Weakly supervised setting for learning concept prerequisite relations using multi-head attention variational graph auto-encoders

Author:

Zhang JuntaoORCID,Lan Hai,Yang Xiandi,Zhang Shuaichao,Song WeiORCID,Peng ZhiyongORCID

Funder

Key Technologies Research and Development Program

National Key Research and Development Program of China

Major Science and Technology Project of Hainan Province

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Management Information Systems,Software

Reference46 articles.

1. Concepts and cognitive science;Laurence,1999

2. Resources sequencing using automatic prerequisite-outcome annotation;Changuel;ACM Trans. Intell. Syst. Technol.,2015

3. Jean Michel Rouly, Huzefa Rangwala, Aditya Johri, What are we teaching?: Automated evaluation of CS curricula content using topic modeling, in: Proceedings of the 11th Annual International Conference on International Computing Education Research, 2015, pp. 189–197.

4. Jibing Gong, Shen Wang, Jinlong Wang, Wenzheng Feng, Hao Peng, Jie Tang, Philip S. Yu, Attentional graph convolutional networks for knowledge concept recommendation in MOOCs in a heterogeneous view, in: Proceedings of the 43rd International ACM Conference on Research and Development in Information Retrieval, 2020, pp. 79–88.

5. Learning concept graphs from online educational data;Liu;J. Artif. Intell. Res.,2016

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4. WikiCPRL: A Weakly Supervised Approach for Wikipedia Concept Prerequisite Relation Learning;Lecture Notes in Computer Science;2024

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