지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술대회자료
- 저자정보
- 발행연도
- 2013.10
- 수록면
- 1,199 - 1,202 (4page)
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초록· 키워드
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Question answering generally generates the answer to the question by extracting the named entity from the sentences containing the answer to the question from information sources. However, it is not always true that a named entity is an answer to the question. So we propose a method for generating the answer sentence using statistical machine translation. The probability models are constructed by learning from enormous samples of the set of question sentence, extracted sentence, and answer sentence. The question sentence and the sentence extracted by the question answering from information source are regarded as an input of machine translation. They are translated to a suitable answer sentence to the question. In this paper, we attempted to apply our method to several simple types questions that can also be answered by the named entity extraction.
목차
Abstract
1. INTRODUCTION
2. RELATEDWORKS
3. STATISTICAL MACHINE TRANSLATION
4. OUR APPROACH
5. CONCLUSION AND FUTURE WORKS
REFERENCES
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