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Research on Precise Ideological and Political Education Based on Improved K-means Algorithm for College Students' Portrait Construction

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DOI: 10.23977/jaip.2023.060408 | Downloads: 9 | Views: 342

Author(s)

Qingpeng Huang 1

Affiliation(s)

1 School of Automobile, Guangdong Mechanical & Electrical Polytechnic, Guangzhou, 510550, China

Corresponding Author

Qingpeng Huang

ABSTRACT

In order to analyze the performance of college students' learning and life in all aspects during their stay in school, by collecting quantitative daily life behavior data such as moral, intellectual, physical, aesthetic and labor of college students, the attribute characteristics used to construct student user portraits are selected, and the data analysis model is established by using the improved K-means algorithm to select the initial center point.Based on K-means clustering technology, this paper analyzes student behavior data and student achievement data. The students' performance is divided into six dimensions: professional performance, sports performance, competition performance, scholarship level, student cadre status, and second classroom performance. Drawing a crowd portrait that can fully show the students ' ability, accurately evaluate the students ' comprehensive ability, and realize the scientificity and feasibility of accurate ideological and political education.

KEYWORDS

K-means clustering algorithm; Ideological and political education; Crowd portrait; Student performance

CITE THIS PAPER

Qingpeng Huang, Research on Precise Ideological and Political Education Based on Improved K-means Algorithm for College Students' Portrait Construction. Journal of Artificial Intelligence Practice (2023) Vol. 6: 58-64. DOI: http://dx.doi.org/10.23977/jaip.2023.060408.

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