Abstract
The traditional anomaly detection method of intelligent teaching system has some problems, such as poor accuracy and response efficiency. Therefore, this paper proposes a distributed anomaly detection method of intelligent teaching system based on cloud computing. Collect the abnormal data of distributed intelligent teaching system through cloud computing method, calculate the local reachable density according to Gaussian distribution function, build a data management model, and use distributed technology to locate and manage the abnormal area of teaching data, so as to achieve the goal of data detection and identification. The experimental results show that this method can effectively improve the recall rate of anomaly detection data in intelligent teaching system, and the response efficiency has been effectively improved.
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© 2022 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Zheng, F., Ma, L., Yang, H., Liu, L. (2022). Research on Anomaly Detection of Distributed Intelligent Teaching System Based on Cloud Computing. In: Fu, W., Sun, G. (eds) e-Learning, e-Education, and Online Training. eLEOT 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 453. Springer, Cham. https://doi.org/10.1007/978-3-031-21161-4_54
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DOI: https://doi.org/10.1007/978-3-031-21161-4_54
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