{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T19:06:26Z","timestamp":1778871986531,"version":"3.51.4"},"reference-count":26,"publisher":"IEEE Comput. Soc","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"DOI":"10.1109\/icdm.2003.1250911","type":"proceedings-article","created":{"date-parts":[[2004,4,23]],"date-time":"2004-04-23T18:38:15Z","timestamp":1082745495000},"page":"123-130","source":"Crossref","is-referenced-by-count":215,"title":["Dynamic weighted majority: a new ensemble method for tracking concept drift"],"prefix":"10.1109","author":[{"given":"J.Z.","family":"Kolter","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"M.A.","family":"Maloof","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.1963.10500830"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1145\/502512.502529"},{"key":"ref12","first-page":"338","article-title":"Estimating continuous distributions in Bayesian classifiers","author":"john","year":"1995","journal-title":"Proceedings of the 11th Conference on Uncertainty in Artificial Intelligence"},{"key":"ref13","first-page":"202","article-title":"Scaling up the accuracy of naive-Bayes classi-fiers: A decision-tree hybrid","author":"kohavi","year":"1996","journal-title":"Proceedings of the International Conference on Knowledge Discovery and Data Mining"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1007\/BF00116827"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1006\/inco.1994.1009"},{"key":"ref16","first-page":"546","article-title":"An empirical evaluation of bagging and boosting","author":"maclin","year":"1997","journal-title":"Proceedings of the 4th National Conference on Artificial Intelligence"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2003.1224005"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1023\/A:1007661119649"},{"key":"ref19","article-title":"Incremental learning with partial instance memory","author":"maloof","year":"0","journal-title":"Artificial Intelligence"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1007\/BF00058655"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1023\/A:1007335615132"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/347090.347107"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1023\/A:1007607513941"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1023\/A:1025619426553"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/312129.312283"},{"key":"ref2","author":"blake","year":"1998","journal-title":"UCI repository of machine learning databases"},{"key":"ref9","first-page":"148","article-title":"Experiments with a new boosting algorithm","author":"freund","year":"1996","journal-title":"Proceedings of the 13th International Conference on Machine Learning"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1023\/A:1007515423169"},{"key":"ref20","article-title":"Incremental generation of VLl hypotheses: The underlying methodology and the description of program AQ11","author":"michalski","year":"1983","journal-title":"Technical Report UIUCDCS-F-83-905"},{"key":"ref22","author":"quinlan","year":"1993","journal-title":"C4 5 Programs for Machine Learning"},{"key":"ref21","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1613\/jair.614","article-title":"Popular ensemble methods: An empirical study","volume":"11","author":"opitz","year":"1999","journal-title":"Journal of Artificial Intelligence Research"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1145\/502512.502568"},{"key":"ref23","first-page":"502","article-title":"Beyond incremental processing: Tracking concept drift","author":"schlimmer","year":"1986","journal-title":"Proceedings of the 5th National Conference on Artificial Intelligence"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1007\/BF00116900"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1023\/A:1007413323501"}],"event":{"name":"Third IEEE International Conference on Data Mining","location":"Melbourne, FL, USA","acronym":"ICDM-03"},"container-title":["Third IEEE International Conference on Data Mining"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx5\/8854\/27998\/01250911.pdf?arnumber=1250911","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,4,1]],"date-time":"2020-04-01T18:56:10Z","timestamp":1585767370000},"score":1,"resource":{"primary":{"URL":"http:\/\/ieeexplore.ieee.org\/document\/1250911\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[null]]},"references-count":26,"URL":"https:\/\/doi.org\/10.1109\/icdm.2003.1250911","relation":{},"subject":[]}}