政大學術集成


請使用永久網址來引用或連結此文件: https://ah.nccu.edu.tw/handle/140.119/75487


題名: Risk statement recognition in news articles
作者: Chen, Tsai-jyh;Lu, H.-M.;Li, S.-H.
陳彩稚
貢獻者: 風管系
關鍵詞: Business organizations;Design frameworks;Information sources;Logistic regressions;NAtural language processing;News articles;Prototype system;Risk impact;Risk recognition;Risk types;Text mining;Textual data;Wall Street Journal;Design;Information systems;Logistics;Natural language processing systems;Risk management;Data mining
日期: 2009-12
上傳時間: 2015-06-01 17:47:39 (UTC+8)
摘要: Textual data are an important information source for risk management for business organizations. To effectively recognize, extract, and analyze risk-related statements in textual data, these processes need to be automated. We developed a design framework for firm-specific risk statements guided by previous economic, managerial, and natural language processing research. Four information types (risk impact, risk type, future timing, and uncertainty) were identified as the key requirements for risk recognition systems. A prototype system, AZRisk, was constructed to verify the framework. Evaluation using news sentences from the Wall Street Journal confirmed the design framework. The performance of AZRisk showed promising results for automated risk recognition.
關聯: ICIS 2009 Proceedings - Thirtieth International Conference on Information Systems,-
資料類型: conference
顯示於類別:[風險管理與保險學系] 會議論文

文件中的檔案:

檔案 描述 大小格式瀏覽次數
index.html0KbHTML710檢視/開啟


在學術集成中所有的資料項目都受到原著作權保護.


社群 sharing