人工知能学会第二種研究会資料
Online ISSN : 2436-5556
第24回金融情報学研究会
文脈を考慮した決算短信からの業績要因抽出
加藤 悠太酒井 浩之
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研究報告書・技術報告書 フリー

2020 年 2020 巻 FIN-024 号 p. 234-

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In this paper, we proposed a method for automatically extracting sentences containing corporate performance factors from summaries of financial statements at high accuracy. More specifically, only sentences that can be determined to be corporate performance factors in the summaries of financial statements with high probability are extracted, and those sentences are used as training data. We trained the neural network by using the word representation of the training data. Furthermore, by using the appearance tendency of the corporate performance factor sentence specific to summaries of financial statements as a bias of model output, it became possible to extract with a higher f-measure than related work that performs filtering processing using corporate keywords.

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