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Analysis and Research of Psychological Education Based on Data Mining Technology
Author(s) -
Hai-Yun Sang
Publication year - 2021
Publication title -
security and communication networks
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.446
H-Index - 43
eISSN - 1939-0114
pISSN - 1939-0122
DOI - 10.1155/2021/8979507
Subject(s) - state (computer science) , computer science , psychological health , the internet , point (geometry) , crisis intervention , psychological research , mental health , artificial intelligence , applied psychology , psychology , social psychology , clinical psychology , world wide web , algorithm , psychotherapist , geometry , mathematics
With the era of the Internet, linking the prevention and treatment of mental health problems in colleges and universities with the Internet will become a general trend. In order to improve the effect of identifying the psychological crisis state of college students, a method of identifying the psychological crisis state of college students based on data mining technology is proposed. First, we analyze the current research progress of college students’ psychological crisis state recognition and point out the defects of the current college students’ psychological crisis state recognition methods; then, we collect college students’ psychological crisis state data and use the support vector machine in data mining technology to analyze the psychological crisis state data. We analyze and model and then establish the recognition model of college students’ psychological crisis state; finally, we carry out the simulation experiment of college students’ psychological crisis state recognition. The experimental results show that the accuracy rate of college students’ psychological crisis state recognition by this method is over 90%, and the rejection rate and misrecognition rate are extremely low. The recognition effect is significantly better than other methods, and it can provide valuable information for college student psychological management personnel.

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