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https://ah.lib.nccu.edu.tw/handle/140.119/73492
題名: | Exploring Fraudulent Financial Reporting with GHSOM | 作者: | 蔡瑞煌 Tsaih, Rua-Huan;Lin, Wan-Ying;Huang, Shin-Ying |
貢獻者: | 資管系 | 關鍵詞: | Financial Reporting Fraud; Growing Hierarchical Self-Organizing Map; Knowledge Extraction | 日期: | 2009 | 上傳時間: | 12-Feb-2015 | 摘要: | The issue of fraudulent financial reporting has drawn much public as well as academic attention. However, most relevant researches focus on predicting financial distress or bankruptcy. Little emphasis has been placed on exploring the financial reporting fraud itself. This study addresses the challenge of obtaining an enhanced understanding of the financial reporting fraud through the approach with the following four phases: (1) to identify a set of financial and corporate governance indicators that are significantly correlated with fraudulent financial reporting; (2) to use the Growing Hierarchical Self-Organizing Map (GHSOM) to cluster data from listed companies into fraud and non-fraud subsets; (3) to extract knowledge from the fraudulent financial reporting through observing the hierarchical relationship displayed in the trained GHSOM; and (4) to provide justification to the extracted knowledge. | 關聯: | Intelligence and Security Informatics Lecture Notes in Computer Science Volume,5477,31-41 | 資料類型: | article | DOI: | http://dx.doi.org/10.1007/978-3-642-01393-5_5 |
Appears in Collections: | 期刊論文 |
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