Recommending Learning Objects through Attentive Heterogeneous Graph Convolution and Operation- Aware Neural Network (Extended Abstract)-Reference-Cited by-同舟云学术

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Recommending Learning Objects through Attentive Heterogeneous Graph Convolution and Operation- Aware Neural Network (Extended Abstract)

Published:2024-05-13 Issue: Volume: Page:5747-5748
ISSN:
Container-title:2024 IEEE 40th International Conference on Data Engineering (ICDE)
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Author:

Zhu Yifan¹,Lin Qika²,Lu Hao³,Shi Kaize⁴,Liu Donglei⁵,Chambua James⁶,Wan Shanshan⁷,Niu Zhendong⁵

Affiliation:

1. Beijing University of Posts and Telecommunications

2. National University of Singapore

3. Institute of Automation, Chinese Academy of Sciences

4. University of Technology Sydney

5. Beijing Institute of Technology

6. University of Dar-es-Salaam

7. Beijing University of Civil Engineering and Architecture

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10597630/10597390/10598126.pdf?arnumber=10598126

Reference5 articles.

1. Understanding Dropouts in MOOCs

2. Knowledge-based recommendation: a review of ontology-based recommender systems for e-learning

3. A learner oriented learning recommendation approach based on mixed concept mapping and immune algorithm

4. Composition-based multi-relational graph convolutional networks;Vashishth;ICLR 2020

5. MOOCCube: A Large-scale Data Repository for NLP Applications in MOOCs

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