Abstract
This paper addresses the automatic transformation of financial statements into conceptual graph interchange format (CGIF). The method mainly involves extracting relevant financial performance indicators, parsing it to obtain syntactic sentence structure and to generate the CGIF for the extracted text. The required components for the transformation are detailed out with an illustrative example. The paper also discusses the potential manipulation of the resulting CGIF for knowledge discovery and more precisely for deviation detection.
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Kamaruddin, S.S., Hamdan, A.R., Bakar, A.A., Mat Nor, F. (2009). Conceptual Graph Interchange Format for Mining Financial Statements. In: Wen, P., Li, Y., Polkowski, L., Yao, Y., Tsumoto, S., Wang, G. (eds) Rough Sets and Knowledge Technology. RSKT 2009. Lecture Notes in Computer Science(), vol 5589. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02962-2_73
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DOI: https://doi.org/10.1007/978-3-642-02962-2_73
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