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- W4297846228 abstract "In the context of the new crown epidemic, online education courses have become mainstream. Along with the rapid development of the Internet and the rich reserves of educational resources, how to accurately understand the state of students to provide the required teaching courses, and how to better adapt students to online education to meet the differentiation between each other has become a mainstream problem and challenge at present. Analyze the user data, obtain the decision attributes therein, and explore the classification of online education courses; based on collaborative filtering algorithm, realize the accurate matching between students and courses. The intelligent recommendation strategy of online courses not only helps to improve the usage rate of online courses, but also helps to improve students' individuality, responding to the general policy of stopping classes and not studying in major universities, and carrying out more flexible teaching methods." @default.
- W4297846228 created "2022-10-01" @default.
- W4297846228 date "2021-01-01" @default.
- W4297846228 modified "2023-09-28" @default.
- W4297846228 title "An Intelligent Recommendation Strategy for Online Courses Based on Collaborative Filtering Algorithm for Educational Platforms" @default.
- W4297846228 doi "https://doi.org/10.25236/fer.2021.041605" @default.
- W4297846228 hasPublicationYear "2021" @default.
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