Design of the University Psychological Health Management System Based on Data Discovery

Abstract

University students’ psychological state has not only an impact on their individual development but also on the campus’s stability, which in turn has an impact on social cohesion and the general enhancement of human excellence. This article aims to conduct an in-depth study on the management system of psychological health in universities based on data discovery to determine whether university students have psychological problems in time, prevent extreme phenomena, and enhance the efficiency of psychological counseling in universities. This study initially discusses the general functional structure of the mental health management system at universities before breaking it down into three primary modules: user information function management; psychological testing and psychological caution; and psychological counseling management. Furthermore, it analyses and classifies data from the mental health management system using decision tree algorithms written in C4.5. It can effectively solve the problem of multiple attributes that tend to select values when selecting test attributes of the information gain by using the index of split as the information gain rate, which completes the design of the mental health management system by utilizing data discovery. The simulation experiments of the proposed work show that the suggested system has high security and accuracy of discovery, which can effectively improve the efficiency of psychological counseling work in universities.