Design of Enterprise Employee Training Platform Based on C4.5 Decision Tree
- DOI
- 10.2991/978-94-6463-058-9_60How to use a DOI?
- Keywords
- Artificial Intelligence; Enterprise Employees; Training Management; C4.5 Decision Tree; Database
- Abstract
In view of the low efficiency of current employee training in enterprises, combined with artificial intelligence technology, a corporate employee training management system based on the improved C4.5 decision tree is designed. Firstly, based on the C4.5 decision tree algorithm, data preprocessing, empty branch shearing, cross-entropy, and other operations are carried out, and the C4.5 decision tree algorithm is improved. Then J2EE development tool is used to build an enterprise employee training management system, and the system is divided into resources and requirements, planning, activity management and statistical analysis and management of five modules. In addition, the improved C4.5 decision tree is applied to the system for specific design and implementation of each module. Finally, a database is designed to provide data reference for system training management. The results show that the improved algorithm can improve the training management efficiency of the system. The system can replace the traditional manual training management mechanism, reduce the workload of employees, and improve work efficiency, which has certain practical significance.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Xiaofeng Liu PY - 2022 DA - 2022/12/27 TI - Design of Enterprise Employee Training Platform Based on C4.5 Decision Tree BT - Proceedings of the 2nd International Conference on Internet, Education and Information Technology (IEIT 2022) PB - Atlantis Press SP - 361 EP - 365 SN - 2352-538X UR - https://doi.org/10.2991/978-94-6463-058-9_60 DO - 10.2991/978-94-6463-058-9_60 ID - Liu2022 ER -