scholarly journals Application of Association Rule Data Mining in Statistical Analysis of College Students' Mental Health

CONVERTER ◽  
2021 ◽  
pp. 716-724
Author(s):  
Hongrui Zhang
Keyword(s):  
Mental Health ◽  
College Students ◽  
Data Mining ◽  
Big Data ◽  
Data Analysis ◽  
Statistical Analysis ◽  
Statistical Data ◽  
Knowledge Map ◽  
Statistical Indicators ◽  
Big Data Technology

Strengthening the application of big data technology in data analysis can effectively improve the service capability and level of relevant statistics, and provide comprehensive and reliable information support for macro decision-making and trend analysis. This paper comprehensively reviews the research status of big data technology in the field of college students' mental health at home and abroad. Combining with the characteristics of college students' mental health statistical data and the weaknesses in statistical analysis, the feasibility of using knowledge mapping technology is demonstrated. On this basis, the blood relationship graph and influence analysis among the statistical indicators of college students' mental health were constructed through the knowledge map. The application of the knowledge map of college students' mental health statistical indicators in statistical data analysis, statistical indicator identification and statistical data quality management is proposed. Specifically, based on the concept of big data, we can establish a decision analysis platform for college students' mental health. Based on the big data technology, the data mining and analysis ability can be enhanced. In addition, it can change the traditional thinking of college students' mental health statistics and strengthen the construction of statistical team.

scholarly journals Modeling of Vocational College Students' Mental Health Based on Big Data Analysis

CONVERTER ◽  
2021 ◽  
pp. 620-626
Author(s):  
Chang Xiang-Wei
Keyword(s):  
Mental Health ◽  
College Students ◽  
Big Data ◽  
Data Analysis ◽  
Service System ◽  
Big Data Analysis ◽  
Psychological Status ◽  
Vocational College ◽  
Higher Vocational College ◽  
Self Service

With the rapid increase of employment pressure and academic pressure, the psychological status of higher vocational college students is increasingly concerned by schools and teachers. In order to ensure college students' mental health and provide timely and effective psychological counseling and guidance, this paper establishes an information-based mental health counseling platform. Based on big data analysis, this paper studies the modeling of Vocational College Students' mental health. This is the significance of mental health self-service system research under the background of big data. Based on the necessity of research on mental health self-service system and the psychological factors of higher vocational college students, this paper studies the technical framework and functional structure of mental health self-service system. This paper analyzes the difficulties encountered in the operation of the system, and puts forward solutions to build up the platform for the mental health information platform in the era of Internet plus.

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