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Paper Abstract and Keywords
Presentation 2021-01-27 13:30
Automatic Short Answer Scoring using Thesaurus-Based Data Augmentation
Hiroyuki Kato (Kyushu Univ.), Tsunenori Ishioka (DNC), Tsunenori Mine (Kyushu Univ) AI2020-15
Abstract (in Japanese) (See Japanese page) 
(in English) In the field of natural language processing, the invention of large-scale general-purpose language models such as BERT has brought improvements in processing accuracy for various types of tasks, but the accuracy has not yet reached a practical level, also in automatic short answer scoring, and further improvements are desired. In this paper, we propose a method to improve the accuracy of automatic short answer scoring using a thesaurus to replace words in the answers. In an experiment using data from social studies and Japanese language mock exams for high school students, we found that the accuracy improved in the range with a small number of data for social studies and in the range with a large number of data for Japanese language. In addition, we found that in the case of highly accurate learning, the model understands the data after substitution and the original data in a different manner.
Keyword (in Japanese) (See Japanese page) 
(in English) NLP / AutoScoring / DataAugmentation / Thesaurus / BERT / / /  
Reference Info. IEICE Tech. Rep., vol. 120, no. 344, AI2020-15, pp. 7-12, Jan. 2021.
Paper # AI2020-15 
Date of Issue 2021-01-20 (AI) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380
Copyright
and
reproduction
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF AI2020-15

Conference Information
Committee AI  
Conference Date 2021-01-27 - 2021-01-27 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To AI 
Conference Code 2021-01-AI 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Automatic Short Answer Scoring using Thesaurus-Based Data Augmentation 
Sub Title (in English)  
Keyword(1) NLP  
Keyword(2) AutoScoring  
Keyword(3) DataAugmentation  
Keyword(4) Thesaurus  
Keyword(5) BERT  
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1st Author's Name Hiroyuki Kato  
1st Author's Affiliation Kyushu University (Kyushu Univ.)
2nd Author's Name Tsunenori Ishioka  
2nd Author's Affiliation National Center for University Entrance Examinations (DNC)
3rd Author's Name Tsunenori Mine  
3rd Author's Affiliation Kyushu University (Kyushu Univ)
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Speaker
Date Time 2021-01-27 13:30:00 
Presentation Time 25 
Registration for AI 
Paper # IEICE-AI2020-15 
Volume (vol) IEICE-120 
Number (no) no.344 
Page pp.7-12 
#Pages IEICE-6 
Date of Issue IEICE-AI-2021-01-20 


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