효율적인 문서 자동 분류를 위한 대표 색인어 추출 기법

A Feature Selection Technique for an Efficient Document Automatic Classification

  • 김지숙 (창원대학교 컴퓨터공학과) ;
  • 김영지 (창원대학교 컴퓨터공학과) ;
  • 문현정 (창원대학교 컴퓨터공학과) ;
  • 우용태 (창원대학교 컴퓨터공학과)
  • 발행 : 2001.07.01

초록

Recently there are many researches of text mining to find interesting patterns or association rules from mass textual documents. However, the words extracted from informal documents are tend to be irregular and there are too many general words, so if we use pre-exist method, we would have difficulty in retrieving knowledge information effectively. In this paper, we propose a new feature extraction method to classify mass documents using association rule based on unsupervised learning technique. In experiment, we show the efficiency of suggested method by extracting features and classifying of documents.

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