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_2_9_11_2","unstructured":"CaiX. NieF. andHuangH. Multi-view k-means clustering on big data Proceedings of the Twenty-Third International Joint conference on artificial intelligence August 2013."},{"key":"e_1_2_9_12_2","doi-asserted-by":"publisher","DOI":"10.1002\/int.22958"},{"key":"e_1_2_9_13_2","doi-asserted-by":"crossref","unstructured":"KalayehM. M. IdreesH. andShahM. Nmf-knn: image annotation using weighted multi-view non-negative matrix factorization Proceedings of the IEEE conference on computer vision and pattern recognition June 2014 Columbus OH USA 184\u2013191.","DOI":"10.1109\/CVPR.2014.31"},{"key":"e_1_2_9_14_2","doi-asserted-by":"crossref","unstructured":"ZhaoH. DingZ. andFuY. Multi-view clustering via deep matrix factorization Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence January 2017 Washington DC USA.","DOI":"10.1609\/aaai.v31i1.10867"},{"key":"e_1_2_9_15_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2019.107015"},{"key":"e_1_2_9_16_2","doi-asserted-by":"publisher","DOI":"10.1109\/jas.2022.105980"},{"key":"e_1_2_9_17_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00034-021-01833-3"},{"key":"e_1_2_9_18_2","unstructured":"RaiP. TrivediA. Daum\u00e9H.III andDuVallS. L. Multiview clustering with incomplete views Proceedings of the NIPS Workshop on Machine Learning for Social Computing Citeseer December 2010 Washington DC USA."},{"key":"e_1_2_9_19_2","doi-asserted-by":"publisher","DOI":"10.1109\/tcyb.2020.2987164"},{"key":"e_1_2_9_20_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v28i1.8973"},{"key":"e_1_2_9_21_2","unstructured":"ZhaoH. LiuH. andFuY. Incomplete multi-modal visual data grouping Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence (IJCAI-16) June 2016 Boston CA USA 2392\u20132398."},{"key":"e_1_2_9_22_2","doi-asserted-by":"crossref","unstructured":"XuN. GuoY. ZhengX. WangQ. andLuoX. Partial multi-view subspace clustering Proceedings of the 26th ACM International conference on multimedia October 2018 New York NY USA 1794\u20131801.","DOI":"10.1145\/3240508.3240679"},{"key":"e_1_2_9_23_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-23528-8_20"},{"key":"e_1_2_9_24_2","doi-asserted-by":"crossref","unstructured":"ShaoW. HeL. LuC.-T. andPhilipS. Y. Online multi-view clustering with incomplete views Proceedings of the 2016 IEEE International Conference on Big Data (Big Data) December 2016 Washington DC USA IEEE 1012\u20131017.","DOI":"10.1109\/BigData.2016.7840701"},{"key":"e_1_2_9_25_2","doi-asserted-by":"crossref","unstructured":"RaiN. NegiS. ChaudhuryS. andDeshmukhO. Partial multi-view clustering using graph regularized nmf Proceedings of the 2016 23rd International Conference on Pattern Recognition (ICPR) April 2016 Cancun Mexico IEEE 2192\u20132197.","DOI":"10.1109\/ICPR.2016.7899961"},{"key":"e_1_2_9_26_2","unstructured":"HuM.andChenS. Doubly aligned incomplete multi-view clustering 2019 https:\/\/arxiv.org\/abs\/1903.02785."},{"key":"e_1_2_9_27_2","doi-asserted-by":"publisher","DOI":"10.1002\/int.22655"},{"key":"e_1_2_9_28_2","doi-asserted-by":"crossref","unstructured":"WangH. ZongL. LiuB. YangY. andZhouW. Spectral perturbation meets incomplete multi-view data 2019 https:\/\/arxiv.org\/abs\/1906.00098.","DOI":"10.24963\/ijcai.2019\/510"},{"key":"e_1_2_9_29_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2022.109122"},{"key":"e_1_2_9_30_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2017.07.016"},{"key":"e_1_2_9_31_2","doi-asserted-by":"publisher","DOI":"10.3390\/math11030652"},{"key":"e_1_2_9_32_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33014392"},{"key":"e_1_2_9_33_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33015393"},{"key":"e_1_2_9_34_2","doi-asserted-by":"publisher","DOI":"10.1109\/tmm.2020.3013408"},{"key":"e_1_2_9_35_2","doi-asserted-by":"crossref","unstructured":"ShangC. PalmerA. SunJ. ChenK.-S. LuJ. andBiJ. Vigan: missing view imputation with generative adversarial networks Proceedings of the 2017 IEEE International Conference on Big Data (Big Data) Augest 2017 Osaka Japan IEEE 766\u2013775.","DOI":"10.1109\/BigData.2017.8257992"},{"key":"e_1_2_9_36_2","doi-asserted-by":"crossref","unstructured":"WangQ. DingZ. TaoZ. GaoQ. andFuY. Partial multi-view clustering via consistent gan Proceedings of the 2018 IEEE International Conference on Data Mining (ICDM) November 2018 Singapore IEEE 1290\u20131295.","DOI":"10.1109\/ICDM.2018.00174"},{"key":"e_1_2_9_37_2","doi-asserted-by":"publisher","DOI":"10.1109\/tip.2020.3048626"},{"key":"e_1_2_9_38_2","unstructured":"ZhaoQ. ZhouG. XieS. ZhangL. andCichockiA. Tensor ring decomposition 2016 http:\/\/arxiv.org\/abs\/1606.05535."},{"key":"e_1_2_9_39_2","doi-asserted-by":"crossref","unstructured":"ZhaoQ. SugiyamaM. YuanL. andCichockiA. Learning efficient tensor representations with ring-structured networks Proceedings of the ICASSP 2019-2019 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP) May 2019 Brighton UK IEEE 8608\u20138612.","DOI":"10.1109\/ICASSP.2019.8682231"},{"key":"e_1_2_9_40_2","doi-asserted-by":"crossref","unstructured":"WangW. AggarwalV. andAeronS. Efficient low rank tensor ring completion Proceedings of the 2017 IEEE International Conference on Computer Vision (ICCV) May 2017 Venice Italy 5698\u20135706 https:\/\/doi.org\/10.1109\/ICCV.2017.607 2-s2.0-85041771621.","DOI":"10.1109\/ICCV.2017.607"},{"key":"e_1_2_9_41_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33019151"},{"key":"e_1_2_9_42_2","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.3009210"},{"key":"e_1_2_9_43_2","doi-asserted-by":"publisher","DOI":"10.1137\/07070111x"},{"key":"e_1_2_9_44_2","doi-asserted-by":"publisher","DOI":"10.1109\/43.159993"},{"key":"e_1_2_9_45_2","doi-asserted-by":"publisher","DOI":"10.1109\/34.868688"},{"key":"e_1_2_9_46_2","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2021.3106654"},{"key":"e_1_2_9_47_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v30i1.10302"},{"key":"e_1_2_9_48_2","doi-asserted-by":"publisher","DOI":"10.1137\/s106482750037322x"},{"key":"e_1_2_9_49_2","doi-asserted-by":"publisher","DOI":"10.1109\/tip.2017.2754939"},{"key":"e_1_2_9_50_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i11.17231"},{"key":"e_1_2_9_51_2","doi-asserted-by":"publisher","DOI":"10.1109\/tmm.2022.3194332"},{"key":"e_1_2_9_52_2","doi-asserted-by":"crossref","unstructured":"ZhangC. FuH. LiuS. LiuG. andCaoX. Low-rank tensor constrained multiview subspace clustering Proceedings of the IEEE international conference on computer vision December 2015 Santiago Chile 1582\u20131590.","DOI":"10.1109\/ICCV.2015.185"},{"key":"e_1_2_9_53_2","volume-title":"Introduction to Information Retrieval","author":"Sch\u00fctze H.","year":"2008"},{"key":"e_1_2_9_54_2","doi-asserted-by":"publisher","DOI":"10.1007\/bf01908075"}],"container-title":["International Journal of Intelligent Systems"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/ijis\/2023\/7217818.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/ijis\/2023\/7217818.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1155\/2023\/7217818","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,31]],"date-time":"2024-12-31T05:18:07Z","timestamp":1735622287000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1155\/2023\/7217818"}},"subtitle":[],"editor":[{"given":"Vasudevan","family":"Rajamohan","sequence":"additional","affiliation":[],"role":[{"role":"editor","vocabulary":"crossref"}]}],"short-title":[],"issued":{"date-parts":[[2023,1]]},"references-count":54,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2023,1]]}},"alternative-id":["10.1155\/2023\/7217818"],"URL":"https:\/\/doi.org\/10.1155\/2023\/7217818","archive":["Portico"],"relation":{},"ISSN":["0884-8173","1098-111X"],"issn-type":[{"value":"0884-8173","type":"print"},{"value":"1098-111X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,1]]},"assertion":[{"value":"2022-12-02","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2023-04-07","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2023-05-20","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"7217818"}}