Design and Application of Intelligent Analysis System for Ideological Guidance Education and Mental Health in Colleges and Universities Based on Big Data

Zhijun Wu
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Abstract

: With the development of the times and changes in society, the social environment faced by college students is constantly changing. Their own learning initiative, hobbies, academic performance, the expansion of the gap between the rich and the poor in the family, and the pressure of employment competition are all in the past. Different characteristics, the factors that induce their mental health problems also show more complex and diverse characteristics, Therefore, it is necessary to use a lot of data technology to conduct in-depth research on their mental health problems. This article aims to study the design and implementation of an intelligent BD-based mental health analysis system for colleges and universities(CAU). In this study, when analyzing the causes of mental health problems, a comprehensive use of various data and related analysis techniques for in-depth mining and analysis, to make the results of the analysis more logical and effective. This article first analyzes the basic principles of data mining and data warehousing in detail, group analysis methods, anomaly extraction methods, and correlation algorithms, and then designs an algorithm-based algorithm-based mining anomaly algorithm for fast data retrieval. At this point, students who may have mental health problems can be identified. Analysis of logic based on real data can provide a reliable basis for psychological teachers, thereby improving the efficiency and effectiveness of school psychological counseling. Experimental research results show that the system has the most accurate analysis of abnormal eating and sleep states, with 91.61%, and the lowest detection accuracy in psychotic abnormal states, with only 61.28%. In abnormal states such as depression, anxiety, paranoia, and horror, The test results are relatively accurate, about 80%. It is still necessary to strengthen the overall configuration and design of the system to maximize its value in practical applications.
基于大数据的高校思想指导教育与心理健康智能分析系统设计与应用
随着时代的发展和社会的变化,大学生所面临的社会环境也在不断变化。自己的学习主动性、爱好、学习成绩、家庭贫富差距的扩大、就业竞争的压力,都成为过去。不同的特点,诱发其心理健康问题的因素也表现出更加复杂多样的特点,因此,有必要利用大量的数据技术对其心理健康问题进行深入的研究。本文旨在研究基于智能bd的高校心理健康分析系统的设计与实现。本研究在分析心理健康问题的成因时,综合运用各种数据和相关分析技术进行深入挖掘和分析,使分析结果更具逻辑性和有效性。本文首先详细分析了数据挖掘和数据仓库的基本原理、分组分析方法、异常提取方法、关联算法,然后设计了一种基于算法的基于算法的异常挖掘算法,实现快速的数据检索。在这一点上,可能有心理健康问题的学生可以被识别出来。基于真实数据的逻辑分析可以为心理教师提供可靠的依据,从而提高学校心理咨询的效率和效果。实验研究结果表明,该系统对异常饮食和睡眠状态的分析准确率最高,为91.61%,对精神类异常状态的检测准确率最低,仅为61.28%。在抑郁、焦虑、偏执、恐怖等异常状态下,测试结果相对准确,约为80%。还需要加强系统的整体配置和设计,使其在实际应用中的价值最大化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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