Earticle

초록

영어

The advent of KM(knowledge management) concept have led many organizations to seek an effective way to make use of their knowledge. But the absence of right tools for systematic handling of unstructured information makes it difficult to automatically retrieve and share relevant information that exactly meet user's needs. we propose a systematic method to enable content-based information retrieval from corpus of unstructured documents. In our method, a document is represented by using several key terms which are automatically selected based on their quantitative relevancy to the document. Basically, the relevancy is calculated by using a traditional TFIDF measure that are widely accepted in the related research, but to improve effectiveness of the measure, we exploited 'concept network' that represents term-term relationships. In particular, in constructing the concept network, we have also considered relative position of terms occurring in a document. A prototype system for experiment has been implemented. The experiment result shows that our approach can have higher performance over the conventional TFIDF method.

목차

I. 서론
 II. 문서의 표현 방법
  2.1 TFIDF 표현
  2.2 문서-어휘 행렬
 III. 개념 네트워크(Concept Network)를 이용한 문서의 표현
  3.1 어휘의 발생위치를 고려한 개념 행렬(Concept Matrix)
  3.2 개념행렬을 이용한 문서-어휘 행렬 표현
 IV. 실험결과 및 분석
  4.1 문서집합 및 실험설계
  4.2 검색 성능의 비교
 V. 결론 및 토의
 참고문헌

저자

• 허원창 [ Wonchang Hur | 인하대학교 경영학부 ] 교신저자
• 이상진 [ Sangin Lee | 삼성네트웍스 기술솔루션사업팀 ]

참고문헌