政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/45767
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    题名: Identifying Firm-Specific Risk Statements in News Articles
    作者: 陳彩稚
    Lu, Hsin-Min;Huang, Nina WanHsin;Zhang, Zhu;Chen , Tsai-Jyh
    日期: 2009-04
    上传时间: 2010-10-06 10:40:31 (UTC+8)
    摘要: Textual data are an important information source for risk management for business organizations. To effectively identify, extract, and analyze risk-related statements in textual data, these processes need to be automated. We developed an annotation framework for firm-specific risk statements guided by previous economic, managerial, linguistic, and natural language processing research. A manual annotation study using news articles from the Wall Street Journal was conducted to verify the framework. We designed and constructed an automated risk identification system based on the annotation framework. The evaluation using manually annotated risk statements in news articles showed promising results for automated risk identification.
    關聯: Intelligence and Security Informatics, Springer-Verlag, pp.42-53
    数据类型: book/chapter
    DOI 連結: http://dx.doi.org/10.1007/978-3-642-01393-5_6
    DOI: 10.1007/978-3-642-01393-5_6
    显示于类别:[風險管理與保險學系] 專書/專書篇章

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