Research Article
Design of Push Algorithm for Individualized Course Content of College Public Art Education Online Education
@INPROCEEDINGS{10.1007/978-3-031-51465-4_12, author={Fang Li and Jie Li}, title={Design of Push Algorithm for Individualized Course Content of College Public Art Education Online Education}, proceedings={e-Learning, e-Education, and Online Training. 9th EAI International Conference, eLEOT 2023, Yantai, China, August 17-18, 2023, Proceedings, Part I}, proceedings_a={ELEOT}, year={2024}, month={1}, keywords={Convolution Neural Network Fuzzy Weighting Collaborative Filtering Algorithm Resource Push Teaching Resources College Education Public Art Education}, doi={10.1007/978-3-031-51465-4_12} }- Fang Li
Jie Li
Year: 2024
Design of Push Algorithm for Individualized Course Content of College Public Art Education Online Education
ELEOT
Springer
DOI: 10.1007/978-3-031-51465-4_12
Abstract
In order to improve the adaptability of online education personalized course push resources and user demand resources, and reduce the push time, a new push method is designed for online education personalized course content of Public art education courses in colleges and universities. A collaborative filtering algorithm is introduced to determine the target content to be pushed. Through screening similar users, we can master the demand directions of different types of users for course content, and realize the calculation of user preferences. We introduce convolution neural networks to train the data information in the convolution layer of convolution neural networks, obtain the characteristic parameters of course content, and conduct directional extraction of course content of public art education. We introduce a weighted fuzzy calculation method to determine the recommendation levels of course content in combination with the spatial expression of course content, and realize the active recommendation of course content. Experimental results show that the proposed method can reduce the discrepancy between the content of push-forward course and user’s demand, and ensure a higher adaptability between the content and user’s demand.
