Intelligent Integration Method of Ideological and Political Education Resources Based on Deep Mining

• Published in: Mobile information systems Vol. 2022; pp. 1 - 10
• Main Authors: Li, Aiqin, Huang, Yuzhen
• Format: Journal Article
• Language: English
• Published: Amsterdam Hindawi 21.04.2022; John Wiley & Sons, Inc
• Subjects: Accuracy; Algorithms; Artificial intelligence; Classification; Cluster analysis; Clustering; College students; Data mining; Decision trees; Education; Feature extraction; Ideology; Information theory; Knowledge management; Segmentation; Social responsibility; Software; Stability; User needs; Values
• ISSN: 1574-017X; 1875-905X; 1875-905X
• DOI: 10.1155/2022/5144556

An intelligent integration method of ideological and political education resources based on deep mining is proposed to address the problems of low accuracy, efficiency, and stability of resource integration in the current ideological and political education resource integration method. The ideological and political education resources are deeply mined by studying deep mining technology and applying the decision tree algorithm. Preprocess the text of ideological and political education materials after you've dug deep into the ideological and political education resources. Word segmentation based on user dictionary to remove rare words in ideological and political education resources. Based on the principle of educational information remote scheduling, the feature vector of ideological and political education resources is extracted, the characteristic variance contribution rate of ideological and political education resources is calculated, and the observable random vector of the characteristics of ideological and political education resources is obtained. To achieve intelligent integration of ideological and political education resources, the correlation degree is defined using the LDA model's subject text vector, and the text of ideological and political education resources is grouped using the bottom-up hierarchical clustering approach. The experimental results show that the proposed method has high accuracy and efficiency, and can effectively enhance the stability of the intelligent integration of ideological and political education resources.