Academic literature on the topic 'Concept-Drift Management'
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Journal articles on the topic "Concept-Drift Management"
Cano, Andrés, Manuel Gómez-Olmedo, and Serafín Moral. "A Bayesian approach to abrupt concept drift." Knowledge-Based Systems 185 (December 2019): 104909. http://dx.doi.org/10.1016/j.knosys.2019.104909.
Full textBayram, Firas, Bestoun S. Ahmed, and Andreas Kassler. "From concept drift to model degradation: An overview on performance-aware drift detectors." Knowledge-Based Systems 245 (June 2022): 108632. http://dx.doi.org/10.1016/j.knosys.2022.108632.
Full textElkhawaga, Ghada, Mervat Abuelkheir, Sherif I. Barakat, Alaa M. Riad, and Manfred Reichert. "CONDA-PM—A Systematic Review and Framework for Concept Drift Analysis in Process Mining." Algorithms 13, no. 7 (July 3, 2020): 161. http://dx.doi.org/10.3390/a13070161.
Full textZheng, Xiulin, Peipei Li, Xuegang Hu, and Kui Yu. "Semi-supervised classification on data streams with recurring concept drift and concept evolution." Knowledge-Based Systems 215 (March 2021): 106749. http://dx.doi.org/10.1016/j.knosys.2021.106749.
Full textMwitondi, Kassim S., and Raed A. Said. "Dealing with Randomness and Concept Drift in Large Datasets." Data 6, no. 7 (July 19, 2021): 77. http://dx.doi.org/10.3390/data6070077.
Full textCabral, Danilo Rafael de Lima, and Roberto Souto Maior de Barros. "Concept drift detection based on Fisher’s Exact test." Information Sciences 442-443 (May 2018): 220–34. http://dx.doi.org/10.1016/j.ins.2018.02.054.
Full textBarros, Roberto Souto Maior, and Silas Garrido T. Carvalho Santos. "A large-scale comparison of concept drift detectors." Information Sciences 451-452 (July 2018): 348–70. http://dx.doi.org/10.1016/j.ins.2018.04.014.
Full textDelany, Sarah Jane, Pádraig Cunningham, Alexey Tsymbal, and Lorcan Coyle. "A case-based technique for tracking concept drift in spam filtering." Knowledge-Based Systems 18, no. 4-5 (August 2005): 187–95. http://dx.doi.org/10.1016/j.knosys.2004.10.002.
Full textLi, Yanhong, Deyu Li, Suge Wang, and Yanhui Zhai. "Incremental entropy-based clustering on categorical data streams with concept drift." Knowledge-Based Systems 59 (March 2014): 33–47. http://dx.doi.org/10.1016/j.knosys.2014.02.004.
Full textThaipisutikul, Tipajin. "An Adaptive Temporal-Concept Drift Model for Sequential Recommendation." ECTI Transactions on Computer and Information Technology (ECTI-CIT) 16, no. 2 (June 11, 2022): 222–36. http://dx.doi.org/10.37936/ecti-cit.2022162.248019.
Full textDissertations / Theses on the topic "Concept-Drift Management"
Ostovar, Alireza. "Business process drift: Detection and characterization." Thesis, Queensland University of Technology, 2019. https://eprints.qut.edu.au/127157/1/Alireza_Ostovar_Thesis.pdf.
Full textBook chapters on the topic "Concept-Drift Management"
Patil, Malini M. "Handling Concept Drift in Data Streams by Using Drift Detection Methods." In Data Management, Analytics and Innovation, 155–66. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1274-8_12.
Full textWoźniak, Michał, Paweł Ksieniewicz, Bogusław Cyganek, and Krzysztof Walkowiak. "Ensembles of Heterogeneous Concept Drift Detectors - Experimental Study." In Computer Information Systems and Industrial Management, 538–49. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-45378-1_48.
Full textWang, Shenghui, Stefan Schlobach, and Michel Klein. "What Is Concept Drift and How to Measure It?" In Knowledge Engineering and Management by the Masses, 241–56. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16438-5_17.
Full textMarrs, Gary R., Ray J. Hickey, and Michaela M. Black. "The Impact of Latency on Online Classification Learning with Concept Drift." In Knowledge Science, Engineering and Management, 459–69. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15280-1_42.
Full textYang, Ming, William H. Hsu, and Surya Teja Kallumadi. "Predictive Analytics of Social Networks." In Advances in Data Mining and Database Management, 297–333. IGI Global, 2014. http://dx.doi.org/10.4018/978-1-4666-5063-3.ch013.
Full textYang, Ming, William H. Hsu, and Surya Teja Kallumadi. "Predictive Analytics of Social Networks." In Business Intelligence, 1080–116. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-4666-9562-7.ch056.
Full textYang, Ming, William H. Hsu, and Surya Teja Kallumadi. "Predictive Analytics of Social Networks." In Social Media Marketing, 823–62. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-5637-4.ch042.
Full textConference papers on the topic "Concept-Drift Management"
Mak, Lee-onn, and Paul Krause. "Detection & Management of Concept Drift." In 2006 International Conference on Machine Learning and Cybernetics. IEEE, 2006. http://dx.doi.org/10.1109/icmlc.2006.258538.
Full textGözüaçık, Ömer, Alican Büyükçakır, Hamed Bonab, and Fazli Can. "Unsupervised Concept Drift Detection with a Discriminative Classifier." In CIKM '19: The 28th ACM International Conference on Information and Knowledge Management. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3357384.3358144.
Full textBalog, Katalin. "The Concept and Competitiveness of Agile Organization in the Fourth Industrial Revolution’s Drift." In 25th International Scientific Conference Strategic Management and Decision Support Systems in Strategic Management. University of Novi Sad, Faculty of Economics in Subotica, 2020. http://dx.doi.org/10.46541/978-86-7233-386-2_5.
Full textSeeliger, Alexander, Timo Nolle, and Max Mühlhäuser. "Detecting Concept Drift in Processes using Graph Metrics on Process Graphs." In S-BPM ONE '17: Conference on Subject-orientied Business Process Management. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3040565.3040566.
Full textTian, Hongda, Nguyen Lu Dang Khoa, Ali Anaissi, Yang Wang, and Fang Chen. "Concept Drift Adaption for Online Anomaly Detection in Structural Health Monitoring." In CIKM '19: The 28th ACM International Conference on Information and Knowledge Management. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3357384.3357816.
Full textSaurav, Sakti, Pankaj Malhotra, Vishnu TV, Narendhar Gugulothu, Lovekesh Vig, Puneet Agarwal, and Gautam Shroff. "Online anomaly detection with concept drift adaptation using recurrent neural networks." In CoDS-COMAD '18: The ACM India Joint International Conference on Data Science & Management of Data. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3152494.3152501.
Full textHenke, Marcia, Eduardo Souto, and Eulanda M. dos Santos. "Analysis of the evolution of features in classification problems with concept drift: Application to spam detection." In 2015 IFIP/IEEE International Symposium on Integrated Network Management (IM). IEEE, 2015. http://dx.doi.org/10.1109/inm.2015.7140398.
Full textSo¨derkvist, Johan, and Tomas Jansson. "IceMS: A Software for Ice Management." In ASME 2005 24th International Conference on Offshore Mechanics and Arctic Engineering. ASMEDC, 2005. http://dx.doi.org/10.1115/omae2005-67516.
Full textC. Lemos Neto, Álvaro, Rodrigo A. Coelho, and Cristiano L. de Castro. "An Incremental Learning approach using Long Short-Term Memory Neural Networks." In Congresso Brasileiro de Automática - 2020. sbabra, 2020. http://dx.doi.org/10.48011/asba.v2i1.1491.
Full textMo, Jia-hui, Peng Zou, and Jin Chen. "Context of the concept drift in data mining: An empirical study on the regional economic influence to the relation between demographic attributes and credit card holder’s loyalty." In 2008 International Conference on Management Science and Engineering (ICMSE). IEEE, 2008. http://dx.doi.org/10.1109/icmse.2008.4668891.
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