{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T21:43:11Z","timestamp":1777671791371,"version":"3.51.4"},"reference-count":66,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T00:00:00Z","timestamp":1777420800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T00:00:00Z","timestamp":1777420800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int. J. Mach. Learn. &amp; Cyber."],"published-print":{"date-parts":[[2026,6]]},"DOI":"10.1007\/s13042-026-03119-z","type":"journal-article","created":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T06:28:45Z","timestamp":1777444125000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Adaptive similarity-based non-negative matrix factorization with normalization for image clustering"],"prefix":"10.1007","volume":"17","author":[{"given":"Silvia","family":"Sifath","sequence":"first","affiliation":[]},{"given":"Md Manjur","family":"Ahmed","sequence":"additional","affiliation":[]},{"given":"Nor Ashidi","family":"Mat Isa","sequence":"additional","affiliation":[]},{"given":"Rahat Hossain","family":"Faisal","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2026,4,29]]},"reference":[{"key":"3119_CR1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cosrev.2021.100378","volume":"40","author":"F Anowar","year":"2021","unstructured":"Anowar F, Sadaoui S, Selim B (2021) Conceptual and empirical comparison of dimensionality reduction algorithms (pca, kpca, lda, mds, svd, lle, isomap, le, ica, t-sne). Comput Sci Rev 40:100378","journal-title":"Comput Sci Rev"},{"issue":"1","key":"3119_CR2","first-page":"20","volume":"2","author":"BMS Hasan","year":"2021","unstructured":"Hasan BMS, Abdulazeez AM (2021) A review of principal component analysis algorithm for dimensionality reduction. J Soft Comput Data Min 2(1):20\u201330","journal-title":"J Soft Comput Data Min"},{"issue":"6755","key":"3119_CR3","doi-asserted-by":"publisher","first-page":"788","DOI":"10.1038\/44565","volume":"401","author":"DD Lee","year":"1999","unstructured":"Lee DD, Seung HS (1999) Learning the parts of objects by non-negative matrix factorization. Nature 401(6755):788\u2013791","journal-title":"Nature"},{"key":"3119_CR4","doi-asserted-by":"publisher","first-page":"123776","DOI":"10.1109\/ACCESS.2019.2938393","volume":"7","author":"J Wang","year":"2019","unstructured":"Wang J, Fan Y, Feng L, Ye Z, Zhang H (2019) Research hotspot prediction and regular evolutionary pattern identification based on nsfc grants using nmf and semantic retrieval. IEEE Access 7:123776\u2013123787","journal-title":"IEEE Access"},{"key":"3119_CR5","doi-asserted-by":"crossref","unstructured":"Li SZ, Hou XW, Zhang HJ, Cheng QS (2001) Learning spatially localized, parts-based representation. In: Proc. 2001 IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit. (CVPR 2001), vol. 1, p. IEEE","DOI":"10.1109\/CVPR.2001.990477"},{"key":"3119_CR6","doi-asserted-by":"crossref","unstructured":"Karimpour M, Rezghi M (2025) A double sided deep nonnegative matrix factorization network for feature extraction of two dimensional data. Expert Syst. Appl., 126652","DOI":"10.1016\/j.eswa.2025.126652"},{"key":"3119_CR7","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2021.107814","volume":"112","author":"R Hedjam","year":"2021","unstructured":"Hedjam R, Abdesselam A, Melgani F (2021) Nmf with feature relationship preservation penalty term for clustering problems. Pattern Recognit 112:107814","journal-title":"Pattern Recognit"},{"issue":"5","key":"3119_CR8","doi-asserted-by":"publisher","first-page":"515","DOI":"10.1049\/iet-spr.2016.0341","volume":"11","author":"M You","year":"2017","unstructured":"You M, Wang H, Liu Z, Chen C, Liu J, Xu XH, Qiu ZM (2017) Novel feature extraction method for cough detection using nmf. IET Signal Process 11(5):515\u2013520","journal-title":"IET Signal Process"},{"key":"3119_CR9","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcmds.2024.100104","volume":"13","author":"C Castiello","year":"2024","unstructured":"Castiello C, Del Buono N, Esposito F (2024) Novel color space representation extracted by nmf to segment a color image. J Comput Math Data Sci 13:100104","journal-title":"J Comput Math Data Sci"},{"key":"3119_CR10","doi-asserted-by":"crossref","unstructured":"Lin Y, Hu H, Li B, Zhao S, Jing H (2025) Representation auto-fused nmf based hierarchical clustering. Expert Syst. Appl., 127560","DOI":"10.1016\/j.eswa.2025.127560"},{"key":"3119_CR11","doi-asserted-by":"crossref","unstructured":"Lin Y, Hu H, Li B, Zhao S, Jing H (2025) Representation auto-fused nmf based hierarchical clustering. Expert Systems with Applications, 127560","DOI":"10.1016\/j.eswa.2025.127560"},{"issue":"2","key":"3119_CR12","doi-asserted-by":"publisher","first-page":"373","DOI":"10.1016\/j.ipm.2004.11.005","volume":"42","author":"F Shahnaz","year":"2006","unstructured":"Shahnaz F, Berry MW, Pauca VP, Plemmons RJ (2006) Document clustering using nonnegative matrix factorization. Inf Process Manag 42(2):373\u2013386","journal-title":"Inf Process Manag"},{"key":"3119_CR13","doi-asserted-by":"crossref","unstructured":"Cho H, Dhillon I.S, Guan Y, Sra S (2004) Minimum sum-squared residue co-clustering of gene expression data. In: Proc. 2004 SIAM Int. Conf. Data Min., pp. 114\u2013125 . SIAM","DOI":"10.1137\/1.9781611972740.11"},{"issue":"3","key":"3119_CR14","doi-asserted-by":"publisher","first-page":"588","DOI":"10.1109\/TIFS.2007.902017","volume":"2","author":"I Kotsia","year":"2007","unstructured":"Kotsia I, Zafeiriou S, Pitas I (2007) A novel discriminant non-negative matrix factorization algorithm with applications to facial image characterization problems. IEEE Trans Inf Forensics Secur 2(3):588\u2013595","journal-title":"IEEE Trans Inf Forensics Secur"},{"key":"3119_CR15","unstructured":"Feng T, Li SZ, Shum HY, Zhang H (2002) Local non-negative matrix factorization as a visual representation. In: Proc. 2nd Int. Conf. Dev. Learn. (ICDL 2002), pp. 178\u2013183 . IEEE"},{"key":"3119_CR16","doi-asserted-by":"crossref","unstructured":"Liu H, Wu Z, Li X, Cai D, Huang TS (2011) Constrained nonnegative matrix factorization for image representation. IEEE Trans. Pattern Anal. Mach. Intell.34(7), 1299\u20131311","DOI":"10.1109\/TPAMI.2011.217"},{"key":"3119_CR17","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2024.110933","volume":"157","author":"X Yang","year":"2025","unstructured":"Yang X, Zhu T, Peng S, Nie F, Lin Z (2025) Semi-supervised pivotal-aware nonnegative matrix factorization with label and pairwise constraint propagation for data clustering. Pattern Recogn 157:110933","journal-title":"Pattern Recogn"},{"issue":"11","key":"3119_CR18","doi-asserted-by":"publisher","first-page":"3577","DOI":"10.1007\/s13042-022-01614-7","volume":"13","author":"Y Zhang","year":"2022","unstructured":"Zhang Y, Li X, Jia M (2022) Semi-supervised nonnegative matrix factorization with pairwise constraints for image clustering. Int J Mach Learn Cybern 13(11):3577\u20133587","journal-title":"Int J Mach Learn Cybern"},{"key":"3119_CR19","doi-asserted-by":"publisher","first-page":"84","DOI":"10.1016\/j.sigpro.2014.05.015","volume":"105","author":"Y Zhang","year":"2014","unstructured":"Zhang Y, Chen L, Jia J, Zhao Z (2014) Multi-focus image fusion based on non-negative matrix factorization and difference images. Signal Process 105:84\u201397","journal-title":"Signal Process"},{"issue":"5","key":"3119_CR20","doi-asserted-by":"publisher","first-page":"1947","DOI":"10.1109\/TNNLS.2017.2691725","volume":"29","author":"Z Li","year":"2017","unstructured":"Li Z, Tang J, He X (2017) Robust structured nonnegative matrix factorization for image representation. IEEE Trans Neural Netw Learn Syst 29(5):1947\u20131960","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"issue":"1","key":"3119_CR21","doi-asserted-by":"publisher","first-page":"734","DOI":"10.2991\/ijcis.d.200527.003","volume":"13","author":"X Dai","year":"2020","unstructured":"Dai X, Zhang N, Zhang K, Xiong J (2020) Weighted nonnegative matrix factorization for image inpainting and clustering. Int J Comput Intell Syst 13(1):734\u2013743","journal-title":"Int J Comput Intell Syst"},{"key":"3119_CR22","doi-asserted-by":"publisher","DOI":"10.1016\/j.image.2021.116589","volume":"102","author":"H Li","year":"2022","unstructured":"Li H, Gao Y, Liu J, Zhang J, Li C (2022) Semi-supervised graph regularized nonnegative matrix factorization with local coordinate for image representation. Signal Process Image Commun 102:116589","journal-title":"Signal Process Image Commun"},{"key":"3119_CR23","doi-asserted-by":"publisher","first-page":"209","DOI":"10.1016\/j.neucom.2014.01.043","volume":"138","author":"K Zeng","year":"2014","unstructured":"Zeng K, Yu J, Li C, You J, Jin T (2014) Image clustering by hyper-graph regularized non-negative matrix factorization. Neurocomputing 138:209\u2013217","journal-title":"Neurocomputing"},{"issue":"3","key":"3119_CR24","doi-asserted-by":"publisher","first-page":"3227","DOI":"10.1007\/s10489-021-02522-z","volume":"52","author":"S Li","year":"2022","unstructured":"Li S, Li W, Hu J, Li Y (2022a) Semi-supervised bi-orthogonal constraints dual-graph regularized nmf for subspace clustering. Appl Intell 52(3):3227\u20133248","journal-title":"Appl Intell"},{"key":"3119_CR25","doi-asserted-by":"publisher","first-page":"39926","DOI":"10.1109\/ACCESS.2021.3064631","volume":"9","author":"W Guo","year":"2021","unstructured":"Guo W (2021) Sparse dual graph-regularized deep nonnegative matrix factorization for image clustering. IEEE Access 9:39926\u201339938","journal-title":"IEEE Access"},{"key":"3119_CR26","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2024.109629","volume":"139","author":"Z Liu","year":"2025","unstructured":"Liu Z, Zhu F, Xiong H, Chen X, Pelusi D, Vasilakos AV (2025) Graph regularized discriminative nonnegative matrix factorization. Eng Appl Artif Intell 139:109629","journal-title":"Eng Appl Artif Intell"},{"key":"3119_CR27","doi-asserted-by":"publisher","first-page":"108","DOI":"10.1016\/j.neucom.2019.12.054","volume":"390","author":"J Li","year":"2020","unstructured":"Li J, Zhou G, Qiu Y, Wang Y, Zhang Y, Xie S (2020) Deep graph regularized non-negative matrix factorization for multi-view clustering. Neurocomputing 390:108\u2013116","journal-title":"Neurocomputing"},{"key":"3119_CR28","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2023.109963","volume":"145","author":"H Zuo","year":"2024","unstructured":"Zuo H, Li S, Liang C, Li J (2024) Auto-adjustable hypergraph regularized non-negative matrix factorization for image clustering. Pattern Recognit 145:109963","journal-title":"Pattern Recognit"},{"key":"3119_CR29","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2022.109274","volume":"137","author":"J Yin","year":"2023","unstructured":"Yin J, Peng S, Yang Z, Chen B, Lin Z (2023) Hypergraph based semi-supervised symmetric nonnegative matrix factorization for image clustering. Pattern Recognit 137:109274","journal-title":"Pattern Recognit"},{"key":"3119_CR30","doi-asserted-by":"publisher","first-page":"5273","DOI":"10.1109\/TMM.2023.3331197","volume":"26","author":"Y Qin","year":"2023","unstructured":"Qin Y, Pu N, Wu H (2023) Edmc: efficient multi-view clustering via cluster and instance space learning. IEEE Trans Multimedia 26:5273\u20135283","journal-title":"IEEE Trans Multimedia"},{"key":"3119_CR31","doi-asserted-by":"crossref","unstructured":"Qin Y, Qin C, Zhang X, Feng G (2024) Dual consensus anchor learning for fast multi-view clustering. IEEE Transactions on Image Processing","DOI":"10.1109\/TIP.2024.3459651"},{"issue":"4","key":"3119_CR32","doi-asserted-by":"publisher","first-page":"1552","DOI":"10.1109\/TKDE.2023.3305624","volume":"36","author":"Y Qin","year":"2023","unstructured":"Qin Y, Tang Z, Wu H, Feng G (2023) Flexible tensor learning for multi-view clustering with markov chain. IEEE Trans Knowl Data Eng 36(4):1552\u20131565","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"3119_CR33","doi-asserted-by":"publisher","first-page":"34","DOI":"10.1016\/j.neucom.2018.07.049","volume":"316","author":"S Peng","year":"2018","unstructured":"Peng S, Ser W, Chen B, Sun L, Lin Z (2018) Correntropy based graph regularized concept factorization for clustering. Neurocomputing 316:34\u201348","journal-title":"Neurocomputing"},{"key":"3119_CR34","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2019.103354","volume":"88","author":"S Peng","year":"2020","unstructured":"Peng S, Ser W, Chen B, Sun L, Lin Z (2020) Robust nonnegative matrix factorization with local coordinate constraint for image clustering. Eng Appl Artif Intell 88:103354","journal-title":"Eng Appl Artif Intell"},{"issue":"11","key":"3119_CR35","doi-asserted-by":"publisher","first-page":"4027","DOI":"10.1109\/TIP.2015.2456508","volume":"24","author":"Y Wang","year":"2015","unstructured":"Wang Y, Pan C, Xiang S, Zhu F (2015) Robust hyperspectral unmixing with correntropy-based metric. IEEE Trans Image Process 24(11):4027\u20134040","journal-title":"IEEE Trans Image Process"},{"issue":"6","key":"3119_CR36","doi-asserted-by":"publisher","first-page":"1897","DOI":"10.1109\/TPAMI.2019.2962679","volume":"43","author":"Z Yang","year":"2021","unstructured":"Yang Z, Wang H, Pei J (2021) Deep non-negative matrix factorization architecture based on underlying basis images learning. IEEE Trans Pattern Anal Mach Intell 43(6):1897\u20131913","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"3119_CR37","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2025.111427","volume":"162","author":"J Li","year":"2025","unstructured":"Li J, Li C (2025) One-hot constrained symmetric nonnegative matrix factorization for image clustering. Pattern Recogn 162:111427","journal-title":"Pattern Recogn"},{"key":"3119_CR38","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2025.107340","volume":"187","author":"W Jing","year":"2025","unstructured":"Jing W, Lu L, Ou W (2025) Semi-supervised non-negative matrix factorization with structure preserving for image clustering. Neural Netw 187:107340","journal-title":"Neural Netw"},{"key":"3119_CR39","doi-asserted-by":"crossref","unstructured":"Luo M, Li S, Tao J, Vladimirovich PP (2025) Semi-supervised correntropy-based non-negative matrix factorization with hypergraph regularization. International Journal of Machine Learning and Cybernetics, 1\u201320","DOI":"10.1007\/s13042-024-02523-7"},{"key":"3119_CR40","doi-asserted-by":"crossref","unstructured":"Ren X, Yang Y (2025) Semi-supervised symmetric non-negative matrix factorization with graph quality improvement and constraints: X. ren, y. yang. Applied Intelligence55(6), 397","DOI":"10.1007\/s10489-025-06282-y"},{"key":"3119_CR41","doi-asserted-by":"crossref","unstructured":"Ren X, Yang Y (2025) Adaptive hypergraph structure regularized semi-supervised non-negative matrix factorization for image clustering. Neurocomputing, 130895","DOI":"10.1016\/j.neucom.2025.130895"},{"issue":"2","key":"3119_CR42","doi-asserted-by":"publisher","first-page":"111","DOI":"10.1002\/env.3170050203","volume":"5","author":"P Paatero","year":"1994","unstructured":"Paatero P, Tapper U (1994) Positive matrix factorization: A non-negative factor model with optimal utilization of error estimates of data values. Environmetrics 5(2):111\u2013126","journal-title":"Environmetrics"},{"key":"3119_CR43","doi-asserted-by":"crossref","unstructured":"Cai J, Guo W, Zhang Y, Fan J (2025) discdc: Unsupervised discriminative deep image clustering via confidence-driven self-labeling. Pattern Recognition, 112382","DOI":"10.1016\/j.patcog.2025.112382"},{"key":"3119_CR44","doi-asserted-by":"publisher","first-page":"7567","DOI":"10.1109\/TMM.2024.3369862","volume":"26","author":"J Cai","year":"2024","unstructured":"Cai J, Zhang Y, Wang S, Fan J, Guo W (2024) Wasserstein embedding learning for deep clustering: A generative approach. IEEE Trans Multimedia 26:7567\u20137580","journal-title":"IEEE Trans Multimedia"},{"key":"3119_CR45","doi-asserted-by":"crossref","unstructured":"Cai J, Fan J, Guo W, Wang S, Zhang Y, Zhang Z (2022) Efficient deep embedded subspace clustering. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 1\u201310","DOI":"10.1109\/CVPR52688.2022.00012"},{"key":"3119_CR46","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2021.107967","volume":"238","author":"C Xu","year":"2022","unstructured":"Xu C, Lin R, Cai J, Wang S (2022) Deep image clustering by fusing contrastive learning and neighbor relation mining. Knowl-Based Syst 238:107967","journal-title":"Knowl-Based Syst"},{"key":"3119_CR47","volume-title":"Efficient algorithms of box-constrained nonnegative matrix factorization and its applications in image clustering","author":"J Guo","year":"2024","unstructured":"Guo J, Li T, Wan Z, Li J, Xiao Y (2024) Efficient algorithms of box-constrained nonnegative matrix factorization and its applications in image clustering. Appl. Numer, Math"},{"key":"3119_CR48","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2024.121138","volume":"680","author":"W Luo","year":"2024","unstructured":"Luo W, Wu Z, Zhou N (2024) Hypergraph-based convex semi-supervised unconstraint symmetric matrix factorization for image clustering. Inf Sci 680:121138","journal-title":"Inf Sci"},{"issue":"7","key":"3119_CR49","doi-asserted-by":"publisher","first-page":"195","DOI":"10.1007\/s10462-025-11198-7","volume":"58","author":"J Terven","year":"2025","unstructured":"Terven J, Cordova-Esparza D-M, Romero-Gonz\u00e1lez J-A, Ram\u00edrez-Pedraza A, Ch\u00e1vez-Urbiola E (2025) A comprehensive survey of loss functions and metrics in deep learning. Artif Intell Rev 58(7):195","journal-title":"Artif Intell Rev"},{"key":"3119_CR50","doi-asserted-by":"publisher","first-page":"106","DOI":"10.1016\/j.ins.2021.12.098","volume":"590","author":"C Peng","year":"2022","unstructured":"Peng C, Zhang Z, Chen C, Kang Z, Cheng Q (2022) Two-dimensional semi-nonnegative matrix factorization for clustering. Inf Sci 590:106\u2013141","journal-title":"Inf Sci"},{"key":"3119_CR51","doi-asserted-by":"crossref","unstructured":"El\u00a0Morr C, Jammal M, Ali-Hassan H, El-Hallak W (2022) Data preprocessing. In: Mach. Learn. Pract. Decis. Mak.: Multidiscip. Perspect. with Appl. from Healthc., Eng. Bus. Anal., pp. 117\u2013163. Springer, ???","DOI":"10.1007\/978-3-031-16990-8_4"},{"key":"3119_CR52","doi-asserted-by":"crossref","unstructured":"Wang J, Zhou F, Wen S, Liu X, Lin Y (2017) Deep metric learning with angular loss. In: Proc. IEEE Int. Conf. Comput. Vis., pp. 2593\u20132601","DOI":"10.1109\/ICCV.2017.283"},{"issue":"3","key":"3119_CR53","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/1970392.1970395","volume":"58","author":"EJ Cand\u00e8s","year":"2011","unstructured":"Cand\u00e8s EJ, Li X, Ma Y, Wright J (2011) Robust principal component analysis? J ACM (JACM) 58(3):1\u201337","journal-title":"J ACM (JACM)"},{"key":"3119_CR54","doi-asserted-by":"crossref","unstructured":"Yang J, Zhang D, Frangi AF, Yang Jy (2004) Two-dimensional pca: a new approach to appearance-based face representation and recognition. IEEE Trans. Pattern Anal. Mach. Intell.26(1), 131\u2013137","DOI":"10.1109\/TPAMI.2004.1261097"},{"issue":"8","key":"3119_CR55","first-page":"1548","volume":"33","author":"D Cai","year":"2010","unstructured":"Cai D, He X, Han J, Huang TS (2010) Graph regularized nonnegative matrix factorization for data representation. IEEE Trans Pattern Anal Mach Intell 33(8):1548\u20131560","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"3","key":"3119_CR56","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/2601434","volume":"8","author":"J Huang","year":"2014","unstructured":"Huang J, Nie F, Huang H, Ding C (2014) Robust manifold nonnegative matrix factorization. ACM Trans Knowl Discov Data (TKDD) 8(3):1\u201321","journal-title":"ACM Trans Knowl Discov Data (TKDD)"},{"issue":"1","key":"3119_CR57","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1109\/TPAMI.2008.277","volume":"32","author":"CH Ding","year":"2008","unstructured":"Ding CH, Li T, Jordan MI (2008) Convex and semi-nonnegative matrix factorizations. IEEE Trans Pattern Anal Mach Intell 32(1):45\u201355","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"3119_CR58","doi-asserted-by":"publisher","first-page":"5161","DOI":"10.1109\/ACCESS.2016.2605704","volume":"4","author":"Z Yang","year":"2016","unstructured":"Yang Z, Zhang Y, Yan W, Xiang Y, Xie S (2016) A fast non-smooth nonnegative matrix factorization for learning sparse representation. IEEE Access 4:5161\u20135168","journal-title":"IEEE Access"},{"key":"3119_CR59","doi-asserted-by":"crossref","unstructured":"Kasai H ( 2018) Stochastic variance reduced multiplicative update for nonnegative matrix factorization. In: Proc. 2018 IEEE Int. Conf. Acoust., Speech Signal Process. (ICASSP), pp. 6338\u20136342 . IEEE","DOI":"10.1109\/ICASSP.2018.8461325"},{"issue":"1","key":"3119_CR60","doi-asserted-by":"publisher","first-page":"2","DOI":"10.1109\/TKDE.2016.2606098","volume":"29","author":"K Allab","year":"2016","unstructured":"Allab K, Labiod L, Nadif M (2016) A semi-nmf-pca unified framework for data clustering. IEEE Trans Knowl Data Eng 29(1):2\u201316","journal-title":"IEEE Trans Knowl Data Eng"},{"issue":"13","key":"3119_CR61","doi-asserted-by":"publisher","first-page":"2821","DOI":"10.3390\/math11132821","volume":"11","author":"Y Xu","year":"2023","unstructured":"Xu Y, Lu L, Liu Q, Chen Z (2023) Hypergraph-regularized l p smooth nonnegative matrix factorization for data representation. Mathematics 11(13):2821","journal-title":"Mathematics"},{"key":"3119_CR62","doi-asserted-by":"crossref","unstructured":"Jiao CN, Liu JX, Gao YL, Kong XZ, Zheng CH, Yu X ( 2021) Sparse hyper-graph non-negative matrix factorization by maximizing correntropy. In: Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 418\u2013423. IEEE, Houston, TX, USA","DOI":"10.1109\/BIBM52615.2021.9669357"},{"issue":"3","key":"3119_CR63","doi-asserted-by":"publisher","first-page":"3227","DOI":"10.1007\/s10489-021-02522-z","volume":"52","author":"S Li","year":"2022","unstructured":"Li S, Li W, Hu J, Li Y (2022b) Semi-supervised bi-orthogonal constraints dual-graph regularized nmf for subspace clustering. Appl Intell 52(3):3227\u20133248","journal-title":"Appl Intell"},{"key":"3119_CR64","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2023.110465","volume":"268","author":"G Lu","year":"2023","unstructured":"Lu G, Leng C, Li B, Jiao L, Basu A (2023) Robust dual-graph discriminative nmf for data classification. Knowl-Based Syst 268:110465","journal-title":"Knowl-Based Syst"},{"issue":"1","key":"3119_CR65","doi-asserted-by":"publisher","first-page":"214","DOI":"10.26599\/BDMA.2024.9020055","volume":"8","author":"J Yu","year":"2024","unstructured":"Yu J, Che H, Leung M-F, Liu C, Wu W, Yan Z (2024) Robust non-negative matrix tri-factorization with dual hyper-graph regularization. Big Data Mining and Analytics 8(1):214\u2013232","journal-title":"Big Data Mining and Analytics"},{"issue":"7","key":"3119_CR66","doi-asserted-by":"publisher","first-page":"1154","DOI":"10.3390\/sym17071154","volume":"17","author":"W Li","year":"2025","unstructured":"Li W, Zhao J, Chen Y (2025) Orthogonal-constrained graph non-negative matrix factorization for clustering. Symmetry 17(7):1154","journal-title":"Symmetry"}],"container-title":["International Journal of Machine Learning and Cybernetics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-026-03119-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s13042-026-03119-z","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-026-03119-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T08:02:13Z","timestamp":1777449733000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s13042-026-03119-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4,29]]},"references-count":66,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2026,6]]}},"alternative-id":["3119"],"URL":"https:\/\/doi.org\/10.1007\/s13042-026-03119-z","relation":{},"ISSN":["1868-8071","1868-808X"],"issn-type":[{"value":"1868-8071","type":"print"},{"value":"1868-808X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,4,29]]},"assertion":[{"value":"1 September 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 April 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 April 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"285"}}