Design of Auxiliary Monitoring Platform for College Students' Mental Health Education based on Internet Trace Data Mining

Abstract

Combined with the network traces of scientific research groups, data are obtained through tools such as web crawlers, and key indicators of scientific research group ability evaluation are selected, and a scientific research ability cluster analysis method based on PAM algorithm is established. The psychological characteristics of college students are analyzed, and the psychological characteristics are introduced Some basic knowledge of evaluation and mental health, and fully analyzed and explained the necessity of developing this platform. Active traces and passive traces, dominant traces and invisible traces, etc.; and propose different data acquisition methods for different network traces. The platform uses object-oriented technology to develop the entire system, mainly using ASP.NET and AJAX technology to develop.