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Paper Abstract and Keywords
Presentation 2023-09-07 15:30
Bootstrapped Assignment of Polarity to Business Performance Forecast Sentences in Quarterly/Annual Reports
Yuta Hiramatsu (Nagoya Univ.), Yasuhiro Ogawa (Nagoya City Univ.), Katsuhiko Toyama (Nagoya Univ.) NLC2023-11
Abstract (in Japanese) (See Japanese page) 
(in English) Quarterly/Annual Report published by companies contains important information for investors, such as business performance forecast. However, it takes work for novice investors to analyze the reports. Therefore, we propose a method for extracting business performance forecast sentences from the reports and assigning polarity to them. Specifically, we introduce polarity for business performance forecast sentences and compare the rule-based model, the BERT model, and a model that combines these two. The results show that the combined method is more effective than the methods which use each model alone. In addition, we increase training data by bootstrapping and verify its effect with accuracy. The results show that bootstrapping can improve accuracy by 10 points when training data is small.
Keyword (in Japanese) (See Japanese page) 
(in English) Quarterly/Annual Report / Business Performance Forecast Sentence / Information Extraction / Assigning Polarity / BERT / / /  
Reference Info. IEICE Tech. Rep., vol. 123, no. 176, NLC2023-11, pp. 57-62, Sept. 2023.
Paper # NLC2023-11 
Date of Issue 2023-08-30 (NLC) 
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 NLC2023-11

Conference Information
Committee NLC  
Conference Date 2023-09-06 - 2023-09-07 
Place (in Japanese) (See Japanese page) 
Place (in English) Osaka Metropolitan University. Nakamozu Campus. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) The 20th Text Analytics Symposium 
Paper Information
Registration To NLC 
Conference Code 2023-09-NLC 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Bootstrapped Assignment of Polarity to Business Performance Forecast Sentences in Quarterly/Annual Reports 
Sub Title (in English)  
Keyword(1) Quarterly/Annual Report  
Keyword(2) Business Performance Forecast Sentence  
Keyword(3) Information Extraction  
Keyword(4) Assigning Polarity  
Keyword(5) BERT  
Keyword(6)  
Keyword(7)  
Keyword(8)  
1st Author's Name Yuta Hiramatsu  
1st Author's Affiliation Nagoya University (Nagoya Univ.)
2nd Author's Name Yasuhiro Ogawa  
2nd Author's Affiliation Nagoya City University (Nagoya City Univ.)
3rd Author's Name Katsuhiko Toyama  
3rd Author's Affiliation Nagoya University (Nagoya Univ.)
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Speaker Author-1 
Date Time 2023-09-07 15:30:00 
Presentation Time 25 minutes 
Registration for NLC 
Paper # NLC2023-11 
Volume (vol) vol.123 
Number (no) no.176 
Page pp.57-62 
#Pages 6 
Date of Issue 2023-08-30 (NLC) 

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