{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,12]],"date-time":"2025-12-12T13:28:28Z","timestamp":1765546108081,"version":"3.37.3"},"reference-count":25,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2016,4,28]],"date-time":"2016-04-28T00:00:00Z","timestamp":1461801600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China (CN)","doi-asserted-by":"publisher","award":["No. 61303179"],"award-info":[{"award-number":["No. 61303179"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Process Lett"],"published-print":{"date-parts":[[2017,2]]},"DOI":"10.1007\/s11063-016-9526-x","type":"journal-article","created":{"date-parts":[[2016,4,28]],"date-time":"2016-04-28T14:46:38Z","timestamp":1461854798000},"page":"263-277","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Hierarchical Multilabel Classification with Optimal Path Prediction"],"prefix":"10.1007","volume":"45","author":[{"given":"Zhengya","family":"Sun","sequence":"first","affiliation":[]},{"given":"Yangyang","family":"Zhao","sequence":"additional","affiliation":[]},{"given":"Dong","family":"Cao","sequence":"additional","affiliation":[]},{"given":"Hongwei","family":"Hao","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2016,4,28]]},"reference":[{"key":"9526_CR1","doi-asserted-by":"crossref","unstructured":"Barros RC, Cerri R, Freitas AA, de Carvalho ACPLF (2013) Probabilistic clustering for hierarchical multi-label classification of protein functions. In: Machine learning and knowledge discovery in databases, proceedings, part II, pp 385\u2013400","DOI":"10.1007\/978-3-642-40991-2_25"},{"issue":"7","key":"9526_CR2","doi-asserted-by":"crossref","first-page":"830","DOI":"10.1093\/bioinformatics\/btk048","volume":"22","author":"Z Barutcuoglu","year":"2006","unstructured":"Barutcuoglu Z, Schapire RE, Troyanskaya OG (2006) Hierarchical multi-label prediction of gene function. Bioinformatics 22(7):830\u2013836","journal-title":"Bioinformatics"},{"key":"9526_CR3","unstructured":"Bi W, Kwok JT (2011) Multi-label classification on tree- and dag-structured hierarchies. In: Proceedings of the 28th international conference on machine learning, pp 17\u201324"},{"key":"9526_CR4","doi-asserted-by":"crossref","unstructured":"Bi W, Kwok JT (2012) Hierarchical multilabel classification with minimum bayes risk. In: Proceedings of the 12th IEEE international conference on data mining, pp 101\u2013110","DOI":"10.1109\/ICDM.2012.42"},{"issue":"12","key":"9526_CR5","doi-asserted-by":"crossref","first-page":"2275","DOI":"10.1109\/TNNLS.2014.2309437","volume":"25","author":"W Bi","year":"2014","unstructured":"Bi W, Kwok JT (2014) Mandatory leaf node prediction in hierarchical multilabel classification. IEEE Trans Neural Netw Learn Syst 25(12):2275\u20132287","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"9526_CR6","doi-asserted-by":"crossref","unstructured":"Blockeel H, Schietgat L, Struyf J, D\u017eeroski S, Clare A (2006) Decision trees for hierarchical multilabel classification: a case study in functional genomics. In: Proceedings of the 10th European conference on principles of data mining and knowledge discovery, pp 18\u201329","DOI":"10.1007\/11871637_7"},{"key":"9526_CR7","doi-asserted-by":"crossref","unstructured":"Cerri R, Barros RC, de Carvalho ACPLF (2011) Hierarchical multi-label classification for protein function prediction: a local approach based on neural networks. In: Intelligent systems design and applications, pp 337\u2013343","DOI":"10.1109\/ISDA.2011.6121678"},{"key":"9526_CR8","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1016\/j.jcss.2013.03.007","volume":"80","author":"R Cerri","year":"2014","unstructured":"Cerri R, Barros RC, de Carvalho ACPLF (2014) Hierarchical multi-label classification using local neural networks. J Comput Syst Sci 80:39\u201356","journal-title":"J Comput Syst Sci"},{"key":"9526_CR9","doi-asserted-by":"crossref","unstructured":"Cerri R, Barros RC, de Carvalho ACPLF (2015) Hierarchical classification of gene ontology-based protein functions with neural networks. In Proceedings of the 2015 international joint conference on neural networks, pp 1\u20138","DOI":"10.1109\/IJCNN.2015.7280474"},{"key":"9526_CR10","first-page":"31","volume":"7","author":"N Cesa-bianchi","year":"2004","unstructured":"Cesa-bianchi N, Zaniboni L, Collins M (2004) Incremental algorithms for hierarchical classification. J Mach Learn Res 7:31\u201354","journal-title":"J Mach Learn Res"},{"key":"9526_CR11","doi-asserted-by":"crossref","unstructured":"Cesa-bianchi N, Gentile C, Zaniboni L (2006) Hierarchical classification: combining bayes with SVM. In: Proceedings of the 23rd international conference on machine learning, pp 177\u2013184","DOI":"10.1145\/1143844.1143867"},{"key":"9526_CR12","unstructured":"Clare A (2003) Machine learning and data mining for yeast functional genomics. Ph.D. Thesis, University of Wales, Aberystwyth"},{"key":"9526_CR13","unstructured":"Grauman K, Sha F, Hwang SJ (2011) Learning a tree of metrics with disjoint visual features. In: Advances in neural information processing systems 24, pp 621\u2013629"},{"key":"9526_CR14","unstructured":"Hariharan B, Zelnik-Manor L, Vishwanathan SVN, Varma M (2010) Large scale max-margin multi-label classification with priors. In: Proceedings of the 27th international conference on machine learning, pp 423\u2013430"},{"key":"9526_CR15","unstructured":"Hernandez J, Sucar LE, Morales EF (2013) A hybrid global-local approach for hierarchical classification. In: Proceedings of the twenty-sixty international Florida artificial intelligence research society conference, pp 432\u2013437"},{"key":"9526_CR16","unstructured":"Kiritchenko S, Matwin S, Famili AF (2004) Hierarchical text categorization as a tool of associating genes with gene ontology codes. In: European workshop on data mining and text mining in bioinformatics, pp 30\u201334"},{"key":"9526_CR17","unstructured":"Ram\u00edrez-Corona M, Sucar LE, Morales EF (2014) Chained path evaluation for hierarchical multi-label classification. In Proceedings of the twenty-seventh international Florida artificial intelligence research society conference, pp 502\u2013507"},{"key":"9526_CR18","doi-asserted-by":"crossref","unstructured":"Rosipal R, Kr\u00e4mer N (2006) Overview and recent advances in partial least squares. In: Subspace, latent structure and feature selection techniques, pp 34\u201351","DOI":"10.1007\/11752790_2"},{"key":"9526_CR19","first-page":"1601","volume":"7","author":"J Rousu","year":"2006","unstructured":"Rousu J, Saunders C, Szedm\u00e1k S, Shawe-Taylor J (2006) Kernel-based learning of hierarchical multilabel classification models. J Mach Learn Res 7:1601\u20131626","journal-title":"J Mach Learn Res"},{"issue":"1\u20132","key":"9526_CR20","first-page":"31","volume":"22","author":"CN Silla Jr","year":"2011","unstructured":"Silla CN Jr, Freitas AA (2011) A survey of hierarchical classification across different application domains. Data Min Knowl Disc 22(1\u20132):31\u201372","journal-title":"Data Min Knowl Disc"},{"issue":"2","key":"9526_CR21","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1007\/s10994-008-5077-3","volume":"73","author":"C Vens","year":"2008","unstructured":"Vens C, Struyf J, Schietgat L, D\u017eeroski S, Blockeel H (2008) Decision trees for hierarchical multi-label classification. Mach Learn 73(2):185\u2013214","journal-title":"Mach Learn"},{"key":"9526_CR22","doi-asserted-by":"crossref","unstructured":"Wang P, Zhang P, Guo L (2012) Mining multi-label data streams using ensemble-based active learning. In: Proceedings of the 12th SIAM international conference on data mining, pp 1131\u20131140","DOI":"10.1137\/1.9781611972825.97"},{"key":"9526_CR23","doi-asserted-by":"crossref","unstructured":"Wold H (1975) Path models with latent variables: the nipals approach. In: Quantitative sociology: international perspectives on mathematical and statistical model building, pp 307\u2013357","DOI":"10.1016\/B978-0-12-103950-9.50017-4"},{"key":"9526_CR24","doi-asserted-by":"crossref","unstructured":"Wold S, Martens H, Wold H (1983) The multivariate calibration problem in chemistry solved by the pls method. In: Matrix pencils, pp 286\u2013293","DOI":"10.1007\/BFb0062108"},{"key":"9526_CR25","unstructured":"Zhou D, Xiao L, Wu M (2011) Hierarchical classification via orthogonal transfer. In: Proceedings of the 28th international conference on machine learning, pp 801\u2013808"}],"container-title":["Neural Processing Letters"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11063-016-9526-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11063-016-9526-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11063-016-9526-x","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11063-016-9526-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,6,1]],"date-time":"2019-06-01T00:34:13Z","timestamp":1559349253000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11063-016-9526-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,4,28]]},"references-count":25,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2017,2]]}},"alternative-id":["9526"],"URL":"https:\/\/doi.org\/10.1007\/s11063-016-9526-x","relation":{},"ISSN":["1370-4621","1573-773X"],"issn-type":[{"type":"print","value":"1370-4621"},{"type":"electronic","value":"1573-773X"}],"subject":[],"published":{"date-parts":[[2016,4,28]]}}}