{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,31]],"date-time":"2025-12-31T00:44:44Z","timestamp":1767141884089,"version":"build-2238731810"},"reference-count":25,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2023,1,2]],"date-time":"2023-01-02T00:00:00Z","timestamp":1672617600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,2]],"date-time":"2023-01-02T00:00:00Z","timestamp":1672617600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"Special Foundation of Beijing Information Science & Technology University","award":["2022XJJ34"],"award-info":[{"award-number":["2022XJJ34"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Adv Data Anal Classif"],"published-print":{"date-parts":[[2023,12]]},"DOI":"10.1007\/s11634-022-00531-5","type":"journal-article","created":{"date-parts":[[2023,1,2]],"date-time":"2023-01-02T14:05:06Z","timestamp":1672668306000},"page":"1037-1056","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Sparse correspondence analysis for large contingency tables"],"prefix":"10.1007","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8591-7712","authenticated-orcid":false,"given":"Ruiping","family":"Liu","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6109-9935","authenticated-orcid":false,"given":"Ndeye","family":"Niang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3406-5887","authenticated-orcid":false,"given":"Gilbert","family":"Saporta","sequence":"additional","affiliation":[]},{"given":"Huiwen","family":"Wang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,1,2]]},"reference":[{"key":"531_CR1","doi-asserted-by":"publisher","first-page":"275","DOI":"10.1007\/978-1-4614-6170-8_140","volume-title":"Encyclopedia of Social Network Analysis and Mining","author":"H Abdi","year":"2014","unstructured":"Abdi H, B\u00e9ra M (2014) Correspondence Analysis. Encyclopedia of Social Network Analysis and Mining. Springer, New York, New York, NY, pp 275\u2013284"},{"issue":"4","key":"531_CR2","doi-asserted-by":"publisher","first-page":"1403","DOI":"10.1007\/s00180-015-0608-4","volume":"31","author":"K Adachi","year":"2016","unstructured":"Adachi K, Trendafilov NT (2016) Sparse principal component analysis subject to prespecified cardinality of loadings. Computational Statistics 31(4):1403\u20131427","journal-title":"Computational Statistics"},{"key":"531_CR3","doi-asserted-by":"publisher","DOI":"10.1201\/9781315212661","volume-title":"Textual data science with R","author":"M B\u00e9cue-Bertaut","year":"2019","unstructured":"B\u00e9cue-Bertaut M (2019) Textual data science with R. CRC Press"},{"key":"531_CR4","doi-asserted-by":"publisher","DOI":"10.1002\/9781118762875","volume-title":"Correspondence analysis: Theory, practice and new strategies","author":"EJ Beh","year":"2014","unstructured":"Beh EJ, Lombardo R (2014) Correspondence analysis: Theory, practice and new strategies. John Wiley & Sons"},{"key":"531_CR5","unstructured":"Bernard A, Guinot C, Saporta G (2012) Sparse principal component analysis for multiblock data and its extension to sparse multiple correspondence analysis. In: Colubi A et al (eds) Proceedings of the 20th international conference on computational statistics (COMPSTAT 2012). International Association for Statistical Computing, pp 99\u2013106"},{"issue":"4","key":"531_CR6","first-page":"511","volume":"4","author":"L D\u2019Ambra","year":"1992","unstructured":"D\u2019Ambra L, Lauro NC (1992) Non symmetrical exploratory data analysis. Statistica Applicata 4(4):511\u2013529","journal-title":"Statistica Applicata"},{"key":"531_CR7","doi-asserted-by":"publisher","DOI":"10.1002\/9781118649480","volume-title":"Co-clustering: models, algorithms and applications","author":"G Govaert","year":"2013","unstructured":"Govaert G, Nadif M (2013) Co-clustering: models, algorithms and applications. John Wiley & Sons"},{"issue":"5","key":"531_CR8","doi-asserted-by":"publisher","first-page":"613","DOI":"10.1002\/wics.114","volume":"2","author":"MJ Greenacre","year":"2010","unstructured":"Greenacre MJ (2010) Correspondence analysis. Wiley Interdisciplinary Reviews: Computational Statistics 2(5):613\u2013619","journal-title":"Wiley Interdisciplinary Reviews: Computational Statistics"},{"issue":"4","key":"531_CR9","doi-asserted-by":"publisher","first-page":"893","DOI":"10.1007\/s11336-021-09773-2","volume":"86","author":"R Guerra-Urzola","year":"2021","unstructured":"Guerra-Urzola R, Van Deun K, Vera JC, Sijtsma K (2021) A Guide for Sparse PCA: Model Comparison and Applications. Psychometrika 86(4):893\u2013919","journal-title":"Psychometrika"},{"issue":"3","key":"531_CR10","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0211463","volume":"14","author":"V Guillemot","year":"2019","unstructured":"Guillemot V, Beaton D, Gloaguen A, L\u00f6fstedt T, Levine B, Raymond N, Tenenhaus A, Abdi H (2019) A constrained singular value decomposition method that integrates sparsity and orthogonality. PloS one 14(3):e0211463","journal-title":"PloS one"},{"issue":"3","key":"531_CR11","doi-asserted-by":"publisher","first-page":"531","DOI":"10.1198\/1061860032148","volume":"12","author":"IT Jolliffe","year":"2003","unstructured":"Jolliffe IT, Trendafilov NT, Uddin M (2003) A modified principal component technique based on the LASSO. Journal of Computational and Graphical Statistics 12(3):531\u2013547","journal-title":"Journal of Computational and Graphical Statistics"},{"key":"531_CR12","doi-asserted-by":"crossref","unstructured":"Lebart L, Pincemin B, Poudat C (2019) Analyse des donn\u00e9es textuelles. Presses de l\u2019Universit\u00e9 du Qu\u00e9bec","DOI":"10.2307\/j.ctvq4bxws"},{"key":"531_CR13","doi-asserted-by":"crossref","unstructured":"Lebart L, Salem A, Berry L (1997) Exploring textual data. Springer Science & Business Media","DOI":"10.1007\/978-94-017-1525-6"},{"key":"531_CR14","first-page":"31","volume-title":"Visualization and Verbalization of Data","author":"L Lebart","year":"2014","unstructured":"Lebart L, Saporta G (2014) Historical elements of correspondence analysis and multiple correspondence analysis. In: Blasius J, Greenacre MJ (eds) Visualization and Verbalization of Data. Chapman and Hall, London, pp 31\u201344"},{"key":"531_CR15","first-page":"1017","volume-title":"Advances in Neural Information Processing Systems","author":"L Mackey","year":"2009","unstructured":"Mackey L (2009) Deflation Methods for Sparse PCA. In: Koller D, Schuurmans D, Bengio Y, Bottou L (eds) Advances in Neural Information Processing Systems, vol 21. Curran Associates Inc, pp 1017\u20131024"},{"key":"531_CR16","doi-asserted-by":"publisher","first-page":"47","DOI":"10.1007\/978-981-10-0159-8_5","volume-title":"Nonlinear Principal Component Analysis and Its Applications","author":"Y Mori","year":"2016","unstructured":"Mori Y, Kuroda M, Makino N (2016) Sparse Multiple Correspondence Analysis. In: Mori Y, Kuroda M, Makino N (eds) Nonlinear Principal Component Analysis and Its Applications. Springer-Verlag, pp 47\u201356"},{"issue":"6","key":"531_CR17","doi-asserted-by":"publisher","first-page":"57","DOI":"10.14257\/ijdta.2015.8.6.06","volume":"8","author":"S Ning-min","year":"2015","unstructured":"Ning-min S, Jing L (2015) A literature survey on high-dimensional sparse principal component analysis. International Journal of Database Theory and Application 8(6):57\u201374","journal-title":"International Journal of Database Theory and Application"},{"issue":"8","key":"531_CR18","doi-asserted-by":"publisher","first-page":"1645","DOI":"10.1002\/asi.23283","volume":"66","author":"J Savoy","year":"2015","unstructured":"Savoy J (2015) Text clustering: An application with the State of the Union addresses. Journal of the Association for Information Science and Technology 66(8):1645\u20131654","journal-title":"Journal of the Association for Information Science and Technology"},{"key":"531_CR19","doi-asserted-by":"publisher","first-page":"317","DOI":"10.1016\/j.jmva.2012.10.007","volume":"115","author":"D Shen","year":"2013","unstructured":"Shen D, Shen H, Marron JS (2013) Consistency of sparse PCA in high dimension, low sample size contexts. Journal of Multivariate Analysis 115:317\u2013333","journal-title":"Journal of Multivariate Analysis"},{"issue":"6","key":"531_CR20","doi-asserted-by":"publisher","first-page":"1015","DOI":"10.1016\/j.jmva.2007.06.007","volume":"99","author":"H Shen","year":"2008","unstructured":"Shen H, Huang JZ (2008) Sparse principal component analysis via regularized low rank matrix approximation. Journal of Multivariate Analysis 99(6):1015\u20131034","journal-title":"Journal of Multivariate Analysis"},{"issue":"3","key":"531_CR21","doi-asserted-by":"publisher","first-page":"431","DOI":"10.1007\/s00180-013-0434-5","volume":"29","author":"NT Trendafilov","year":"2014","unstructured":"Trendafilov NT (2014) From simple structure to sparse components: a review. Computational Statistics 29(3):431\u2013454","journal-title":"Computational Statistics"},{"issue":"3","key":"531_CR22","doi-asserted-by":"publisher","first-page":"778","DOI":"10.1007\/s11336-017-9575-8","volume":"82","author":"NT Trendafilov","year":"2017","unstructured":"Trendafilov NT, Fontanella S, Adachi K (2017) Sparse exploratory factor analysis. Psychometrika 82(3):778\u2013794","journal-title":"Psychometrika"},{"issue":"5","key":"531_CR23","doi-asserted-by":"publisher","first-page":"834","DOI":"10.1002\/bimj.201400226","volume":"57","author":"I Wilms","year":"2015","unstructured":"Wilms I, Croux C (2015) Sparse canonical correlation analysis from a predictive point of view. Biometrical Journal 57(5):834\u2013851","journal-title":"Biometrical Journal"},{"issue":"3","key":"531_CR24","doi-asserted-by":"publisher","first-page":"515","DOI":"10.1093\/biostatistics\/kxp008","volume":"10","author":"DM Witten","year":"2009","unstructured":"Witten DM, Tibshirani R, Hastie T (2009) A penalized matrix decomposition, with applications to sparse principal components and canonical correlation analysis. Biostatistics 10(3):515\u2013534","journal-title":"Biostatistics"},{"issue":"2","key":"531_CR25","doi-asserted-by":"publisher","first-page":"265","DOI":"10.1198\/106186006X113430","volume":"15","author":"H Zou","year":"2006","unstructured":"Zou H, Hastie T, Tibshirani R (2006) Sparse principal component analysis. Journal of Computational and Graphical Statistics 15(2):265\u2013286","journal-title":"Journal of Computational and Graphical Statistics"}],"updated-by":[{"DOI":"10.1007\/s11634-025-00648-3","type":"correction","label":"Correction","source":"publisher","updated":{"date-parts":[[2025,6,26]],"date-time":"2025-06-26T00:00:00Z","timestamp":1750896000000}}],"container-title":["Advances in Data Analysis and Classification"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11634-022-00531-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11634-022-00531-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11634-022-00531-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,26]],"date-time":"2025-06-26T14:06:03Z","timestamp":1750946763000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11634-022-00531-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,1,2]]},"references-count":25,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2023,12]]}},"alternative-id":["531"],"URL":"https:\/\/doi.org\/10.1007\/s11634-022-00531-5","relation":{},"ISSN":["1862-5347","1862-5355"],"issn-type":[{"value":"1862-5347","type":"print"},{"value":"1862-5355","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,1,2]]},"assertion":[{"value":"22 November 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 December 2022","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 December 2022","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 January 2023","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 June 2025","order":5,"name":"change_date","label":"Change Date","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"Correction","order":6,"name":"change_type","label":"Change Type","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"A Correction to this paper has been published:","order":7,"name":"change_details","label":"Change Details","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"https:\/\/doi.org\/10.1007\/s11634-025-00648-3","URL":"https:\/\/doi.org\/10.1007\/s11634-025-00648-3","order":8,"name":"change_details","label":"Change Details","group":{"name":"ArticleHistory","label":"Article History"}}]}}