{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,25]],"date-time":"2026-04-25T13:05:50Z","timestamp":1777122350225,"version":"3.51.4"},"reference-count":41,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2023,10,4]],"date-time":"2023-10-04T00:00:00Z","timestamp":1696377600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,10,4]],"date-time":"2023-10-04T00:00:00Z","timestamp":1696377600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"Project of Guangxi Key Laboratory of Machine Vision and Intelligent Control","award":["2022B07"],"award-info":[{"award-number":["2022B07"]}]},{"name":"Open Research Fund of Anhui Province Key Laboratory of Machine Vision Inspection","award":["KLMVI-2023-HIT-08"],"award-info":[{"award-number":["KLMVI-2023-HIT-08"]}]},{"DOI":"10.13039\/100012542","name":"Sichuan Province Science and Technology Support Program","doi-asserted-by":"publisher","award":["2023NSFSC0506"],"award-info":[{"award-number":["2023NSFSC0506"]}],"id":[{"id":"10.13039\/100012542","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput & Applic"],"published-print":{"date-parts":[[2024,1]]},"DOI":"10.1007\/s00521-023-09054-2","type":"journal-article","created":{"date-parts":[[2023,10,4]],"date-time":"2023-10-04T05:01:30Z","timestamp":1696395690000},"page":"717-729","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Consider high-order consistency for multi-view clustering"],"prefix":"10.1007","volume":"36","author":[{"given":"Xiaojian","family":"You","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haoran","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiali","family":"You","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3791-9750","authenticated-orcid":false,"given":"Zhenwen","family":"Ren","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,10,4]]},"reference":[{"key":"9054_CR1","doi-asserted-by":"crossref","unstructured":"Zhou S, Liu X, Liu J, Guo X, Zhao Y, Zhu E, Zhai Y, Yin J, Gao W (2020) Multi-view spectral clustering with optimal neighborhood laplacian matrix. In: Proceedings of the AAAI conference on artificial intelligence, vol 34, pp 6965\u20136972","DOI":"10.1609\/aaai.v34i04.6180"},{"key":"9054_CR2","doi-asserted-by":"crossref","unstructured":"Xu J, Tang H, Ren Y, Peng L, Zhu X, He L (2022) Multi-level feature learning for contrastive multi-view clustering. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 16051\u201316060","DOI":"10.1109\/CVPR52688.2022.01558"},{"issue":"1","key":"9054_CR3","first-page":"2094","volume":"29","author":"Z Ren","year":"2019","unstructured":"Ren Z, Sun Q, Wu B, Zhang X, Yan W (2019) Learning latent low-rank and sparse embedding for robust image feature extraction. IEEE Trans Image Process Publ. IEEE Signal Process Soc 29(1):2094\u20132107","journal-title":"IEEE Trans Image Process Publ. IEEE Signal Process Soc"},{"issue":"11","key":"9054_CR4","doi-asserted-by":"publisher","first-page":"3373","DOI":"10.1007\/s13042-022-01600-z","volume":"13","author":"H Li","year":"2022","unstructured":"Li H, Ren Z, Zhao C, Xu Z, Dai J (2022) Self-paced latent embedding space learning for multi-view clustering. Int J Mach Learn Cybern 13(11):3373\u20133386","journal-title":"Int J Mach Learn Cybern"},{"key":"9054_CR5","doi-asserted-by":"publisher","first-page":"2461","DOI":"10.1109\/TMM.2021.3081930","volume":"24","author":"Z Li","year":"2021","unstructured":"Li Z, Tang C, Liu X, Zheng X, Zhang W, Zhu E (2021) Consensus graph learning for multi-view clustering. IEEE Trans Multimed 24:2461\u20132472","journal-title":"IEEE Trans Multimed"},{"key":"9054_CR6","doi-asserted-by":"crossref","unstructured":"Zhang B, Ma X (2022) Multi-view clustering with constructed bipartite graph in embedding space. Knowl-Based Syst 109690","DOI":"10.1016\/j.knosys.2022.109690"},{"key":"9054_CR7","doi-asserted-by":"crossref","unstructured":"Chen M, Huang L, Wang C-D, Huang D (2020) Multi-view clustering in latent embedding space. In: AAAI, pp 3513\u20133520","DOI":"10.1609\/aaai.v34i04.5756"},{"key":"9054_CR8","doi-asserted-by":"crossref","unstructured":"Li R, Zhang C, Hu Q, Zhu P, Wang Z (2019) Flexible multi-view representation learning for subspace clustering. In: Proceedings of the 28th international joint conference on artificial intelligence, pp 2916\u20132922","DOI":"10.24963\/ijcai.2019\/404"},{"key":"9054_CR9","doi-asserted-by":"crossref","unstructured":"Kang, Z, Lu X, Yi J, Xu Z (2018) Self-weighted multiple kernel learning for graph-based clustering and semi-supervised classification. In: Proceedings of the 27th international joint conference on artificial intelligence, pp 2312\u20132318","DOI":"10.24963\/ijcai.2018\/320"},{"key":"9054_CR10","doi-asserted-by":"crossref","unstructured":"Cao X, Zhang C, Fu H, Liu S, Zhang H (2015) Diversity-induced multi-view subspace clustering. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 586\u2013594","DOI":"10.1109\/CVPR.2015.7298657"},{"key":"9054_CR11","doi-asserted-by":"crossref","unstructured":"Zhang C, Hu Q, Fu H, Zhu P, Cao X (2017) Latent multi-view subspace clustering. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 4279\u20134287","DOI":"10.1109\/CVPR.2017.461"},{"key":"9054_CR12","doi-asserted-by":"publisher","first-page":"62","DOI":"10.1016\/j.sigpro.2018.10.018","volume":"156","author":"P Jing","year":"2019","unstructured":"Jing P, Su Y, Li Z, Liu J, Nie L (2019) Low-rank regularized tensor discriminant representation for image set classification. Signal Process 156:62\u201370","journal-title":"Signal Process"},{"key":"9054_CR13","doi-asserted-by":"crossref","unstructured":"Liu Y, Zhang X, Tang G, Wang D (2019) Multi-view subspace clustering based on tensor schatten-p norm. In: 2019 IEEE international conference on big data (big data), pp 5048\u20135055","DOI":"10.1109\/BigData47090.2019.9006347"},{"issue":"4","key":"9054_CR14","doi-asserted-by":"publisher","first-page":"925","DOI":"10.1109\/TPAMI.2019.2891760","volume":"42","author":"C Lu","year":"2019","unstructured":"Lu C, Feng J, Chen Y, Liu W, Lin Z, Yan S (2019) Tensor robust principal component analysis with a new tensor nuclear norm. IEEE Trans Pattern Anal Mach Intell 42(4):925\u2013938","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"10","key":"9054_CR15","doi-asserted-by":"publisher","first-page":"8027","DOI":"10.1007\/s00521-022-06927-w","volume":"34","author":"Y Mi","year":"2022","unstructured":"Mi Y, Ren Z, Xu Z, Li H, Sun Q, Chen H, Dai J (2022) Multi-view clustering with dual tensors. Neural Comput Appl 34(10):8027\u20138038","journal-title":"Neural Comput Appl"},{"key":"9054_CR16","doi-asserted-by":"crossref","unstructured":"Zhang C, Fu H, Liu S, Liu G, Cao X (2015) Low-rank tensor constrained multiview subspace clustering. In: Proceedings of the IEEE international conference on computer vision, pp 1582\u20131590","DOI":"10.1109\/ICCV.2015.185"},{"issue":"11","key":"9054_CR17","doi-asserted-by":"publisher","first-page":"1157","DOI":"10.1007\/s11263-018-1086-2","volume":"126","author":"Y Xie","year":"2018","unstructured":"Xie Y, Tao D, Zhang W, Liu Y, Zhang L, Qu Y (2018) On unifying multi-view self-representations for clustering by tensor multi-rank minimization. Int J Comput Vis 126(11):1157\u20131179","journal-title":"Int J Comput Vis"},{"issue":"1","key":"9054_CR18","doi-asserted-by":"publisher","first-page":"148","DOI":"10.1137\/110837711","volume":"34","author":"ME Kilmer","year":"2013","unstructured":"Kilmer ME, Braman K, Hao N, Hoover RC (2013) Third-order tensors as operators on matrices: a theoretical and computational framework with applications in imaging. SIAM J Matrix Anal Appl 34(1):148\u2013172","journal-title":"SIAM J Matrix Anal Appl"},{"issue":"12","key":"9054_CR19","doi-asserted-by":"publisher","first-page":"5910","DOI":"10.1109\/TIP.2019.2916740","volume":"28","author":"J Wu","year":"2019","unstructured":"Wu J, Lin Z, Zha H (2019) Essential tensor learning for multi-view spectral clustering. IEEE Trans Image Process 28(12):5910\u20135922","journal-title":"IEEE Trans Image Process"},{"key":"9054_CR20","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2022.109342","volume":"252","author":"W Hao","year":"2022","unstructured":"Hao W, Pang S, Yang B, Xue J (2022) Tensor-based multi-view clustering with consistency exploration and diversity regularization. Knowl-Based Syst 252:109342","journal-title":"Knowl-Based Syst"},{"key":"9054_CR21","doi-asserted-by":"crossref","unstructured":"You J, Han C, Ren Z, Li H, You X (2022) Clustering via multiple kernel k-means coupled graph and enhanced tensor learning. Appl Intell 1\u201312","DOI":"10.1007\/s10489-022-03679-x"},{"key":"9054_CR22","doi-asserted-by":"crossref","unstructured":"Wu J, Xie X, Nie L, Lin Z, Zha H (2020) Unified graph and low-rank tensor learning for multi-view clustering. In: Proceedings of the AAAI conference on artificial intelligence, vol 34, pp 6388\u20136395","DOI":"10.1609\/aaai.v34i04.6109"},{"key":"9054_CR23","first-page":"1","volume":"01","author":"M-S Chen","year":"2022","unstructured":"Chen M-S, Wang C-D, Lai J-H (2022) Low-rank tensor based proximity learning for multi-view clustering. IEEE Trans Knowl Data Eng 01:1\u20131","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"9054_CR24","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2021.108142","volume":"120","author":"Y Xu","year":"2021","unstructured":"Xu Y, Chen S, Li J, Luo L, Yang J (2021) Learnable low-rank latent dictionary for subspace clustering. Pattern Recognit 120:108142","journal-title":"Pattern Recognit"},{"key":"9054_CR25","doi-asserted-by":"publisher","first-page":"573","DOI":"10.1016\/j.ins.2021.10.013","volume":"582","author":"J Yang","year":"2022","unstructured":"Yang J, Ma J, Win KT, Gao J, Yang Z (2022) Low-rank and sparse representation based learning for cancer survivability prediction. Inf Sci 582:573\u2013592","journal-title":"Inf Sci"},{"key":"9054_CR26","doi-asserted-by":"crossref","unstructured":"Luo S, Zhang C, Zhang W, Cao X (2018) Consistent and specific multi-view subspace clustering. In: Proceedings of the AAAI conference on artificial intelligence, vol 32","DOI":"10.1609\/aaai.v32i1.11617"},{"key":"9054_CR27","unstructured":"Lin Z, Liu R, Su Z (2011) Linearized alternating direction method with adaptive penalty for low-rank representation. In: Advances in neural information processing systems, pp 612\u2013620"},{"issue":"3","key":"9054_CR28","doi-asserted-by":"publisher","first-page":"851","DOI":"10.1109\/TNNLS.2018.2851444","volume":"30","author":"M Yin","year":"2018","unstructured":"Yin M, Gao J, Xie S, Guo Y (2018) Multiview subspace clustering via tensorial t-product representation. IEEE Trans Neural Netw Learn Syst 30(3):851\u2013864","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"9054_CR29","doi-asserted-by":"publisher","first-page":"50","DOI":"10.1016\/j.patcog.2018.09.009","volume":"88","author":"X Wang","year":"2019","unstructured":"Wang X, Lei Z, Guo X, Zhang C, Shi H, Li SZ (2019) Multi-view subspace clustering with intactness-aware similarity. Pattern Recognit 88:50\u201363","journal-title":"Pattern Recognit"},{"issue":"5","key":"9054_CR30","doi-asserted-by":"publisher","first-page":"3469","DOI":"10.1109\/TCYB.2020.3013136","volume":"52","author":"M Meng","year":"2020","unstructured":"Meng M, Lan M, Yu J, Wu J (2020) Multiview consensus structure discovery. IEEE Trans Cybern 52(5):3469\u20133482","journal-title":"IEEE Trans Cybern"},{"key":"9054_CR31","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2019.105102","volume":"189","author":"Z Kang","year":"2020","unstructured":"Kang Z, Shi G, Huang S, Chen W, Pu X, Zhou JT, Xu Z (2020) Multi-graph fusion for multi-view spectral clustering. Knowl-Based Syst 189:105102","journal-title":"Knowl-Based Syst"},{"issue":"10","key":"9054_CR32","doi-asserted-by":"publisher","first-page":"1984","DOI":"10.1109\/TKDE.2018.2872061","volume":"31","author":"K Zhan","year":"2018","unstructured":"Zhan K, Niu C, Chen C, Nie F, Zhang C, Yang Y (2018) Graph structure fusion for multiview clustering. IEEE Trans Knowl Data Eng 31(10):1984\u20131993","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"9054_CR33","doi-asserted-by":"crossref","unstructured":"Nie F, Cai G, Li X (2017) Multi-view clustering and semi-supervised classification with adaptive neighbours. In: Proceedings of the thirty-first AAAI conference on artificial intelligence, pp 2408\u20132414","DOI":"10.1609\/aaai.v31i1.10909"},{"key":"9054_CR34","unstructured":"Peng X, Huang Z, Lv J, Zhu H, Zhou JT (2019) Comic: multi-view clustering without parameter selection. In: International conference on machine learning, pp 5092\u20135101"},{"key":"9054_CR35","doi-asserted-by":"crossref","unstructured":"Yan D, Huang L, Jordan MI (2009) Fast approximate spectral clustering. In: Proceedings of the 15th ACM SIGKDD international conference on knowledge discovery and data mining, pp 907\u2013916","DOI":"10.1145\/1557019.1557118"},{"issue":"1","key":"9054_CR36","doi-asserted-by":"publisher","first-page":"171","DOI":"10.1109\/TPAMI.2012.88","volume":"35","author":"G Liu","year":"2012","unstructured":"Liu G, Lin Z, Yan S, Sun J, Yu Y, Ma Y (2012) Robust recovery of subspace structures by low-rank representation. IEEE Trans Pattern Anal Mach Intell 35(1):171\u2013184","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"9054_CR37","doi-asserted-by":"crossref","unstructured":"Gao H, Nie F, Li X, Huang H (2015) Multi-view subspace clustering. In: Proceedings of the IEEE international conference on computer vision, pp 4238\u20134246","DOI":"10.1109\/ICCV.2015.482"},{"key":"9054_CR38","doi-asserted-by":"crossref","unstructured":"Zhang C, Wang S, Liu J, Zhou S, Zhang P, Liu X, Zhu E, Zhang C (2021) Multi-view clustering via deep matrix factorization and partition alignment. In: Proceedings of the 29th ACM international conference on multimedia, pp 4156\u20134164","DOI":"10.1145\/3474085.3475548"},{"issue":"12","key":"9054_CR39","doi-asserted-by":"publisher","first-page":"4784","DOI":"10.1109\/TCSVT.2021.3055039","volume":"31","author":"Y Jia","year":"2021","unstructured":"Jia Y, Liu H, Hou J, Kwong S, Zhang Q (2021) Multi-view spectral clustering tailored tensor low-rank representation. IEEE Trans Circuits Syst Video Technol 31(12):4784\u20134797","journal-title":"IEEE Trans Circuits Syst Video Technol"},{"issue":"9","key":"9054_CR40","doi-asserted-by":"publisher","first-page":"8976","DOI":"10.1109\/TCYB.2021.3061660","volume":"52","author":"Z Kang","year":"2021","unstructured":"Kang Z, Lin Z, Zhu X, Xu W (2021) Structured graph learning for scalable subspace clustering: From single view to multiview. IEEE Trans Cybern 52(9):8976\u20138986","journal-title":"IEEE Trans Cybern"},{"issue":"02","key":"9054_CR41","first-page":"1872","volume":"35","author":"Z Lin","year":"2023","unstructured":"Lin Z, Kang Z, Zhang L, Tian L (2023) Multi-view attributed graph clustering. IEEE Trans Knowl Data Eng 35(02):1872\u20131880","journal-title":"IEEE Trans Knowl Data Eng"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-023-09054-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-023-09054-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-023-09054-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,5]],"date-time":"2024-01-05T07:07:49Z","timestamp":1704438469000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-023-09054-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10,4]]},"references-count":41,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2024,1]]}},"alternative-id":["9054"],"URL":"https:\/\/doi.org\/10.1007\/s00521-023-09054-2","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,10,4]]},"assertion":[{"value":"8 December 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 September 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"4 October 2023","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"On behalf of all authors, the corresponding author states that there is no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}