{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,5]],"date-time":"2026-05-05T10:12:20Z","timestamp":1777975940852,"version":"3.51.4"},"reference-count":35,"publisher":"Springer Science and Business Media LLC","issue":"10","license":[{"start":{"date-parts":[[2020,5,3]],"date-time":"2020-05-03T00:00:00Z","timestamp":1588464000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,5,3]],"date-time":"2020-05-03T00:00:00Z","timestamp":1588464000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61806208"],"award-info":[{"award-number":["61806208"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Tianjin Education Committee Research Project","award":["2018KJ246"],"award-info":[{"award-number":["2018KJ246"]}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["3122018S008"],"award-info":[{"award-number":["3122018S008"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int. J. Mach. Learn. & Cyber."],"published-print":{"date-parts":[[2020,10]]},"DOI":"10.1007\/s13042-020-01114-6","type":"journal-article","created":{"date-parts":[[2020,5,3]],"date-time":"2020-05-03T18:02:38Z","timestamp":1588528958000},"page":"2261-2274","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["ELM-MC: multi-label classification framework based on extreme learning machine"],"prefix":"10.1007","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7696-3514","authenticated-orcid":false,"given":"Haigang","family":"Zhang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jinfeng","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guimin","family":"Jia","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shaocheng","family":"Han","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xinran","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,5,3]]},"reference":[{"issue":"3","key":"1114_CR1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.4018\/jdwm.2007070101","volume":"3","author":"G Tsoumakas","year":"2007","unstructured":"Tsoumakas G, Katakis I, Taniar D (2007) Multi-label classification: an overview. Int J Data Warehous Min 3(3):1\u201313","journal-title":"Int J Data Warehous Min"},{"key":"1114_CR2","doi-asserted-by":"publisher","first-page":"313","DOI":"10.1016\/j.neucom.2017.04.052","volume":"260","author":"F Luo","year":"2017","unstructured":"Luo F, Guo W, Yu Y, Chen G (2017) A multi-label classification algorithm based on kernel extreme learning machine. Neurocomputing 260:313\u2013320","journal-title":"Neurocomputing"},{"issue":"8","key":"1114_CR3","doi-asserted-by":"publisher","first-page":"1819","DOI":"10.1109\/TKDE.2013.39","volume":"26","author":"ML Zhang","year":"2014","unstructured":"Zhang ML, Zhou ZH (2014) A review on multi-label learning algorithms. IEEE Transa Knowl Data Eng 26(8):1819\u20131837","journal-title":"IEEE Transa Knowl Data Eng"},{"key":"1114_CR4","doi-asserted-by":"crossref","unstructured":"Sun L, Ji S, Ye J (2008) Hypergraph spectral learning for multi-label classification. In: Acm Sigkdd international conference on knowledge discovery & data mining, DBLP","DOI":"10.1145\/1401890.1401971"},{"issue":"9","key":"1114_CR5","doi-asserted-by":"publisher","first-page":"2508","DOI":"10.1162\/NECO_a_00320","volume":"24","author":"F Tai","year":"2012","unstructured":"Tai F, Lin HT (2012) Multilabel classification with principal label space transformation. Neural Comput 24(9):2508\u20132542","journal-title":"Neural Comput"},{"key":"1114_CR6","doi-asserted-by":"crossref","unstructured":"Freund Y, Schapire RE (1995) A desicion-theoretic generalization of online learning and an application to boosting. In: European conference on computational learning theory, Springer, pp 23\u201337","DOI":"10.1007\/3-540-59119-2_166"},{"key":"1114_CR7","doi-asserted-by":"publisher","first-page":"222","DOI":"10.1016\/j.ymssp.2017.10.016","volume":"113","author":"J Cao","year":"2018","unstructured":"Cao J, Shang L, Wang J et al (2018) A novel distance estimation algorithm for periodic surface vibrations based on frequency band energy percentage feature. Mech Syst Signal Process 113:222\u2013236","journal-title":"Mech Syst Signal Process"},{"key":"1114_CR8","unstructured":"Bhatia K, Jain H, Kar P et al (2015) Sparse local embeddings for extreme multi-label classification. Adv Neural Inf Process Syst 730\u2013738"},{"key":"1114_CR9","unstructured":"Yu HF, Jain P, Kar P et al (2013) Large-scale multi-label learning with missing labels. In: International conference on machine learning"},{"issue":"3","key":"1114_CR10","doi-asserted-by":"publisher","first-page":"383","DOI":"10.1109\/TNNLS.2012.2235082","volume":"24","author":"Y Deng","year":"2013","unstructured":"Deng Y, Dai Q, Liu R et al (2013) Low-rank structure learning via nonconvex heuristic recovery. IEEE Trans Neural Netw Learn Syst 24(3):383\u2013396","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"1114_CR11","unstructured":"Bi W, Kwok J (2013) Efficient multi-label classification with many labels. In: International conference on machine learning, pp 405\u2013413"},{"issue":"10","key":"1114_CR12","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) Multi-label 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"},{"key":"1114_CR13","doi-asserted-by":"crossref","unstructured":"Nam J, Kim J, Gurevych I et al (2014) Large-scale multi-label text classification\u2014revisiting neural networks. In: Joint European conference on machine learning and knowledge discovery in databases. Springer, Berlin, Heidelberg","DOI":"10.1007\/978-3-662-44851-9_28"},{"issue":"9","key":"1114_CR14","doi-asserted-by":"publisher","first-page":"1901","DOI":"10.1109\/TPAMI.2015.2491929","volume":"38","author":"Y Wei","year":"2016","unstructured":"Wei Y, Xia W, Lin M et al (2016) HCP: a flexible CNN framework for multi-label image classification. IEEE Trans Pattern Anal Mach Intell 38(9):1901\u20131907","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"1114_CR15","doi-asserted-by":"crossref","unstructured":"Wang J, Yang Y, Mao J et al (2016) CNN-RNN: a unified framework for multi-label image classification. In: IEEE conference on computer vision and pattern recognition (CVPR). IEEE","DOI":"10.1109\/CVPR.2016.251"},{"issue":"1","key":"1114_CR16","doi-asserted-by":"publisher","first-page":"489","DOI":"10.1016\/j.neucom.2005.12.126","volume":"70","author":"GB Huang","year":"2006","unstructured":"Huang GB, Zhu QY, Siew CK (2006) Extreme learning machine: theory and applications. Neurocomputing 70(1):489\u2013501","journal-title":"Neurocomputing"},{"issue":"3","key":"1114_CR17","doi-asserted-by":"publisher","first-page":"376","DOI":"10.1007\/s12559-014-9255-2","volume":"6","author":"GB Huang","year":"2014","unstructured":"Huang GB (2014) An insight into extreme learning machines: random neurons, random features and kernels. Cogn Comput 6(3):376\u2013390","journal-title":"Cogn Comput"},{"issue":"6","key":"1114_CR18","doi-asserted-by":"publisher","first-page":"1411","DOI":"10.1109\/TNN.2006.880583","volume":"17","author":"NY Liang","year":"2006","unstructured":"Liang NY, Huang GB, Saratchandran P, Sundararajan N (2006) A fast and accurate online sequential learning algorithm for feedforward networks. IEEE Trans Neural Netw 17(6):1411\u20131423","journal-title":"IEEE Trans Neural Netw"},{"key":"1114_CR19","doi-asserted-by":"publisher","first-page":"232","DOI":"10.1016\/j.neucom.2015.04.106","volume":"174","author":"H Zhang","year":"2016","unstructured":"Zhang H, Yin Y, Zhang S (2016) An improved elm algorithm for the measurement of hot metal temperature in blast furnace. Neurocomputing 174:232\u2013237","journal-title":"Neurocomputing"},{"issue":"6","key":"1114_CR20","doi-asserted-by":"publisher","first-page":"225","DOI":"10.3390\/e18060225","volume":"18","author":"X Sun","year":"2016","unstructured":"Sun X, Xu J, Jiang C et al (2016) Extreme learning machine for multi-label classification. Entropy 18(6):225","journal-title":"Entropy"},{"key":"1114_CR21","unstructured":"Ferng CS, Lin HT (2011) Multi-label classification with error-correcting codes. In: Asian conference on machine learning, pp 281\u2013295"},{"issue":"1","key":"1114_CR22","doi-asserted-by":"publisher","first-page":"359","DOI":"10.1016\/j.neucom.2008.01.005","volume":"72","author":"HJ Rong","year":"2008","unstructured":"Rong HJ, Ong YS, Tan AH, Zhu Z (2008) A fast pruned-extreme learning machine for classification problem. Neurocomputing 72(1):359\u2013366","journal-title":"Neurocomputing"},{"key":"1114_CR23","doi-asserted-by":"publisher","first-page":"32","DOI":"10.1016\/j.neunet.2014.10.001","volume":"61","author":"G Huang","year":"2015","unstructured":"Huang G, Huang GB, Song S, You K (2015) Trends in extreme learning machines: a review. Neural Netw 61:32\u201348","journal-title":"Neural Netw"},{"issue":"1\u20133","key":"1114_CR24","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1016\/0169-7439(87)80084-9","volume":"2","author":"S Wold","year":"1987","unstructured":"Wold S, Esbensen K, Geladi P (1987) Principal component analysis. Chemom Intell Lab Syst 2(1\u20133):37\u201352","journal-title":"Chemom Intell Lab Syst"},{"issue":"12","key":"1114_CR25","doi-asserted-by":"publisher","first-page":"4392","DOI":"10.1109\/TCYB.2016.2609999","volume":"47","author":"J Cao","year":"2016","unstructured":"Cao J, Wang W, Wang J, Wang R (2016) Excavation equipment recognition based on novel acoustic statistical features. IEEE Trans Cybern 47(12):4392\u20134404","journal-title":"IEEE Trans Cybern"},{"key":"1114_CR26","series-title":"Springer texts in statistics","doi-asserted-by":"publisher","DOI":"10.1007\/978-0-387-78189-1_8","volume-title":"Modern multivariate statistical techniques","author":"AJ Izenman","year":"2013","unstructured":"Izenman AJ (2013) Linear discriminant analysis. In: Modern multivariate statistical techniques. Springer texts in statistics. Springer, New York, NY. https:\/\/doi.org\/10.1007\/978-0-387-78189-1_8"},{"key":"1114_CR27","series-title":"Springer briefs in optimization","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4419-9878-1_4","volume-title":"Robust data mining","author":"P Xanthopoulos","year":"2013","unstructured":"Xanthopoulos P, Pardalos PM, Trafalis TB (2013) Linear discriminant analysis. In: Robust data mining. Springer briefs in optimization. Springer, New York, NY. https:\/\/doi.org\/10.1007\/978-1-4419-9878-1_4"},{"issue":"1","key":"1114_CR28","first-page":"37","volume":"6","author":"DW Aha","year":"2013","unstructured":"Aha DW, Kibler D, Albert MK (2013) Instance-based learning algorithms. Mach Learn 6(1):37\u201366","journal-title":"Mach Learn"},{"issue":"3","key":"1114_CR29","first-page":"235","volume":"16","author":"SL Salzberg","year":"1994","unstructured":"Salzberg SL (1994) Book Review: \u201cC4.5: Programs for Machine Learning\u201d by J. Ross Quinlan. Mach Learn 16(3):235\u2013240","journal-title":"Mach Learn"},{"key":"1114_CR30","unstructured":"John GH, Langley P (2013) Estimating continuous distributions in Bayesian classifiers. In: Proceedings of the eleventh conference on uncertainty in artificial intelligence"},{"key":"1114_CR31","unstructured":"Zeng ZQ, Yu HB, Xu HR, et. al (2008) Fast training support vector machines using parallel sequential minimal optimization. In: 3rd international conference on intelligent system andknowledge engineering, Xiamen, pp 997\u20131001. IEEE"},{"key":"1114_CR32","doi-asserted-by":"crossref","unstructured":"Rodriguez-Fdez I, Canosa A, Mucientes M et al (2015) STAC: A web platform for the comparison of algorithms using statistical tests. In: 2015 IEEE international conference on fuzzy systems (FUZZ-IEEE), IEEE","DOI":"10.1109\/FUZZ-IEEE.2015.7337889"},{"key":"1114_CR33","doi-asserted-by":"publisher","first-page":"482","DOI":"10.1214\/aoms\/1177704575","volume":"33","author":"JL Hodges","year":"1962","unstructured":"Hodges JL, Lehmann EL (1962) Ranks methods for combination of independent experiments in analysis of variance. Ann Math Stat 33:482\u2013497","journal-title":"Ann Math Stat"},{"issue":"9","key":"1114_CR34","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 Recognit 37(9):1757\u20131771","journal-title":"Pattern Recognit"},{"key":"1114_CR35","doi-asserted-by":"crossref","unstructured":"Goncalves T, Quaresma P (2003) A preliminary approach to the multilabel classification problem of portuguese juridical documents. In: EPIA 2902, Springer, pp 435\u2013444","DOI":"10.1007\/978-3-540-24580-3_50"}],"container-title":["International Journal of Machine Learning and Cybernetics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-020-01114-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s13042-020-01114-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-020-01114-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,5,3]],"date-time":"2021-05-03T22:19:12Z","timestamp":1620080352000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s13042-020-01114-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,5,3]]},"references-count":35,"journal-issue":{"issue":"10","published-print":{"date-parts":[[2020,10]]}},"alternative-id":["1114"],"URL":"https:\/\/doi.org\/10.1007\/s13042-020-01114-6","relation":{},"ISSN":["1868-8071","1868-808X"],"issn-type":[{"value":"1868-8071","type":"print"},{"value":"1868-808X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,5,3]]},"assertion":[{"value":"27 December 2018","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 March 2020","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 May 2020","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}