Asia pacific journal of information systems

The Korea Society of Management Information Systems (한국경영정보학회)
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A Hangul Document Classification System using Case-based Reasoning

사례기반 추론을 이용한 한글 문서분류 시스템

  • 이재식 (아주대학교 경영대학) ;
  • 이종운 (대우정보시스템 건설시스템팀)
  • Published : 2002.06.30
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Abstract

In this research, we developed an efficient Hangul document classification system for text mining. We mean 'efficient' by maintaining an acceptable classification performance while taking shorter computing time. In our system, given a query document, k documents are first retrieved from the document case base using the k-nearest neighbor technique, which is the main algorithm of case-based reasoning. Then, TFIDF method, which is the traditional vector model in information retrieval technique, is applied to the query document and the k retrieved documents to classify the query document. We call this procedure 'CB_TFIDF' method. The result of our research showed that the classification accuracy of CB_TFIDF was similar to that of traditional TFIDF method. However, the average time for classifying one document decreased remarkably.

Keywords

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