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基于Apriori算法的学生压力多元因素挖掘和分析

Mining and Analysis of Multiple Factors of Student Stress Based on Apriori Algorithm

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在多样的社会环境下,由于心理、生理、环境、学业、社会等多方面因素,导致学生压力剧增.为了找到影响学生压力的主要原因并解决学生压力过大问题,文章选用了多方面因素影响学生压力的数据集,利用Apriori算法研究了与学生压力相关的多方面因素的影响情况,分析了不同因素与压力的频繁项集和关联规则,发现了焦虑问题、睡眠问题、环境安全、霸凌等问题对学生压力影响较大.研究结果显示,减轻学业压力、抵制霸凌和改善学生生活环境有助于降低学生的压力.
In a variety of social environments,due to psychological,physiological,environmental,academic,social and other factors,the student stress has increased dramatically.In order to find the main causes of student stress and solve the problem of excessive student stress,this paper selects the dataset of multiple factors affecting student stress,uses the Apriori algorithm to research the influence situation of multiple factors related to student stress,and analyzes the frequent item sets and association rules of different factors and stress,then finds that anxiety problems,sleep problems,environmental safety,bullying and other problems have a great impact on student stress.Research results show that reducing academic stress,resisting bullying and improving the living environment of students can help reduce student stress.

student stressApriori algorithmmultiple factorsassociation rule

申悦、张一涵、王弯弯

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河南工业大学 人工智能与大数据学院,河南 郑州 450001

科大讯飞股份有限公司,安徽 合肥 230088

学生压力 Apriori算法 多元因素 关联规则

2024

现代信息科技
广东省电子学会

现代信息科技

ISSN:2096-4706
年,卷(期):2024.8(23)