Network education recommendation and teaching resource sharing based on improved neural network

Abstract

Intelligent network teaching system provides learners with abundant teaching resources and convenient, excellent and efficient learning environment. However, network teaching resources are widely distributed and difficult to centralize. Resource sharing has become a key problem to be solved in the network environment. The current research on online education resource recommendation mainly focuses on offline education, and there are few studies on online education resources. Based on this, this study studies the link prediction methods in online education and establishes appropriate models for online education. In the research, through improved analysis of traditional algorithms, an improved neural network path sorting algorithm based on path sorting method is proposed. At the same time, we use the path sorting algorithm based on random walk model and neural network-path sorting algorithm to realize the link prediction problem in the online learning knowledge base. In addition, the performance analysis of the algorithm is carried out by contrast method, and the performance comparison analysis is carried out by combining various common traditional recommendation algorithms with the research algorithm of this study.

Study on Resource Sharing Strategy of e-Commerce Innovation and Entrepreneurship Education Based on Cloud Computing

“…high load and low load conditions, up to 97%. In other literature studies, the safety of system in reference [9] is relatively high and that of reference [15] is relatively low. e reason for the good security performance of the system in this paper is that during the construction of the platform, an access tool is designed to detect the security performance regularly and the administrator will also maintain the security of the system in daily operation, which improves the security of the platform built in this paper.…”

“…It provides a theoretical reference for the new cooperative practice to require physical education planning, and the research of this method is relatively single. e work in [9] points out that resource sharing has become a key problem to be solved in the network environment. is paper studies the link prediction method in online education and establishes an appropriate model for online education.…”

“…By selecting load capacity and response time as indicators, the performance of platforms of this paper and [9], [10], [14], and [15] is compared and tested. e response time refers to the time when the system makes the response when the user visits; the shorter the response time, which indicates that the higher the efficiency of the system, the higher the user experience.…”

“…e educational resource sharing platform in this paper can better cope with the system load. e security is high under Reference [9] Reference [10] Reference [14] Reference [15] Figure 8: Performance test analysis of the platform. high load and low load conditions, up to 97%.…”

An English Reading and Learning System Based on Web

“…(1) Calculate the weight vector of online learning resources. To solve the online learning resource recommendation model based on multiobjective optimization strategy [15,16], first decompose the online learning resource problem so that each online learning resource subproblem corresponds to a θ vector and calculate the weight vector of the online learning resource subproblem:…”