{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T04:20:29Z","timestamp":1777695629140,"version":"3.51.4"},"reference-count":23,"publisher":"SAGE Publications","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IDA"],"published-print":{"date-parts":[[2018,2,22]]},"DOI":"10.3233\/ida-163264","type":"journal-article","created":{"date-parts":[[2018,3,2]],"date-time":"2018-03-02T15:50:30Z","timestamp":1520005830000},"page":"103-115","source":"Crossref","is-referenced-by-count":3,"title":["Multi-label classification of documents using fine-grained weights and modified co-training"],"prefix":"10.1177","volume":"22","author":[{"given":"Chang-Hwan","family":"Lee","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","reference":[{"key":"10.3233\/IDA-163264_ref1","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1007\/978-3-319-11433-0_2","article-title":"A pairwise class interaction framework for multilabel classification","author":"Arias","year":"2014","journal-title":"Probabilistic Graphical Models"},{"issue":"6","key":"10.3233\/IDA-163264_ref2","doi-asserted-by":"crossref","first-page":"705","DOI":"10.1016\/j.ijar.2011.01.007","article-title":"Multidimensional classification with bayesian networks","volume":"52","author":"Bielza","year":"2011","journal-title":"International Journal of Approximate Reasoning"},{"key":"10.3233\/IDA-163264_ref3","first-page":"78","article-title":"Hierarchical document categorization with support vector machines","author":"Cai","year":"2004","journal-title":"Proceedings of the 13th ACM International Conference on Information and Knowledge Management"},{"key":"10.3233\/IDA-163264_ref4","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1145\/1143844.1143867","article-title":"Hierarchical classification: Combining bayes with svm","author":"Cesa-Bianchi","year":"2006","journal-title":"Proceedings of the 23rd International Conference on Machine Learning"},{"key":"10.3233\/IDA-163264_ref6","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1007\/s10994-012-5285-8","article-title":"On label dependence and loss minimization in multi-label classification","volume":"88","author":"Dembczy\u0144ski","year":"2012","journal-title":"Machine Learning"},{"key":"10.3233\/IDA-163264_ref8","doi-asserted-by":"crossref","unstructured":"N. Ghamrawi and A. McCallum, Collective multi-label classification, in Inter. Conf. on Inform. and Know. Manage, 2005.","DOI":"10.21236\/ADA440081"},{"key":"10.3233\/IDA-163264_ref9","doi-asserted-by":"crossref","unstructured":"S. Godbole and S. Sarawagi, Discriminative methods for multi-labeled classification, in The 8-th Pacific-Asia Conference on Knowledge Discovery and Data Mining, 2004.","DOI":"10.1007\/978-3-540-24775-3_5"},{"key":"10.3233\/IDA-163264_ref10","unstructured":"B. Hariharan, L. Zelnik-Manor, S.V.N. Vishwanathan and M. Varma. Large scale max-margin multi-label classification with priors, in Proceedings of the 27th International Conference on Machine Learning, 2010."},{"issue":"11","key":"10.3233\/IDA-163264_ref11","doi-asserted-by":"crossref","first-page":"1457","DOI":"10.1109\/TKDE.2006.180","article-title":"Some effective techniques for na\u00efve bayes text classification","volume":"18","author":"Kim","year":"2006","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"10.3233\/IDA-163264_ref12","doi-asserted-by":"crossref","unstructured":"C.-H. Lee, F. Gutierrez and D. Dou, Calculating feature weights in na\u00efve bayes with kullbackleibler measure, in 11th IEEE International Conference on Data Mining, 2011.","DOI":"10.1109\/ICDM.2011.29"},{"key":"10.3233\/IDA-163264_ref14","doi-asserted-by":"crossref","unstructured":"B. Jin, B. Muller, C. Zhai and X. Lu, Multi-label literature classification based on the gene ontology graph, Bioinformatics 9(1) (2008).","DOI":"10.1186\/1471-2105-9-525"},{"key":"10.3233\/IDA-163264_ref15","unstructured":"A. McCallum and K. Nigam, A comparison of event models for naive bayes text classification, in AAAI-98 Workshop on Learning for Text Categorization, 1998."},{"key":"10.3233\/IDA-163264_ref16","unstructured":"A. McCallum, Multi-label text classification with a mixture model trained by em, in AAAI99 Workshop on Text Learning, 1999."},{"key":"10.3233\/IDA-163264_ref17","first-page":"254","article-title":"Classifier chains for multi-label classification","author":"Read","year":"2009","journal-title":"ECML\/PKDD"},{"key":"10.3233\/IDA-163264_ref18","unstructured":"J. Rennie, L. Shih, J. Teevan and D. Karger, Tackling the poor assumptions of naive bayes text classifiers, in Proceedings of the 20th International Conference on Machine Learning (ICML), 2003, pp. 616\u2013623."},{"key":"10.3233\/IDA-163264_ref19","doi-asserted-by":"crossref","unstructured":"J. Rodriguez and J. Lozano, Multiple-objective learning of multi-dimensional bayesian classifiers, in Inter. Conf. on Hybrid Intelligent Systems, 2008.","DOI":"10.1109\/HIS.2008.143"},{"key":"10.3233\/IDA-163264_ref20","doi-asserted-by":"crossref","unstructured":"J. Rousu, C. Saunders, S. Szedmak and J. Shawe-Taylor, Learning hierarchical multi-category text classifcation models, in Proceedings of the 22nd International Conference on Machine Learning, 2005, pp. 774\u2013751.","DOI":"10.1145\/1102351.1102445"},{"key":"10.3233\/IDA-163264_ref22","first-page":"682","article-title":"Techniques for improving the performance of na\u00efve bayes for text classification","volume":"3406","author":"Schneider","year":"2005","journal-title":"LNCS"},{"key":"10.3233\/IDA-163264_ref23","doi-asserted-by":"crossref","unstructured":"S.-H. Song and C.-H. Lee, Improving Multi-label Classification of Documents Using Fine-Grained Weights. in IEA\/AIE 2015: The 28th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, 2015.","DOI":"10.1007\/978-3-319-19066-2_47"},{"key":"10.3233\/IDA-163264_ref24","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1016\/j.patrec.2013.11.007","article-title":"Multilabel classification with Bayesian network-based chain classifiers","volume":"41","author":"Sucar","year":"2014","journal-title":"Pattern Recognition Letters"},{"key":"10.3233\/IDA-163264_ref26","doi-asserted-by":"crossref","unstructured":"P. de Waal and L. van der Gaag, Inference and learning in multi-dimensional bayesian network classifiers, in Proc. of Euro. Conf. on Symb. and Quant. Appr. to Reason. with Uncertain, 2007.","DOI":"10.1007\/978-3-540-75256-1_45"},{"key":"10.3233\/IDA-163264_ref27","doi-asserted-by":"crossref","unstructured":"M.-L. Zhang and Z.-H. Zhou, A k-nearest neighbor based algorithm for multi-label classification, in Granular Computing, 2005 IEEE International Conference on, Vol 2, 2005, pp. 718\u2013721.","DOI":"10.1109\/GRC.2005.1547385"},{"key":"10.3233\/IDA-163264_ref28","doi-asserted-by":"crossref","unstructured":"M.-L. Zhang and K. Zhang, Multi-label learning by exploiting label dependency, in Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2010, pp.\u00a0999\u20131008.","DOI":"10.1145\/1835804.1835930"}],"container-title":["Intelligent Data Analysis"],"original-title":[],"link":[{"URL":"https:\/\/content.iospress.com\/download?id=10.3233\/IDA-163264","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T09:18:01Z","timestamp":1777454281000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/full\/10.3233\/IDA-163264"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,2,22]]},"references-count":23,"journal-issue":{"issue":"1"},"URL":"https:\/\/doi.org\/10.3233\/ida-163264","relation":{},"ISSN":["1088-467X","1571-4128"],"issn-type":[{"value":"1088-467X","type":"print"},{"value":"1571-4128","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,2,22]]}}}