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Paper Abstract and Keywords
Presentation 2022-07-09 13:35
Retrieval of Similar Questions from QAbot Data based on Transformer Language Model
Zihao Chen, Hisashi Handa, Kimiaki Shirahama (Kindai Univ.) ET2022-9
Abstract (in Japanese) (See Japanese page) 
(in English) It has recently become possible to collect a large amount of question-answer pairs that arose in certain educational courses. However, one of the biggest difficulties to utilize such data is the lack of a retrieval system that helps a student efficiently find answers to his/her own question. This paper presents our system that takes advantage of a transformer language model which keeps breaking the state-of-the-art in various natural language processing tasks. In particular, our system uses Sentence-BERT to extract a useful feature of a question, so that questions semantically similar to the user’s one can be accurately identified through their feature matching. In addition, an important prerequisite for objective performance evaluation is a large-scale dataset containing many question-answer pairs. For this, a bot is developed on Slack to collect 1142 question-answer pairs that are individually annotated with the relevance to each of 20 queries. The experimental results on this dataset validate the effectiveness of our system based on Sentence-BERT.
Keyword (in Japanese) (See Japanese page) 
(in English) Question answering / Information retrieval / Transformer / Sentence-BERT / QAbot / / /  
Reference Info. IEICE Tech. Rep., vol. 122, no. 102, ET2022-9, pp. 5-11, July 2022.
Paper # ET2022-9 
Date of Issue 2022-07-02 (ET) 
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 ET2022-9

Conference Information
Committee ET  
Conference Date 2022-07-09 - 2022-07-09 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Data Accumulation, Analysis and Practice Application of Learning History Data, etc. 
Paper Information
Registration To ET 
Conference Code 2022-07-ET 
Language English 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Retrieval of Similar Questions from QAbot Data based on Transformer Language Model 
Sub Title (in English)  
Keyword(1) Question answering  
Keyword(2) Information retrieval  
Keyword(3) Transformer  
Keyword(4) Sentence-BERT  
Keyword(5) QAbot  
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1st Author's Name Zihao Chen  
1st Author's Affiliation Kindai University (Kindai Univ.)
2nd Author's Name Hisashi Handa  
2nd Author's Affiliation Kindai University (Kindai Univ.)
3rd Author's Name Kimiaki Shirahama  
3rd Author's Affiliation Kindai University (Kindai Univ.)
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Speaker Author-1 
Date Time 2022-07-09 13:35:00 
Presentation Time 25 minutes 
Registration for ET 
Paper # ET2022-9 
Volume (vol) vol.122 
Number (no) no.102 
Page pp.5-11 
#Pages
Date of Issue 2022-07-02 (ET) 


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