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Paper Abstract and Keywords
Presentation 2024-08-09 14:25
Experiment of AI Learning Relations between Technical Sentences and Creating Training Data for Fine-Tuning using Natural Language Processing
Jun Yoshinaga (NALTEC) CPSY2024-35 DC2024-35 RECONF2024-35
Abstract (in Japanese) (See Japanese page) 
(in English) The ambiguity included in natural language sometimes shown in specification , that are difficult problem for machine learning.
This paper describes an approach and experiment result to create training data from a small number of descriptions of the relationship between functional requirements and specification requirements, and confirmed using sample documents.
Keyword (in Japanese) (See Japanese page) 
(in English) Named Entity Recognition / NER / railway product / domein knowledges / Sentece BERT / functional requirement / /  
Reference Info. IEICE Tech. Rep., vol. 124, no. 149, DC2024-35, pp. 108-111, Aug. 2024.
Paper # DC2024-35 
Date of Issue 2024-07-31 (CPSY, DC, RECONF) 
ISSN 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 CPSY2024-35 DC2024-35 RECONF2024-35

Conference Information
Committee CPSY DC RECONF IPSJ-ARC  
Conference Date 2024-08-07 - 2024-08-09 
Place (in Japanese) (See Japanese page) 
Place (in English) Awagin Hall 
Topics (in Japanese) (See Japanese page) 
Topics (in English) SWoPP2024: Parallel, Distributed and Cooperative Processing Systems and Dependable Computing 
Paper Information
Registration To DC 
Conference Code 2024-08-CPSY-DC-RECONF-ARC 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Experiment of AI Learning Relations between Technical Sentences and Creating Training Data for Fine-Tuning using Natural Language Processing 
Sub Title (in English)  
Keyword(1) Named Entity Recognition  
Keyword(2) NER  
Keyword(3) railway product  
Keyword(4) domein knowledges  
Keyword(5) Sentece BERT  
Keyword(6) functional requirement  
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1st Author's Name Jun Yoshinaga  
1st Author's Affiliation National Agency for Automobile and Land Transport Technology (NALTEC)
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Speaker Author-1 
Date Time 2024-08-09 14:25:00 
Presentation Time 25 minutes 
Registration for DC 
Paper # CPSY2024-35, DC2024-35, RECONF2024-35 
Volume (vol) vol.124 
Number (no) no.148(CPSY), no.149(DC), no.150(RECONF) 
Page pp.108-111 
#Pages 4 
Date of Issue 2024-07-31 (CPSY, DC, RECONF) 

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