Affiliation:
1. Huai’an Campus of Nanjing Forestry University, Nanjing, Jiangsu 210037, China
2. School of Mechatronics and Information, Wuxi Vocational Institute of Arts and Technology, Yixing 214206, China
Abstract
In order to overcome the problems of low accuracy, low recommendation efficiency, and low user satisfaction of educational resources recommendation algorithm, this paper proposes a personalized recommendation algorithm for online educational resources based on knowledge association. Firstly, online education resources are collected according to association rules. Secondly, firefly algorithm is used to classify online education resources. Then, the vector space function is constructed to filter the classified online education resources. Finally, the correlation between knowledge points is calculated by knowledge association theory, and the knowledge with the highest user interest is selected as the target recommendation resource to realize the personalized recommendation of online education resources. The resource recommendation accuracy of this method can reach 97%, the recommendation time is less than 5.0 s, and users are more satisfied with it, indicating that its recommendation effect is good.
Funder
Research Project of Educational Informatization in Jiangsu Province
Subject
General Mathematics,General Medicine,General Neuroscience,General Computer Science
Reference15 articles.
1. Network education recommendation and teaching resource sharing based on improved neural network
2. Educational resource online evaluation system based on neural network dynamic feedback algorithm[J];Y. Han;Journal of Intelligent and Fuzzy Systems,2020
3. Mode Optimization and Rule Management of Intellectual Property Rights Protection of Educational Resource Data Based on Machine Learning Algorithm
4. Accurate recommendation algorithm of agricultural massive information resources based on knowledge map[J];H. Yu;Computer Simulation,2021
5. A collaborative filtering recommendation method for online learning resources incorporating the learner model;F. Liu;CAAI Transactions on Intelligent Systems,2021
Cited by
4 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献