人工知能学会第二種研究会資料
Online ISSN : 2436-5556
企業業績発表記事からの因果関係抽出
坂地 泰紀酒井 浩之増山 繁
著者情報
研究報告書・技術報告書 フリー

2013 年 2013 巻 FIN-011 号 p. 09-

詳細
抄録

This paper proposes a method that extracts causal knowledge from Japanese financial articles concerning business performance of companies via clue expressions. Our method decides whether a sentence includes causal knowledge or not when the method extracts it. For example, a sentence fragment "World economy recession due to the subprime loan crisis ..." contains causal knowledge in which \World economy recession" is an effect phrase and \the subprime loan crisis" is its cause phrase. These relations are found by clue phrases,such as "ため(tame: because)" and "により(niyori: due to)". We found that some specific syntactic patterns are useful to improve accuracy of extracting causal knowledge. Therefore, our method can extract causal knowledge accurately.

著者関連情報
© 2013 著作者
前の記事
feedback
Top