Political Thought Pre-Alarm Mechanism of Campus Emergencies Based on Data Mining Technology

Abstract

Political thought education is the lifeblood of all work. It is a critical and urgent task for current political thought education and campus management to investigate how to effectively prevent and respond to campus emergencies in a scientifically sound manner. This paper examines and evaluates the current state of political thought as a pre-alarm system for campus emergencies. Then, using DM technology, the cluster analysis algorithm and correlation analysis algorithm are used to mine and analyze potential links in the massive data on campus, study the characteristics of students’ behaviours, analyze the rules of students’ behaviours, and cluster out the categories of students’ behaviours. The political thought pre-alarm model of campus emergencies is built on this foundation. This pre-alarm model is compared to two other emergency pre-alarm models in order to ensure its reliability and applicability. Many experimental results show that this pre-alarm model has a prediction accuracy of up to 94.68 percent, which is higher than the traditional pre-alarm model’s 9.17 percent. The application of DM technology to political thought pre-alarm of campus emergencies has produced positive results in this paper. It has some theoretical and practical implications for the field of political thought prior to the campus emergency alarm.

Secure MapReduce Framework with Data Compression Model to Evaluate Ideological Evaluation Contribution on Students

“…However, ideological evaluation can also be divisive, as it can reinforce existing divisions and create new ones. When students are exposed to ideological perspectives that are different from their own, it can create tension and conflict, especially if the ideological differences are seen as fundamental and non-negotiable [3]. Furthermore, ideological evaluation can be used to promote particular agendas or values, which may not necessarily be objective or inclusive.…”