Innovation of Computer-assisted Instruction Mode of News Dissemination Course Based on Improved Collaborative Filtering Algorithm

被引:0
作者
He W. [1 ]
机构
[1] School of Media, HENAN Vocational Institute of Arts, Henan, Zhengzhou
关键词
Collaborative Filtering; Computer-Assisted Instruction; Course Recommendation; News Dissemination;
D O I
10.14733/cadaps.2024.S10.225-239
中图分类号
学科分类号
摘要
Computer-assisted instruction (CAI) refers to the proper selection and full and reasonable use of computer media for teaching assistance under the normal teaching mode, so as to achieve good teaching results. With the increasing quantity of online users and courses, the course suggestion system exposes some problems such as diverse user characteristics, complex student interests and preferences, and changeable user behaviors, which reduces the accuracy of the suggestion algorithm. This article proposes a individualized model of news dissemination course resources based on improved collaborative filtering (CF) algorithm. This model transforms student's interest behavior into student's interest keyword score, and changes in student's interest into changes in student's interest keyword score, so as to establish and update the student's interest model. The improved CF recommendation model can recommend course resources for students in a individualized and customized way, and can effectively enhance students' learning interest. On the basis of improving the sparsity and timeliness of data, the improved algorithm can improve the accuracy of course suggestion and satisfy users. © 2024 U-turn Press LLC.
引用
收藏
页码:225 / 239
页数:14
相关论文
共 19 条
[11]  
Pei Z., Wang Y., Analysis of computer aided teaching management system for music appreciation course based on network resources, Computer-Aided Design and Applications, 19, pp. 1-11, (2021)
[12]  
Tahir S., Hafeez Y., Abbas M.-A., Nawaz A., Hamid B., Smart learning objects retrieval for E-Learning with contextual recommendation based on collaborative filtering, Education and Information Technologies, 27, 6, pp. 8631-8668, (2022)
[13]  
Thakker U., Patel R., Shah M., A comprehensive analysis on movie recommendation system employing collaborative filtering, Multimedia Tools and Applications, 80, 19, pp. 28647-28672, (2021)
[14]  
Tohidi N., Dadkhah C., Improving the performance of video collaborative filtering recommender systems using optimization algorithm, International Journal of Nonlinear Analysis and Applications, 11, 1, pp. 483-495, (2020)
[15]  
Wang X., Building a parallel corpus for English translation teaching based on computer-aided translation software, Computer-Aided Design and Applications, 18, pp. 175-185, (2021)
[16]  
Xin Y., Henan B., Jianmin N., Wenjuan Y., Honggen Z., Xingyu J., Pengfei Y., Coating matching recommendation based on improved fuzzy comprehensive evaluation and collaborative filtering algorithm, Scientific Reports, 11, 1, (2021)
[17]  
Xu Y., Computer-aided design of personalized recommendation in teaching system, Computer-Aided Design and Applications, 17, pp. 44-56, (2019)
[18]  
Zhao H., Guo L., Design of intelligent computer aided network teaching system based on web, Computer-Aided Design and Applications, 19, pp. 12-23, (2021)
[19]  
Zhou Y., Liu L., Lee K., Palanisamy B., Zhang Q., Improving collaborative filtering with social influence over heterogeneous information networks, ACM Transactions on Internet Technology (TOIT), 20, 4, pp. 1-29, (2020)