{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,26]],"date-time":"2026-06-26T15:46:21Z","timestamp":1782488781345,"version":"3.54.5"},"reference-count":62,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100004731","name":"Natural Science Foundation of Zhejiang Province","doi-asserted-by":"publisher","award":["LMS26F020035"],"award-info":[{"award-number":["LMS26F020035"]}],"id":[{"id":"10.13039\/501100004731","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2022YFC3302103"],"award-info":[{"award-number":["2022YFC3302103"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["ZBKF-24-12"],"award-info":[{"award-number":["ZBKF-24-12"]}],"id":[{"id":"10.13039\/501100012166","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":[[2026,12]]},"DOI":"10.1016\/j.neunet.2026.109265","type":"journal-article","created":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T23:17:56Z","timestamp":1781651876000},"page":"109265","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Semi-supervised multi-label feature selection with consistent sparse graph learning"],"prefix":"10.1016","volume":"204","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0005-2620","authenticated-orcid":false,"given":"Yan","family":"Zhong","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8204-6197","authenticated-orcid":false,"given":"Xingyu","family":"Wu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinping","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1610-6056","authenticated-orcid":false,"given":"Li","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinyuan","family":"Song","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5570-7818","authenticated-orcid":false,"given":"Lei","family":"Shi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2217-6202","authenticated-orcid":false,"given":"Bingbing","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"1","key":"10.1016\/j.neunet.2026.109265_bib0001","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1007\/s10115-015-0841-8","article-title":"Soft-constrained laplacian score for semi-supervised multi-label feature selection","volume":"47","author":"Alalga","year":"2016","journal-title":"Knowledge and Information Systems"},{"issue":"6","key":"10.1016\/j.neunet.2026.109265_bib0002","doi-asserted-by":"crossref","first-page":"1373","DOI":"10.1162\/089976603321780317","article-title":"Laplacian eigenmaps for dimensionality reduction and data representation","volume":"15","author":"Belkin","year":"2003","journal-title":"Neural Computation"},{"key":"10.1016\/j.neunet.2026.109265_bib0003","series-title":"Convex optimization","author":"Boyd","year":"2004"},{"key":"10.1016\/j.neunet.2026.109265_bib0004","series-title":"Proceedings of the AAAI conference on artificial intelligence","article-title":"A convex formulation for semi-supervised multi-label feature selection","volume":"vol. 28","author":"Chang","year":"2014"},{"key":"10.1016\/j.neunet.2026.109265_bib0005","series-title":"Pacific-asia conference on knowledge discovery and data mining","first-page":"74","article-title":"Semi-supervised feature analysis for multimedia annotation by mining label correlation","author":"Chang","year":"2014"},{"key":"10.1016\/j.neunet.2026.109265_bib0006","article-title":"Exploiting attributes and keywords for session-based recommendation with multi-view graph neural network","volume":"296","author":"Chen","year":"2025","journal-title":"Expert Systems with Applications"},{"issue":"9","key":"10.1016\/j.neunet.2026.109265_bib0007","doi-asserted-by":"crossref","first-page":"1744","DOI":"10.1109\/TCYB.2014.2359984","article-title":"Similarity learning of manifold data","volume":"45","author":"Chen","year":"2014","journal-title":"IEEE Transactions on Cybernetics"},{"issue":"1","key":"10.1016\/j.neunet.2026.109265_bib0008","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1109\/TKDE.2018.2879797","article-title":"Semi-supervised feature selection via sparse rescaled linear square regression","volume":"32","author":"Chen","year":"2020","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"issue":"1","key":"10.1016\/j.neunet.2026.109265_bib0009","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1109\/TPAMI.2008.277","article-title":"Convex and semi-nonnegative matrix factorizations","volume":"32","author":"Ding","year":"2008","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"10.1016\/j.neunet.2026.109265_bib0010","doi-asserted-by":"crossref","first-page":"285","DOI":"10.1016\/j.patcog.2019.06.015","article-title":"Sparse graphs with smoothness constraints: Application to dimensionality reduction and semi-supervised classification","volume":"95","author":"Dornaika","year":"2019","journal-title":"Pattern Recognition"},{"key":"10.1016\/j.neunet.2026.109265_bib0011","series-title":"Pattern classification","author":"Duda","year":"2006"},{"key":"10.1016\/j.neunet.2026.109265_bib0012","series-title":"The cambridge dictionary of statistics","volume":"vol. 140","author":"Everitt","year":"2002"},{"key":"10.1016\/j.neunet.2026.109265_bib0013","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2023.109899","article-title":"Learning correlation information for multi-label feature selection","volume":"145","author":"Fan","year":"2024","journal-title":"Pattern Recognition"},{"key":"10.1016\/j.neunet.2026.109265_bib0014","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2025.111941","article-title":"Reconstructing data representation for multi-label feature selection","volume":"169","author":"Fan","year":"2026","journal-title":"Pattern Recognition"},{"issue":"1","key":"10.1016\/j.neunet.2026.109265_bib0015","doi-asserted-by":"crossref","DOI":"10.1109\/TNNLS.2022.3178075","article-title":"Causal feature selection with dual correction","volume":"35","author":"Guo","year":"2022","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"},{"issue":"3","key":"10.1016\/j.neunet.2026.109265_bib0016","doi-asserted-by":"crossref","first-page":"876","DOI":"10.1109\/TCYB.2017.2663838","article-title":"Joint feature selection and classification for multilabel learning","volume":"48","author":"Huang","year":"2017","journal-title":"IEEE Transactions on Cybernetics"},{"key":"10.1016\/j.neunet.2026.109265_bib0017","series-title":"Ijcai","article-title":"Multi-label informed feature selection","volume":"vol. 16","author":"Jian","year":"2016"},{"issue":"7","key":"10.1016\/j.neunet.2026.109265_bib0018","first-page":"1643","article-title":"Semi-supervised feature selection with adaptive graph learning","volume":"50","author":"Jiang","year":"2022","journal-title":"Acta Electonica Sinica"},{"issue":"3","key":"10.1016\/j.neunet.2026.109265_bib0019","doi-asserted-by":"crossref","first-page":"3615","DOI":"10.1109\/TNNLS.2022.3194957","article-title":"Semi-supervised multi-view feature selection with adaptive graph learning","volume":"35","author":"Jiang","year":"2024","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"},{"issue":"3","key":"10.1016\/j.neunet.2026.109265_bib0020","doi-asserted-by":"crossref","DOI":"10.1016\/j.ipm.2023.103633","article-title":"Multi-label feature selection with high-sparse personalized and low-redundancy shared common features","volume":"61","author":"Li","year":"2024","journal-title":"Information Processing & Management"},{"issue":"4","key":"10.1016\/j.neunet.2026.109265_bib0021","doi-asserted-by":"crossref","DOI":"10.1016\/j.ipm.2024.103727","article-title":"Adaptive orthogonal semi-supervised feature selection with reliable label matrix learning","volume":"61","author":"Liao","year":"2024","journal-title":"Information Processing & Management"},{"issue":"1","key":"10.1016\/j.neunet.2026.109265_bib0022","doi-asserted-by":"crossref","first-page":"401","DOI":"10.1109\/TETCI.2023.3302653","article-title":"Multi-label feature selection via positive or negative correlation","volume":"8","author":"Lin","year":"2024","journal-title":"IEEE Transactions on Emerging Topics in Computational Intelligence"},{"key":"10.1016\/j.neunet.2026.109265_bib0023","series-title":"Proceedings of the 40th international ACM SIGIR conference on research and development in information retrieval","first-page":"115","article-title":"Deep learning for extreme multi-label text classification","author":"Liu","year":"2017"},{"issue":"10","key":"10.1016\/j.neunet.2026.109265_bib0024","doi-asserted-by":"crossref","first-page":"3384","DOI":"10.1109\/TFUZZ.2023.3255893","article-title":"SemiFREE: Semi-supervised feature selection with fuzzy relevance and redundancy","volume":"31","author":"Liu","year":"2023","journal-title":"IEEE Transactions on Fuzzy Systems"},{"key":"10.1016\/j.neunet.2026.109265_bib0025","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1016\/j.neucom.2012.05.031","article-title":"Efficient semi-supervised feature selection with noise insensitive trace ratio criterion","volume":"105","author":"Liu","year":"2013","journal-title":"Neurocomputing"},{"issue":"10","key":"10.1016\/j.neunet.2026.109265_bib0026","doi-asserted-by":"crossref","first-page":"1943","DOI":"10.1109\/TKDE.2018.2810286","article-title":"Semi-supervised feature selection via insensitive sparse regression with application to video semantic recognition","volume":"30","author":"Luo","year":"2018","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"10.1016\/j.neunet.2026.109265_bib0027","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2021.106757","article-title":"Semi-supervised multi-label feature selection with adaptive structure learning and manifold learning","volume":"214","author":"Lv","year":"2021","journal-title":"Knowledge-based Systems"},{"key":"10.1016\/j.neunet.2026.109265_bib0028","article-title":"Discriminative multi-label feature selection with adaptive graph diffusion","volume":"148","author":"Ma","year":"2023","journal-title":"Pattern Recognition"},{"issue":"4","key":"10.1016\/j.neunet.2026.109265_bib0029","doi-asserted-by":"crossref","first-page":"1021","DOI":"10.1109\/TMM.2012.2187179","article-title":"Web image annotation via subspace-sparsity collaborated feature selection","volume":"14","author":"Ma","year":"2012","journal-title":"IEEE Transactions on Multimedia"},{"issue":"6","key":"10.1016\/j.neunet.2026.109265_bib0030","doi-asserted-by":"crossref","first-page":"1662","DOI":"10.1109\/TMM.2012.2199293","article-title":"Discriminating joint feature analysis for multimedia data understanding","volume":"14","author":"Ma","year":"2012","journal-title":"IEEE Transactions on Multimedia"},{"key":"10.1016\/j.neunet.2026.109265_bib0031","first-page":"1813","article-title":"Efficient and robust feature selection via joint l2, 1-norms minimization","volume":"23","author":"Nie","year":"2010","journal-title":"Advances in Neural Information Processing Systems"},{"issue":"3","key":"10.1016\/j.neunet.2026.109265_bib0032","first-page":"1210","article-title":"Structured graph optimization for unsupervised feature selection","volume":"33","author":"Nie","year":"2021","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"10.1016\/j.neunet.2026.109265_bib0033","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2023.110521","article-title":"Hessian-based semi-supervised feature selection using generalized uncorrelated constraint","volume":"269","author":"Sheikhpour","year":"2023","journal-title":"Knowledge-Based Systems"},{"key":"10.1016\/j.neunet.2026.109265_bib0034","doi-asserted-by":"crossref","DOI":"10.1016\/j.ins.2024.121800","article-title":"Robust semi-supervised multi-label feature selection based on shared subspace and manifold learning","volume":"699","author":"Sheikhpour","year":"2025","journal-title":"Information Sciences"},{"key":"10.1016\/j.neunet.2026.109265_bib0035","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1016\/j.patcog.2016.11.003","article-title":"A survey on semi-supervised feature selection methods","volume":"64","author":"Sheikhpour","year":"2017","journal-title":"Pattern Recognition"},{"key":"10.1016\/j.neunet.2026.109265_bib0036","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/j.ins.2020.03.094","article-title":"A robust graph-based semi-supervised sparse feature selection method","volume":"531","author":"Sheikhpour","year":"2020","journal-title":"Information Sciences"},{"issue":"3","key":"10.1016\/j.neunet.2026.109265_bib0037","first-page":"2299","article-title":"Binary label learning for semi-supervised feature selection","volume":"35","author":"Shi","year":"2023","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"10.1016\/j.neunet.2026.109265_bib0038","doi-asserted-by":"crossref","first-page":"838","DOI":"10.1109\/TIP.2023.3234497","article-title":"Unsupervised adaptive feature selection with binary hashing","volume":"32","author":"Shi","year":"2023","journal-title":"IEEE Transactions on Image Processing"},{"key":"10.1016\/j.neunet.2026.109265_bib0039","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2024.111444","article-title":"Partial multi-label learning via semi-supervised subspace collaboration","volume":"287","author":"Tan","year":"2024","journal-title":"Knowledge-Based Systems"},{"issue":"10","key":"10.1016\/j.neunet.2026.109265_bib0040","doi-asserted-by":"crossref","first-page":"4705","DOI":"10.1109\/TKDE.2020.3048678","article-title":"Cross-view locality preserved diversity and consensus learning for multi-view unsupervised feature selection","volume":"34","author":"Tang","year":"2022","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"10.1016\/j.neunet.2026.109265_bib0041","series-title":"Data Classification: Algorithms and Applications","first-page":"37","article-title":"Feature selection for classification: A review","author":"Tang","year":"2014"},{"key":"10.1016\/j.neunet.2026.109265_bib0042","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1016\/j.imavis.2017.05.004","article-title":"Semi-supervised multi-label feature selection via label correlation analysis with l1-norm graph embedding","volume":"63","author":"Wang","year":"2017","journal-title":"Image and Vision Computing"},{"issue":"2","key":"10.1016\/j.neunet.2026.109265_bib0043","doi-asserted-by":"crossref","first-page":"707","DOI":"10.1109\/TCYB.2021.3139898","article-title":"Feature selection with maximal relevance and minimal supervised redundancy","volume":"53","author":"Wang","year":"2023","journal-title":"IEEE Transactions on Cybernetics"},{"key":"10.1016\/j.neunet.2026.109265_bib0044","series-title":"Inverting Modified Matrices","author":"Woodbury","year":"1950"},{"key":"10.1016\/j.neunet.2026.109265_bib0045","series-title":"Proceedings of the AAAI conference on artificial intelligence","first-page":"6430","article-title":"Multi-label causal feature selection","volume":"vol. 34","author":"Wu","year":"2020"},{"key":"10.1016\/j.neunet.2026.109265_bib0046","series-title":"Proceedings of the 27th ACM international conference on information and knowledge management","first-page":"783","article-title":"Semi-supervised multi-label feature selection by preserving feature-label space consistency","author":"Xu","year":"2018"},{"key":"10.1016\/j.neunet.2026.109265_bib0047","doi-asserted-by":"crossref","DOI":"10.1016\/j.ins.2023.119525","article-title":"Multi-label feature selection based on stable label relevance and label-specific features","volume":"648","author":"Yang","year":"2023","journal-title":"Information Sciences"},{"issue":"1","key":"10.1016\/j.neunet.2026.109265_bib0048","doi-asserted-by":"crossref","first-page":"57","DOI":"10.3390\/info15010057","article-title":"SFS-AGGL: Semi-supervised feature selection integrating adaptive graph with global and local information","volume":"15","author":"Yi","year":"2024","journal-title":"Information"},{"issue":"3","key":"10.1016\/j.neunet.2026.109265_bib0049","doi-asserted-by":"crossref","first-page":"2901","DOI":"10.1109\/TKDE.2021.3113514","article-title":"Online multi-label streaming feature selection with label correlation","volume":"35","author":"You","year":"2023","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"10.1016\/j.neunet.2026.109265_bib0050","series-title":"International conference on knowledge science, engineering and management","first-page":"148","article-title":"Multi-label feature selection with adaptive subspace learning","author":"Yuan","year":"2024"},{"issue":"4","key":"10.1016\/j.neunet.2026.109265_bib0051","doi-asserted-by":"crossref","first-page":"5721","DOI":"10.1109\/TNNLS.2022.3208956","article-title":"Fast multilabel feature selection via global relevance and redundancy optimization","volume":"35","author":"Zhang","year":"2022","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"},{"issue":"7","key":"10.1016\/j.neunet.2026.109265_bib0052","doi-asserted-by":"crossref","first-page":"2038","DOI":"10.1016\/j.patcog.2006.12.019","article-title":"ML-KNN: A lazy learning approach to multi-label learning","volume":"40","author":"Zhang","year":"2007","journal-title":"Pattern Recognition"},{"issue":"19","key":"10.1016\/j.neunet.2026.109265_bib0053","doi-asserted-by":"crossref","first-page":"3218","DOI":"10.1016\/j.ins.2009.06.010","article-title":"Feature selection for multi-label naive bayes classification","volume":"179","author":"Zhang","year":"2009","journal-title":"Information Sciences"},{"issue":"12","key":"10.1016\/j.neunet.2026.109265_bib0054","doi-asserted-by":"crossref","first-page":"4640","DOI":"10.1109\/TIP.2013.2277780","article-title":"Pairwise sparsity preserving embedding for unsupervised subspace learning and classification","volume":"22","author":"Zhang","year":"2013","journal-title":"IEEE Transactions on Image Processing"},{"issue":"9","key":"10.1016\/j.neunet.2026.109265_bib0055","first-page":"1","article-title":"Multi-label feature selection via adaptive label correlation estimation","volume":"17","author":"Zhang","year":"2023","journal-title":"ACM Transactions on Knowledge Discovery from Data"},{"issue":"10\u201312","key":"10.1016\/j.neunet.2026.109265_bib0056","doi-asserted-by":"crossref","first-page":"1842","DOI":"10.1016\/j.neucom.2007.06.014","article-title":"Locality sensitive semi-supervised feature selection","volume":"71","author":"Zhao","year":"2008","journal-title":"Neurocomputing"},{"issue":"4","key":"10.1016\/j.neunet.2026.109265_bib0057","doi-asserted-by":"crossref","first-page":"5139","DOI":"10.1007\/s40747-024-01439-7","article-title":"Sparse semi-supervised multi-label feature selection based on latent representation","volume":"10","author":"Zhao","year":"2024","journal-title":"Complex & Intelligent Systems"},{"key":"10.1016\/j.neunet.2026.109265_bib0058","series-title":"2021 International joint conference on neural networks","first-page":"1","article-title":"Multi-label local-to-global feature selection","author":"Zhong","year":"2021"},{"issue":"16","key":"10.1016\/j.neunet.2026.109265_bib0059","first-page":"321","article-title":"Learning with local and global consistency","volume":"16","author":"Zhou","year":"2004","journal-title":"Advances in Neural Information Processing Systems"},{"key":"10.1016\/j.neunet.2026.109265_bib0060","series-title":"International conference on artificial neural networks","first-page":"3","article-title":"Multi-label robust feature selection via subspace-sparsity learning","author":"Zhou","year":"2024"},{"key":"10.1016\/j.neunet.2026.109265_bib0061","series-title":"Icml 2003 workshop","first-page":"58","article-title":"Combining active learning and semi-supervised learning using gaussian fields and harmonic functions","volume":"vol. 3","author":"Zhu","year":"2003"},{"key":"10.1016\/j.neunet.2026.109265_bib0062","doi-asserted-by":"crossref","DOI":"10.1016\/j.jclepro.2024.144572","article-title":"ESGReveal: An llm-based approach for extracting structured data from esg reports","volume":"489","author":"Zou","year":"2025","journal-title":"Journal of Cleaner Production"}],"container-title":["Neural Networks"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0893608026007252?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0893608026007252?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,6,26]],"date-time":"2026-06-26T14:51:36Z","timestamp":1782485496000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0893608026007252"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,12]]},"references-count":62,"alternative-id":["S0893608026007252"],"URL":"https:\/\/doi.org\/10.1016\/j.neunet.2026.109265","relation":{},"ISSN":["0893-6080"],"issn-type":[{"value":"0893-6080","type":"print"}],"subject":[],"published":{"date-parts":[[2026,12]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Semi-supervised multi-label feature selection with consistent sparse graph learning","name":"articletitle","label":"Article Title"},{"value":"Neural Networks","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.neunet.2026.109265","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":"109265"}}