{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,12]],"date-time":"2026-06-12T01:00:43Z","timestamp":1781226043883,"version":"3.54.1"},"reference-count":44,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100003392","name":"Fujian Provincial Natural Science Foundation","doi-asserted-by":"publisher","award":["2025J011036"],"award-info":[{"award-number":["2025J011036"]}],"id":[{"id":"10.13039\/501100003392","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100009617","name":"Putian Science and Technology Bureau","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100009617","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62562029"],"award-info":[{"award-number":["62562029"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004761","name":"Natural Science Foundation of Hainan Province","doi-asserted-by":"publisher","award":["625MS050"],"award-info":[{"award-number":["625MS050"]}],"id":[{"id":"10.13039\/501100004761","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Knowledge-Based Systems"],"published-print":{"date-parts":[[2026,6]]},"DOI":"10.1016\/j.knosys.2026.116028","type":"journal-article","created":{"date-parts":[[2026,4,17]],"date-time":"2026-04-17T06:46:36Z","timestamp":1776408396000},"page":"116028","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["High-order relation driven multi-view representation learning"],"prefix":"10.1016","volume":"343","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1672-3065","authenticated-orcid":false,"given":"Na","family":"Song","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhenheng","family":"Lin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shiyang","family":"Lan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9162-6994","authenticated-orcid":false,"given":"Zhongyue","family":"Lei","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5195-9682","authenticated-orcid":false,"given":"Shiping","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.knosys.2026.116028_b1","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2025.113507","article-title":"Confidence-enhanced dual-space semantic alignment for partial multi-view incomplete multi-label classification","volume":"318","author":"Chen","year":"2025","journal-title":"Knowl.-Based Syst."},{"key":"10.1016\/j.knosys.2026.116028_b2","doi-asserted-by":"crossref","first-page":"2245","DOI":"10.1109\/TPAMI.2024.3506283","article-title":"Foundation models defining a new era in vision: A survey and outlook","volume":"47","author":"Awais","year":"2025","journal-title":"IEEE Trans. Pattern Anal. Machine Intell."},{"key":"10.1016\/j.knosys.2026.116028_b3","doi-asserted-by":"crossref","DOI":"10.1016\/j.inffus.2024.102831","article-title":"Multi-relational multi-view clustering and its applications in cancer subtype identification","volume":"117","author":"Zhang","year":"2025","journal-title":"Inf. Fusion"},{"key":"10.1016\/j.knosys.2026.116028_b4","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2025.114103","article-title":"Medcongtm: Interpretable multi-label clinical code prediction with dual-view graph contrastive topic modeling","volume":"327","author":"\u00c7elikten","year":"2025","journal-title":"Knowl.-Based Syst."},{"key":"10.1016\/j.knosys.2026.116028_b5","doi-asserted-by":"crossref","DOI":"10.1016\/j.compbiolchem.2025.108530","article-title":"Integrative strategies in drug discovery: Harnessing genomics, deep learning, and computer-aided drug design","volume":"119","author":"Ali","year":"2025","journal-title":"Comput. Biol. Chem."},{"key":"10.1016\/j.knosys.2026.116028_b6","doi-asserted-by":"crossref","DOI":"10.1016\/j.inffus.2024.102345","article-title":"Self-paced semi-supervised feature selection with application to multi-modal alzheimer\u2019s disease classification","volume":"107","author":"Zhang","year":"2024","journal-title":"Inf. Fusion"},{"key":"10.1016\/j.knosys.2026.116028_b7","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2025.128859","article-title":"Sspfusion: A semantic structure-preserving approach for multi-modality image fusion","volume":"295","author":"Yang","year":"2026","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.knosys.2026.116028_b8","doi-asserted-by":"crossref","first-page":"1074","DOI":"10.1109\/TMM.2021.3138298","article-title":"DualGNN: Dual graph neural network for multimedia recommendation","volume":"25","author":"Wang","year":"2023","journal-title":"IEEE Trans. Multimed."},{"key":"10.1016\/j.knosys.2026.116028_b9","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2025.113719","article-title":"A reinforcement learning approach to edge suggestion for fair information access on social networks","volume":"322","author":"Wang","year":"2025","journal-title":"Knowl.-Based Syst."},{"issue":"10","key":"10.1016\/j.knosys.2026.116028_b10","doi-asserted-by":"crossref","DOI":"10.1111\/exsy.13451","article-title":"Exploiting community and structural hole spanner for influence maximization in social networks","volume":"40","author":"Li","year":"2023","journal-title":"Expert. Syst.: J. Knowl. Eng."},{"key":"10.1016\/j.knosys.2026.116028_b11","doi-asserted-by":"crossref","first-page":"1863","DOI":"10.1109\/TKDE.2018.2872063","article-title":"A survey of multi-view representation learning","volume":"31","author":"Li","year":"2019","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"10.1016\/j.knosys.2026.116028_b12","doi-asserted-by":"crossref","DOI":"10.1016\/j.neunet.2024.106763","article-title":"Self-adaptive label discovery and multi-view fusion for complementary label learning","volume":"181","author":"Tang","year":"2025","journal-title":"Neural Netw."},{"key":"10.1016\/j.knosys.2026.116028_b13","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1016\/j.inffus.2019.08.005","article-title":"Multi-view diffusion maps","volume":"55","author":"Lindenbaum","year":"2020","journal-title":"Inf. Fusion"},{"key":"10.1016\/j.knosys.2026.116028_b14","doi-asserted-by":"crossref","first-page":"4203","DOI":"10.1109\/TIP.2025.3583122","article-title":"Multi-view clustering with incremental instances and views","volume":"34","author":"Zhang","year":"2025","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.knosys.2026.116028_b15","doi-asserted-by":"crossref","unstructured":"M. Qu, J. Tang, J. Shang, X. Ren, M. Zhang, J. Han, An Attention-based Collaboration Framework for Multi-View Network Representation Learning, in: Proceedings of the ACM on Conference on Information and Knowledge Management, 2017, pp. 1767\u20131776.","DOI":"10.1145\/3132847.3133021"},{"key":"10.1016\/j.knosys.2026.116028_b16","doi-asserted-by":"crossref","unstructured":"L. Zheng, Y. Cheng, H. Yang, N. Cao, J. He, Deep Co-Attention Network for Multi-View Subspace Learning, in: Proceedings of the Web Conference, 2021, pp. 1528\u20131539.","DOI":"10.1145\/3442381.3449801"},{"key":"10.1016\/j.knosys.2026.116028_b17","doi-asserted-by":"crossref","unstructured":"S. Fadadu, S. Pandey, D. Hegde, Y. Shi, F. Chou, N. Djuric, C. Vallespi-Gonzalez, Multi-View Fusion of Sensor Data for Improved Perception and Prediction in Autonomous Driving, in: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision, 2022, pp. 3292\u20133300.","DOI":"10.1109\/WACV51458.2022.00335"},{"key":"10.1016\/j.knosys.2026.116028_b18","doi-asserted-by":"crossref","unstructured":"S. Deng, Z. Liang, L. Sun, K. Jia, VISTA: Boosting 3D Object Detection via Dual Cross-VIew SpaTial Attention, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2022, pp. 8438\u20138447.","DOI":"10.1109\/CVPR52688.2022.00826"},{"key":"10.1016\/j.knosys.2026.116028_b19","unstructured":"J. Fan, Multi-Mode Deep Matrix and Tensor Factorization, in: International Conference on Learning Representations, 2022."},{"key":"10.1016\/j.knosys.2026.116028_b20","doi-asserted-by":"crossref","DOI":"10.1016\/j.inffus.2024.102661","article-title":"Divergence-guided disentanglement of view-common and view-unique representations for multi-view data","volume":"114","author":"Lu","year":"2025","journal-title":"Inf. Fusion"},{"key":"10.1016\/j.knosys.2026.116028_b21","doi-asserted-by":"crossref","first-page":"2050","DOI":"10.1109\/TCBB.2022.3229678","article-title":"Multi-view clustering for integration of gene expression and methylation data with tensor decomposition and self-representation learning","volume":"20","author":"Gao","year":"2023","journal-title":"IEEE ACM Trans. Comput. Biology Bioinformaticsis"},{"key":"10.1016\/j.knosys.2026.116028_b22","doi-asserted-by":"crossref","first-page":"5355","DOI":"10.1109\/TCSVT.2025.3536629","article-title":"Tensorized tri-factor decomposition for multi-view clustering","volume":"35","author":"Wang","year":"2025","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.knosys.2026.116028_b23","doi-asserted-by":"crossref","first-page":"676","DOI":"10.1109\/TCBB.2021.3059415","article-title":"Predicting biomedical interactions with higher-order graph convolutional networks","volume":"19","author":"K.C.","year":"2022","journal-title":"IEEE ACM Trans. Comput. Biology Bioinform."},{"key":"10.1016\/j.knosys.2026.116028_b24","doi-asserted-by":"crossref","DOI":"10.1016\/j.neunet.2024.106859","article-title":"Tensorial multiview low-rank high-order graph learning for context-enhanced domain adaptation","volume":"181","author":"Zhu","year":"2025","journal-title":"Neural Netw."},{"key":"10.1016\/j.knosys.2026.116028_b25","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2025.129057","article-title":"Capturing local and global information: Multi-view graph convolutional network via granular-ball computing and collaborative matrix","volume":"296","author":"Wang","year":"2026","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.knosys.2026.116028_b26","unstructured":"A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A.N. Gomez, L. Kaiser, I. Polosukhin, Attention is All you Need, in: Proceedings of the Annual Conference on Neural Information Processing Systems, 2017, pp. 5998\u20136008."},{"key":"10.1016\/j.knosys.2026.116028_b27","doi-asserted-by":"crossref","first-page":"88:1","DOI":"10.1145\/3502730","article-title":"Exploiting higher order multi-dimensional relationships with self-attention for author name disambiguation","volume":"16","author":"Pooja","year":"2022","journal-title":"ACM Trans. Knowl. Discov. from Data"},{"key":"10.1016\/j.knosys.2026.116028_b28","doi-asserted-by":"crossref","DOI":"10.1016\/j.inffus.2024.102664","article-title":"Zero-shot sim-to-real transfer using siamese-q-based reinforcement learning","volume":"114","author":"Zhang","year":"2025","journal-title":"Inf. Fusion"},{"key":"10.1016\/j.knosys.2026.116028_b29","doi-asserted-by":"crossref","first-page":"459","DOI":"10.1007\/s10107-013-0701-9","article-title":"Proximal alternating linearized minimization for nonconvex and nonsmooth problems","volume":"146","author":"Bolte","year":"2014","journal-title":"Math. Program."},{"key":"10.1016\/j.knosys.2026.116028_b30","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1007\/s10107-011-0484-9","article-title":"Convergence of descent methods for semi-algebraic and tame problems: proximal algorithms, forward\u2013backward splitting, and regularized Gauss\u2013Seidel methods","volume":"137","author":"Attouch","year":"2013","journal-title":"Math. Program."},{"key":"10.1016\/j.knosys.2026.116028_b31","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1109\/MSP.2020.3016905","article-title":"Algorithm unrolling: Interpretable, efficient deep learning for signal and image processing","volume":"38","author":"Monga","year":"2021","journal-title":"IEEE Signal Process. Mag."},{"key":"10.1016\/j.knosys.2026.116028_b32","doi-asserted-by":"crossref","unstructured":"Y. Geng, Z. Han, C. Zhang, Q. Hu, Uncertainty-Aware Multi-View Representation Learning, in: Proceedings of the AAAI Conference on Artificial Intelligence, 2021, pp. 7545\u20137553.","DOI":"10.1609\/aaai.v35i9.16924"},{"key":"10.1016\/j.knosys.2026.116028_b33","doi-asserted-by":"crossref","unstructured":"H. Tang, Y. Liu, Deep Safe Multi-view Clustering: Reducing the Risk of Clustering Performance Degradation Caused by View Increase, in: Proceedings of IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2022, pp. 202\u2013211.","DOI":"10.1109\/CVPR52688.2022.00030"},{"key":"10.1016\/j.knosys.2026.116028_b34","doi-asserted-by":"crossref","unstructured":"M. Sun, P. Zhang, S. Wang, S. Zhou, W. Tu, X. Liu, E. Zhu, C. Wang, Scalable Multi-view Subspace Clustering with Unified Anchors, in: Proceedings of the Multimedia Conference, 2021, pp. 3528\u20133536.","DOI":"10.1145\/3474085.3475516"},{"key":"10.1016\/j.knosys.2026.116028_b35","doi-asserted-by":"crossref","unstructured":"Y. Tan, Y. Liu, H. Wu, J. Lv, S. Huang, Metric Multi-View Graph Clustering, in: Proceedings of the Conference on Artificial Intelligence, 2023, pp. 9962\u20139970.","DOI":"10.1609\/aaai.v37i8.26188"},{"key":"10.1016\/j.knosys.2026.116028_b36","doi-asserted-by":"crossref","first-page":"4207","DOI":"10.1109\/TKDE.2024.3364663","article-title":"Robust and consistent anchor graph learning for multi-view clustering","volume":"36","author":"Liu","year":"2024","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"10.1016\/j.knosys.2026.116028_b37","doi-asserted-by":"crossref","first-page":"4627","DOI":"10.1109\/TIP.2024.3444320","article-title":"Scalable and structural multi-view graph clustering with adaptive anchor fusion","volume":"33","author":"Wang","year":"2024","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.knosys.2026.116028_b38","doi-asserted-by":"crossref","DOI":"10.1016\/j.neunet.2025.107779","article-title":"Anchor graph learning with double noise removal for multi-view clustering","volume":"191","author":"Chen","year":"2025","journal-title":"Neural Netw."},{"key":"10.1016\/j.knosys.2026.116028_b39","doi-asserted-by":"crossref","unstructured":"S. Li, W. Li, W. Wang, Co-GCN for Multi-View Semi-Supervised Learning, in: Proceedings of the AAAI Conference on Artificial Intelligence, 2020, pp. 4691\u20134698.","DOI":"10.1609\/aaai.v34i04.5901"},{"key":"10.1016\/j.knosys.2026.116028_b40","first-page":"5042","article-title":"Learning deep sparse regularizers with applications to multi-view clustering and semi-supervised classification","volume":"44","author":"Wang","year":"2022","journal-title":"IEEE Trans. Pattern Anal. Machine Intell."},{"key":"10.1016\/j.knosys.2026.116028_b41","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1016\/j.inffus.2023.02.013","article-title":"Learnable graph convolutional network and feature fusion for multi-view learning","volume":"95","author":"Chen","year":"2023","journal-title":"Inf. Fusion"},{"key":"10.1016\/j.knosys.2026.116028_b42","doi-asserted-by":"crossref","first-page":"8593","DOI":"10.1109\/TMM.2023.3260649","article-title":"Interpretable graph convolutional network for multi-view semi-supervised learning","volume":"25","author":"Wu","year":"2023","journal-title":"IEEE Trans. Multimed."},{"key":"10.1016\/j.knosys.2026.116028_b43","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1016\/j.neunet.2023.09.006","article-title":"Joint learning of feature and topology for multi-view graph convolutional network","volume":"168","author":"Chen","year":"2023","journal-title":"Neural Netw."},{"key":"10.1016\/j.knosys.2026.116028_b44","first-page":"1","article-title":"Multi-channel equilibrium graph neural network for multi-view semi-supervised learning","volume":"1","author":"Wang","year":"2025","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."}],"container-title":["Knowledge-Based Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0950705126007549?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0950705126007549?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,6,12]],"date-time":"2026-06-12T00:17:35Z","timestamp":1781223455000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0950705126007549"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6]]},"references-count":44,"alternative-id":["S0950705126007549"],"URL":"https:\/\/doi.org\/10.1016\/j.knosys.2026.116028","relation":{},"ISSN":["0950-7051"],"issn-type":[{"value":"0950-7051","type":"print"}],"subject":[],"published":{"date-parts":[[2026,6]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"High-order relation driven multi-view representation learning","name":"articletitle","label":"Article Title"},{"value":"Knowledge-Based Systems","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.knosys.2026.116028","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"116028"}}