Extracting important pages of notice of a general meeting of stockholders using deep learning

Abstract

The shareholder convocation notice contains a lot of useful information, such as company profile, major shareholder, and bills to be discussed. The purpose of our research is to automatically extract pages that are likely to affect the stock price from shareholder convocation notices. To this end, we need to tag the pages to automatically extract what information is described on a page-by-page basis. In our research, we propose the following framework: we automatically create training data by a rule-based method and train the deep learning model that extracts important pages. We confirm the effectiveness of our framework for pages that cannot be extracted by the rule-based method.