{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T18:22:01Z","timestamp":1776190921705,"version":"3.50.1"},"reference-count":49,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62466035"],"award-info":[{"award-number":["62466035"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004479","name":"Jiangxi Provincial Natural Science Foundation","doi-asserted-by":"publisher","award":["20242BAB25106"],"award-info":[{"award-number":["20242BAB25106"]}],"id":[{"id":"10.13039\/501100004479","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Neural Networks"],"published-print":{"date-parts":[[2026,9]]},"DOI":"10.1016\/j.neunet.2026.108894","type":"journal-article","created":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T00:16:56Z","timestamp":1774311416000},"page":"108894","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Dual contrastive learning with graph masking: A self-supervised framework for multi-view clustering"],"prefix":"10.1016","volume":"201","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9029-357X","authenticated-orcid":false,"given":"Jian-Sheng","family":"Wu","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0007-9202-485X","authenticated-orcid":false,"given":"Wen-Ting","family":"Li","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0000-7164-0839","authenticated-orcid":false,"given":"Jun-Yun","family":"Wu","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2526-2181","authenticated-orcid":false,"given":"Weidong","family":"Min","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.neunet.2026.108894_bib0001","series-title":"Eccv","first-page":"348","article-title":"MultiMAE: Multi-modal multi-task masked autoencoders","author":"Bachmann","year":"2022"},{"key":"10.1016\/j.neunet.2026.108894_bib0002","series-title":"Iclr","first-page":"1","article-title":"BEIt: Bert pre-training of image transformers","author":"Bao","year":"2022"},{"key":"10.1016\/j.neunet.2026.108894_bib0003","series-title":"The web conference","first-page":"1400","article-title":"Structural deep clustering network","author":"Bo","year":"2020"},{"issue":"12","key":"10.1016\/j.neunet.2026.108894_bib0004","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1093\/bioinformatics\/bts220","article-title":"Joint stage recognition and anatomical annotation of drosophila gene expression patterns","volume":"28","author":"Cai","year":"2012","journal-title":"Bioinformatics"},{"key":"10.1016\/j.neunet.2026.108894_bib0005","doi-asserted-by":"crossref","DOI":"10.1016\/j.inffus.2024.102245","article-title":"Projected cross-view learning for unbalanced incomplete multi-view clustering","volume":"105","author":"Cai","year":"2024","journal-title":"Information Fusion"},{"key":"10.1016\/j.neunet.2026.108894_bib0006","series-title":"Machine Learning and Data Mining in Pattern Recognition","first-page":"324","article-title":"Transductive learning from relational data","author":"Ceci","year":"2007"},{"issue":"2","key":"10.1016\/j.neunet.2026.108894_bib0007","doi-asserted-by":"crossref","first-page":"146","DOI":"10.1109\/TAI.2021.3065894","article-title":"A survey on multiview clustering","volume":"2","author":"Chao","year":"2021","journal-title":"IEEE Transactions on Artificial Intelligence"},{"key":"10.1016\/j.neunet.2026.108894_bib0008","series-title":"Ijcai","first-page":"3577","article-title":"Deep multi-view subspace clustering with anchor graph","author":"Cui","year":"2023"},{"issue":"8","key":"10.1016\/j.neunet.2026.108894_bib0009","doi-asserted-by":"crossref","first-page":"11436","DOI":"10.1109\/TNNLS.2023.3261460","article-title":"Efficient multi-view clustering via unified and discrete bipartite graph learning","volume":"35","author":"Fang","year":"2024","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"},{"key":"10.1016\/j.neunet.2026.108894_bib0010","series-title":"Cvpr workshop","article-title":"Learning generative visual models from few training examples: An incremental bayesian approach tested on 101 object categories","author":"Fei-Fei","year":"2004"},{"key":"10.1016\/j.neunet.2026.108894_bib0011","series-title":"Iclr","first-page":"1","article-title":"Contrastive audio-visual masked autoencoder","author":"Gong","year":"2023"},{"key":"10.1016\/j.neunet.2026.108894_bib0012","doi-asserted-by":"crossref","DOI":"10.1016\/j.neunet.2025.107409","article-title":"Restarted multiple kernel algorithms with self-guiding for large-scale multi-view clustering","volume":"187","author":"Guo","year":"2025","journal-title":"Neural Networks"},{"key":"10.1016\/j.neunet.2026.108894_bib0013","series-title":"Cvpr","first-page":"16000","article-title":"Masked autoencoders are scalable vision learners","author":"He","year":"2022"},{"key":"10.1016\/j.neunet.2026.108894_bib0014","series-title":"Iccv","first-page":"1208","article-title":"Neighborhood preserving embedding","author":"He","year":"2005"},{"key":"10.1016\/j.neunet.2026.108894_bib0015","series-title":"Kdd","first-page":"594","article-title":"GraphMAE: Self-supervised masked graph autoencoders","author":"Hou","year":"2022"},{"issue":"4","key":"10.1016\/j.neunet.2026.108894_bib0016","doi-asserted-by":"crossref","first-page":"2506","DOI":"10.1109\/TPAMI.2023.3336525","article-title":"Contrastive masked autoencoders are stronger vision learners","volume":"46","author":"Huang","year":"2024","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"10.1016\/j.neunet.2026.108894_bib0017","series-title":"Icsp","first-page":"39","article-title":"Multi-view clustering via deep graph embedding","author":"Huang","year":"2023"},{"key":"10.1016\/j.neunet.2026.108894_bib0018","series-title":"Cvpr","first-page":"17947","article-title":"Multi-modal contrastive masked autoencoders: A two-stage progressive pre-training approach for RGBD datasets","author":"Jamal","year":"2025"},{"key":"10.1016\/j.neunet.2026.108894_bib0019","series-title":"Nips","first-page":"23","article-title":"Deep subspace clustering networks","author":"Ji","year":"2017"},{"key":"10.1016\/j.neunet.2026.108894_bib0020","series-title":"Icmr","first-page":"1","article-title":"Consumer video understanding: A benchmark database and an evaluation of human and machine performance","author":"Jiang","year":"2011"},{"key":"10.1016\/j.neunet.2026.108894_bib0021","series-title":"Cvpr","first-page":"26774","article-title":"Rethinking multi-view representation learning via distilled disentangling","author":"Ke","year":"2024"},{"key":"10.1016\/j.neunet.2026.108894_bib0022","series-title":"Nips","first-page":"1413","article-title":"Co-regularized multi-view spectral clustering","author":"Kumar","year":"2011"},{"key":"10.1016\/j.neunet.2026.108894_bib0023","doi-asserted-by":"crossref","DOI":"10.1016\/j.neucom.2025.129889","article-title":"Dcmvc: Dual contrastive multi-view clustering","volume":"635","author":"Li","year":"2025","journal-title":"Neurocomputing"},{"issue":"7","key":"10.1016\/j.neunet.2026.108894_bib0024","first-page":"3418","article-title":"Multi-view spectral clustering with high-order optimal neighborhood laplacian matrix","volume":"34","author":"Liang","year":"2020","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"issue":"3","key":"10.1016\/j.neunet.2026.108894_bib0025","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3632751","article-title":"Less is more: Removing redundancy of graph convolutional networks for recommendation","volume":"42","author":"Peng","year":"2024","journal-title":"ACM Transactions on Information Systems"},{"key":"10.1016\/j.neunet.2026.108894_bib0026","series-title":"Icml","first-page":"5092","article-title":"COMIC: Multi-view clustering without parameter selection","author":"Peng","year":"2019"},{"key":"10.1016\/j.neunet.2026.108894_bib0027","doi-asserted-by":"crossref","first-page":"5298","DOI":"10.1109\/TIP.2024.3459651","article-title":"Dual consensus anchor learning for fast multi-view clustering","volume":"33","author":"Qin","year":"2024","journal-title":"IEEE Transactions on Image Processing"},{"issue":"5500","key":"10.1016\/j.neunet.2026.108894_bib0028","doi-asserted-by":"crossref","first-page":"2323","DOI":"10.1126\/science.290.5500.2323","article-title":"Nonlinear dimensionality reduction by locally linear embedding","volume":"290","author":"Roweis","year":"2000","journal-title":"Science"},{"key":"10.1016\/j.neunet.2026.108894_bib0029","series-title":"Www","first-page":"1177","article-title":"Web-scale k-means clustering","author":"Sculley","year":"2010"},{"issue":"6","key":"10.1016\/j.neunet.2026.108894_bib0030","doi-asserted-by":"crossref","first-page":"10283","DOI":"10.1109\/TNNLS.2025.3540063","article-title":"When heterophily meets heterogeneous graphs: Latent graphs guided unsupervised representation learning","volume":"36","author":"Shen","year":"2025","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"},{"key":"10.1016\/j.neunet.2026.108894_bib0031","series-title":"Nips","first-page":"31629","article-title":"Beyond redundancy: Information-aware unsupervised multiplex graph structure learning","author":"Shen","year":"2024"},{"key":"10.1016\/j.neunet.2026.108894_bib0032","series-title":"Acm wsdm","first-page":"787","article-title":"S2GAE: Self-supervised graph autoencoders are generalizable learners with graph masking","author":"Tan","year":"2023"},{"key":"10.1016\/j.neunet.2026.108894_bib0033","series-title":"Cvpr","first-page":"1255","article-title":"Reconsidering representation alignment for multi-view clustering","author":"Trosten","year":"2021"},{"issue":"6","key":"10.1016\/j.neunet.2026.108894_bib0034","doi-asserted-by":"crossref","first-page":"1116","DOI":"10.1109\/TKDE.2019.2903810","article-title":"Gmc: Graph-based multi-view clustering","volume":"32","author":"Wang","year":"2020","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"10.1016\/j.neunet.2026.108894_bib0035","series-title":"Ijcai","first-page":"3230","article-title":"Cdimc-net: Cognitive deep incomplete multi-view clustering network","author":"Wen","year":"2021"},{"key":"10.1016\/j.neunet.2026.108894_bib0036","series-title":"Acm wsdm","first-page":"654","article-title":"Neural demographic prediction using search query","author":"Wu","year":"2019"},{"key":"10.1016\/j.neunet.2026.108894_bib0037","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2024.111322","article-title":"Deep multi-view clustering with diverse and discriminative feature learning","volume":"161","author":"Xu","year":"2025","journal-title":"Pattern Recognition"},{"key":"10.1016\/j.neunet.2026.108894_bib0038","doi-asserted-by":"crossref","first-page":"279","DOI":"10.1016\/j.ins.2020.12.073","article-title":"Deep embedded multi-view clustering with collaborative training","volume":"573","author":"Xu","year":"2021","journal-title":"Information Sciences"},{"issue":"7","key":"10.1016\/j.neunet.2026.108894_bib0039","doi-asserted-by":"crossref","first-page":"7470","DOI":"10.1109\/TKDE.2022.3193569","article-title":"Self-supervised discriminative feature learning for deep multi-view clustering","volume":"35","author":"Xu","year":"2023","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"10.1016\/j.neunet.2026.108894_bib0040","series-title":"Cvpr","first-page":"16051","article-title":"Multi-level feature learning for contrastive multi-view clustering","author":"Xu","year":"2022"},{"key":"10.1016\/j.neunet.2026.108894_bib0041","series-title":"Cvpr","first-page":"19863","article-title":"Gcfagg: Global and cross-view feature aggregation for multi-view clustering","author":"Yan","year":"2023"},{"issue":"2","key":"10.1016\/j.neunet.2026.108894_bib0042","doi-asserted-by":"crossref","first-page":"3797","DOI":"10.1109\/TNNLS.2024.3357087","article-title":"Anchor-sharing and clusterwise contrastive network for multiview representation learning","volume":"36","author":"Yan","year":"2025","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"},{"issue":"4","key":"10.1016\/j.neunet.2026.108894_bib0043","doi-asserted-by":"crossref","first-page":"1126","DOI":"10.1109\/TETCI.2022.3221491","article-title":"Multi-view adjacency-constrained hierarchical clustering","volume":"7","author":"Yang","year":"2023","journal-title":"IEEE Transactions on Emerging Topics in Computational Intelligence"},{"key":"10.1016\/j.neunet.2026.108894_bib0044","series-title":"Acm mm","first-page":"337","article-title":"DealMVC: Dual contrastive calibration for multi-view clustering","author":"Yang","year":"2023"},{"key":"10.1016\/j.neunet.2026.108894_bib0045","doi-asserted-by":"crossref","first-page":"1595","DOI":"10.1109\/LSP.2024.3408606","article-title":"Separable consistency and diversity feature learning for multi-view clustering","volume":"31","author":"Zhang","year":"2024","journal-title":"IEEE Signal Processing Letters"},{"key":"10.1016\/j.neunet.2026.108894_bib0046","doi-asserted-by":"crossref","DOI":"10.1016\/j.neunet.2024.106529","article-title":"Tensorized incomplete multi-view kernel subspace clustering","volume":"179","author":"Zhang","year":"2024","journal-title":"Neural Networks"},{"key":"10.1016\/j.neunet.2026.108894_bib0047","doi-asserted-by":"crossref","DOI":"10.1016\/j.neunet.2025.107954","article-title":"Structure-preserving contrastive graph clustering with dual-channel label alignment","volume":"193","author":"Zhang","year":"2026","journal-title":"Neural Networks"},{"key":"10.1016\/j.neunet.2026.108894_bib0048","series-title":"Cvpr","first-page":"5468","article-title":"Self-supervised convolutional subspace clustering network","author":"Zhang","year":"2019"},{"issue":"1","key":"10.1016\/j.neunet.2026.108894_bib0049","first-page":"1","article-title":"Two-stage fusion multiview graph clustering based on the attention mechanism","volume":"64","author":"Zhao","year":"2024","journal-title":"Journal of Tsinghua University (Science and Technology)"}],"container-title":["Neural Networks"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0893608026003552?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0893608026003552?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T17:31:12Z","timestamp":1776187872000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0893608026003552"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9]]},"references-count":49,"alternative-id":["S0893608026003552"],"URL":"https:\/\/doi.org\/10.1016\/j.neunet.2026.108894","relation":{},"ISSN":["0893-6080"],"issn-type":[{"value":"0893-6080","type":"print"}],"subject":[],"published":{"date-parts":[[2026,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Dual contrastive learning with graph masking: A self-supervised framework for multi-view clustering","name":"articletitle","label":"Article Title"},{"value":"Neural Networks","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.neunet.2026.108894","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"108894"}}