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A knowledge set recommendation method for online education in universities based on DV-TransE model and social networks

Author

Listed:
  • Die Meng
  • Beibei Ma
  • Zhanlei Shang

Abstract

In order to improve the recommendation accuracy of existing online education knowledge sets in universities and shorten the recommendation response time, a recommendation method for online education knowledge sets in universities based on DV-TransE model and social network is proposed. This method is first based on the principle of knowledge graph, extracting descriptive features of the knowledge set, and introducing the TransE algorithm to construct the DV-TransE model of the online education knowledge set in universities. Then, based on social networks, the similarity between users is calculated, and finally, it is combined with the constructed knowledge set DV-TransE model to achieve recommendation of online education knowledge sets in universities. The experimental results show that after the application of the proposed method, its recommended response time is less than 14.5 ms, and the recommendation accuracy is as high as 95%, which is superior to the comparison method.

Suggested Citation

  • Die Meng & Beibei Ma & Zhanlei Shang, 2024. "A knowledge set recommendation method for online education in universities based on DV-TransE model and social networks," International Journal of Networking and Virtual Organisations, Inderscience Enterprises Ltd, vol. 30(1), pages 44-56.
    • Handle: RePEc:ids:ijnvor:v:30:y:2024:i:1:p:44-56
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