Frontiers of Data and Domputing ›› 2022, Vol. 4 ›› Issue (3): 3-18.

CSTR: 32002.14.jfdc.CN10-1649/TP.2022.03.001

doi: 10.11871/jfdc.issn.2096-742X.2022.03.001

• Special Issue: Advanced Intelligent Computing Platform and Application • Previous Articles     Next Articles

Online Educational Resources Recommendation System Based on Knowledge Graph Technology

LUO Jiexi(),LIU Shuai(),ZHANG Yuzhi(),LI Zhengdan(),SUN Yufei(),ZHANG Shenglin()   

  1. Department of Software, Nankai University, Tianjin 300350, China
  • Received:2022-02-06 Online:2022-06-20 Published:2022-06-20
  • Contact: ZHANG Yuzhi E-mail:thevolga@163.com;978951827@qq.com;zyz@nankai.edu.cn;lzd@nankai.edu.cn;yufei_sun@sina.com;zhangsl@nankai.edu.cn

Abstract:

[Objective] Based on the field of online educational resources, this paper designs and implements a mixed recommendation system of educational resources by knowledge graph technology. [Context] Online educational resources are diverse and numerous and lack standardized construction and systematic management. It is inconvenient for the teachers to manage educational resources and for the learners to find effective information. [Methods] By designing knowledge graph data structure, we construct knowledge semantic association of the whole discipline and integrate graph embedding and rule extraction to realize the educational resource recommendation. [Results] The proposed methodology in this paper has been applied to the educational resource online platform of Nankai University, which achieves remarkable results in the recommendation of knowledge points in multi-disciplinary fields. [Conclusions] By analyzing the experimental results, it turns out that the proposed recommendation system can alleviate the "long tail effect" to some extent, and its practicability is verified by visual case analysis.

Key words: knowledge graph, educational resource, recommendation system, graph embedding