PQSCT: Pseudo-Siamese BERT for Concept Tagging With Both Questions and Solutions-Reference-Cited by-同舟云学术

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PQSCT: Pseudo-Siamese BERT for Concept Tagging With Both Questions and Solutions

Published:2023-10 Issue:5 Volume:16 Page:831-846
ISSN:1939-1382
Container-title:IEEE Transactions on Learning Technologies
language:
Short-container-title:IEEE Trans. Learning Technol.

Author:

Huang Tao¹^ORCID,Hu Shengze²^ORCID,Yang Huali³^ORCID,Geng Jing¹^ORCID,Liu Sannyuya¹,Zhang Hao¹^ORCID,Yang Zongkai¹^ORCID

Affiliation:

1. National Engineering Research Center of Educational Big Data, Central China Normal University, Wuhan, China

2. Faculty of Artificial Intelligence in Education, Central China Normal University, Wuhan, China

3. School of Computer Science and Artificial Intelligence, Wuhan Textile University, Wuhan, China

Funder

State Key Program of National Natural Science of China

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Science Applications,General Engineering,Education

Link

http://xplorestaging.ieee.org/ielx7/4620076/10287010/10123979.pdf?arnumber=10123979

Reference68 articles.

1. Longformer: The long-document transformer;beltagy,2020

2. Momentum Contrast for Unsupervised Visual Representation Learning

3. Circle Loss: A Unified Perspective of Pair Similarity Optimization

4. A Dynamic Knowledge Diagnosis Approach Integrating Cognitive Features

5. No reference quality assessment for screen content images

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