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Application of Big Data Technology in the Research on Mental Health Education of College Students from Poverty-Stricken Families

机译:大数据技术在贫困家庭大学生心理健康教育研究中的应用

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In the information age, the big data technology has been applied to all walks of life, bringing a new angle of thinking to personal life and social development. The mental health education problems have been increasingly prominent among college students and gradually become a focus of attention from universities and colleges, families and society due to the particularity of their identity and severity of their impacts. Affected by various factors, these students are more susceptible to some unhealthy mental states and mental problems in daily study and life. In this paper, the K-means clustering algorithm and C4.5 decision tree algorithm were used to establish mental health databases based on the Hadoop technology. The limitations of physical space were broken through and those of static data were improved through the data collection and processing, storage and management, analysis and mining, etc., so as to realize the accurate recognition, comprehensive mastery, coordinated development and active forewarning of students from poverty-stricken families. This study can further enhance the timeliness and pertinence of mental health education among college students from poverty-stricken families and drive the students to welcome healthy growth and become useful persons.
机译:在信息时代,大数据技术已经应用到各行各业,为个人生活和社会发展带来了新的思维视角。大学生心理健康教育问题日益突出,由于其身份的特殊性和影响的严重性,逐渐成为高校、家庭和社会关注的焦点。受各种因素的影响,这些学生在日常学习和生活中更容易出现一些不健康的心理状态和心理问题。本文研究了K-均值聚类算法和C4。5.基于Hadoop技术,采用决策树算法建立心理健康数据库。通过数据收集与处理、存储与管理、分析与挖掘等,突破物理空间的局限性,改善静态数据的局限性,实现贫困家庭学生的准确识别、全面掌握、协调发展和主动预警。本研究可以进一步提高贫困家庭大学生心理健康教育的时效性和针对性,推动贫困家庭大学生健康成长成才。

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