{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,28]],"date-time":"2025-11-28T17:22:19Z","timestamp":1764350539374,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":20,"publisher":"ACM","license":[{"start":{"date-parts":[[2019,11,20]],"date-time":"2019-11-20T00:00:00Z","timestamp":1574208000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,11,20]]},"DOI":"10.1145\/3372454.3372466","type":"proceedings-article","created":{"date-parts":[[2020,1,21]],"date-time":"2020-01-21T12:17:26Z","timestamp":1579609046000},"page":"12-17","source":"Crossref","is-referenced-by-count":13,"title":["Adaptive Normalization in Streaming Data"],"prefix":"10.1145","author":[{"given":"Vibhuti","family":"Gupta","sequence":"first","affiliation":[{"name":"Department of Computer Science, Whitacre College of Engineering, Texas Tech University, Lubbock, Texas"}]},{"given":"Rattikorn","family":"Hewett","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Whitacre College of Engineering, Texas Tech University, Lubbock, Texas"}]}],"member":"320","published-online":{"date-parts":[[2020,1,21]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"crossref","first-page":"1517","DOI":"10.1109\/TNN.2011.2160459","article-title":"Incremental learning of concept drift in nonstationary environments","author":"Elwell R.","year":"2011","journal-title":"IEEE Transactions on Neural Networks"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2015.12.006"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1186\/s41044-016-0014-0"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"crossref","unstructured":"Garc\u00eda S. etal \"Data Preprocessing in Data Mining\" Springer 2015. Garc\u00eda S. et al. \"Data Preprocessing in Data Mining\" Springer 2015.","DOI":"10.1007\/978-3-319-10247-4"},{"key":"e_1_3_2_1_5_1","unstructured":"Proceedings of 11th International Computer Conference on Wavelet Actiev Media Technology and Information Processing (ICCWAMTIP) Proceedings of 11th International Computer Conference on Wavelet Actiev Media Technology and Information Processing (ICCWAMTIP) X. F. Gu An improving online accuracy updated ensemble method in learning from evolving data streams 2014 430 433"},{"key":"e_1_3_2_1_6_1","unstructured":"San Francisco: Morgan Kauffman San Francisco: Morgan Kauffman J. Han Data concepts and techniques 2001"},{"key":"e_1_3_2_1_7_1","unstructured":"Haykin S. etal \"Neural networks and learning machines\" Upper Saddle River: Pearson education 2009. Haykin S. et al. \"Neural networks and learning machines\" Upper Saddle River: Pearson education 2009."},{"key":"e_1_3_2_1_8_1","unstructured":"Proceedings of 49th Hawaii International Conference on System Sciences (HICSS) Proceedings of 49th Hawaii International Conference on System Sciences (HICSS) H. Hu M. Kantardzic Smart preprocessing improves data stream mining 2016 1749 1757"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0731-9053(04)19007-5"},{"issue":"3","key":"e_1_3_2_1_10_1","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1007\/s12243-018-0663-2","article-title":"A fast unsupervised preprocessing method for network monitoring","volume":"74","author":"Lopez M. A.","year":"2019","journal-title":"Annals of Telecommunications"},{"key":"e_1_3_2_1_11_1","unstructured":"Proceedings of International Joint Conference on Neural Networks (IJCNN) Proceedings of International Joint Conference on Neural Networks (IJCNN) E. Ogasawara Adaptive A novel data normalization approach for non-stationary time series 2010 1 8"},{"key":"e_1_3_2_1_12_1","unstructured":"Proceedings of IEEE International Conference on Data Mining Workshop Proceedings of IEEE International Conference on Data Mining Workshop B. S. Parker Incremental ensemble classifier addressing non-stationary fast data streams 2014 716 723"},{"key":"e_1_3_2_1_13_1","unstructured":"Passalis N. etal \"Deep Adaptive Input Normalization for Price Forecasting using Limit Order Book Data.\" arXiv:190.07892 2019. Passalis N. et al. \"Deep Adaptive Input Normalization for Price Forecasting using Limit Order Book Data.\" arXiv:190.07892 2019."},{"key":"e_1_3_2_1_14_1","unstructured":"Pyle D. Data preparation for data mining morgan kaufmann 1999. Pyle D. Data preparation for data mining morgan kaufmann 1999."},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2017.01.078"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/502512.502568"},{"key":"e_1_3_2_1_17_1","series-title":"Vol. 321321367","volume-title":"Introduction to Data mining","author":"Tan P. N.","year":"2005"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"crossref","unstructured":"Zliobaite I. & Gabrys B. \"Adaptive preprocessing for streaming data\" IEEE transactions on knowledge and data Engineering 26(2) 309--321 2012. Zliobaite I. & Gabrys B. \"Adaptive preprocessing for streaming data\" IEEE transactions on knowledge and data Engineering 26(2) 309--321 2012.","DOI":"10.1109\/TKDE.2012.147"},{"key":"e_1_3_2_1_19_1","unstructured":"Proceedings of the ACM SIGMOD international conference on Management of data ACM Proceedings of the ACM SIGMOD international conference on Management of data ACM Toshniwal Storm 2014"},{"key":"e_1_3_2_1_20_1","unstructured":"Harries M. & Wales N. S. Splice-2 comparative evaluation: Electricity pricing 1999. Harries M. & Wales N. S. Splice-2 comparative evaluation: Electricity pricing 1999."}],"event":{"name":"ICBDR 2019: 2019 The 3rd International Conference on Big Data Research","sponsor":["Shandong Univ. Shandong University","The University of Versailles Saint-Quentin The University of Versailles Saint-Quentin, Versailles, France"],"location":"Cergy-Pontoise France","acronym":"ICBDR 2019"},"container-title":["Proceedings of the 2019 3rd International Conference on Big Data Research"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3372454.3372466","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T22:02:22Z","timestamp":1750197742000},"score":1,"resource":{"primary":{"URL":"http:\/\/dl.acm.org\/doi\/10.1145\/3372454.3372466"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,11,20]]},"references-count":20,"alternative-id":["10.1145\/3372454.3372466","10.1145\/3372454"],"URL":"https:\/\/doi.org\/10.1145\/3372454.3372466","relation":{},"subject":[],"published":{"date-parts":[[2019,11,20]]}}}