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질문대답 아카이브에서 어휘 연관성을 이용한 질문 분류

Question Classification Based on Word Association for Question and Answer Archives

  • 김설영 (전북대학교 컴퓨터공학과) ;
  • 이경순 (전북대학교 컴퓨터공학부/영상정보신기술연구센터)
  • 투고 : 2010.02.25
  • 심사 : 2010.04.20
  • 발행 : 2010.08.31

초록

보통 두 세 개의 어휘로 구성된 질문 분류에서 어휘의 다양한 표현으로 인한 어휘 불일치문제는 성능 저하의 주요 원인이다. 따라서 질문 분류에서 어휘 사이의 연관성을 반영하는 것이 필수적이다. 본 논문에서는 같은 범주의 질문-질문 쌍들에 대해 계산한 어휘 번역확률을 번역기반 언어모델에 반영하여 질문을 분류하는 방법을 제안한다. 실험에서 야후!앤써 질문대답 아카이브를 이용해서 전체 질문-대답 쌍들에 대해서 번역확률을 계산하는 것보다 같은 범주에 속하는 질문-질문 쌍들에 대해서 번역확률을 계산하는 것이 질문 분류에서 더 좋은 번역확률인 것을 증명한다.

Word mismatch is the most significant problem that causes low performance in question classification, whose questions consist of only two or three words that expressed in many different ways. So, it is necessary to apply word association in question classification. In this paper, we propose question classification method using translation-based language model, which use word translation probabilities for question-question pair that is learned in the same category. In the experiment, we prove that translation probabilities of question-question pairs in the same category is more effective than question-answer pairs in total collection.

키워드

참고문헌

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피인용 문헌

  1. Question and Answering System through Search Result Summarization of Q&A Documents vol.3, pp.4, 2014, https://doi.org/10.3745/KTSDE.2014.3.4.149