Traction of Students' Curriculum Information Based on Association Rule Optimization
- 10.2991/cnci-19.2019.96How to use a DOI?
- Apriori algorithm, credit weighting, correlation analysis.
In colleges and universities, the data on student’s performance are numerous. However, these data are often not well utilized and only served as a query. In order to make better use of these data, this paper will improve the traditional association rules and dig into the course performance information. Through the analysis of the association rules of students' different grades, the correlation between the courses and their traction are sought. The test results show that the optimized data mining algorithm has a good mining effect on the data, which can highlight the importance of different courses and make the data better reflect the links between curriculum and other courses.In this way,it is convenient for the teaching management department to better arrange the order of courses for students,so as to provide support and help for the teaching activities of students and teachers.
- © 2019, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Zhe Zhou AU - Yong Ouyang AU - Yawen Zeng PY - 2019/05 DA - 2019/05 TI - Traction of Students' Curriculum Information Based on Association Rule Optimization BT - Proceedings of the 2019 International Conference on Computer, Network, Communication and Information Systems (CNCI 2019) PB - Atlantis Press SP - 693 EP - 698 SN - 2352-538X UR - https://doi.org/10.2991/cnci-19.2019.96 DO - 10.2991/cnci-19.2019.96 ID - Zhou2019/05 ER -