Affiliations:
North China University of Science and Technology, Tangshan, Hebei, China
Correspondence:
[*]
Corresponding author. Qiuju Feng, North China University of Science and Technology, Tangshan, Hebei, China.
E-mail: wujian753159@163.com.
Abstract: If the online education platform simply presents offline course content and teaching resources, it will result in poor interaction between teachers and students and poor student learning efficiency because of the time and space barriers in distance education. At the same time, it has a one-way teaching for all students without any difference, so its personalization is poor. In order to improve the efficiency of network education knowledge recommendation, based on the traditional neural network, this study combines the actual needs of network education to construct an improved neural network-path sorting algorithm. Moreover, this study builds a network education knowledge recommendation system based on the algorithm and explores the functions of each module of the system to realize all system functions. In addition, this study performs system function tests on a complete system. The results show that the proposed algorithm is higher than the traditional recommendation algorithm in recommendation effect and recommendation efficiency, and has certain practical effects, and can provide theoretical reference for subsequent related research.
