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昆明冶金高等专科学校学报 ›› 2025, Vol. 41 ›› Issue (1): 70-.DOI: 10.3969/j.issn.1009-0479.2025.01.010

• 电子信息技术 • 上一篇    

关联规则挖掘在高校师生政治理论学习中的应用


  

  1. 昆明冶金高等专科学校 a.校团委;b.计算机信息学院,云南 昆明 65003
  • 收稿日期:2023-02-01 出版日期:2025-02-07 发布日期:2025-09-28
  • 作者简介:欧阳志平 (1985-),男,湖南邵阳人,讲师,理学硕士,主要从事数据库、数据挖掘研究。
  • 基金资助:
    云南省教育厅科学研究基金项目 “模糊对象的空间 colocation模式挖掘及可视化研究” (2022J1309);昆明 冶金高等专科学校科研基金项目 “数据挖掘技术在师生政治理论学习中的应用研究”(2020XJSK04)。

The Application of Association Rule Mining in PoliticalTheory Learning for Teachers and Students

  1. a. Youth League Committee; b. Faculty of Computer Information, Kunming Metallurgy College, Kunming 650033, China
  • Received:2023-02-01 Online:2025-02-07 Published:2025-09-28

摘要: 针对目前高校师生政治理论学习中存在的内容针对性不强、缺乏精细化管理等问题,提出基于关联规 则的数据挖掘技术在师生政治理论学习中的应用研究,通过分析并提取师生政治理论学习对象特征,利用关联 规则算法挖掘特征间的关联关系,并根据结果开展差异化、有针对性的学习。首先是建立问题模型;其次通过 Apriori算法对对象进行关联规则挖掘,同时通过剪枝处理提出优化算法,加快规则集的产生,提升算法效率; 最后通过大量实验来证明问题模型、算法及剪枝算法的有效性。

关键词: 关联规则, 数据挖掘, 政治理论学习

Abstract:  Currently, there are several issues in teacher and student political theory learning, such as in-sulficient relevance and lack of refined management. This paper explores the application of associationrule mining technology in teacher and student politieal theory learning. By analyzing and extracting thecharacteristies of teacher and student learning objects, the paper mines the relationships between thesefeatures using association rule algorihms. Based on the results , differentiated and targeted learning strat.egies are implemented. Firstly, a problem model is established. Secondly, the Apriori algorihm is applied to mine association rules from the dataset. Additionally, an optimization algorithm using pruningtechniques is proposed to accelerate rule generation and improve algorithm elficiency. Finally, extensiveexperiments are conducted to verily the effectiveness of the problem model, algorithms, and pruning tech-niques.

Key words: association rules, data mining, political theory learning