{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,28]],"date-time":"2025-05-28T04:18:09Z","timestamp":1748405889030,"version":"3.41.0"},"publisher-location":"Cham","reference-count":13,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319190655"},{"type":"electronic","value":"9783319190662"}],"license":[{"start":{"date-parts":[[2015,1,1]],"date-time":"2015-01-01T00:00:00Z","timestamp":1420070400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2015,1,1]],"date-time":"2015-01-01T00:00:00Z","timestamp":1420070400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2015]]},"DOI":"10.1007\/978-3-319-19066-2_51","type":"book-chapter","created":{"date-parts":[[2015,4,30]],"date-time":"2015-04-30T01:20:34Z","timestamp":1430356834000},"page":"526-535","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Comparison of Adjusted Methods for Selecting Useful Unlabeled Data for Semi-Supervised Learning Algorithms"],"prefix":"10.1007","author":[{"given":"Thanh-Binh","family":"Le","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sang-Woon","family":"Kim","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2015,5,1]]},"reference":[{"unstructured":"Bache, K., Lichman, M.: UCI Machine Learning Repository. University of California, Irvine, School of Information and Computer Sciences, CA (2013)","key":"51_CR1"},{"doi-asserted-by":"crossref","unstructured":"Blum, A., Mitchell, T.: Combining labeled and unlabeled data with co-training. In: Proc. of the 11th Ann. Conf. Computational Learning Theory (COLT 98), Madison, WI, pp. 92\u2013100 (1998)","key":"51_CR2","DOI":"10.1145\/279943.279962"},{"issue":"3","key":"51_CR3","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/1961189.1961199","volume":"2","author":"C-C Chang","year":"2011","unstructured":"Chang, C.-C., Lin, C.-J.: LIBSVM: a library for support vector machines. ACM Trans. Intelligent Systems and Technology 2(3), 1\u201327 (2011). http:\/\/www.csie.ntu.edu.tw\/$$\\sim $$cjlin\/libsvm","journal-title":"ACM Trans. Intelligent Systems and Technology"},{"key":"51_CR4","doi-asserted-by":"publisher","DOI":"10.7551\/mitpress\/9780262033589.001.0001","volume-title":"Semi-Supervised Learning","author":"O Chapelle","year":"2006","unstructured":"Chapelle, O., Sch\u00f6lkopf, B., Zien, A.: Semi-Supervised Learning. The MIT Press, MA (2006)"},{"doi-asserted-by":"crossref","unstructured":"d\u2019Alch\u00e9-Buc, F., Grandvalet, Y., Ambroise, C.: Semi-supervised marginboost. Advances in Neural Information Processing Systems (NIPS), pp. 553\u2013560. The MIT Press, London (2002)","key":"51_CR5","DOI":"10.7551\/mitpress\/1120.003.0076"},{"doi-asserted-by":"crossref","unstructured":"Dagan, I., Engelson, S. P.: Committee-based sampling for training probabilistic classifiers. In: Proc. of the 12th Int\u2019l Conf. on Machine Learning (ICML 1995), pp. 150\u2013157. Morgan Kaufmann, Tahoe City, CA (1995)","key":"51_CR6","DOI":"10.1016\/B978-1-55860-377-6.50027-X"},{"key":"51_CR7","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1016\/j.patrec.2013.08.026","volume":"41","author":"T-B Le","year":"2014","unstructured":"Le, T.-B., Kim, S.-W.: On incrementally using a small portion of strong unlabeled data for semi-supervised learning algorithms. Pattern Recognition Letters 41, 53\u201364 (2014)","journal-title":"Pattern Recognition Letters"},{"doi-asserted-by":"crossref","unstructured":"Le, T. -B., Kim, S. -W.: On selecting helpful unlabeled data for improving semi-supervised support vector machines. In: Proc. of the 3rd Int\u2019l Conf. on Pattern Recognition Applications and Methods (ICPRAM 2014), Angers, France, pp. 48\u201359 (2014)","key":"51_CR8","DOI":"10.5220\/0004810500480059"},{"issue":"11","key":"51_CR9","doi-asserted-by":"publisher","first-page":"2000","DOI":"10.1109\/TPAMI.2008.235","volume":"31","author":"PK Mallapragada","year":"2009","unstructured":"Mallapragada, P.K., Jain, A.K., Liu, Y.: SemiBoost: boosting for semi-supervised learning. IEEE Trans. Pattern Anal. and Machine Intell. 31(11), 2000\u20132014 (2009)","journal-title":"IEEE Trans. Pattern Anal. and Machine Intell."},{"key":"51_CR10","volume-title":"Advances in Large Margin Classifiers","author":"JC Platt","year":"2000","unstructured":"Platt, J.C.: Probabilistic outputs for support vector machines and comparison to regularized likelihood methods. In: Smola, A., Bartlett, P., Sch\u00f6lkopf, B., Schuurmans, D. (eds.) Advances in Large Margin Classifiers. The MIT Press, Cambridge (2000)"},{"key":"51_CR11","doi-asserted-by":"publisher","first-page":"106","DOI":"10.1016\/j.ins.2012.11.015","volume":"230","author":"T Reitmaier","year":"2013","unstructured":"Reitmaier, T., Sick, B.: Let us know your decision: Pool-based active training of a generative classifier with the selection strategy 4DS. Information Sciences 230, 106\u2013131 (2013)","journal-title":"Information Sciences"},{"doi-asserted-by":"crossref","unstructured":"Yarowsky, D.: Unsupervised word sense disambiguation rivaling supervised methods. In: Proc. of the 33rd annual meeting on Association for Computational Linguistics (ACL1995), Cambridge, MA, 189\u2013196 (1995)","key":"51_CR12","DOI":"10.3115\/981658.981684"},{"unstructured":"Zhu, X.: Semi-Supervised Learning Literature Survey. Technical Report 1530, Dept. of Computer Sciences, University of Wisconsin at Madison, MA (2006)","key":"51_CR13"}],"container-title":["Lecture Notes in Computer Science","Current Approaches in Applied Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-19066-2_51","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,27]],"date-time":"2025-05-27T18:03:41Z","timestamp":1748369021000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-319-19066-2_51"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015]]},"ISBN":["9783319190655","9783319190662"],"references-count":13,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-19066-2_51","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2015]]},"assertion":[{"value":"1 May 2015","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}}]}}