Design and Construction of Personalized Recommendation Teaching System Under Artificial Intelligence Background
- DOI
- 10.2991/978-94-6463-172-2_177How to use a DOI?
- Keywords
- artificial intelligence; personalized recommendation; collaborative filtering algorithm; Teaching system design
- Abstract
Facing the problem of single teaching mode in teaching reform, this paper studies the personalized recommendation teaching system under the artificial intelligence background of sharing teaching resources to improve teaching quality and strengthen students’ autonomous learning ability. The system adopts the framework of Springboot + Vue + Mybatis to separate the front end from the back end, and MySQL 8.0.28 is selected to help manage the data. Aiming at the educational demand of information technology, this paper designs and implements a personalized recommendation teaching system under the background of artificial intelligence. This paper introduces the system structure design, the implementation process of collaborative filtering recommendation algorithm CF and other solutions.
- 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 - Yue Liu PY - 2023 DA - 2023/06/30 TI - Design and Construction of Personalized Recommendation Teaching System Under Artificial Intelligence Background BT - Proceedings of the 2023 4th International Conference on Education, Knowledge and Information Management (ICEKIM 2023) PB - Atlantis Press SP - 1601 EP - 1605 SN - 2589-4900 UR - https://doi.org/10.2991/978-94-6463-172-2_177 DO - 10.2991/978-94-6463-172-2_177 ID - Liu2023 ER -