Abstract
The traditional online education system data query method has the problem of unclear track data type, which leads to a long query time. To solve this problem, this study designs a data optimization query method of online education system based on decision tree. According to the teaching objectives of teachers and the characteristics of courses, extract the course characteristics of online education system, and adjust the data segmentation process, so as to extract the grid memory query index structure. Then select a field as the segmentation basis and mark, and use the decision tree to identify the trajectory data type. Finally, set the data optimization query mode by continuously predefined query interval. The experimental results show that compared with the other two query methods, the query time of this method is less, which shows that the application performance of the data optimization query method of online education system integrated with decision tree is better.
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© 2022 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Zhang, Y., Wang, Y. (2022). Data Optimization Query Method of Online Education System Based on Decision Tree. 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 454. Springer, Cham. https://doi.org/10.1007/978-3-031-21164-5_19
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DOI: https://doi.org/10.1007/978-3-031-21164-5_19
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