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| Abstract |
企業分析は、有望な企業に投資する目的のみならず、取引先の選定や就職活動など、多くの場面で必要とされている。従来、企業分析は主に財務数値のデータに対して行われていたが、近年、自然言語処理技術の発達に伴って、テキストデータ(非財務データ) を分析対象とした研究が盛んになっている。本研究では医薬品製造業の有価証券報告書のテキスト情報から、該当企業の翌年の利益伸び率の推定を試みた。文書単位の分析と文単位の...分析を融合することで、文書単位による利益伸び率上位の企業の推定性能が向上した。
A business analysis is needed in many scenes, such as selection of a promising company for the investment and for job-hunting activities. Conventionally, a business analysis was mainly conducted on financial numerical data. In recent years, thanks to the development of the natural language processing and related tools, financial text data are gaining hot attention as the target of text mining. The present paper proposes a method to predict the growth rate of operating income of the next accounting period using the securities report. The proposed method applies feature selection to construct models to predict if a sentence appears in securities reports with high growth rate. The models are then used for prediction with respect to reports. Empirical evaluation is conducted for the securities reports of pharmaceutical companies and confirmed that the proposed method outperforms a baseline method that uses document based SVM (support vector machine) with the optimal parameter.show more
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