{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,14]],"date-time":"2026-03-14T20:53:34Z","timestamp":1773521614411,"version":"3.50.1"},"reference-count":51,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100002365","name":"China Agricultural University","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100002365","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Expert Systems with Applications"],"published-print":{"date-parts":[[2026,5]]},"DOI":"10.1016\/j.eswa.2026.131119","type":"journal-article","created":{"date-parts":[[2026,1,10]],"date-time":"2026-01-10T07:42:11Z","timestamp":1768030931000},"page":"131119","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Sparse convex clustering based on structural sparsity and linear projection"],"prefix":"10.1016","volume":"309","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-0602-726X","authenticated-orcid":false,"given":"Tiankuo","family":"Shao","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1515-3475","authenticated-orcid":false,"given":"Ping","family":"Zhong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"key":"10.1016\/j.eswa.2026.131119_bib0001","series-title":"2022\u202fIEEE International smart cities conference (ISC2)","first-page":"1","article-title":"Personalized federated learning via convex clustering","author":"Armacki","year":"2022"},{"key":"10.1016\/j.eswa.2026.131119_bib0002","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2022.109144","article-title":"Finding compact and well-separated clusters: Clustering using silhouette coefficients","volume":"135","author":"Bagirov","year":"2023","journal-title":"Pattern Recognition"},{"key":"10.1016\/j.eswa.2026.131119_bib0003","series-title":"Proceedings of the IEEE conference on computer vision and pattern recognition","first-page":"1081","article-title":"Weakly supervised object detection with convex clustering","author":"Bilen","year":"2015"},{"key":"10.1016\/j.eswa.2026.131119_bib0004","article-title":"A relaxed customized proximal point algorithm for separable convex programming","author":"Cai","year":"2011","journal-title":"Optimization Online"},{"key":"10.1016\/j.eswa.2026.131119_bib0005","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2022.108689","article-title":"Nonconvex clustering via \u21130 fusion penalized regression","volume":"128","author":"Chen","year":"2022","journal-title":"Pattern Recognition"},{"issue":"3","key":"10.1016\/j.eswa.2026.131119_bib0006","doi-asserted-by":"crossref","first-page":"5006","DOI":"10.1109\/TNNLS.2024.3372004","article-title":"Heterogeneous domain adaptation with generalized similarity and dissimilarity regularization","volume":"36","author":"Chen","year":"2024","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"},{"issue":"1","key":"10.1016\/j.eswa.2026.131119_bib0007","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1111\/biom.12540","article-title":"Convex biclustering","volume":"73","author":"Chi","year":"2017","journal-title":"Biometrics"},{"issue":"4","key":"10.1016\/j.eswa.2026.131119_bib0008","doi-asserted-by":"crossref","first-page":"994","DOI":"10.1080\/10618600.2014.948181","article-title":"Splitting methods for convex clustering","volume":"24","author":"Chi","year":"2015","journal-title":"Journal of Computational and Graphical Statistics"},{"key":"10.1016\/j.eswa.2026.131119_bib0009","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1016\/j.neucom.2019.10.018","article-title":"Unsupervised feature selection via adaptive hypergraph regularized latent representation learning","volume":"378","author":"Ding","year":"2020","journal-title":"Neurocomputing"},{"issue":"10","key":"10.1016\/j.eswa.2026.131119_bib0010","doi-asserted-by":"crossref","first-page":"13122","DOI":"10.1109\/TNNLS.2023.3276393","article-title":"A review of convex clustering from multiple perspectives: Models, optimizations, statistical properties, applications, and connections","volume":"35","author":"Feng","year":"2023","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"},{"issue":"1","key":"10.1016\/j.eswa.2026.131119_bib0011","doi-asserted-by":"crossref","first-page":"108","DOI":"10.1186\/s13634-022-00942-8","article-title":"A parallel ADMM-based convex clustering method","volume":"2022","author":"Fodor","year":"2022","journal-title":"EURASIP Journal on Advances in Signal Processing"},{"key":"10.1016\/j.eswa.2026.131119_bib0012","unstructured":"He, B., & Yuan, X. (2021). Balanced augmented lagrangian method for convex programming. arXiv: 2108.08554."},{"key":"10.1016\/j.eswa.2026.131119_bib0013","series-title":"28th international conference on machine learning","first-page":"1","article-title":"Clusterpath an algorithm for clustering using convex fusion penalties","author":"Hocking","year":"2011"},{"key":"10.1016\/j.eswa.2026.131119_bib0014","doi-asserted-by":"crossref","DOI":"10.1016\/j.conbuildmat.2023.134498","article-title":"Global sensitivity analysis for seismic performance of shear wall with high-strength steel bars and recycled aggregate concrete","volume":"411","author":"Idriss","year":"2024","journal-title":"Construction and Building Materials"},{"key":"10.1016\/j.eswa.2026.131119_bib0015","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2023.121541","article-title":"A reinforcement learning recommender system using bi-clustering and markov decision process","volume":"237","author":"Iftikhar","year":"2024","journal-title":"Expert Systems with Applications"},{"issue":"10","key":"10.1016\/j.eswa.2026.131119_bib0016","doi-asserted-by":"crossref","first-page":"10569","DOI":"10.1109\/TKDE.2023.3249765","article-title":"Structure-aware subspace clustering","volume":"35","author":"Kou","year":"2023","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"issue":"1","key":"10.1016\/j.eswa.2026.131119_bib0017","doi-asserted-by":"crossref","first-page":"333","DOI":"10.1007\/s10107-014-0850-5","article-title":"A schur complement based semi-proximal ADMM for convex quadratic conic programming and extensions","volume":"155","author":"Li","year":"2016","journal-title":"Mathematical Programming"},{"key":"10.1016\/j.eswa.2026.131119_bib0018","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2021.107331","article-title":"Robust supervised multi-view feature selection with weighted shared loss and maximum margin criterion","volume":"229","author":"Lin","year":"2021","journal-title":"Knowledge-Based Systems"},{"issue":"12","key":"10.1016\/j.eswa.2026.131119_bib0019","doi-asserted-by":"crossref","first-page":"10065","DOI":"10.1109\/TNNLS.2022.3164540","article-title":"Convex subspace clustering by adaptive block diagonal representation","volume":"34","author":"Lin","year":"2022","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"},{"key":"10.1016\/j.eswa.2026.131119_bib0020","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2025.127560","article-title":"Representation auto-fused NMF based hierarchical clustering","volume":"283","author":"Lin","year":"2025","journal-title":"Expert Systems with Applications"},{"key":"10.1016\/j.eswa.2026.131119_bib0021","series-title":"2011\u202fIEEE Statistical signal processing workshop (SSP)","first-page":"201","article-title":"Clustering using sum-of-norms regularization: With application to particle filter output computation","author":"Lindsten","year":"2011"},{"key":"10.1016\/j.eswa.2026.131119_bib0022","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1016\/j.neucom.2018.04.001","article-title":"Structure preserving unsupervised feature selection","volume":"301","author":"Lu","year":"2018","journal-title":"Neurocomputing"},{"key":"10.1016\/j.eswa.2026.131119_bib0023","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2025.126890","article-title":"Robust sparse orthogonal basis clustering for unsupervised feature selection","volume":"274","author":"Miao","year":"2025","journal-title":"Expert Systems with Applications"},{"key":"10.1016\/j.eswa.2026.131119_bib0024","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1016\/j.neucom.2021.09.065","article-title":"An accurate and practical algorithm for internet traffic recovery problem","volume":"467","author":"Ming","year":"2022","journal-title":"Neurocomputing"},{"issue":"3","key":"10.1016\/j.eswa.2026.131119_bib0025","first-page":"1210","article-title":"Structured graph optimization for unsupervised feature selection","volume":"33","author":"Nie","year":"2019","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"issue":"6","key":"10.1016\/j.eswa.2026.131119_bib0026","doi-asserted-by":"crossref","first-page":"1423","DOI":"10.1109\/TCYB.2016.2546965","article-title":"Nonsmooth penalized clustering via \u2113{p} regularized sparse regression","volume":"47","author":"Niu","year":"2016","journal-title":"IEEE Transactions on Cybernetics"},{"issue":"1","key":"10.1016\/j.eswa.2026.131119_bib0027","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1007\/s11222-024-10550-1","article-title":"Multi-task learning via robust regularized clustering with non-convex group penalties","volume":"35","author":"Okazaki","year":"2025","journal-title":"Statistics and Computing"},{"key":"10.1016\/j.eswa.2026.131119_bib0028","doi-asserted-by":"crossref","DOI":"10.1016\/j.conbuildmat.2023.134775","article-title":"Global sensitivity analysis for studying hot-mix asphalt dynamic modulus parameters","volume":"413","author":"Owais","year":"2024","journal-title":"Construction and Building Materials"},{"issue":"7","key":"10.1016\/j.eswa.2026.131119_bib0029","doi-asserted-by":"crossref","first-page":"6439","DOI":"10.1007\/s10462-022-10325-y","article-title":"Data clustering: Application and trends","volume":"56","author":"Oyewole","year":"2023","journal-title":"Artificial Intelligence Review"},{"issue":"3","key":"10.1016\/j.eswa.2026.131119_bib0030","doi-asserted-by":"crossref","first-page":"844","DOI":"10.1016\/j.ejor.2020.09.010","article-title":"A dual reformulation and solution framework for regularized convex clustering problems","volume":"290","author":"Pi","year":"2021","journal-title":"European Journal of Operational Research"},{"issue":"2","key":"10.1016\/j.eswa.2026.131119_bib0031","doi-asserted-by":"crossref","first-page":"731","DOI":"10.1007\/s00500-019-04471-9","article-title":"Robust convex clustering","volume":"24","author":"Quan","year":"2020","journal-title":"Soft Computing"},{"key":"10.1016\/j.eswa.2026.131119_bib0032","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2022.118179","article-title":"Feature selection via non-convex constraint and latent representation learning with laplacian embedding","volume":"208","author":"Shang","year":"2022","journal-title":"Expert Systems with Applications"},{"issue":"11","key":"10.1016\/j.eswa.2026.131119_bib0033","doi-asserted-by":"crossref","first-page":"4424","DOI":"10.1109\/TNNLS.2019.2955209","article-title":"Robust structured graph clustering","volume":"31","author":"Shi","year":"2019","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"},{"issue":"4","key":"10.1016\/j.eswa.2026.131119_bib0034","doi-asserted-by":"crossref","first-page":"2671","DOI":"10.1007\/s00180-021-01101-7","article-title":"Bayesian sparse convex clustering via global-local shrinkage priors","volume":"36","author":"Shimamura","year":"2021","journal-title":"Computational Statistics"},{"key":"10.1016\/j.eswa.2026.131119_bib0035","doi-asserted-by":"crossref","DOI":"10.1016\/j.ins.2024.121276","article-title":"Clean affinity matrix induced hyper-laplacian regularization for unsupervised multi-view feature selection","volume":"682","author":"Song","year":"2024","journal-title":"Information Sciences"},{"key":"10.1016\/j.eswa.2026.131119_bib0036","doi-asserted-by":"crossref","first-page":"575","DOI":"10.1016\/j.patcog.2018.04.019","article-title":"Convex clustering with metric learning","volume":"81","author":"Sui","year":"2018","journal-title":"Pattern Recognition"},{"issue":"9","key":"10.1016\/j.eswa.2026.131119_bib0037","first-page":"1","article-title":"Convex clustering: Model, theoretical guarantee and efficient algorithm","volume":"22","author":"Sun","year":"2021","journal-title":"Journal of Machine Learning Research"},{"issue":"4","key":"10.1016\/j.eswa.2026.131119_bib0038","doi-asserted-by":"crossref","first-page":"997","DOI":"10.1093\/bioinformatics\/btab704","article-title":"Clustering spatial transcriptomics data","volume":"38","author":"Teng","year":"2022","journal-title":"Bioinformatics"},{"issue":"2","key":"10.1016\/j.eswa.2026.131119_bib0039","doi-asserted-by":"crossref","first-page":"393","DOI":"10.1080\/10618600.2017.1377081","article-title":"Sparse convex clustering","volume":"27","author":"Wang","year":"2018","journal-title":"Journal of Computational and Graphical Statistics"},{"issue":"6","key":"10.1016\/j.eswa.2026.131119_bib0040","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":"2019","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"issue":"55","key":"10.1016\/j.eswa.2026.131119_bib0041","first-page":"1","article-title":"Integrative generalized convex clustering optimization and feature selection for mixed multi-view data","volume":"22","author":"Wang","year":"2021","journal-title":"Journal of Machine Learning Research"},{"key":"10.1016\/j.eswa.2026.131119_bib0042","series-title":"2016\u202fIEEE 16th international conference on data mining (ICDM)","first-page":"1263","article-title":"Robust convex clustering analysis","author":"Wang","year":"2016"},{"key":"10.1016\/j.eswa.2026.131119_bib0043","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1016\/j.neucom.2020.10.105","article-title":"Convex clustering method for compositional data via sparse group lasso","volume":"425","author":"Wang","year":"2021","journal-title":"Neurocomputing"},{"key":"10.1016\/j.eswa.2026.131119_bib0044","series-title":"2021\u202fIEEE data science and learning workshop (DSLW)","first-page":"1","article-title":"Simultaneous grouping and denoising via sparse convex wavelet clustering","author":"Weylandt","year":"2021"},{"key":"10.1016\/j.eswa.2026.131119_bib0045","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1016\/j.neunet.2020.01.009","article-title":"Robust adaptation regularization based on within-class scatter for domain adaptation","volume":"124","author":"Yang","year":"2020","journal-title":"Neural Networks"},{"issue":"3","key":"10.1016\/j.eswa.2026.131119_bib0046","doi-asserted-by":"crossref","first-page":"2294","DOI":"10.1137\/21M1441080","article-title":"A dimension reduction technique for large-scale structured sparse optimization problems with application to convex clustering","volume":"32","author":"Yuan","year":"2022","journal-title":"SIAM Journal on Optimization"},{"issue":"7","key":"10.1016\/j.eswa.2026.131119_bib0047","doi-asserted-by":"crossref","DOI":"10.1093\/bioinformatics\/btad417","article-title":"Information-incorporated sparse convex clustering for disease subtyping","volume":"39","author":"Zhang","year":"2023","journal-title":"Bioinformatics"},{"key":"10.1016\/j.eswa.2026.131119_bib0048","doi-asserted-by":"crossref","first-page":"360","DOI":"10.1016\/j.neucom.2018.06.010","article-title":"Low-rank structure preserving for unsupervised feature selection","volume":"314","author":"Zheng","year":"2018","journal-title":"Neurocomputing"},{"key":"10.1016\/j.eswa.2026.131119_bib0049","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2022.110244","article-title":"Simultaneous laplacian embedding and subspace clustering for incomplete multi-view data","volume":"262","author":"Zhong","year":"2023","journal-title":"Knowledge-Based Systems"},{"issue":"8","key":"10.1016\/j.eswa.2026.131119_bib0050","doi-asserted-by":"crossref","first-page":"10776","DOI":"10.1109\/TNNLS.2023.3243914","article-title":"Typicality-aware adaptive similarity matrix for unsupervised learning","volume":"35","author":"Zhou","year":"2023","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"},{"issue":"3","key":"10.1016\/j.eswa.2026.131119_bib0051","doi-asserted-by":"crossref","first-page":"1436","DOI":"10.1109\/TCYB.2025.3526176","article-title":"Reweighted subspace clustering guided by local and global structure preservation","volume":"55","author":"Zhou","year":"2025","journal-title":"IEEE Transactions on Cybernetics"}],"container-title":["Expert Systems with Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0957417426000333?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0957417426000333?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,3,14]],"date-time":"2026-03-14T19:27:17Z","timestamp":1773516437000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0957417426000333"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,5]]},"references-count":51,"alternative-id":["S0957417426000333"],"URL":"https:\/\/doi.org\/10.1016\/j.eswa.2026.131119","relation":{},"ISSN":["0957-4174"],"issn-type":[{"value":"0957-4174","type":"print"}],"subject":[],"published":{"date-parts":[[2026,5]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Sparse convex clustering based on structural sparsity and linear projection","name":"articletitle","label":"Article Title"},{"value":"Expert Systems with Applications","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.eswa.2026.131119","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":"131119"}}