{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T20:18:50Z","timestamp":1740169130714,"version":"3.37.3"},"reference-count":49,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2019]]},"DOI":"10.1109\/access.2019.2960626","type":"journal-article","created":{"date-parts":[[2019,12,18]],"date-time":"2019-12-18T20:58:17Z","timestamp":1576702697000},"page":"183580-183588","source":"Crossref","is-referenced-by-count":7,"title":["Incorporating Label Co-Occurrence Into Neural Network-Based Models for Multi-Label Text Classification"],"prefix":"10.1109","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7390-5156","authenticated-orcid":false,"given":"Jiaqi","family":"Yao","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5846-7119","authenticated-orcid":false,"given":"Keren","family":"Wang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2600-968X","authenticated-orcid":false,"given":"Jikun","family":"Yan","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2006.12.019"},{"key":"ref38","first-page":"406","article-title":"Random k-labelsets: An ensemble method for multilabel classification","volume":"4701","author":"tsoumakas","year":"2007","journal-title":"Machine Learning"},{"key":"ref33","article-title":"BERT: Pre-training of deep bidirectional transformers for language understanding","author":"devlin","year":"2018","journal-title":"CoRR"},{"article-title":"Improving language understanding with unsupervised learning","year":"2018","author":"radford","key":"ref32"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P18-1031"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/N18-1202"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-008-5064-8"},{"key":"ref36","first-page":"254","article-title":"Classifier chains for multi-label classification","volume":"5782","author":"read","year":"2009","journal-title":"Machine Learning and Knowledge Discovery in Databases"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2004.03.009"},{"key":"ref34","article-title":"Tutorial on learning from multi-label data","author":"tsoumakas","year":"2009","journal-title":"Proc ECML PKDD"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/N16-1174"},{"key":"ref27","article-title":"Attention is all you need","author":"vaswani","year":"2017","journal-title":"arXiv 1706 03762"},{"key":"ref29","article-title":"Improved semantic representations from tree-structured long short-term memory networks","author":"sheng","year":"2015","journal-title":"arXiv 1503 00075"},{"key":"ref2","first-page":"437","article-title":"Large-scale multi-label text classification—Revisiting neural networks","author":"nam","year":"2014","journal-title":"Proc Knowl Discovery Data Mining"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2013.39"},{"key":"ref20","article-title":"Bag of tricks for efficient text classification","author":"joulin","year":"2016","journal-title":"arXiv 1607 01759"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/D14-1181"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/621"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/E17-1104"},{"key":"ref23","first-page":"649","article-title":"Character-level convolutional networks for text classification","author":"zhang","year":"2015","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref26","first-page":"2267","article-title":"Recurrent convolutional neural networks for text classification","volume":"333","author":"lai","year":"2015","journal-title":"Proc AAAI"},{"key":"ref25","first-page":"6000","article-title":"Attention is all you need","author":"vaswani","year":"2017","journal-title":"Proc Adv Neural Inf Process"},{"key":"ref10","article-title":"Consistent multilabel ranking through univariate losses","author":"dembczynski","year":"2012","journal-title":"arXiv 1206 6401"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2006.162"},{"key":"ref40","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1007\/3-540-44794-6_4","article-title":"Knowledge discovery in multi-label phenotype data","volume":"2168","author":"clare","year":"2001","journal-title":"Principles of Data Mining and Knowledge Discovery"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1145\/3077136.3080834"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9781139020411"},{"journal-title":"Deep Learning","year":"2016","author":"goodfellow","key":"ref14"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.2200\/S00762ED1V01Y201703HLT037"},{"key":"ref16","first-page":"1137","article-title":"A neural probabilistic language model","volume":"3","author":"bengio","year":"2003","journal-title":"J Mach Learn Res"},{"key":"ref17","first-page":"746","article-title":"Linguistic regularities in continuous space word representations","volume":"13","author":"mikolov","year":"2013","journal-title":"Proc HLT-NAACL"},{"key":"ref18","article-title":"Efficient estimation of word representations in vector space","author":"mikolov","year":"2013","journal-title":"arXiv 1301 3781 [cs]"},{"key":"ref19","first-page":"3111","article-title":"Distributed representations of words and phrases and their compositionality","author":"mikolov","year":"2013","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2017.2785795"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-018-1345-5"},{"key":"ref6","article-title":"Multi-label learning by exploiting label correlations locally","author":"huang","year":"2012","journal-title":"Proc 26th AAAI Conf Artif Intell"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-011-5256-5"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/1835804.1835930"},{"key":"ref7","article-title":"Multilabel classification with label correlations and missing labels","author":"bi","year":"2014","journal-title":"Proc 28th AAAI Conf Artif Intell"},{"key":"ref49","doi-asserted-by":"crossref","first-page":"150","DOI":"10.3390\/info10040150","article-title":"Text classification algorithms: A survey","volume":"10","author":"kowsari","year":"2019","journal-title":"Information"},{"key":"ref9","first-page":"341","article-title":"On the consistency of multi-label learning","author":"gao","year":"2011","journal-title":"Proc 24th Annu Conf Learn Theory"},{"key":"ref46","first-page":"1","article-title":"Statistical comparisons of classifiers over multiple data sets","volume":"7","author":"dem\u0161ar","year":"2006","journal-title":"J Mach Learn Res"},{"key":"ref45","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"2015","journal-title":"Proc ICLR"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2016.2536748"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2015.2412676"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1145\/312624.312647"},{"key":"ref41","first-page":"681","article-title":"A kernel method for multi-labelled classification","volume":"14","author":"elisseeff","year":"2002","journal-title":"Advances in neural information processing systems"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2012.03.004"},{"key":"ref43","first-page":"361","article-title":"RCV1: A new benchmark collection for text categorization research","volume":"5","author":"lewis","year":"2004","journal-title":"J Mach Learn Res"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/8600701\/08936450.pdf?arnumber=8936450","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,27]],"date-time":"2022-01-27T09:34:38Z","timestamp":1643276078000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8936450\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"references-count":49,"URL":"https:\/\/doi.org\/10.1109\/access.2019.2960626","relation":{},"ISSN":["2169-3536"],"issn-type":[{"type":"electronic","value":"2169-3536"}],"subject":[],"published":{"date-parts":[[2019]]}}}