{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,6]],"date-time":"2026-01-06T13:31:32Z","timestamp":1767706292660,"version":"3.40.3"},"publisher-location":"Berlin, Heidelberg","reference-count":17,"publisher":"Springer Berlin Heidelberg","isbn-type":[{"type":"print","value":"9783642247996"},{"type":"electronic","value":"9783642248009"}],"license":[{"start":{"date-parts":[[2011,1,1]],"date-time":"2011-01-01T00:00:00Z","timestamp":1293840000000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2011]]},"DOI":"10.1007\/978-3-642-24800-9_17","type":"book-chapter","created":{"date-parts":[[2011,10,24]],"date-time":"2011-10-24T03:29:17Z","timestamp":1319426957000},"page":"162-172","source":"Crossref","is-referenced-by-count":13,"title":["Learning about the Learning Process"],"prefix":"10.1007","author":[{"given":"Jo\u00e3o","family":"Gama","sequence":"first","affiliation":[]},{"given":"Petr","family":"Kosina","sequence":"additional","affiliation":[]}],"member":"297","reference":[{"issue":"11","key":"17_CR1","doi-asserted-by":"publisher","first-page":"643","DOI":"10.1145\/361179.361202","volume":"17","author":"W. Dijkstra","year":"1974","unstructured":"Dijkstra, W.: Self-stabilizing systems in spite of distributed control. Communications of the ACM\u00a017(11), 643\u2013644 (1974)","journal-title":"Communications of the ACM"},{"key":"17_CR2","series-title":"Lecture Notes in Artificial Intelligence","doi-asserted-by":"publisher","first-page":"286","DOI":"10.1007\/978-3-540-28645-5_29","volume-title":"Advances in Artificial Intelligence \u2013 SBIA 2004","author":"J. Gama","year":"2004","unstructured":"Gama, J., Medas, P., Castillo, G., Rodrigues, P.: Learning with drift detection. In: Bazzan, A.L.C., Labidi, S. (eds.) SBIA 2004. LNCS (LNAI), vol.\u00a03171, pp. 286\u2013295. Springer, Heidelberg (2004)"},{"key":"17_CR3","first-page":"233","volume-title":"ICDIM","author":"M. Granitzer","year":"2008","unstructured":"Granitzer, M., Kr\u00f6ll, M., Seifert, C., Rath, A.S., Weber, N., Dietzel, O., Lindstaedt, S.N.: Analysis of machine learning techniques for context extraction. In: Pichappan, P., Abraham, A. (eds.) ICDIM, pp. 233\u2013240. IEEE, Los Alamitos (2008)"},{"key":"17_CR4","volume-title":"Statistical Quality Control","author":"E. Grant","year":"1996","unstructured":"Grant, E., Leavenworth, R.: Statistical Quality Control. McGraw-Hill, New York (1996)"},{"key":"17_CR5","doi-asserted-by":"publisher","first-page":"101","DOI":"10.1023\/A:1007420529897","volume":"32","author":"M.B. Harries","year":"1998","unstructured":"Harries, M.B., Sammut, C., Horn, K.: Extracting hidden context. Machine Learning\u00a032, 101\u2013126 (1998)","journal-title":"Machine Learning"},{"key":"17_CR6","doi-asserted-by":"publisher","first-page":"371","DOI":"10.1007\/s10115-009-0206-2","volume":"22","author":"I. Katakis","year":"2010","unstructured":"Katakis, I., Tsoumakas, G., Vlahavas, I.: Tracking recurring contexts using ensemble classifiers: an application to email filtering. Knowledge and Information Systems\u00a022, 371\u2013391 (2010)","journal-title":"Knowledge and Information Systems"},{"issue":"3","key":"17_CR7","doi-asserted-by":"crossref","first-page":"281","DOI":"10.3233\/IDA-2004-8305","volume":"8","author":"R. Klinkenberg","year":"2004","unstructured":"Klinkenberg, R.: Learning drifting concepts: Example selection vs. example weighting. Intelligent Data Analysis\u00a08(3), 281\u2013300 (2004)","journal-title":"Intelligent Data Analysis"},{"key":"17_CR8","unstructured":"Lazarescu, M.M.: A multi-resolution learning approach to tracking concept drift and recurrent concepts. In: Proceedings of the 5th International Workshop on Pattern Recognition in Information Systems (2005)"},{"key":"17_CR9","unstructured":"Ortega, J.: Exploiting multiple existing models and learning algorithms. In: AAAI 1996 - Workshop in Induction of Multiple Learning Models, pp. 17\u201321 (1995)"},{"issue":"4","key":"17_CR10","doi-asserted-by":"publisher","first-page":"470","DOI":"10.1007\/PL00011679","volume":"3","author":"J. Ortega","year":"2001","unstructured":"Ortega, J., Koppel, M., Argamon, S.: Arbitrating among competing classifiers using learned referees. Knowledge and Information Systems\u00a03(4), 470\u2013490 (2001)","journal-title":"Knowledge and Information Systems"},{"key":"17_CR11","first-page":"404","volume-title":"ICMLA 2007: Proceedings of the Sixth International Conference on Machine Learning and Applications","author":"S. Ramamurthy","year":"2007","unstructured":"Ramamurthy, S., Bhatnagar, R.: Tracking recurrent concept drift in streaming data using ensemble classifiers. In: ICMLA 2007: Proceedings of the Sixth International Conference on Machine Learning and Applications, pp. 404\u2013409. IEEE Computer Society, Washington, DC, USA (2007)"},{"key":"17_CR12","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"115","DOI":"10.1007\/3-540-44816-0_12","volume-title":"Advances in Intelligent Data Analysis","author":"A. Seewald","year":"2001","unstructured":"Seewald, A., F\u00fcrnkranz, J.: An evaluation of grading classifiers. In: Hoffmann, F., Hand, D.J., Adams, N., Fisher, D., Guimaraes, G. (eds.) IDA 2001. LNCS, vol.\u00a02189, pp. 115\u2013124. Springer, Heidelberg (2001)"},{"key":"17_CR13","first-page":"377","volume-title":"Knowledge Discovery and Data Mining","author":"W. Nick Street","year":"2001","unstructured":"Nick Street, W., Kim, Y.: A streaming ensemble algorithm (sea) for large-scale classification. In: Knowledge Discovery and Data Mining, pp. 377\u2013382. ACM Press, New York (2001)"},{"key":"17_CR14","unstructured":"Turney, P.: The management of context-sensitive features: A review of strategies (1996)"},{"issue":"3","key":"17_CR15","doi-asserted-by":"publisher","first-page":"259","DOI":"10.1023\/A:1007365809034","volume":"27","author":"G. Widmer","year":"1997","unstructured":"Widmer, G.: Tracking context changes through meta-learning. Machine Learning\u00a027(3), 259\u2013286 (1997)","journal-title":"Machine Learning"},{"issue":"1","key":"17_CR16","first-page":"69","volume":"23","author":"G. Widmer","year":"1996","unstructured":"Widmer, G., Kubat, M.: Learning in the presence of concept drift and hidden contexts. Machine Learning\u00a023(1), 69\u2013101 (1996)","journal-title":"Machine Learning"},{"issue":"3","key":"17_CR17","doi-asserted-by":"publisher","first-page":"261","DOI":"10.1007\/s10618-006-0050-x","volume":"13","author":"Y. Yang","year":"2006","unstructured":"Yang, Y., Wu, X., Zhu, X.: Mining in anticipation for concept change: Proactive-reactive prediction in data streams. Data Mining and Knowledge Discovery\u00a013(3), 261\u2013289 (2006)","journal-title":"Data Mining and Knowledge Discovery"}],"container-title":["Lecture Notes in Computer Science","Advances in Intelligent Data Analysis X"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-642-24800-9_17","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,1,26]],"date-time":"2019-01-26T07:13:49Z","timestamp":1548486829000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-642-24800-9_17"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2011]]},"ISBN":["9783642247996","9783642248009"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-3-642-24800-9_17","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2011]]}}}