Issue |
MATEC Web Conf.
Volume 228, 2018
2018 3rd International Conference on Circuits and Systems (CAS 2018)
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Article Number | 01017 | |
Number of page(s) | 5 | |
Section | Intelligent Computing and Information Processing | |
DOI | https://doi.org/10.1051/matecconf/201822801017 | |
Published online | 14 November 2018 |
Application of Improved Eclat Algorithm in Students’ Evaluation of Teaching
School of Computer and Communication Engineering, Liaoning Shihua University, 113001 Fushun Liaoning, China
a Author: 412602026@qq.com
The evaluation system of students is to find a way to solve the status way according to the exact needs of students and the teaching requirements of teachers, so as to improve the teaching level of teachers and improve the quality of school education. This paper uses the real evaluation sample and uses the data mining association rule algorithm to comprehensively analyze the massive data of the evaluation data and the basic information of the teacher. The purpose is to obtain the association rules between the teacher’s comprehensive information and its evaluation results. Using the evaluation data to explore its core issues. In this paper, the Eclat algorithm of association rules improves the problem of insufficient memory and occupying a large amount of time when searching for frequent itemsets in the data. The breadth-first algorithm is added to save operation time and improve the efficiency of the algorithm. The effectiveness of the improved algorithm is verified by comparative experiments and applied to the evaluation system so as to provide suggestions for the professional development of teachers from an objective perspective, and to build a harmonious, "people-oriented" evaluation system for students.
Key words: Student evaluation of teaching / Association rules / Eclat algorithm / Python
© The Authors, published by EDP Sciences, 2018
This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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