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. |
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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 |
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Important articles extraction |
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Investment decision support |
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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 |
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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 |
6 |
Date of Issue |
2013-09-05 (NLC) |
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