Research on Clustering Recommendation Based on analysis of students of College English Source Data in Chinese Mainland
J. S. Huang, Haibing Hou · 2023
Due to the current shortage of educational resources, it is difficult to teach in line with the students’ ability. This paper aims to use data mining and artificial intelligence technology to explore the clustering recommendation research based on the analysis of learning situation of college English source data in Chinese Mainland. For one thing, the source data is analyzed to find the differences in English proficiency among students followed by the application of KMeans clustering. For another, based on user and article association rules, the collaborative filtering recommendation algorithm is combined to cluster recommendation providing personalized English learning resources and learning paths for students in the "second classroom". This study is expected to provide reference for personalized recommendation and optimization of college English education and improve the quality of education.