Abstract
In the process of online course resource recommendation, the output of recommendation results is often unstable. Therefore, a physical education online course resource recommendation method based on collaborative filtering technology is proposed. Firstly, the learning preference of e-learners is calculated, the frequency index of the word frequency-inverse document is defined, the correlation between courses is reflected, and the specific needs of students for PE online course resource recommendation are understood. Then, the collaborative filtering recommendation algorithm is used to generate the similarity matrix and correlation matrix, update the edge characteristics of sports online curriculum resources, collect and refine the hidden index of sports online curriculum resources, optimize the prediction rules of the neighborhood of the most similar teaching unit, and complete the recommendation of sports online curriculum resources. Experimental results show that, for 1000 keywords, the method has the highest single average matching degree, the recommendation process is stable, and the F1 value is more than 0.9, and the practical application is ensured.
Highlights
Online course support platform can generally support thousands of courses and support the creation of the unlimited curriculum directory
Network course support platform can support the digital learning of schools and support the upload and download of resources, and resources can be classified into management and research
While the advantages of the web support platform are demonstrated in distance training, it has disadvantages, such as visualization of remote guidance and personalized recommendation of resources [1]
Summary
Hunan University of Humanities, Science and Technology, 417000 Hunan Loudi, China. Received 31 August 2021; Revised 26 September 2021; Accepted 18 October 2021; Published 29 October 2021. In the process of online course resource recommendation, the output of recommendation results is often unstable. Erefore, a physical education online course resource recommendation method based on collaborative filtering technology is proposed. En, the collaborative filtering recommendation algorithm is used to generate the similarity matrix and correlation matrix, update the edge characteristics of sports online curriculum resources, collect and refine the hidden index of sports online curriculum resources, optimize the prediction rules of the neighborhood of the most similar teaching unit, and complete the recommendation of sports online curriculum resources. Experimental results show that, for 1000 keywords, the method has the highest single average matching degree, the recommendation process is stable, and the F1 value is more than 0.9, and the practical application is ensured
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