Journal of the Institute of Electronics Engineers of Korea CI (전자공학회논문지CI)

The Institute of Electronics and Information Engineers (대한전자공학회)
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Analyses and Comparisons of Human and Statistic-based MMR Summarizations of Single Documents

단일 문서의 인위적 요약과 MMR 통계요약의 비교 및 분석

  • 유준현 (전북대학교 전자정보공학부) ;
  • 변동률 (전북대학교 전자정보공학) ;
  • 박순철 (전북대학교 전자정보공학부)
  • Published : 2004.03.01
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Abstract

The Statistic-based method is widely used for automatic single document summarization in large sets of documents such as those on the web. However, the results of this method shows high redundancies in the summarized sentences because this method selects sentences including words that frequently appear in the document. We solve this problem using the method MMR to raise the quality of document summary (The best results are appeared around λ=0.6). Also, we compare the MMR summaries with those done by human subjects and verify their accuracy.

웹과 같은 대량의 문서집단에서 단일 문서에 대한 자동 요약은 일반적으로 통계요약 방법을 이용한다. 그러나 단순한 통계 요약 방법은 문서내의 빈도수가 높은 단어를 포함하는 문장들이 중복되어 나타날 확률이 높다. 이러한 단점을 보완하기 위하여 본 논문에서는 통계기반 요약방법에 MMR 기법을 적용하여 요약의 질을 향상시켰다(약 λ=0.6에서 최고의 성능을 보임). 또한 본 논문에서는 인위적 요약을 수행하여 MMR 통계기반의 요약 결과의 성능을 평가하였다.

Keywords

References

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