The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
An Overview of Concept Drift Applications
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Citations
Cites
A survey on concept drift adaptation
Gama, J., Žliobaitė, I., Bifet, A., Pechenizkiy, M., & Bouchachia, A. (2014) · ACM Computing Surveys · doi:10.1145/2523813 · Cited by 3,735
Self-citationKeeping the Resident in the Loop: Adapting the Smart Home to the User
Rashidi, P., & Cook, D. J. (2009) · IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans · doi:10.1109/tsmca.2009.2025137 · Cited by 443
Cited by
Ensemble learning for data stream analysis: A survey
Krawczyk, B., Minku, L. L., Gama, J., Stefanowski, J., & Woźniak, M. (2017) · Information Fusion · doi:10.1016/j.inffus.2017.02.004 · Cited by 1,050
Self-citationDiez-Olivan, A., Del Ser, J., Galar, D., & Sierra, B. (2019) · Information Fusion · doi:10.1016/j.inffus.2018.10.005 · Cited by 633
Trustworthy AI: From Principles to Practices
Li, B., Qi, P., Liu, B., Di, S., Liu, J., Pei, J., Yi, J., & Zhou, B. (2023) · ACM Computing Surveys · doi:10.1145/3555803 · Cited by 612
“Deployment Anomaly Monitoring [70, 257, 394] Human-AI Interaction [72, 179, 301, 326] Fail-Safe Mechanism [126, 160, 230, 252] Hardware Security [264, 287, 364]”
BackgroundMethodApplication of machine learning and artificial intelligence in oil and gas industry
Sircar, A., Yadav, K., Rayavarapu, K., Bist, N., & Oza, H. (2021) · Petroleum Research · doi:10.1016/j.ptlrs.2021.05.009 · Cited by 560
Machine learning in oil and gas; a SWOT analysis approach
Hajizadeh, Y. (2019) · Journal of Petroleum Science and Engineering · doi:10.1016/j.petrol.2019.01.113 · Cited by 111
Metadata
- Authors
- Žliobaitė, I., Pechenizkiy, M., & Gama, J.
- Venue
- Studies in Big Data
- Publisher
- Springer International Publishing
- Published
- 2015-12-17
- Pages
- 91-114
- ISSN
- 2197-6503 (ISSN-L)
- 2197-6511
- OpenAlex
- W2289463038
- Cited by
- 379
- References
- 2
- FWCI
- 29.57
- Type
- book chapter
- Language
- en
- Open access
- green
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- Žliobaitė, I., Pechenizkiy, M., & Gama, J. (2016). An Overview of Concept Drift Applications. Studies in Big Data. https://doi.org/10.1007/978-3-319-26989-4_4
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
