Design and implementation of teaching analysis system based on data mining

被引：0

作者：

Zhang, Tiancheng ^{[1
]}

Dong, Wei ^{[1
]}

Shi, He ^{[1
]}

Liu, Ruomei ^{[1
]}

Sun, Hao ^{[1
]}

机构：

[1] Northeastern Univ, Sch Comp Sci & Engn, Shenyang 110169, Peoples R China

来源：

PROCEEDINGS OF THE 2019 31ST CHINESE CONTROL AND DECISION CONFERENCE (CCDC 2019) | 2019年

基金：

中国国家自然科学基金;

关键词：

Data mining; Cluster analysis; Association analysis; Teaching analysis;

D O I：

10.1109/ccdc.2019.8832973

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

With the development of informatization and data collection, more and more educational process data can be obtained by education practitioners, and these massive data need to be processed in order to be used by people. Based on the classical algorithm and technical principle of data mining, this paper designs and implements a teaching analysis system based on data mining, which mainly provides the related functions of clustering analysis, regression analysis and association analysis for users. According to the K-means algorithm, the students data are divided into several clusters in order to complete the clustering analysis of the students' scores. FP-Growth algorithm is used to analyze the strong association rules between courses. Through Python's drawing package, the data can be displayed clearly and intuitively; thus completing the data visualization. Finally, a user-friendly interface is built by PyQt5, and the analysis results are visualized and output.

引用

页码：4400 / 4405

页数：6

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