Research on knn algorithm based on kmeans clustering and collaborative filtering hybrid algorithm in AI teaching

With the development of higher education in recent years, curriculum teaching is advocated to gradually change from experiential teaching to precision teaching, so it is increasingly urgent to analyze and apply the results of teaching process. The AI teaching platform makes detailed analysis of stud...

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Veröffentlicht in:Proceedings (International Conference on Information Systems Engineering. Online) S. 453 - 456
Hauptverfasser: Zhao, Yang, Zhang, Jun
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 23.06.2023
Schlagworte:
Analytical models
Clustering algorithms
Collaborative filtering
Education
Filtering algorithms
Hybrid algorithm
Information filters
kmeans
Knn
Systematics
ISSN:2643-7309
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Zusammenfassung:With the development of higher education in recent years, curriculum teaching is advocated to gradually change from experiential teaching to precision teaching, so it is increasingly urgent to analyze and apply the results of teaching process. The AI teaching platform makes detailed analysis of students' performance and excavates its deep application, and gives full play to the advantages of artificial intelligence through systematic classroom teaching to achieve precision and personalized teaching. This paper discusses the application principle of recommendation algorithm and collaborative filtering hybrid algorithm based on Knn-kmeans model in AI teaching platform. This paper analyzes the model method of analyzing teaching process results, and analyzes the personalized learning recommendation processing process based on Knn-kmeans model and collaborative filtering hybrid recommendation algorithm in detail.
ISSN:2643-7309
DOI:10.1109/ICISE60366.2023.00102