{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,7]],"date-time":"2026-08-07T17:01:01Z","timestamp":1786122061066,"version":"build-2736575974"},"reference-count":52,"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\/100008992","name":"Yantai University","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100008992","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100007129","name":"Shandong Province Natural Science Foundation","doi-asserted-by":"publisher","award":["ZR2023MF063"],"award-info":[{"award-number":["ZR2023MF063"]}],"id":[{"id":"10.13039\/501100007129","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Pattern Recognition"],"published-print":{"date-parts":[[2026,12]]},"DOI":"10.1016\/j.patcog.2026.114239","type":"journal-article","created":{"date-parts":[[2026,6,11]],"date-time":"2026-06-11T19:58:52Z","timestamp":1781207932000},"page":"114239","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"PB","title":["Tensorized synergistic representation for multi-view unsupervised feature selection"],"prefix":"10.1016","volume":"180","author":[{"given":"Chen","family":"Wang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6567-663X","authenticated-orcid":false,"given":"Peng","family":"Song","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Changjia","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"6","key":"10.1016\/j.patcog.2026.114239_b1","doi-asserted-by":"crossref","first-page":"7412","DOI":"10.1109\/TPAMI.2022.3218605","article-title":"Human collective intelligence inspired multi-view representation learning\u2014Enabling view communication by simulating human communication mechanism","volume":"45","author":"Jia","year":"2023","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.patcog.2026.114239_b2","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2025.112728","article-title":"Multi-view unsupervised feature selection with unified measurement of consistency and diversity","volume":"172","author":"Xu","year":"2026","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.patcog.2026.114239_b3","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2024.111113","article-title":"Structured multi-view k-means clustering","volume":"160","author":"Zhang","year":"2025","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.patcog.2026.114239_b4","doi-asserted-by":"crossref","unstructured":"F. Lv, X. Chen, Y. Huang, L. Duan, G. Lin, Progressive modality reinforcement for human multimodal emotion recognition from unaligned multimodal sequences, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2021, pp. 2554\u20132562.","DOI":"10.1109\/CVPR46437.2021.00258"},{"issue":"6","key":"10.1016\/j.patcog.2026.114239_b5","first-page":"1","article-title":"Robust adaptive linear discriminant analysis with bidirectional reconstruction constraint","volume":"14","author":"Guo","year":"2020","journal-title":"ACM Trans. Knowl. Discov. Data (TKDD)"},{"issue":"4","key":"10.1016\/j.patcog.2026.114239_b6","doi-asserted-by":"crossref","first-page":"949","DOI":"10.1109\/TEVC.2022.3186667","article-title":"Feature extraction for recommendation of constrained multiobjective evolutionary algorithms","volume":"27","author":"Qiao","year":"2023","journal-title":"IEEE Trans. Evol. Comput."},{"issue":"8","key":"10.1016\/j.patcog.2026.114239_b7","doi-asserted-by":"crossref","first-page":"5276","DOI":"10.1109\/TCYB.2022.3185554","article-title":"Information-theory-based nondominated sorting ant colony optimization for multiobjective feature selection in classification","volume":"53","author":"Wang","year":"2023","journal-title":"IEEE Trans. Cybern."},{"issue":"11","key":"10.1016\/j.patcog.2026.114239_b8","doi-asserted-by":"crossref","first-page":"7326","DOI":"10.1109\/TKDE.2024.3419215","article-title":"Ze-HFS: Zentropy-based uncertainty measure for heterogeneous feature selection and knowledge discovery","volume":"36","author":"Yuan","year":"2024","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"10.1016\/j.patcog.2026.114239_b9","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":"Knowl.-Based Syst."},{"key":"10.1016\/j.patcog.2026.114239_b10","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2022.109111","article-title":"A unified low-order information-theoretic feature selection framework for multi-label learning","volume":"134","author":"Gao","year":"2023","journal-title":"Pattern Recognit."},{"issue":"11","key":"10.1016\/j.patcog.2026.114239_b11","doi-asserted-by":"crossref","first-page":"6124","DOI":"10.1109\/TKDE.2024.3397878","article-title":"Exploring feature selection with limited labels: A comprehensive survey of semi-supervised and unsupervised approaches","volume":"36","author":"Li","year":"2024","journal-title":"IEEE Trans. Knowl. Data Eng."},{"issue":"4","key":"10.1016\/j.patcog.2026.114239_b12","doi-asserted-by":"crossref","first-page":"4587","DOI":"10.1109\/TPAMI.2025.3647921","article-title":"Robust semi-supervised feature selection with multi-granularity zentropy modeling","volume":"48","author":"Yuan","year":"2025","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.patcog.2026.114239_b13","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2020.107742","article-title":"Joint adaptive manifold and embedding learning for unsupervised feature selection","volume":"112","author":"Wu","year":"2021","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.patcog.2026.114239_b14","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2025.113455","article-title":"Diversity and consistency graph learning guided multi-view unsupervised feature selection","volume":"317","author":"Xu","year":"2025","journal-title":"Knowl.-Based Syst."},{"key":"10.1016\/j.patcog.2026.114239_b15","article-title":"An overlap-extended fuzzy rough self-information measure for feature selection and imbalanced data classification","volume":"523","author":"Pan","year":"2025","journal-title":"Fuzzy Sets and Systems"},{"key":"10.1016\/j.patcog.2026.114239_b16","doi-asserted-by":"crossref","unstructured":"C. Zhang, X. Liang, P. Zhou, Z. Ling, Y. Zhang, X. Wu, W. Sheng, B. Jiang, Scalable multi-view unsupervised feature selection with structure learning and fusion, in: Proceedings of the 32nd ACM International Conference on Multimedia, 2024, pp. 5479\u20135488.","DOI":"10.1145\/3664647.3681223"},{"key":"10.1016\/j.patcog.2026.114239_b17","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":"Inform. Sci."},{"key":"10.1016\/j.patcog.2026.114239_b18","doi-asserted-by":"crossref","unstructured":"R. Hu, J. Gan, M. Zhan, L. Li, M. Wei, Unsupervised kernel-based multi-view feature selection with robust self-representation and binary hashing, in: Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 39, 2025, pp. 17287\u201317294.","DOI":"10.1609\/aaai.v39i16.33900"},{"key":"10.1016\/j.patcog.2026.114239_b19","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2025.113043","article-title":"Graph\u2013regularized consensus learning and diversity representation for unsupervised multi-view feature selection","volume":"311","author":"Xu","year":"2025","journal-title":"Knowl.-Based Syst."},{"key":"10.1016\/j.patcog.2026.114239_b20","doi-asserted-by":"crossref","unstructured":"X. Dong, L. Zhu, X. Song, J. Li, Z. Cheng, Adaptive collaborative similarity learning for unsupervised multi-view feature selection, in: Proceedings of the 27th International Joint Conference on Artificial Intelligence, 2018, pp. 2064\u20132070.","DOI":"10.24963\/ijcai.2018\/285"},{"key":"10.1016\/j.patcog.2026.114239_b21","doi-asserted-by":"crossref","first-page":"5471","DOI":"10.1109\/TNSE.2025.3649358","article-title":"MG-WEP: Multi-granularity workload ensemble and variational inference for multivariate computing power prediction","volume":"13","author":"Liu","year":"2025","journal-title":"IEEE Trans. Netw. Sci. Eng."},{"key":"10.1016\/j.patcog.2026.114239_b22","first-page":"1","article-title":"Ensemble workload prediction with fluctuation division control in the computing power network","author":"Liu","year":"2026","journal-title":"IEEE Trans. Cloud Comput."},{"key":"10.1016\/j.patcog.2026.114239_b23","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1016\/j.neucom.2022.02.005","article-title":"Multi-view unsupervised feature selection with tensor low-rank minimization","volume":"487","author":"Yuan","year":"2022","journal-title":"Neurocomputing"},{"key":"10.1016\/j.patcog.2026.114239_b24","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2024.112902","article-title":"Low-rank tensor based smooth representation learning for multi-view unsupervised feature selection","volume":"309","author":"Wang","year":"2025","journal-title":"Knowl.-Based Syst."},{"key":"10.1016\/j.patcog.2026.114239_b25","article-title":"Laplacian score for feature selection","volume":"18","author":"He","year":"2005","journal-title":"Adv. Neural Inf. Process. Syst."},{"issue":"3","key":"10.1016\/j.patcog.2026.114239_b26","first-page":"1747","article-title":"Wrapper framework for test-cost-sensitive feature selection","volume":"51","author":"Jiang","year":"2021","journal-title":"IEEE Trans. Syst. Man Cybern.: Syst."},{"key":"10.1016\/j.patcog.2026.114239_b27","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1016\/j.neunet.2019.04.015","article-title":"Unsupervised feature selection via latent representation learning and manifold regularization","volume":"117","author":"Tang","year":"2019","journal-title":"Neural Netw."},{"key":"10.1016\/j.patcog.2026.114239_b28","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2021.107156","article-title":"Adaptive graph-based generalized regression model for unsupervised feature selection","volume":"227","author":"Huang","year":"2021","journal-title":"Knowl.-Based Syst."},{"issue":"5","key":"10.1016\/j.patcog.2026.114239_b29","doi-asserted-by":"crossref","DOI":"10.1007\/s11432-022-3579-1","article-title":"Unsupervised feature selection via multiple graph fusion and feature weight learning","volume":"66","author":"Tang","year":"2023","journal-title":"Sci. China Inf. Sci."},{"key":"10.1016\/j.patcog.2026.114239_b30","doi-asserted-by":"crossref","unstructured":"Z. Li, Y. Yang, J. Liu, X. Zhou, H. Lu, Unsupervised feature selection using nonnegative spectral analysis, in: Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 26, 2012, pp. 1026\u20131032.","DOI":"10.1609\/aaai.v26i1.8289"},{"key":"10.1016\/j.patcog.2026.114239_b31","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2022.119468","article-title":"Soft-label guided non-negative matrix factorization for unsupervised feature selection","volume":"216","author":"Zhou","year":"2023","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.patcog.2026.114239_b32","doi-asserted-by":"crossref","first-page":"7407","DOI":"10.1109\/TIP.2025.3620667","article-title":"Bi-sparse unsupervised feature selection","volume":"34","author":"Xiu","year":"2025","journal-title":"IEEE Trans. Image Process."},{"issue":"1","key":"10.1016\/j.patcog.2026.114239_b33","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1109\/TETCI.2023.3306233","article-title":"Joint multi-view unsupervised feature selection and graph learning","volume":"8","author":"Fang","year":"2024","journal-title":"IEEE Trans. Emerg. Top. Comput. Intell."},{"key":"10.1016\/j.patcog.2026.114239_b34","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 Trans. Image Process."},{"key":"10.1016\/j.patcog.2026.114239_b35","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2023.121893","article-title":"Structure learning with consensus label information for multi-view unsupervised feature selection","volume":"238","author":"Cao","year":"2024","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.patcog.2026.114239_b36","doi-asserted-by":"crossref","DOI":"10.1016\/j.neucom.2023.127119","article-title":"Consistency\u2013exclusivity guided unsupervised multi-view feature selection","volume":"569","author":"Zhou","year":"2024","journal-title":"Neurocomputing"},{"key":"10.1016\/j.patcog.2026.114239_b37","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2025.111874","article-title":"Multiview feature selection combining latent space and similarity structure learning","volume":"169","author":"Li","year":"2026","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.patcog.2026.114239_b38","doi-asserted-by":"crossref","DOI":"10.1016\/j.neunet.2025.108478","article-title":"Robust structure-preservation tensorized representation for multi-view unsupervised feature selection","volume":"197","author":"Wang","year":"2026","journal-title":"Neural Netw."},{"issue":"10","key":"10.1016\/j.patcog.2026.114239_b39","doi-asserted-by":"crossref","first-page":"10681","DOI":"10.1109\/TKDE.2023.3266595","article-title":"C2IMUFS: Complementary and consensus learning-based incomplete multi-view unsupervised feature selection","volume":"35","author":"Huang","year":"2023","journal-title":"IEEE Trans. Knowl. Data Eng."},{"issue":"3","key":"10.1016\/j.patcog.2026.114239_b40","doi-asserted-by":"crossref","first-page":"1493","DOI":"10.1109\/TCYB.2019.2943691","article-title":"Scaled simplex representation for subspace clustering","volume":"51","author":"Xu","year":"2021","journal-title":"IEEE Trans. Cybern."},{"key":"10.1016\/j.patcog.2026.114239_b41","doi-asserted-by":"crossref","first-page":"6621","DOI":"10.1109\/TMM.2024.3355649","article-title":"Tensorized scaled simplex representation for multi-view clustering","volume":"26","author":"Cai","year":"2024","journal-title":"IEEE Trans. Multimed."},{"issue":"5","key":"10.1016\/j.patcog.2026.114239_b42","doi-asserted-by":"crossref","first-page":"5076","DOI":"10.1109\/TKDE.2022.3151861","article-title":"Low-rank tensor based proximity learning for multi-view clustering","volume":"35","author":"Chen","year":"2023","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"10.1016\/j.patcog.2026.114239_b43","doi-asserted-by":"crossref","DOI":"10.1016\/j.ins.2024.121532","article-title":"Enhanced tensor based embedding anchor learning for multi-view clustering","volume":"690","author":"Yang","year":"2025","journal-title":"Inform. Sci."},{"key":"10.1016\/j.patcog.2026.114239_b44","doi-asserted-by":"crossref","unstructured":"L. Du, Y.D. Shen, Unsupervised feature selection with adaptive structure learning, in: Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015, pp. 209\u2013218.","DOI":"10.1145\/2783258.2783345"},{"key":"10.1016\/j.patcog.2026.114239_b45","series-title":"2017 IEEE International Conference on Image Processing","first-page":"2398","article-title":"Unsupervised feature selection by manifold regularized self-representation","author":"Liang","year":"2017"},{"key":"10.1016\/j.patcog.2026.114239_b46","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1016\/j.neunet.2018.08.007","article-title":"Low-rank representation with adaptive graph regularization","volume":"108","author":"Wen","year":"2018","journal-title":"Neural Netw."},{"issue":"11","key":"10.1016\/j.patcog.2026.114239_b47","doi-asserted-by":"crossref","first-page":"1157","DOI":"10.1007\/s11263-018-1086-2","article-title":"On unifying multi-view self-representations for clustering by tensor multi-rank minimization","volume":"126","author":"Xie","year":"2018","journal-title":"Int. J. Comput. Vis."},{"issue":"5","key":"10.1016\/j.patcog.2026.114239_b48","doi-asserted-by":"crossref","first-page":"2355","DOI":"10.1109\/TCYB.2025.3546658","article-title":"Unsupervised feature selection for high-order embedding learning and sparse learning","volume":"55","author":"Hu","year":"2025","journal-title":"IEEE Trans. Cybern."},{"issue":"7","key":"10.1016\/j.patcog.2026.114239_b49","doi-asserted-by":"crossref","first-page":"12799","DOI":"10.1109\/TNNLS.2024.3482440","article-title":"Partition-level tensor learning-based multiview unsupervised feature selection","volume":"36","author":"Cao","year":"2025","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"10.1016\/j.patcog.2026.114239_b50","doi-asserted-by":"crossref","DOI":"10.1016\/j.ins.2024.120178","article-title":"Multi-view unsupervised feature selection with consensus partition and diverse graph","volume":"661","author":"Cao","year":"2024","journal-title":"Inform. Sci."},{"key":"10.1016\/j.patcog.2026.114239_b51","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2025.110041","article-title":"Unsupervised multi-view feature selection based on weighted low-rank tensor learning and its application in multi-omics datasets","volume":"143","author":"Wang","year":"2025","journal-title":"Eng. Appl. Artif. Intell."},{"issue":"Nov","key":"10.1016\/j.patcog.2026.114239_b52","first-page":"2579","article-title":"Visualizing data using t-SNE","volume":"9","author":"Maaten","year":"2008","journal-title":"J. Mach. Learn. Res."}],"container-title":["Pattern Recognition"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0031320326012045?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0031320326012045?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,8,7]],"date-time":"2026-08-07T08:20:51Z","timestamp":1786090851000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0031320326012045"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,12]]},"references-count":52,"alternative-id":["S0031320326012045"],"URL":"https:\/\/doi.org\/10.1016\/j.patcog.2026.114239","relation":{},"ISSN":["0031-3203"],"issn-type":[{"value":"0031-3203","type":"print"}],"subject":[],"published":{"date-parts":[[2026,12]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Tensorized synergistic representation for multi-view unsupervised feature selection","name":"articletitle","label":"Article Title"},{"value":"Pattern Recognition","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.patcog.2026.114239","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":"114239"}}