TY - GEN
T1 - University Course Recommendation Based on Multi-source Educational Knowledge Graph
AU - Peng, Junsheng
AU - Long, Jiang
AU - Guo, Yangming
AU - Wang, Jin
AU - Zheng, Bo
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - In response to the course recommendation problem in the undergraduate teaching scenario of higher education, a recommendation algorithm based on a multi-source educational knowledge graph is proposed. Firstly, the course correlation is analyzed, and relevant data is extracted from various databases of the university for preprocessing. Then, a multi-path RNN encoding method is proposed to embed multi-source information into the educational knowledge graph. Subsequently, an MLP is utilized to model the interaction between students and courses, aiming to predict student course selections. Finally, a comparative experiment is conducted to validate the feasibility of the university recommendation method based on the multi-source educational knowledge graph.
AB - In response to the course recommendation problem in the undergraduate teaching scenario of higher education, a recommendation algorithm based on a multi-source educational knowledge graph is proposed. Firstly, the course correlation is analyzed, and relevant data is extracted from various databases of the university for preprocessing. Then, a multi-path RNN encoding method is proposed to embed multi-source information into the educational knowledge graph. Subsequently, an MLP is utilized to model the interaction between students and courses, aiming to predict student course selections. Finally, a comparative experiment is conducted to validate the feasibility of the university recommendation method based on the multi-source educational knowledge graph.
KW - course recommendation
KW - educational data mining
KW - higher education
KW - knowledge graph
UR - http://www.scopus.com/inward/record.url?scp=85197206125&partnerID=8YFLogxK
U2 - 10.1109/ICCBD-AI62252.2023.00132
DO - 10.1109/ICCBD-AI62252.2023.00132
M3 - 会议稿件
AN - SCOPUS:85197206125
T3 - Proceedings - 2023 4th International Conference on Computer, Big Data and Artificial Intelligence, ICCBD+AI 2023
SP - 727
EP - 732
BT - Proceedings - 2023 4th International Conference on Computer, Big Data and Artificial Intelligence, ICCBD+AI 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 4th International Conference on Computer, Big Data and Artificial Intelligence, ICCBD+AI 2023
Y2 - 15 December 2023 through 17 December 2023
ER -