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Paper Abstract and Keywords
Presentation 2013-09-13 10:55
Extraction of important articles that influence the stock price of companies from financial articles
Masaru Nakayama, Hiroyuki Sakai (Seikei Univ.) NLC2013-26
Abstract (in Japanese) (See Japanese page) 
(in English) Currently, the number of private investors is increasing. However, all private investors don’t have the knowledge on investment. Therefore, we proposed a method for extracting important articles that influence the stock price of companies from financial articles. Actually, we calculate change of stock price from previous day. Then, we extract newspaper articles related to companies from set of articles issued on the day.
We create a training data set from extracted newspaper articles. Our method extracts features from words contained in the training data set, and classifies the extracted articles into important articles that influence the stock price of companies and unimportant articles by SVM. Experimental results showed that our method achieved 44 F-measure.
Moreover, we adds keywords extracted from web pages of companies to features of SVM for improving F-measure. In this result, our method achieved 57 F-measure and 73% accuracy.
Keyword (in Japanese) (See Japanese page) 
(in English) Important articles extraction / Investment decision support / Text Mining / / / / /  
Reference Info. IEICE Tech. Rep., vol. 113, no. 213, NLC2013-26, pp. 61-66, Sept. 2013.
Paper # NLC2013-26 
Date of Issue 2013-09-05 (NLC) 
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)
Notes on Review This article is a technical report without peer review, and its polished version will be published elsewhere.
Download PDF NLC2013-26

Conference Information
Committee NLC  
Conference Date 2013-09-12 - 2013-09-13 
Place (in Japanese) (See Japanese page) 
Place (in English) National Olympics Memorial Youth Center 
Topics (in Japanese) (See Japanese page) 
Topics (in English) The Third Symposium on Text Mining 
Paper Information
Registration To NLC 
Conference Code 2013-09-NLC 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Extraction of important articles that influence the stock price of companies from financial articles 
Sub Title (in English)  
Keyword(1) Important articles extraction  
Keyword(2) Investment decision support  
Keyword(3) Text Mining  
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1st Author's Name Masaru Nakayama  
1st Author's Affiliation Seikei University (Seikei Univ.)
2nd Author's Name Hiroyuki Sakai  
2nd Author's Affiliation Seikei University (Seikei Univ.)
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Speaker Author-1 
Date Time 2013-09-13 10:55:00 
Presentation Time 25 minutes 
Registration for NLC 
Paper # NLC2013-26 
Volume (vol) vol.113 
Number (no) no.213 
Page pp.61-66 
#Pages
Date of Issue 2013-09-05 (NLC) 


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