{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T09:10:36Z","timestamp":1750151436079,"version":"3.40.3"},"reference-count":41,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2024,10,3]],"date-time":"2024-10-03T00:00:00Z","timestamp":1727913600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,10,3]],"date-time":"2024-10-03T00:00:00Z","timestamp":1727913600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62273248"],"award-info":[{"award-number":["62273248"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int. J. Mach. Learn. &amp; Cyber."],"published-print":{"date-parts":[[2025,4]]},"DOI":"10.1007\/s13042-024-02403-0","type":"journal-article","created":{"date-parts":[[2024,10,3]],"date-time":"2024-10-03T15:02:10Z","timestamp":1727967730000},"page":"2487-2502","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["An incomplete multi-view clustering approach using subspace alignment constraint"],"prefix":"10.1007","volume":"16","author":[{"given":"Xueying","family":"Niu","sequence":"first","affiliation":[]},{"given":"Xiaojie","family":"Zhao","sequence":"additional","affiliation":[]},{"given":"Lihua","family":"Hu","sequence":"additional","affiliation":[]},{"given":"Jifu","family":"Zhang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,10,3]]},"reference":[{"issue":"2","key":"2403_CR1","doi-asserted-by":"publisher","first-page":"146","DOI":"10.1109\/TAI.2021.3065894","volume":"2","author":"G Chao","year":"2021","unstructured":"Chao G, Sun S, Bi J (2021) A survey on multiview clustering. IEEE Trans Artif Intell 2(2):146\u2013168. https:\/\/doi.org\/10.1109\/TAI.2021.3065894","journal-title":"IEEE Trans Artif Intell"},{"issue":"2","key":"2403_CR2","doi-asserted-by":"publisher","first-page":"1456","DOI":"10.1109\/TII.2022.3206343","volume":"19","author":"C Xu","year":"2022","unstructured":"Xu C, Zhao W, Zhao J, Guan Z, Song X, Li J (2022) Uncertainty-aware multiview deep learning for internet of things applications. IEEE Trans Ind Inf 19(2):1456\u20131466","journal-title":"IEEE Trans Ind Inf"},{"key":"2403_CR3","doi-asserted-by":"crossref","unstructured":"Xu C, Zhao W, Zhao J, Guan Z, Yang Y, Chen L, Song X (2023) Progressive deep multi-view comprehensive representation learning. In: Proceedings of the AAAI conference on artificial intelligence, vol 37, pp 10557\u201310565","DOI":"10.1609\/aaai.v37i9.26254"},{"issue":"12","key":"2403_CR4","doi-asserted-by":"publisher","first-page":"9236","DOI":"10.1109\/TPAMI.2021.3125995","volume":"44","author":"X Liang","year":"2022","unstructured":"Liang X, Qian Y, Guo Q, Cheng H, Liang J (2022) AF: an association-based fusion method for multi-modal classification. IEEE Trans Pattern Anal Mach Intell 44(12):9236\u20139254","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"2403_CR5","doi-asserted-by":"crossref","unstructured":"Liang X, Fu P, Guo Q, Zheng K, Qian Y (2024) DC-NAS: divide-and-conquer neural architecture search for multi-modal classification. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol 38(12), pp 13754\u201313762","DOI":"10.1609\/aaai.v38i12.29281"},{"key":"2403_CR6","doi-asserted-by":"crossref","unstructured":"Xu C, Si J, Guan Z, Zhao W, Wu Y, Gao X (2024) Reliable conflictive multi-view learning. In: Proceedings of the AAAI conference on artificial intelligence, pp 16129\u201316137","DOI":"10.1609\/aaai.v38i14.29546"},{"issue":"2","key":"2403_CR7","doi-asserted-by":"publisher","first-page":"1136","DOI":"10.1109\/TSMC.2022.3192635","volume":"53","author":"J Wen","year":"2022","unstructured":"Wen J, Zhang Z, Fei L, Zhang B, Xu Y, Zhang Z, Li J (2022) A survey on incomplete multiview clustering. IEEE Trans Syst Man Cybern Syst 53(2):1136\u20131149","journal-title":"IEEE Trans Syst Man Cybern Syst"},{"key":"2403_CR8","doi-asserted-by":"publisher","first-page":"4790","DOI":"10.1109\/TIP.2022.3187562","volume":"31","author":"Z Lv","year":"2022","unstructured":"Lv Z, Gao Q, Zhang X, Li Q, Yang M (2022) View-consistency learning for incomplete multiview clustering. IEEE Trans Image Process 31:4790\u20134802","journal-title":"IEEE Trans Image Process"},{"key":"2403_CR9","doi-asserted-by":"publisher","first-page":"102086","DOI":"10.1016\/j.inffus.2023.102086","volume":"103","author":"A Li","year":"2024","unstructured":"Li A, Feng C, Cheng Y, Zhang Y, Yang H (2024) Incomplete multiview subspace clustering based on multiple kernel low-redundant representation learning. Inf Fusion 103:102086","journal-title":"Inf Fusion"},{"key":"2403_CR10","doi-asserted-by":"publisher","first-page":"175","DOI":"10.1109\/TIP.2022.3226408","volume":"32","author":"Y Qin","year":"2022","unstructured":"Qin Y, Qin C, Zhang X, Qi D, Feng G (2022) Nim-Nets: noise-aware incomplete multi-view learning networks. IEEE Trans Image Process 32:175\u2013189","journal-title":"IEEE Trans Image Process"},{"key":"2403_CR11","doi-asserted-by":"publisher","first-page":"2493","DOI":"10.1109\/TMM.2020.3013408","volume":"23","author":"J Wen","year":"2020","unstructured":"Wen J, Yan K, Zhang Z, Xu Y, Zhang B (2020) Adaptive graph completion based incomplete multi-view clustering. IEEE Trans Multimed 23:2493\u20132504","journal-title":"IEEE Trans Multimed"},{"key":"2403_CR12","doi-asserted-by":"publisher","first-page":"4101","DOI":"10.1007\/s13042-023-01883-w","volume":"14","author":"Y Zhang","year":"2023","unstructured":"Zhang Y, Zhu C (2023) Incomplete multi-view clustering via attention-based contrast learning. Int J Mach Learn Cybern 14:4101\u20134117","journal-title":"Int J Mach Learn Cybern"},{"key":"2403_CR13","doi-asserted-by":"crossref","unstructured":"Lin Y, Gou Y, Liu Z, Li B, Lv J, Peng X (2021) Completer: incomplete multi-view clustering via contrastive prediction. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 11174\u201311183","DOI":"10.1109\/CVPR46437.2021.01102"},{"issue":"10","key":"2403_CR14","doi-asserted-by":"publisher","first-page":"2410","DOI":"10.1109\/TPAMI.2018.2879108","volume":"41","author":"X Liu","year":"2018","unstructured":"Liu X, Zhu X, Li M, Wang L, Tang C, Yin J, Shen D, Wang H, Gao W (2018) Late fusion incomplete multi-view clustering. IEEE Trans Pattern Anal Mach Intell 41(10):2410\u20132423","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"2403_CR15","doi-asserted-by":"publisher","first-page":"103965","DOI":"10.1016\/j.compbiomed.2020.103965","volume":"125","author":"P Dutta","year":"2020","unstructured":"Dutta P, Mishra P, Saha S (2020) Incomplete multi-view gene clustering with data regeneration using shape Boltzmann machine. Comput Biol Med 125:103965","journal-title":"Comput Biol Med"},{"key":"2403_CR16","doi-asserted-by":"publisher","first-page":"104311","DOI":"10.1016\/j.imavis.2021.104311","volume":"115","author":"X Zeng","year":"2021","unstructured":"Zeng X, Hu R, Shi W, Qiao Y (2021) Multi-view self-supervised learning for 3d facial texture reconstruction from single image. Image Vis Comput 115:104311","journal-title":"Image Vis Comput"},{"key":"2403_CR17","doi-asserted-by":"publisher","unstructured":"Li Z, Tang C, Zheng X, Liu X, Zhang W, Zhu E (2022) High-order correlation preserved incomplete multi-view subspace clustering. IEEE Trans Image Process 31:2067\u20132080. https:\/\/doi.org\/10.1109\/TIP.2022.3147046","DOI":"10.1109\/TIP.2022.3147046"},{"key":"2403_CR18","doi-asserted-by":"crossref","unstructured":"Hu M, Chen S (2019) One-pass incomplete multi-view clustering. In: Proceedings of the AAAI conference on artificial intelligence, vol 33, pp 3838\u20133845","DOI":"10.1609\/aaai.v33i01.33013838"},{"key":"2403_CR19","doi-asserted-by":"crossref","unstructured":"Hu M, Chen S (2018) Doubly aligned incomplete multi-view clustering. In: IJCAI, pp 2262\u20132268","DOI":"10.24963\/ijcai.2018\/313"},{"key":"2403_CR20","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TIP.2021.3128325","volume":"31","author":"Y Qin","year":"2021","unstructured":"Qin Y, Wu H, Zhang X, Feng G (2021) Semi-supervised structured subspace learning for multi-view clustering. IEEE Trans Image Process 31:1\u201314","journal-title":"IEEE Trans Image Process"},{"key":"2403_CR21","doi-asserted-by":"crossref","unstructured":"Qin Y, Pu N, Wu H (2023) Elastic multi-view subspace clustering with pairwise and high-order correlations. IEEE Trans Knowl Data Eng","DOI":"10.1109\/TKDE.2023.3293498"},{"key":"2403_CR22","doi-asserted-by":"publisher","first-page":"108298","DOI":"10.1016\/j.patcog.2021.108298","volume":"122","author":"J Tan","year":"2022","unstructured":"Tan J, Yang Z, Ren J, Wang B, Cheng Y, Ling W-K (2022) A novel robust low-rank multi-view diversity optimization model with adaptive-weighting based manifold learning. Pattern Recogn 122:108298","journal-title":"Pattern Recogn"},{"issue":"11","key":"2403_CR23","doi-asserted-by":"publisher","first-page":"7940","DOI":"10.1109\/TPAMI.2021.3114089","volume":"44","author":"W Zhao","year":"2021","unstructured":"Zhao W, Xu C, Guan Z, Wu X, Zhao W, Miao Q, He X, Wang Q (2021) TelecomNet: tag-based weakly-supervised modally cooperative hashing network for image retrieval. IEEE Trans Pattern Anal Mach Intell 44(11):7940\u20137954","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"2403_CR24","unstructured":"Zhao H, Liu H, Fu Y (2016) Incomplete multi-modal visual data grouping. In: IJCAI, pp 2392\u20132398"},{"key":"2403_CR25","doi-asserted-by":"crossref","unstructured":"Shang C, Palmer A, Sun J, Chen K-S, Lu J, Bi J (2017) Vigan: missing view imputation with generative adversarial networks. In: 2017 IEEE international conference on Big Data (Big Data). IEEE, pp 766\u2013775","DOI":"10.1109\/BigData.2017.8257992"},{"key":"2403_CR26","doi-asserted-by":"crossref","unstructured":"Wen J, Zhang Z, Zhang Z, Wu Z, Fei L, Xu Y, Zhang B (2020) DIMC-NET: deep incomplete multi-view clustering network. In: Proceedings of the 28th ACM international conference on multimedia, pp 3753\u20133761","DOI":"10.1145\/3394171.3413807"},{"key":"2403_CR27","doi-asserted-by":"publisher","unstructured":"Wen J, Xu G, Tang Z, Wang W, Fei L, Xu Y (2023) Graph regularized and feature aware matrix factorization for robust incomplete multi-view clustering. IEEE Trans Circuits Syst Video Technol 34(5):3728\u20133741. https:\/\/doi.org\/10.1109\/TCSVT.2023.3317877","DOI":"10.1109\/TCSVT.2023.3317877"},{"key":"2403_CR28","doi-asserted-by":"publisher","first-page":"118408","DOI":"10.1016\/j.eswa.2022.118408","volume":"210","author":"X Liu","year":"2022","unstructured":"Liu X, Song P (2022) Incomplete multi-view clustering via virtual-label guided matrix factorization. Expert Syst Appl 210:118408","journal-title":"Expert Syst Appl"},{"key":"2403_CR29","doi-asserted-by":"crossref","unstructured":"Wen J, Liu C, Xu G, Wu Z, Huang C, Fei L, Xu Y (2023) Highly confident local structure based consensus graph learning for incomplete multi-view clustering. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 15712\u201315721","DOI":"10.1109\/CVPR52729.2023.01508"},{"key":"2403_CR30","doi-asserted-by":"publisher","unstructured":"Li X-L, Chen M-S, Wang C-D, Lai J-H (2022) Refining graph structure for incomplete multi-view clustering. IEEE Trans Neural Netw Learn Syst 35(2):2300\u20132313. https:\/\/doi.org\/10.1109\/TNNLS.2022.3189763","DOI":"10.1109\/TNNLS.2022.3189763"},{"issue":"1","key":"2403_CR31","doi-asserted-by":"publisher","first-page":"201","DOI":"10.1109\/TNNLS.2021.3093297","volume":"34","author":"S Shi","year":"2021","unstructured":"Shi S, Nie F, Wang R, Li X (2021) Multi-view clustering via nonnegative and orthogonal graph reconstruction. IEEE Trans Neural Netw Learn Syst 34(1):201\u2013214","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"issue":"12","key":"2403_CR32","doi-asserted-by":"publisher","first-page":"5869","DOI":"10.1109\/TKDE.2021.3068461","volume":"34","author":"S Huang","year":"2021","unstructured":"Huang S, Tsang IW, Xu Z, Lv J (2021) Measuring diversity in graph learning: a unified framework for structured multi-view clustering. IEEE Trans Knowl Data Eng 34(12):5869\u20135883","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"2403_CR33","doi-asserted-by":"crossref","unstructured":"Gao H, Peng Y, Jian S (2016) Incomplete multi-view clustering. In: Intelligent information processing VIII: 9th IFIP TC 12 international conference, IIP 2016, Melbourne, VIC, Australia, November 18\u201321, 2016, Proceedings, vol 9. Springer, Berlin, pp 245\u2013255","DOI":"10.1007\/978-3-319-48390-0_25"},{"key":"2403_CR34","doi-asserted-by":"crossref","unstructured":"Wang H, Zong L, Liu B, Yang Y, Zhou W (2019) Spectral perturbation meets incomplete multi-view data. arXiv preprint arXiv:1906.00098","DOI":"10.24963\/ijcai.2019\/510"},{"issue":"4","key":"2403_CR35","doi-asserted-by":"publisher","first-page":"1418","DOI":"10.1109\/TCYB.2018.2884715","volume":"50","author":"J Wen","year":"2018","unstructured":"Wen J, Xu Y, Liu H (2018) Incomplete multiview spectral clustering with adaptive graph learning. IEEE Trans Cybern 50(4):1418\u20131429","journal-title":"IEEE Trans Cybern"},{"key":"2403_CR36","doi-asserted-by":"crossref","unstructured":"Xu C, Guan Z, Zhao W, Wu H, Niu Y, Ling B (2019) Adversarial incomplete multi-view clustering. In: IJCAI, vol 7, pp 3933\u20133939","DOI":"10.24963\/ijcai.2019\/546"},{"issue":"8","key":"2403_CR37","first-page":"2634","volume":"43","author":"X Liu","year":"2020","unstructured":"Liu X, Li M, Tang C, Xia J, Xiong J, Liu L, Kloft M, Zhu E (2020) Efficient and effective regularized incomplete multi-view clustering. IEEE Trans Pattern Anal Mach Intell 43(8):2634\u20132646","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"2403_CR38","doi-asserted-by":"publisher","first-page":"110816","DOI":"10.1016\/j.knosys.2023.110816","volume":"277","author":"X Niu","year":"2023","unstructured":"Niu X, Zhang C, Ma Y, Hu L, Zhang J (2023) A multi-view subspace representation learning approach powered by subspace transformation relationship. Knowl-Based Syst 277:110816","journal-title":"Knowl-Based Syst"},{"issue":"4","key":"2403_CR39","doi-asserted-by":"publisher","first-page":"2467","DOI":"10.1109\/TCYB.2020.3004220","volume":"52","author":"Y Pan","year":"2022","unstructured":"Pan Y, Huang C-Q, Wang D (2022) Multiview spectral clustering via robust subspace segmentation. IEEE Trans Cybern 52(4):2467\u20132476. https:\/\/doi.org\/10.1109\/TCYB.2020.3004220","journal-title":"IEEE Trans Cybern"},{"key":"2403_CR40","doi-asserted-by":"publisher","first-page":"279","DOI":"10.1016\/j.neunet.2019.10.010","volume":"122","author":"KA Zhao","year":"2020","unstructured":"Zhao KA, Xz A, Chong PB, Hz C, Jtz D, Xi PE, Wc A, Zxa F (2020) Partition level multiview subspace clustering. Neural Netw 122:279\u2013288","journal-title":"Neural Netw"},{"key":"2403_CR41","unstructured":"Ng A, Jordan M, Weiss Y (2001) On spectral clustering: analysis and an algorithm. In: Advances in neural information processing systems, vol 14"}],"container-title":["International Journal of Machine Learning and Cybernetics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-024-02403-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s13042-024-02403-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-024-02403-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,7]],"date-time":"2025-04-07T07:29:06Z","timestamp":1744010946000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s13042-024-02403-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10,3]]},"references-count":41,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2025,4]]}},"alternative-id":["2403"],"URL":"https:\/\/doi.org\/10.1007\/s13042-024-02403-0","relation":{},"ISSN":["1868-8071","1868-808X"],"issn-type":[{"type":"print","value":"1868-8071"},{"type":"electronic","value":"1868-808X"}],"subject":[],"published":{"date-parts":[[2024,10,3]]},"assertion":[{"value":"21 February 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"23 September 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 October 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declared that they have no Conflict of interest in this work.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}