{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T11:16:32Z","timestamp":1775214992284,"version":"3.50.1"},"publisher-location":"Cham","reference-count":78,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783319269870","type":"print"},{"value":"9783319269894","type":"electronic"}],"license":[{"start":{"date-parts":[[2015,12,17]],"date-time":"2015-12-17T00:00:00Z","timestamp":1450310400000},"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":[[2016]]},"DOI":"10.1007\/978-3-319-26989-4_4","type":"book-chapter","created":{"date-parts":[[2015,12,16]],"date-time":"2015-12-16T03:47:29Z","timestamp":1450237649000},"page":"91-114","source":"Crossref","is-referenced-by-count":218,"title":["An Overview of Concept Drift Applications"],"prefix":"10.1007","author":[{"given":"Indr\u0117","family":"\u017dliobait\u0117","sequence":"first","affiliation":[]},{"given":"Mykola","family":"Pechenizkiy","sequence":"additional","affiliation":[]},{"given":"Jo\u00e3o","family":"Gama","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2015,12,17]]},"reference":[{"issue":"10","key":"4_CR1","doi-asserted-by":"crossref","first-page":"2343","DOI":"10.1109\/TKDE.2012.172","volume":"25","author":"Hock Hee Ang","year":"2013","unstructured":"Ang, H.H., Gopalkrishnan V., Zliobaite I., Pechenizkiy M., Hoi S.C.H.: Predictive handling of asynchronous concept drifts in distributed environments. IEEE Trans. Knowl. Data Eng. 25, 2343\u20132355 (2013)","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"4_CR2","unstructured":"Anguita, D.: Smart adaptive systems: state of the art and future directions of research. In: Proceedings of the 1st European Sympposium on Intelligent Technologies, Hybrid Systems and Smart Adaptive Systems, EUNITE (2001)"},{"issue":"1","key":"4_CR3","doi-asserted-by":"publisher","first-page":"20","DOI":"10.1198\/TECH.2009.08136","volume":"52","author":"RA Becker","year":"2010","unstructured":"Becker, R.A., Volinsky, C., Wilks, A.R.: Fraud detection in telecommunications: History and lessons learned. Technometrics 52(1), 20\u201333 (2010)","journal-title":"Technometrics"},{"key":"4_CR4","first-page":"99","volume-title":"CISM International Centre for Mechanical Sciences","author":"Daniel Billsus","year":"1999","unstructured":"Billsus, D., Pazzani, M.: A hybrid user model for news story classification. In: Proceedings of the 7th International Conference on User Modeling, UM, pp. 99\u2013108 (1999)"},{"key":"4_CR5","doi-asserted-by":"crossref","first-page":"74","DOI":"10.1007\/3-540-46019-5_6","volume-title":"Soft-Ware 2002: Computing in an Imperfect World","author":"Michaela Black","year":"2002","unstructured":"Black, M., Hickey, R.: Classification of customer call data in the presence of concept drift and noise. In: Proceedings of the 1st International Conference on Computing in an Imperfect World, pp. 74\u201387 (2002)"},{"key":"4_CR6","doi-asserted-by":"crossref","unstructured":"Black, M., Hickey, R.: Detecting and adapting to concept drift in bioinformatics, pp. 161\u2013168. In Proc. of Knowledge Exploration in Life Science Informatics, International Symposium (2004)","DOI":"10.1007\/978-3-540-30478-4_14"},{"issue":"3","key":"4_CR7","doi-asserted-by":"publisher","first-page":"235","DOI":"10.1214\/ss\/1042727940","volume":"17","author":"R Bolton","year":"2002","unstructured":"Bolton, R., Hand, D.: Statistical fraud detection: A review. Stat. Sci. 17(3), 235\u2013255 (2002)","journal-title":"Stat. Sci."},{"key":"4_CR8","doi-asserted-by":"crossref","unstructured":"Bose, R.P.J.C., van der Aalst W.M.P., Zliobaite, I., Pechenizkiy, M. Dealing with concept drift in process mining. IEEE Trans. Neur. Net. Lear. Syst. accepted (2013)","DOI":"10.1109\/TNNLS.2013.2278313"},{"key":"4_CR9","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1007\/978-3-319-12571-8_5","volume-title":"Advances in Intelligent Data Analysis XIII","author":"Marcin Budka","year":"2014","unstructured":"Budka, M., Eastwood, M., Gabrys, B., Kadlec, P., Martin-Salvador, M., Schwan, S., Tsakonas, A., Zliobaite, I.: From sensor readings to predictions: on the process of developing practical soft sensors. In: Procedings of the 13th International Symposium on Intelligent Data Analysis, pp. 49\u201360 (2014)"},{"key":"4_CR10","doi-asserted-by":"crossref","first-page":"90","DOI":"10.1007\/978-3-642-34156-4_10","volume-title":"Advances in Intelligent Data Analysis XI","author":"Josep Carmona","year":"2012","unstructured":"Carmona, J., Gavald\u00e0, R.: Online techniques for dealing with concept drift in process mining. In: Proceedings of the 11th International Symposium on Intelligent Data Analysis, pp. 90\u2013102 (2012)"},{"key":"4_CR11","unstructured":"Chapman, P., Clinton, J., Kerber, R., Khabaza, T., Reinartz, T., Shearer, C., Wirth, R.: CRISP-DM 1.0 step-by-step data mining guide. Technical report, The CRISP-DM consortium (2000)"},{"key":"4_CR12","unstructured":"Charles, D., Kerr, A., McNeill, M., McAlister, M. Black, M., Kucklich, J., Moore, A., Stringer, K.: Player-centred game design: player modelling and adaptive digital games. In: Proceedings of the Digital Games Research Conference, pp. 285\u2013298 (2005)"},{"key":"4_CR13","doi-asserted-by":"publisher","first-page":"267","DOI":"10.1016\/j.fss.2004.03.028","volume":"150","author":"F Crespo","year":"2005","unstructured":"Crespo, F., Weber, R.: A methodology for dynamic data mining based on fuzzy clustering. Fuzzy Sets and Syst. 150, 267\u2013284 (2005)","journal-title":"Fuzzy Sets and Syst."},{"issue":"1","key":"4_CR14","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1093\/imaman\/4.1.111","volume":"4","author":"J. N. CROOK","year":"1992","unstructured":"Crook, J., Hamilton, R., Thomas, L.C.: The degradation of the scorecard over the business cycle. IMA J. Manage. Math. 4, 111\u2013123 (1992)","journal-title":"IMA Journal of Management Mathematics"},{"key":"4_CR15","doi-asserted-by":"crossref","unstructured":"da Silva, A., Lechevallier, Y., Rossi, F., de Carvalho, F.: Construction and analysis of evolving data summaries: an application on web usage data. In: Proceedings of the 7th International Conference on Intelligent Systems Design and Applications, pp. 377\u2013380 (2007)","DOI":"10.1109\/ISDA.2007.51"},{"key":"4_CR16","doi-asserted-by":"crossref","unstructured":"De Bra, P., Aerts, A., Berden, B., de Lange, B., Rousseau, B., Santic, T., Smits, D., Stash, N.: AHA! the adaptive hypermedia architecture. In: Proceedings of the 14th ACM Conference on Hypertext and hypermedia, pp. 81\u201384 (2003)","DOI":"10.1145\/900065.900068"},{"key":"4_CR17","unstructured":"Delany, S., Cunningham, P., Tsymbal, A.: A comparison of ensemble and case-base maintenance techniques for handling concept drift in spam filtering. In: Proceedings of Florida Artificial Intelligence Research Society Conference, pp. 340\u2013345 (2006)"},{"key":"4_CR18","doi-asserted-by":"crossref","unstructured":"Ding, Y., Li, X.: Time weight collaborative filtering. In: Proceedings of the 14th ACM International Conference on Information and Knowledge Management, pp. 485\u2013492 (2005)","DOI":"10.1145\/1099554.1099689"},{"key":"4_CR19","doi-asserted-by":"crossref","unstructured":"Donoho, S.: Early detection of insider trading in option markets. In: Proceedings of the 10th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 420\u2013429 (2004)","DOI":"10.1145\/1014052.1014100"},{"key":"4_CR20","doi-asserted-by":"crossref","unstructured":"Ekanayake, J., Tappolet, J., Gall, H.C., Bernstein, A.: Tracking concept drift of software projects using defect prediction quality. In: Proceedings of the 6th IEEE International Working Conference on Mining Software Repositories, pp. 51\u201360 (2009)","DOI":"10.1109\/MSR.2009.5069480"},{"issue":"1","key":"4_CR21","doi-asserted-by":"publisher","first-page":"36","DOI":"10.1016\/j.eswa.2006.04.011","volume":"33","author":"F Fdez-Riverola","year":"2007","unstructured":"Fdez-Riverola, F., Iglesias, E., Diaz, F., Mendez, J., Corchado, J.: Applying lazy learning algorithms to tackle concept drift in spam filtering. Expert Syst. Appl. 33(1), 36\u201348 (2007)","journal-title":"Expert Syst. Appl."},{"key":"4_CR22","doi-asserted-by":"crossref","unstructured":"Flasch, O., Kaspari, A., Morik, K., Wurst, M.: Aspect-based tagging for collaborative media organization. In: Proceedings of Workshop on Web Mining, From Web to Social Web: Discovering and Deploying User and Content Profiles, pp. 122\u2013141 (2007)","DOI":"10.1007\/978-3-540-74951-6_7"},{"key":"4_CR23","unstructured":"Forman, G.: Incremental machine learning to reduce biochemistry lab costs in the search for drug discovery. In: Proceedings of the 2nd Workshop on Data Mining in Bioinformatics, pp. 33\u201336 (2002)"},{"key":"4_CR24","doi-asserted-by":"crossref","unstructured":"Gago, P., Silva, A., Santos, M.: Adaptive decision support for intensive care. In: Proceedings of 13th Portuguese Conference on Artificial Intelligence, pp. 415\u2013425 (2007)","DOI":"10.1007\/978-3-540-77002-2_35"},{"key":"4_CR25","doi-asserted-by":"crossref","unstructured":"Gama, J., Kosina, P.: Learning about the learning process. In: Proceedings of the 10th International Conference on Advances in intelligent data analysis, IDA, pp. 162\u2013172, Germany, Springer (2011)","DOI":"10.1007\/978-3-642-24800-9_17"},{"key":"4_CR26","doi-asserted-by":"crossref","first-page":"286","DOI":"10.1007\/978-3-540-28645-5_29","volume-title":"Advances in Artificial Intelligence \u2013 SBIA 2004","author":"Jo\u00e3o Gama","year":"2004","unstructured":"Gama, J., Medas, P., Castillo, G., Rodrigues, P.: Learning with drift detection. In: Proceedings of the 17th Brazilian Symposium on Artificial Intelligence, pp. 286\u2013295 (2004)"},{"issue":"4","key":"4_CR27","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/2523813","volume":"46","author":"Jo\u00e3o Gama","year":"2014","unstructured":"Gama, J., Zliobaite, I., Bifet, A., Pechenizkiy, M., Bouchachia, A.: A survey on concept drift adaptation. ACM Comput. Surv. 46(4), 44:1\u201344:37 (2014)","journal-title":"ACM Computing Surveys"},{"key":"4_CR28","doi-asserted-by":"crossref","unstructured":"Gauch, S. Speretta, M., Chandramouli, A., Micarelli, A.: User profiles for personalized information access. In: Brusilovsky, P., Kobsa, A., Nejdl, W. (eds.) The Adaptive Web, pp. 54\u201389. Springer (2007)","DOI":"10.1007\/978-3-540-72079-9_2"},{"key":"4_CR29","doi-asserted-by":"crossref","unstructured":"Giacomini, R., Rossi, B.: Detecting and predicting forecast breakdowns. Working Paper 638, ECB (2006)","DOI":"10.2139\/ssrn.905083"},{"issue":"1","key":"4_CR30","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1198\/TECH.2009.09115","volume":"52","author":"David J. Hand","year":"2010","unstructured":"Hand, D.J.: Fraud detection in telecommunications and banking: discussion of Becker, Volinsky, and Wilks (2010); Sudjianto et al. Technometrics 52(1), 34\u201338 (2010)","journal-title":"Technometrics"},{"issue":"1","key":"4_CR31","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1214\/088342306000000060","volume":"21","author":"D Hand","year":"2006","unstructured":"Hand, D.: Classifier technology and the illusion of progress. Stat. Sci. 21(1), 1\u201314 (2006)","journal-title":"Stat. Sci."},{"issue":"3","key":"4_CR32","doi-asserted-by":"publisher","first-page":"408","DOI":"10.1057\/jors.2013.55","volume":"65","author":"DJ Hand","year":"2014","unstructured":"Hand, D.J., Adams, N.M.: Selection bias in credit scorecard evaluation. JORS 65(3), 408\u2013415 (2014)","journal-title":"JORS"},{"key":"4_CR33","unstructured":"Harries, M., Horn, K.: Detecting concept drift in financial time series prediction using symbolic machine learning. In: In Proceedings of the 8th Australian Joint Conference on Artificial Intelligence, pp. 91\u201398 (1995)"},{"issue":"2","key":"4_CR34","doi-asserted-by":"publisher","first-page":"101","DOI":"10.1023\/A:1007420529897","volume":"32","author":"M Harries","year":"1998","unstructured":"Harries, M., Sammut, C., Horn, K.: Extracting hidden context. Mach. Learn. 32(2), 101\u2013126 (1998)","journal-title":"Mach. Learn."},{"key":"4_CR35","doi-asserted-by":"crossref","first-page":"104","DOI":"10.1007\/978-3-540-89533-6_11","volume-title":"Digital Libraries: Universal and Ubiquitous Access to Information","author":"Md Maruf Hasan","year":"2008","unstructured":"Hasan, M., Nantajeewarawat, E.: Towards intelligent and adaptive digital library services. In: Proceedings of the 11th International Conference on Asian Digital Libraries, pp. 104\u2013113 (2008)"},{"issue":"2","key":"4_CR36","doi-asserted-by":"publisher","first-page":"526","DOI":"10.1109\/78.348134","volume":"43","author":"S Haykin","year":"1995","unstructured":"Haykin, S., Li, L.: Nonlinear adaptive prediction of nonstationary signals. IEEE Trans. Sig. Process. 43(2), 526\u2013535 (1995)","journal-title":"IEEE Trans. Sig. Process."},{"issue":"9","key":"4_CR37","doi-asserted-by":"publisher","first-page":"11559","DOI":"10.1016\/j.eswa.2009.03.031","volume":"36","author":"C Hilas","year":"2009","unstructured":"Hilas, C.: Designing an expert system for fraud detection in private telecommunications networks. Expert Syst. Appl. 36(9), 11559\u201311569 (2009)","journal-title":"Expert Syst. Appl."},{"key":"4_CR38","unstructured":"Horta, R., de Lima, B., Borges, C.: Data pre-processing of bankruptcy prediction models using data mining techniques (2009)"},{"key":"4_CR39","unstructured":"Jermaine, C.: Data mining for multiple antibiotic resistance. Online (2008)"},{"key":"4_CR40","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.compchemeng.2010.07.034","volume":"35","author":"P Kadlec","year":"2011","unstructured":"Kadlec, P., Grbic, R., Gabrys, B.: Review of adaptation mechanisms for data-driven soft sensors. Comput. Chem. Eng. 35, 1\u201324 (2011)","journal-title":"Comput. Chem. Eng."},{"issue":"5","key":"4_CR41","doi-asserted-by":"publisher","first-page":"1288","DOI":"10.1002\/aic.12346","volume":"57","author":"P Kadlec","year":"2011","unstructured":"Kadlec, P., Gabrys, B.: Local learning-based adaptive soft sensor for catalyst activation prediction. AIChE J. 57(5), 1288\u20131301 (2011)","journal-title":"AIChE J."},{"key":"4_CR42","doi-asserted-by":"crossref","unstructured":"Kiseleva, J., Crestan, E., Brigo, R., Dittel, R.: Modelling and detecting changes in user satisfaction. In: Proceedings of the 23rd ACM International Conference on Information and Knowledge Management, pp. 1449\u20131458 (2014)","DOI":"10.1145\/2661829.2661960"},{"key":"4_CR43","doi-asserted-by":"crossref","unstructured":"Kleinberg, J.: Bursty and hierarchical structure in streams. In: Proceedings of the 8th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 91\u2013101. ACM (2002)","DOI":"10.1145\/775060.775061"},{"key":"4_CR44","unstructured":"Klinkenberg, R.: Meta-learning, model selection and example selection in machine learning domains with concept drift. In: Proceedings of annual workshop of the Special Interest Group on Machine Learning, Knowledge Discovery, and Data Mining, pp. 64\u2013171 (2005)"},{"issue":"4","key":"4_CR45","doi-asserted-by":"publisher","first-page":"89","DOI":"10.1145\/1721654.1721677","volume":"53","author":"Y Koren","year":"2010","unstructured":"Koren, Y.: Collaborative filtering with temporal dynamics. Commun. ACM 53(4), 89\u201397 (2010)","journal-title":"Commun. ACM"},{"key":"4_CR46","doi-asserted-by":"crossref","first-page":"355","DOI":"10.1007\/978-3-540-39907-0_49","volume-title":"Artificial Intelligence in Medicine","author":"Matja\u017e Kukar","year":"2003","unstructured":"Kukar, M.: Drifting concepts as hidden factors in clinical studies. In: Proceedings of the 9th Conference on Artificial Intelligence in Medicine in Europe, pp. 355\u2013364 (2003)"},{"key":"4_CR47","doi-asserted-by":"crossref","unstructured":"Lathia, N., Hailes, S., Capra, L.: kNN CF: a temporal social network. In: Proceedings of the ACM Conference on Recommender Systems, pp. 227\u2013234 (2008)","DOI":"10.1145\/1454008.1454044"},{"key":"4_CR48","doi-asserted-by":"crossref","first-page":"118","DOI":"10.1007\/11780519_11","volume-title":"RoboCup 2005: Robot Soccer World Cup IX","author":"Andreas D. Lattner","year":"2006","unstructured":"Lattner, A., Miene, A., Visser, U., Herzog, O.: Sequential pattern mining for situation and behavior prediction in simulated robotic soccer. In: Proceedings of Robot Soccer World Cup IX, pp. 118\u2013129 (2006)"},{"key":"4_CR49","doi-asserted-by":"crossref","unstructured":"Lebanon, G., Zhao, Y.: Local likelihood modeling of temporal text streams. In: Proceedings of the 25th International Conference on Machine Learning, pp. 552\u2013559 (2008)","DOI":"10.1145\/1390156.1390226"},{"issue":"6","key":"4_CR50","doi-asserted-by":"publisher","first-page":"533","DOI":"10.1023\/A:1006624031083","volume":"14","author":"W Lee","year":"2000","unstructured":"Lee, W., Stolfo, S.J., Mok, K.W.: Adaptive intrusion detection: A data mining approach. Artif. Intell. Rev. 14(6), 533\u2013567 (2000)","journal-title":"Artif. Intell. Rev."},{"issue":"5\u20136","key":"4_CR51","doi-asserted-by":"publisher","first-page":"311","DOI":"10.1016\/j.artint.2007.01.006","volume":"171","author":"L Liao","year":"2007","unstructured":"Liao, L., Patterson, D., Fox, D., Kautz, H.: Learning and inferring transportation routines. Artif. Intell. 171(5\u20136), 311\u2013331 (2007)","journal-title":"Artif. Intell."},{"key":"4_CR52","doi-asserted-by":"crossref","unstructured":"Luo, J., Pronobis, A., Caputo, B., Jensfelt, P.: Incremental learning for place recognition in dynamic environments. In: Proceedings of the IEEE\/RSJ International Conference on Intelligent Robots and Systems, pp. 721\u2013728 (2007)","DOI":"10.1109\/IROS.2007.4398986"},{"key":"4_CR53","doi-asserted-by":"publisher","first-page":"3","DOI":"10.3109\/19396368.2011.652288","volume":"58","author":"MT Martin","year":"2012","unstructured":"Martin, M.T., Knudsen, T.B., Judson, R.S., Kavlock, R.J., Dix, D.J.: Economic benefits of using adaptive predictive models of reproductive toxicity in the context of a tiered testing program. Syst. Biol. Reprod. Med. 58, 3\u20139 (2012)","journal-title":"Syst. Biol. Reprod. Med."},{"key":"4_CR54","doi-asserted-by":"crossref","unstructured":"Mazhelis, O., Puuronen, S.: Comparing classifier combining techniques for mobile-masquerader detection. In: Proceedings of the The 2nd International Conference on Availability, Reliability and Security, pp. 465\u2013472 (2007)","DOI":"10.1109\/ARES.2007.58"},{"issue":"5","key":"4_CR55","doi-asserted-by":"publisher","first-page":"730","DOI":"10.1109\/TKDE.2009.156","volume":"22","author":"LL Minku","year":"2010","unstructured":"Minku, L.L., White, A.P., Yao, X.: The impact of diversity on online ensemble learning in the presence of concept drift. IEEE Trans. Knowl. Data Eng. 22(5), 730\u2013742 (2010)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"4_CR56","unstructured":"Morales, G.D.F., A, Bifet.: SAMOA: Scalable advanced massive online analysis. J. Mach. Learn. Res. 16, 149\u2013153 (2015)"},{"key":"4_CR57","unstructured":"Moreira, J.: Travel time prediction for the planning of mass transit companies: a machine learning approach. PhD thesis, University of Porto (2008)"},{"issue":"1","key":"4_CR58","doi-asserted-by":"crossref","first-page":"521","DOI":"10.1016\/j.patcog.2011.06.019","volume":"45","author":"Jose G. Moreno-Torres","year":"2012","unstructured":"Moreno-Torres, J.G., Raeder, T., Alaiz-Rodr\u00edguez, R., Chawla, N.V., Herrera, F.: A unifying view on dataset shift in classification. Pattern Recogn. 45(1), 521\u2013530 (2012)","journal-title":"Pattern Recognition"},{"key":"4_CR59","doi-asserted-by":"crossref","unstructured":"Mourao, F., Rocha, L., Araujo, R., Couto, T., Goncalves, M., Meira, W.: Understanding temporal aspects in document classification. In: Proceedings of the International Conference on Web Search and Web Data Mining, pp. 159\u2013170 (2008)","DOI":"10.1145\/1341531.1341554"},{"issue":"4","key":"4_CR60","doi-asserted-by":"publisher","first-page":"407","DOI":"10.1007\/s10588-007-9018-7","volume":"13","author":"A Pawling","year":"2007","unstructured":"Pawling, A., Chawla, N., Madey, G.: Anomaly detection in a mobile communication network. Comput. Math. Organ. Theory 13(4), 407\u2013422 (2007)","journal-title":"Comput. Math. Organ. Theory"},{"issue":"2","key":"4_CR61","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1145\/1809400.1809423","volume":"11","author":"M Pechenizkiy","year":"2009","unstructured":"Pechenizkiy, M., Bakker, J., Zliobaite, I., Ivannikov, A., Karkkainen, T.: Online mass flow prediction in CFB boilers with explicit detection of sudden concept drift. SIGKDD Explor. 11(2), 109\u2013116 (2009)","journal-title":"SIGKDD Explor."},{"key":"4_CR62","first-page":"753","volume-title":"Advances in Biometrics","author":"Norman Poh","year":"2009","unstructured":"Poh, N., Wong, R., Kittler, J., Roli, F.: Challenges and research directions for adaptive biometric recognition systems. In: Proceedings of the 3rd International Conference on Advances in Biometrics, pp. 753\u2013764 (2009)"},{"issue":"2","key":"4_CR63","doi-asserted-by":"publisher","first-page":"145","DOI":"10.1002\/rob.20279","volume":"26","author":"M Procopio","year":"2009","unstructured":"Procopio, M., Mulligan, J., Grudic, G.: Learning terrain segmentation with classifier ensembles for autonomous robot navigation in unstructured environments. J. Field Robot. 26(2), 145\u2013175 (2009)","journal-title":"J. Field Robot."},{"issue":"5","key":"4_CR64","doi-asserted-by":"crossref","first-page":"949","DOI":"10.1109\/TSMCA.2009.2025137","volume":"39","author":"P. Rashidi","year":"2009","unstructured":"Rashidi, P., Cook, D.: Keeping the resident in the loop: Adapting the smart home to the user. IEEE Trans. Syst. Man Cybern. Part A Syst. Hum 39(5), 949\u2013959 (2009)","journal-title":"IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans"},{"key":"4_CR65","doi-asserted-by":"crossref","unstructured":"Reinartz, T.P.: Focusing solutions for data mining: analytical studies and experimental results in real-world domains. In: Lecture Notes in Computer Science, vol. 1623. Springer (1999)","DOI":"10.1007\/3-540-48316-0"},{"issue":"3","key":"4_CR66","doi-asserted-by":"crossref","first-page":"273","DOI":"10.3233\/IDA-2005-9304","volume":"9","author":"A Rozsypal","year":"2005","unstructured":"Rozsypal, A., Kubat, M.: Association mining in time-varying domains. Intell. Data Anal. 9(3), 273\u2013288 (2005)","journal-title":"Intell. Data Anal."},{"key":"4_CR67","doi-asserted-by":"crossref","first-page":"454","DOI":"10.1007\/978-3-540-89378-3_46","volume-title":"AI 2008: Advances in Artificial Intelligence","author":"Joel Scanlan","year":"2008","unstructured":"Scanlan, J., Hartnett, J., Williams. R.: DynamicWEB: adapting to concept drift and object drift in cobweb. In: Proceedings of the 21st Australasian Joint Conference on Artificial Intelligence, pp. 454\u2013460 (2008)"},{"issue":"1","key":"4_CR68","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1198\/TECH.2010.07032","volume":"52","author":"A Sudjianto","year":"2010","unstructured":"Sudjianto, A., Nair, S., Yuan, M., Zhang, A., Kern, D., Cela-Diaz, F.: Statistical methods for fighting financial crimes. Technometrics 52(1), 5\u201319 (2010)","journal-title":"Technometrics"},{"issue":"1","key":"4_CR69","doi-asserted-by":"publisher","first-page":"63","DOI":"10.1080\/07421222.1999.11518234","volume":"16","author":"T Sung","year":"1999","unstructured":"Sung, T., Chang, N., Lee, G.: Dynamics of modeling in data mining: interpretive approach to bankruptcy prediction. J. Manage. Inf. Syst. 16(1), 63\u201385 (1999)","journal-title":"J. Manage. Inf. Syst."},{"issue":"9","key":"4_CR70","doi-asserted-by":"publisher","first-page":"661","DOI":"10.1002\/rob.20147","volume":"23","author":"S Thrun","year":"2006","unstructured":"Thrun, S., Montemerlo, M., Dahlkamp, H., Stavens, D., Aron, A., Diebel, J., Fong, P., Gale, J., Halpenny, M., Hoffmann, G., Lau, K., Oakley, C., Palatucci, M., Pratt, V., Stang, P., Strohband, S., Dupont, C., Jendrossek, L.-E., Koelen, C., Markey, C., Rummel, C., van Niekerk, J., Jensen, E., Alessandrini, P., Bradski, G., Davies, B., Ettinger, S., Kaehler, A., Nefian, A., Mahoney, P.: Winning the darpa grand challenge. J. Field Robot. 23(9), 661\u2013692 (2006)","journal-title":"J. Field Robot."},{"key":"4_CR71","unstructured":"Tsymbal, A.: The problem of concept drift: definitions and related work. Technical report, Department of Computer Science, Trinity College Dublin, Ireland (2004)"},{"issue":"1","key":"4_CR72","doi-asserted-by":"publisher","first-page":"56","DOI":"10.1016\/j.inffus.2006.11.002","volume":"9","author":"A Tsymbal","year":"2008","unstructured":"Tsymbal, A., Pechenizkiy, M., Cunningham, P., Puuronen, S.: Dynamic integration of classifiers for handling concept drift. Inf. Fusion 9(1), 56\u201368 (2008)","journal-title":"Inf. Fusion"},{"issue":"1","key":"4_CR73","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. Mach. Learn. 23(1), 69\u2013101 (1996)","journal-title":"Mach. Learn."},{"issue":"3","key":"4_CR74","doi-asserted-by":"crossref","first-page":"401","DOI":"10.1109\/TKDE.2005.48","volume":"17","author":"D.H. Widyantoro","year":"2005","unstructured":"Widyantoro, D., Yen, J.: Relevant data expansion for learning concept drift from sparsely labeled data. IEEE Trans. Knowl. Data Eng. 17(3), 401\u2013412 (2005)","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"issue":"10","key":"4_CR75","doi-asserted-by":"publisher","first-page":"76","DOI":"10.4304\/jcp.2.10.76-88","volume":"2","author":"R Yampolskiy","year":"2007","unstructured":"Yampolskiy, R., Govindaraju, V.: Direct and indirect human computer interaction based biometrics. J. Comput. 2(10), 76\u201388 (2007)","journal-title":"J. Comput."},{"issue":"3","key":"4_CR76","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 Min. Knowl. Discov. 13(3), 261\u2013289 (2006)","journal-title":"Data Min. Knowl. Discov."},{"key":"4_CR77","unstructured":"Zhou, J., Cheng, L., Bischof, W.: Prediction and change detection in sequential data for interactive applications. In: Proceedings of the 23rd AAAI Conference on Artificial Intelligence, pp. 805\u2013810 (2008)"},{"issue":"1","key":"4_CR78","doi-asserted-by":"publisher","first-page":"806","DOI":"10.1016\/j.eswa.2011.07.078","volume":"31","author":"I Zliobaite","year":"2012","unstructured":"Zliobaite, I., Bakker, J., Pechenizkiy, M.: Beating the baseline prediction in food sales: How intelligent an intelligent predictor is? Expert Syst. Appl. 31(1), 806\u2013815 (2012)","journal-title":"Expert Syst. Appl."}],"container-title":["Studies in Big Data","Big Data Analysis: New Algorithms for a New Society"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-26989-4_4","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,29]],"date-time":"2022-05-29T11:46:54Z","timestamp":1653824814000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-319-26989-4_4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,12,17]]},"ISBN":["9783319269870","9783319269894"],"references-count":78,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-26989-4_4","relation":{},"ISSN":["2197-6503","2197-6511"],"issn-type":[{"value":"2197-6503","type":"print"},{"value":"2197-6511","type":"electronic"}],"subject":[],"published":{"date-parts":[[2015,12,17]]}}}