Open AccessRETRACTED: Application of Clustering Algorithm in Ideological and Political Education in Colleges and Universities
Author(s) -
Qibin Wang
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1852/3/032041
Subject(s) - cluster analysis , ideology , computer science , field (mathematics) , political education , information technology , algorithm , sample (material) , data mining , canopy clustering algorithm , politics , artificial intelligence , correlation clustering , mathematics , political science , chemistry , chromatography , pure mathematics , law , operating system
In recent years, with the rapid development of information technology, China has entered the information age. Information technology has changed our life, but also affected the form of ideological and political education(IAPE) management in colleges and universities(CAU). Data mining technology based on clustering algorithm has been widely used in university education management, but the application research of this technology in the field of IAPE is still insufficient. Therefore, this paper puts forward the application research of clustering algorithm in IAPE in CAU. After research, this paper believes that the existing IAPE in CAU is still based on the traditional management mode, lack of data sensitivity and insufficient utilization of teaching information data. In view of this situation, according to the education and management needs of IAPE, combined with the characteristics of clustering algorithm, the traditional clustering algorithm is optimized and improved. Compared with the traditional algorithm, the improved algorithm simplifies the calculation steps, improves the accuracy of calculation, and is more suitable for the application in the field of IAPE in CAU. In order to further verify the actual effect of this algorithm, the improved clustering algorithm is verified by experiments. In this experiment, the proportion of the three types of fraction is 25%, 64.4%, 10.6%, which is much higher than the previous sample data. Analysis shows that the algorithm in this paper has played a positive role in improving the management effect of IAPE in CAU and promoting the optimization and reform of IAPE in China.