{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T19:59:11Z","timestamp":1760385551118,"version":"3.37.3"},"reference-count":28,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2017,6,3]],"date-time":"2017-06-03T00:00:00Z","timestamp":1496448000000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"name":"Practice Innovation Training Program Projects for Jiangsu College Students","award":["Grant 201610298066Z"],"award-info":[{"award-number":["Grant 201610298066Z"]}]},{"name":"National Foundation for Distinguished Young Scientists","award":["Grant 31125008"],"award-info":[{"award-number":["Grant 31125008"]}]},{"name":"Scientific Research Foundation for Advanced Talents and Returned Overseas Schol-ars of Nanjing Forestry University"},{"name":"Natural Science Foundation of the Jiangsu Higher Education Institutions","award":["Grant 14KJB520018"],"award-info":[{"award-number":["Grant 14KJB520018"]}]},{"DOI":"10.13039\/501100001809","name":"National Science Foundation of China","doi-asserted-by":"crossref","award":["Grant 61101197","Grant 61401214"],"award-info":[{"award-number":["Grant 61101197","Grant 61401214"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Top-notch Academic Programs Project of Jiangsu Higher Education Institutions","award":["No. PPZY2015A062"],"award-info":[{"award-number":["No. PPZY2015A062"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Process Lett"],"published-print":{"date-parts":[[2018,2]]},"DOI":"10.1007\/s11063-017-9624-4","type":"journal-article","created":{"date-parts":[[2017,6,3]],"date-time":"2017-06-03T07:32:53Z","timestamp":1496475173000},"page":"21-38","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["A Feature Selection Method for Projection Twin Support Vector Machine"],"prefix":"10.1007","volume":"47","author":[{"given":"A. Rui","family":"Yan","sequence":"first","affiliation":[]},{"given":"B. Qiaolin","family":"Ye","sequence":"additional","affiliation":[]},{"given":"C. Liyan","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"D. Ning","family":"Ye","sequence":"additional","affiliation":[]},{"given":"E. Xiangbo","family":"Shu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2017,6,3]]},"reference":[{"key":"9624_CR1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1080\/10556780008805771","volume":"13","author":"S Bradley","year":"2000","unstructured":"Bradley S, Mangasarian OL (2000) Massive data discrimination via linear support vector machines. Optim Methods Softw 13:1\u201310","journal-title":"Optim Methods Softw"},{"issue":"3","key":"9624_CR2","doi-asserted-by":"crossref","first-page":"239","DOI":"10.1023\/A:1026097128675","volume":"17","author":"HM Je","year":"2003","unstructured":"Je HM, Kim D, Bang SY (2003) Human face detection in digital video using SVMEnsemble. Neural Process Lett 17(3):239\u2013252","journal-title":"Neural Process Lett"},{"key":"9624_CR3","volume-title":"Text categorization with support vector machines: learning with many relevant features, ECML-98","author":"T Joachims","year":"1998","unstructured":"Joachims T (1998) Text categorization with support vector machines: learning with many relevant features, ECML-98. Springer, Berlin"},{"issue":"9","key":"9624_CR4","doi-asserted-by":"crossref","first-page":"2827","DOI":"10.1109\/TIP.2015.2421443","volume":"24","author":"J Tang","year":"2015","unstructured":"Tang J, Li Z, Wang M et al (2015) Neighborhood discriminant hashing for large-scale image retrieval. IEEE Trans Image Process 24(9):2827\u20132840","journal-title":"IEEE Trans Image Process"},{"key":"9624_CR5","doi-asserted-by":"publisher","unstructured":"Tang J, Shu X, Qi GJ et al (2016) Tri-clustered tensor completion for social-aware image tag refinement. IEEE Trans Pattern Anal Mach Intell. doi:\n                        10.1109\/TPAMI.2016.2608882","DOI":"10.1109\/TPAMI.2016.2608882"},{"issue":"1\u20132","key":"9624_CR6","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1007\/s10994-005-0463-6","volume":"59","author":"GM Fung","year":"2005","unstructured":"Fung GM, Mangasarian OL (2005) Multicategory proximal support vector machine classifiers. Mach Learn 59(1\u20132):77\u201397","journal-title":"Mach Learn"},{"issue":"1","key":"9624_CR7","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1109\/TPAMI.2006.17","volume":"28","author":"OL Mangasarian","year":"2006","unstructured":"Mangasarian OL, Wild E (2006) Multisurface proximal support vector machine classification via generalized eigenvalues. IEEE Trans Pattern Anal Mach Intell 28(1):69\u201374","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"5","key":"9624_CR8","doi-asserted-by":"crossref","first-page":"905","DOI":"10.1109\/TPAMI.2007.1068","volume":"29","author":"R Khemchandani","year":"2007","unstructured":"Khemchandani R, Jayadeva Chandra S (2007) Fuzzy twin support vector machines for pattern classification. IEEE Trans Pattern Anal Mach Intell 29(5):905\u2013910","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"4","key":"9624_CR9","doi-asserted-by":"crossref","first-page":"1059","DOI":"10.1007\/s10489-014-0563-8","volume":"41","author":"X Xie","year":"2014","unstructured":"Xie X, Sun S (2014) Multi-view Laplacian twin support vector machines. Appl Intell 41(4):1059\u20131068","journal-title":"Appl Intell"},{"issue":"4","key":"9624_CR10","doi-asserted-by":"crossref","first-page":"701","DOI":"10.3233\/IDA-150740","volume":"19","author":"X Xie","year":"2015","unstructured":"Xie X, Sun S (2015) Multi-view twin support vector machines. Intell Data Anal 19(4):701\u2013712","journal-title":"Intell Data Anal"},{"issue":"PB","key":"9624_CR11","doi-asserted-by":"crossref","first-page":"1085","DOI":"10.1016\/j.neucom.2014.07.025","volume":"149","author":"X Xie","year":"2015","unstructured":"Xie X, Sun S (2015) Multitask centroid twin support vector machines. Neurocomputing 149(PB):1085\u20131091","journal-title":"Neurocomputing"},{"issue":"13","key":"9624_CR12","doi-asserted-by":"crossref","first-page":"2006","DOI":"10.1016\/j.patrec.2010.06.005","volume":"42","author":"Q Ye","year":"2010","unstructured":"Ye Q, Zhao C, Ye N et al (2010) Multi-weight vector projection support vector machines. Pattern Recognit Lett 42(13):2006\u20132011","journal-title":"Pattern Recognit Lett"},{"issue":"s 10\u201311","key":"9624_CR13","doi-asserted-by":"crossref","first-page":"2643","DOI":"10.1016\/j.patcog.2011.03.001","volume":"44","author":"X Chen","year":"2011","unstructured":"Chen X, Yang J, Ye Q et al (2011) Recursive projection twin support vector machine via within-class variance minimization. Pattern Recognit 44(s 10\u201311):2643\u20132655","journal-title":"Pattern Recognit"},{"issue":"6","key":"9624_CR14","doi-asserted-by":"crossref","first-page":"2299","DOI":"10.1016\/j.patcog.2011.11.028","volume":"45","author":"YH Shao","year":"2012","unstructured":"Shao YH, Deng NY, Yang ZM (2012) Least squares recursive projection twin support vector machine for classification. Pattern Recognit 45(6):2299\u20132307","journal-title":"Pattern Recognit"},{"key":"9624_CR15","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/j.neucom.2013.02.046","volume":"130","author":"S Ding","year":"2014","unstructured":"Ding S, Hua X (2014) Recursive least squares projection twin support vector machines for nonlinear classification. Neurocomputing 130:3\u20139","journal-title":"Neurocomputing"},{"issue":"1","key":"9624_CR16","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1023\/B:NEPL.0000016836.03614.9f","volume":"19","author":"ML Zhang","year":"2004","unstructured":"Zhang ML, Zhou ZH (2004) Improve multi-instance neural networks through feature selection. Neural Process Lett 19(1):1\u201310","journal-title":"Neural Process Lett"},{"issue":"10","key":"9624_CR17","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TPAMI.2015.2470496","volume":"37","author":"Z Li","year":"2015","unstructured":"Li Z, Liu J, Tang J et al (2015) Robust structured subspace learning for data representation. IEEE Trans Pattern Anal Mach Intell 37(10):1\u20131","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"1","key":"9624_CR18","doi-asserted-by":"crossref","first-page":"174","DOI":"10.1016\/j.neucom.2014.05.040","volume":"144","author":"J Guo","year":"2014","unstructured":"Guo J, Yi P, Wang R et al (2014) Feature selection for least squares projection twin support vector machine. Neurocomputing 144(1):174\u2013183","journal-title":"Neurocomputing"},{"issue":"2","key":"9624_CR19","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1145\/1899412.1899418","volume":"2","author":"J Tang","year":"2011","unstructured":"Tang J, Hong R, Yan S et al (2011) Image annotation by k NN-sparse graph-based label propagation over noisily tagged web images. ACM Trans Intell Syst Technol 2(2):135\u2013136","journal-title":"ACM Trans Intell Syst Technol"},{"issue":"3","key":"9624_CR20","first-page":"1517","volume":"7","author":"OL Mangasarian","year":"2006","unstructured":"Mangasarian OL (2006) Exact 1-norm support vector machines via unconstrained convex differentiable minimization. J Mach Learn Res 7(3):1517\u20131530","journal-title":"J Mach Learn Res"},{"issue":"17","key":"9624_CR21","doi-asserted-by":"crossref","first-page":"3590","DOI":"10.1016\/j.neucom.2011.06.015","volume":"74","author":"S Gao","year":"2011","unstructured":"Gao S, Ye Q, Ye N (2011) 1-Norm least squares twin support vector machines. Neurocomputing 74(17):3590\u20133597","journal-title":"Neurocomputing"},{"issue":"3","key":"9624_CR22","doi-asserted-by":"crossref","first-page":"431","DOI":"10.1080\/10556788.2010.526608","volume":"27","author":"Q Ye","year":"2012","unstructured":"Ye Q, Zhao C, Ye N et al (2012) A feature selection method for nonparallel plane support vector machine classification. Optim Methods Softw 27(3):431\u2013443","journal-title":"Optim Methods Softw"},{"key":"9624_CR23","doi-asserted-by":"crossref","first-page":"1039","DOI":"10.1016\/j.procs.2013.05.132","volume":"17","author":"ZM Yang","year":"2013","unstructured":"Yang ZM, He JY, Shao YH (2013) Feature selection based on linear twin support vector machines. Procedia Comput Sci 17:1039\u20131046","journal-title":"Procedia Comput Sci"},{"issue":"2","key":"9624_CR24","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1023\/B:COAP.0000026884.66338.df","volume":"28","author":"G Fung","year":"2004","unstructured":"Fung G, Mangasarian OL (2004) A feature selection Newton method for support vector machine classification. Comput Optim Appl 28(2):185\u2013202","journal-title":"Comput Optim Appl"},{"key":"9624_CR25","unstructured":"Tikhonov Andrei N, Arsenin Vasiliy Y (1977) Solutions of Ill-posed Problems. Translated from the Russian, Preface by translation editor Fritz John, Scripta Series in Mathematics"},{"issue":"17","key":"9624_CR26","doi-asserted-by":"crossref","first-page":"913","DOI":"10.1080\/1055678021000028375","volume":"17","author":"OL Mangasarian","year":"2002","unstructured":"Mangasarian OL (2002) A finite newton method for classification. Optim Methods Softw 17(17):913\u2013929","journal-title":"Optim Methods Softw"},{"key":"9624_CR27","unstructured":"http:\/\/archive.ics.uci.edu\/ml\/"},{"key":"9624_CR28","unstructured":"http:\/\/www.cs.nyu.edu\/~roweis\/data.html"}],"container-title":["Neural Processing Letters"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11063-017-9624-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11063-017-9624-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11063-017-9624-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2018,3,2]],"date-time":"2018-03-02T06:52:25Z","timestamp":1519973545000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11063-017-9624-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,6,3]]},"references-count":28,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2018,2]]}},"alternative-id":["9624"],"URL":"https:\/\/doi.org\/10.1007\/s11063-017-9624-4","relation":{},"ISSN":["1370-4621","1573-773X"],"issn-type":[{"type":"print","value":"1370-4621"},{"type":"electronic","value":"1573-773X"}],"subject":[],"published":{"date-parts":[[2017,6,3]]}}}