Trust Assessment on Data Stream Imputation in IoT Environments
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-41456-5_30
Reference16 articles.
1. Adams, S., Beling, P.A., Greenspan, S., Velez-Rojas, M., Mankovski, S.: Model-based trust assessment for internet of things networks. In: 2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE), pp. 1838–1843. IEEE (2018)
2. Barddal, J.P.: Vertical and horizontal partitioning in data stream regression ensembles. In: 2019 International Joint Conference on Neural Networks (IJCNN), pp. 1–8. IEEE (2019)
3. Lecture Notes in Computer Science;E Bertino,2015
4. Chhabra, G., Vashisht, V., Ranjan, J.: A comparison of multiple imputation methods for data with missing values. Indian J. Sci. Technol. 10(19), 1–7 (2017)
5. Dong, W., Gao, S., Yang, X., Yu, H.: An exploration of online missing value imputation in non-stationary data stream. SN Comput. Sci. 2(2), 1–11 (2021)
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