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  • 标题:学習データの自動生成による深層学習を用いた株主招集通知の重要ページ抽出
  • 本地全文:下载
  • 作者:高野 海斗 ; 酒井 浩之 ; 中川 慧
  • 期刊名称:人工知能学会論文誌
  • 印刷版ISSN:1346-0714
  • 电子版ISSN:1346-8030
  • 出版年度:2021
  • 卷号:36
  • 期号:1
  • 页码:1-19
  • DOI:10.1527/tjsai.36-1_WI2-G
  • 出版社:The Japanese Society for Artificial Intelligence
  • 摘要:A shareholder convocation notice is a letter that the company is obliged to send to shareholders when holding a shareholder’s meeting. We can access it on corporate websites and acquire as PDF file. It contains a lot of useful information, such as company profile, major shareholders, and bills to be discussed. Therefore, institutional investors often use that information in their investment decisions. However, the following challenges exist for institutional investors to extract information that is likely to affect the stock price. The number of pages ranges from more than a dozen to more than a hundred. In addition, since they are issued before a shareholder’s meetings, they are issued in large numbers in a particular month, i.e., thousands of company notices are issued in June, the most concentrated month. This is a significant burden for institutional investors.
  • 关键词:deep learning;information extraction;text mining
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