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재정정보 활용을 위한 텍스트 마이닝 기반 회계용어 형태소 분석기 구축
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Publication Year
2019-12
Journal
정보시스템연구
Publisher
한국정보시스템학회
Citation
정보시스템연구, Vol.28 No.4, pp.155-174
Keyword
text miningtext tokenizingN-grammorphological analyzeraccounting terminology analyzerfinancial statementsnotes
Abstract
Purpose Social interest in financial statement notes has recently increased. However, contrary to the keen interest in financial statement notes, there is no morphological analyzer for accounting terms, which is why researchers are having considerable difficulty in carrying out research. In this study, we build a morphological analyzer for accounting related text mining techniques. This morphological analyzer can handle accounting terms like financial statements and we expect it to serve as a springboard for growth in the text mining research field. <br> <br> <br>Design/methodology/approach In this study, we build customized korean morphological analyzer to extract proper accounting terms. First, we collect Company’s Financial Statement notes, financial information data published by KPFIS(Korea Public Finance Information Service), K-IFRS accounting terms data. Second, we cleaning and tokeninzing and removing stopwords. Third, we customize morphological analyzer using n-gram methodology. <br> <br> <br>Findings Existing morphological analyzer cannot extract accounting terms because it split accounting terms to many nouns. In this study, the new customized morphological analyzer can detect more appropriate accounting terms comparing to the existing morphological analyzer. We found that accounting words that were not detected by existing morphological analyzers were detected in new customized morphological analyzers.
ISSN
1229-8476
Language
Kor
URI
https://aurora.ajou.ac.kr/handle/2018.oak/35136
DOI
https://doi.org/10.5859/KAIS.2019.28.4.155
Type
Article
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Kang, Ju Young Image
Kang, Ju Young강주영
Department of Business Intelligence
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