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

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 ideologic...

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Vydáno v:Mobile information systems Ročník 2022; s. 1 - 10
Hlavní autoři: Li, Aiqin, Huang, Yuzhen
Médium: Journal Article
Jazyk:angličtina
Vydáno: Amsterdam Hindawi 21.04.2022
John Wiley & Sons, Inc
Témata:
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
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Shrnutí: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.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1574-017X
1875-905X
DOI:10.1155/2022/5144556