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    Title: Exploring Fraudulent Financial Reporting with GHSOM
    Authors: 蔡瑞煌
    Tsaih, Rua-Huan;Lin, Wan-Ying;Huang, Shin-Ying
    Contributors: 資管系
    Keywords: Financial Reporting Fraud;Growing Hierarchical Self-Organizing Map;Knowledge Extraction
    Date: 2009
    Issue Date: 2015-02-12 12:23:37 (UTC+8)
    Abstract: 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.
    Relation: Intelligence and Security Informatics Lecture Notes in Computer Science Volume,5477,31-41
    Data Type: article
    DOI link: http://dx.doi.org/10.1007/978-3-642-01393-5_5
    DOI: 10.1007/978-3-642-01393-5_5
    Appears in Collections:[Department of MIS] Periodical Articles

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