Research and Implementation of Learning Resource Recommendation Method for Online Education

The role of learning resource recommendation in online education is very important, but there is a problem that the recommendation is unreasonable. Traditional resource integration methods cannot solve the problems of resource arrangement and resource classification in massive data, and the recommendation effect is not satisfactory. Therefore, this paper proposes an online recommendation algorithm. Firstly, the resource planning theory is used to divide the resources and realize the preprocessing of resource recommendation. Then, use online division to form a collection of resource recommendations. MATLAB simulation shows that the recommendation accuracy and readability of online recommendation algorithms are better than traditional resource integration methods under certain requirements of online education.