Development of Search Tool for Listed Company Related to ThemesUsing Text Mining [in Japanese]

Masanori HIRANO, Hiroki SAKAJI, Shoko KIMURA, Kiyoshi IZUMI, Hiroyasu MATSUSHIMA, Shintaro NAGAO, Atsuo KATO

The 24th meeting of Special Interest Group on Financial Informatics of Japanese Society for Artificial Intelligence, pp. 1-8, Mar. 15, 2020

Conference

The 24th meeting of Special Interest Group on Financial Informatics of Japanese Society for Artificial Intelligence (SIG-FIN)

Abstract

Wepropose a scheme for selecting stocks related to a theme. This scheme was designed to support fund managers who are building themed mutual funds. Our scheme is a type of natural language processing method and based on words extracted according to their similarity to a theme using word2vec and our unique similarity based on co-occurrence in company information. We used data including investor relations and official websites as company information data. We also conducted several other experiments, including hyperparameter tuning, in our scheme.

Keywords

テーマ型投資信託; テキストマイニング; 関連度計算; 銘柄抽出; 株式市場;

Paper

PDF, Official page

bibtex

@inproceedings{Hirano2020-sigfin24,
  title={{Development of Search Tool for Listed Company Related to ThemesUsing Text Mining [in Japanese]}},
  author={Masanori HIRANO and Hiroki SAKAJI and Shoko KIMURA and Kiyoshi IZUMI and Hiroyasu MATSUSHIMA and Shintaro NAGAO and Atsuo KATO},
  booktitle={The 24th meeting of Special Interest Group on Financial Informatics of Japanese Society for Artificial Intelligence},
  pages={1-8},
  url={https://sigfin.org/?024-41},
  year={2020}
}