{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,4]],"date-time":"2025-06-04T11:30:29Z","timestamp":1749036629191,"version":"3.37.3"},"reference-count":37,"publisher":"Springer Science and Business Media LLC","issue":"14","license":[{"start":{"date-parts":[[2021,6,9]],"date-time":"2021-06-09T00:00:00Z","timestamp":1623196800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,6,9]],"date-time":"2021-06-09T00:00:00Z","timestamp":1623196800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Soft Comput"],"published-print":{"date-parts":[[2021,7]]},"DOI":"10.1007\/s00500-021-05884-1","type":"journal-article","created":{"date-parts":[[2021,6,9]],"date-time":"2021-06-09T14:21:44Z","timestamp":1623248504000},"page":"9307-9323","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Feature-label dual-mapping for missing label-specific features learning"],"prefix":"10.1007","volume":"25","author":[{"given":"Lulu","family":"Zhang","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6562-1153","authenticated-orcid":false,"given":"Yusheng","family":"Cheng","sequence":"additional","affiliation":[]},{"given":"Yibin","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Gensheng","family":"Pei","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,6,9]]},"reference":[{"issue":"2","key":"5884_CR1","doi-asserted-by":"publisher","first-page":"229","DOI":"10.1109\/TKDE.2018.2833850","volume":"31","author":"AH Akbarnejad","year":"2018","unstructured":"Akbarnejad AH, Baghshah MS (2018) An efficient semi-supervised multi-label classifier capable of handling missing labels. IEEE Trans Knowl Data Eng 31(2):229\u2013242","journal-title":"IEEE Trans Knowl Data Eng"},{"issue":"1","key":"5884_CR2","doi-asserted-by":"publisher","first-page":"183","DOI":"10.1137\/080716542","volume":"2","author":"A Beck","year":"2009","unstructured":"Beck A, Teboulle M (2009) A fast iterative shrinkage-thresholding algorithm for linear inverse problems. SIAM J Imag Sci 2(1):183\u2013202","journal-title":"SIAM J Imag Sci"},{"key":"5884_CR3","doi-asserted-by":"crossref","unstructured":"Bi W, Kwok J T (2014) Multilabel classification with label correlations and missing labels. In proceedings of 28th AAAI conference on artificial intelligence, 1680\u20131686","DOI":"10.1609\/aaai.v28i1.8996"},{"issue":"9","key":"5884_CR4","doi-asserted-by":"publisher","first-page":"1757","DOI":"10.1016\/j.patcog.2004.03.009","volume":"37","author":"MR Boutell","year":"2004","unstructured":"Boutell MR, Luo J, Shen X, Brown CM (2004) Learning multi-label scene classification. Pattern Recogn 37(9):1757\u20131771","journal-title":"Pattern Recogn"},{"key":"5884_CR5","unstructured":"Chen M, Zheng A, Weinberger K. Fast image tagging. Proceedings of International Conference on Machine Learning. 2013: 1274\u20131282."},{"key":"5884_CR6","doi-asserted-by":"publisher","first-page":"105924","DOI":"10.1016\/j.asoc.2019.105924","volume":"86","author":"Y Cheng","year":"2020","unstructured":"Cheng Y, Qian K, Wang Y, Zhao D (2020) Missing multi-label learning with non-equilibrium based on classification margin. Appl Soft Comput 86:105924","journal-title":"Appl Soft Comput"},{"key":"5884_CR7","first-page":"1","volume":"7","author":"J Dem\u0161ar","year":"2006","unstructured":"Dem\u0161ar J (2006) Statistical comparisons of classifiers over multiple data sets. J Mach Learn Res 7:1\u201330","journal-title":"J Mach Learn Res"},{"issue":"2","key":"5884_CR8","doi-asserted-by":"publisher","first-page":"133","DOI":"10.1007\/s10994-008-5064-8","volume":"73","author":"J F\u00fcrnkranz","year":"2008","unstructured":"F\u00fcrnkranz J, H\u00fcllermeier E, Menc\u00eda EL, Brinker K (2008) Multilabel classification via calibrated label ranking. Mach Learn 73(2):133\u2013153","journal-title":"Mach Learn"},{"key":"5884_CR9","doi-asserted-by":"publisher","first-page":"145","DOI":"10.1016\/j.knosys.2018.08.018","volume":"163","author":"ZF He","year":"2019","unstructured":"He ZF, Yang M, Gao Y, Liu HD, Yin Y (2019) Joint multi-label classification and label correlations with missing labels and feature selection. Knowl-Based Syst 163:145\u2013158","journal-title":"Knowl-Based Syst"},{"key":"5884_CR10","doi-asserted-by":"crossref","unstructured":"Huang J, Li G R, Wang S H, Zhang W G, Huang Q M (2015) Group sensitive classifier chains for multi-label classification, In proceedings of IEEE international conference multimedia expo, 1\u20136","DOI":"10.1109\/ICME.2015.7177400"},{"issue":"12","key":"5884_CR11","doi-asserted-by":"publisher","first-page":"3309","DOI":"10.1109\/TKDE.2016.2608339","volume":"28","author":"J Huang","year":"2016","unstructured":"Huang J, Li G, Huang Q, Wu X (2016) Learning label-specific features and class-dependent labels for multi-label classification. IEEE Trans Knowl Data Eng 28(12):3309\u20133323","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"5884_CR12","doi-asserted-by":"publisher","first-page":"124","DOI":"10.1016\/j.ins.2019.04.021","volume":"492","author":"J Huang","year":"2019","unstructured":"Huang J, Qin F, Zheng X, Cheng Z, Yuan Z, Zhang W, Huang Q (2019) Improving multi-label classification with missing labels by learning label-specific features. Inf Sci 492:124\u2013146","journal-title":"Inf Sci"},{"issue":"16\u201317","key":"5884_CR13","doi-asserted-by":"publisher","first-page":"1897","DOI":"10.1016\/j.artint.2008.08.002","volume":"172","author":"E H\u00fcllermeier","year":"2008","unstructured":"H\u00fcllermeier E, F\u00fcrnkranz J, Cheng W, Brinker K (2008) Label ranking by learning pairwise preferences. Artif Intell 172(16\u201317):1897\u20131916","journal-title":"Artif Intell"},{"issue":"1","key":"5884_CR14","doi-asserted-by":"publisher","first-page":"89","DOI":"10.1016\/S0933-3657(01)00077-X","volume":"23","author":"I Kononenko","year":"2001","unstructured":"Kononenko I (2001) Machine learning for medical diagnosis: history, state of the art and perspective. Artif Intell Med 23(1):89\u2013109","journal-title":"Artif Intell Med"},{"key":"5884_CR15","unstructured":"Lin Z, Ding G, Hu M, Wang J (2014) Multi-label classification via feature-aware implicit label space encoding. Proceedings of international conference on machine learning. 325\u2013333"},{"key":"5884_CR16","doi-asserted-by":"publisher","first-page":"172","DOI":"10.1016\/j.flowmeasinst.2017.01.007","volume":"54","author":"D Petkovi\u0107","year":"2017","unstructured":"Petkovi\u0107 D, Nikoli\u0107 V, Miti\u0107 VV, Koci\u0107 L (2017) Estimation of fractal representation of wind speed fluctuation by artificial neural network with different training algorothms. Flow Meas Instrum 54:172\u2013176","journal-title":"Flow Meas Instrum"},{"issue":"3","key":"5884_CR17","doi-asserted-by":"publisher","first-page":"333","DOI":"10.1007\/s10994-011-5256-5","volume":"85","author":"J Read","year":"2011","unstructured":"Read J, Pfahringer B, Holmes G, Frank E (2011) Classifier chains for multi-label classification. Mach Learn 85(3):333\u2013359","journal-title":"Mach Learn"},{"issue":"5","key":"5884_CR18","first-page":"427","volume":"31","author":"M Shariati","year":"2019","unstructured":"Shariati M, Trung NT, Wakil K, Mehrabi P, Safa M, Khorami M (2019) Estimation of moment and rotation of steel rack connections using extreme learning machine. Steel Compos Struct 31(5):427\u2013435","journal-title":"Steel Compos Struct"},{"key":"5884_CR19","first-page":"1393","volume":"13","author":"L Song","year":"2012","unstructured":"Song L, Smola A, Gretton A, Bedo J, Borgwardt K (2012) Feature selection via dependence maximization. J Mach Learn Res 13:1393\u20131434","journal-title":"J Mach Learn Res"},{"key":"5884_CR20","doi-asserted-by":"crossref","unstructured":"Sun Y Y, Zhang Y, Zhou Z H (2010) Multi-label learning with weak label. Proceedings of 24th AAAI conference on artificial intelligence. 593\u2013598","DOI":"10.1609\/aaai.v24i1.7699"},{"issue":"5","key":"5884_CR21","first-page":"639","volume":"70","author":"NT Trung","year":"2019","unstructured":"Trung NT, Shahgoli AF, Zandi Y, Shariati M, Wakil K, Safa M, Khorami M (2019) Moment-rotation prediction of precast beam-to-column connections using extreme learning machine. Struct Eng Mech 70(5):639\u2013647","journal-title":"Struct Eng Mech"},{"key":"5884_CR22","doi-asserted-by":"crossref","unstructured":"Wang X, Sukthankar G (2013) Multi-label relational neighbor classification using social context features. Proceedings of the 19th ACM SIGKDD international conference on knowledge discovery and data mining. 464\u2013472","DOI":"10.1145\/2487575.2487610"},{"key":"5884_CR23","doi-asserted-by":"publisher","first-page":"385","DOI":"10.1016\/j.neucom.2017.07.044","volume":"273","author":"W Weng","year":"2018","unstructured":"Weng W, Lin Y, Wu S, Li Y, Kang Y (2018) Multi-label learning based on label-specific features and local pairwise label correlation. Neurocomputing 273:385\u2013394","journal-title":"Neurocomputing"},{"issue":"9","key":"5884_CR24","first-page":"1992","volume":"25","author":"L Wu","year":"2014","unstructured":"Wu L, Zhang ML (2014) Research of label-specific features on multi-label learning algorithm. J Softw 25(9):1992\u20132001 ((in Chinese))","journal-title":"J Softw"},{"key":"5884_CR25","unstructured":"Xu M, Jin R, Zhou ZH (2013) Speedup matrix completion with side information: Application to multi-label learning. In proceedings of 26th international conference on neural information processing systems, 2301\u20132309"},{"key":"5884_CR26","doi-asserted-by":"crossref","unstructured":"Xu L, Wang Z, Shen Z, Wang Y, Chen E (2014) Learning low-rank label correlations for multi-label classification with missing labels. In proceedings of the 14th IEEE international conference on data mining, 1067\u20131072","DOI":"10.1109\/ICDM.2014.125"},{"key":"5884_CR27","doi-asserted-by":"publisher","first-page":"52","DOI":"10.1016\/j.knosys.2016.04.012","volume":"104","author":"S Xu","year":"2016","unstructured":"Xu S, Yang X, Yu H, Yu DJ, Yang J, Tsang EC (2016) Multi-label learning with label-specific feature reduction. Knowl-Based Syst 104:52\u201361","journal-title":"Knowl-Based Syst"},{"key":"5884_CR28","doi-asserted-by":"crossref","unstructured":"Yu G, Domeniconi C, Rangwala H, Zhang G (2013) Protein function prediction using dependence maximization. In proceedings of conference on machine learning and knowledge discovery in databases. 574\u2013589","DOI":"10.1007\/978-3-642-40988-2_37"},{"key":"5884_CR29","unstructured":"Yu H F, Jain P, Kar P, Dhillon I (2014) Large-scale multi-label learning with missing labels. International conference on machine learning. 593\u2013601."},{"issue":"1","key":"5884_CR30","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1109\/TPAMI.2014.2339815","volume":"37","author":"ML Zhang","year":"2015","unstructured":"Zhang ML, Wu L (2015) Lift: Multi-label learning with label-specific features. IEEE Trans Pattern Anal Mach Intell 37(1):107\u2013120","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"10","key":"5884_CR31","doi-asserted-by":"publisher","first-page":"1338","DOI":"10.1109\/TKDE.2006.162","volume":"18","author":"ML Zhang","year":"2006","unstructured":"Zhang ML, Zhou ZH (2006) Multilabel neural networks with applications to functional genomics and text categorization. IEEE Trans Knowl Data Eng 18(10):1338\u20131351","journal-title":"IEEE Trans Knowl Data Eng"},{"issue":"7","key":"5884_CR32","doi-asserted-by":"publisher","first-page":"2038","DOI":"10.1016\/j.patcog.2006.12.019","volume":"40","author":"ML Zhang","year":"2007","unstructured":"Zhang ML, Zhou ZH (2007) ML-KNN: a lazy learning approach to multi-label learning. Pattern Recogn 40(7):2038\u20132048","journal-title":"Pattern Recogn"},{"issue":"3","key":"5884_CR33","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/1839490.1839495","volume":"4","author":"Y Zhang","year":"2010","unstructured":"Zhang Y, Zhou ZH (2010) Multilabel dimensionality reduction via dependence maximization. ACM Trans Knowl Discov Data (TKDD) 4(3):1\u201321","journal-title":"ACM Trans Knowl Discov Data (TKDD)"},{"issue":"8","key":"5884_CR34","doi-asserted-by":"publisher","first-page":"1819","DOI":"10.1109\/TKDE.2013.39","volume":"26","author":"ML Zhang","year":"2013","unstructured":"Zhang ML, Zhou ZH (2013) A review on multi-label learning algorithms. IEEE Trans Knowl Data Eng 26(8):1819\u20131837","journal-title":"IEEE Trans Knowl Data Eng"},{"issue":"2","key":"5884_CR35","doi-asserted-by":"publisher","first-page":"191","DOI":"10.1007\/s11704-017-7031-7","volume":"12","author":"ML Zhang","year":"2018","unstructured":"Zhang ML, Li YK, Liu XY, Geng X (2018a) Binary relevance for multi-label learning: an overview. Front Comp Sci 12(2):191\u2013202","journal-title":"Front Comp Sci"},{"key":"5884_CR36","doi-asserted-by":"publisher","first-page":"148","DOI":"10.1016\/j.knosys.2018.07.003","volume":"159","author":"J Zhang","year":"2018","unstructured":"Zhang J, Li C, Cao D, Lin Y, Su S, Dai L, Li S (2018b) Multi-label learning with label-specific features by resolving label correlations. Knowl-Based Syst 159:148\u2013157","journal-title":"Knowl-Based Syst"},{"issue":"6","key":"5884_CR37","doi-asserted-by":"publisher","first-page":"1081","DOI":"10.1109\/TKDE.2017.2785795","volume":"30","author":"Y Zhu","year":"2017","unstructured":"Zhu Y, Kwok JT, Zhou ZH (2017) Multi-label learning with global and local label correlation. IEEE Trans Knowl Data Eng 30(6):1081\u20131094","journal-title":"IEEE Trans Knowl Data Eng"}],"container-title":["Soft Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00500-021-05884-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00500-021-05884-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00500-021-05884-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,30]],"date-time":"2022-12-30T12:56:21Z","timestamp":1672404981000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00500-021-05884-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,6,9]]},"references-count":37,"journal-issue":{"issue":"14","published-print":{"date-parts":[[2021,7]]}},"alternative-id":["5884"],"URL":"https:\/\/doi.org\/10.1007\/s00500-021-05884-1","relation":{},"ISSN":["1432-7643","1433-7479"],"issn-type":[{"type":"print","value":"1432-7643"},{"type":"electronic","value":"1433-7479"}],"subject":[],"published":{"date-parts":[[2021,6,9]]},"assertion":[{"value":"13 May 2021","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 June 2021","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declared that they have no conflicts of interest in this work. We declare that we do not have any commercial or associative interest that represents a conflict of interest is connected with the work submitted.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"This article does not contain any studies with human participants or animals performed by any authors.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}}]}}