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Subject

Answer Snippet Retrieval for Question Answering of Medical Documents
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의학문서 질의응답을 위한 정답 스닛핏 검색

논문 기본 정보

Type
Academic journal
Author
Hyeon-gu Lee (강원대학교) Minkyoung Kim (강원대학교) Harksoo Kim (강원대학교)
Journal
Korean Institute of Information Scientists and Engineers Journal of KIISE Vol.43 No.8 KCI Excellent Accredited Journal
Published
2016.8
Pages
927 - 932 (6page)

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Result
Answer Snippet Retrieval for Question Answering of Medical Documents
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Abstract· Keywords

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With the explosive increase in the number of online medical documents, the demand for question-answering systems is increasing. Recently, question-answering models based on machine learning have shown high performances in various domains. However, many question-answering models within the medical domain are still based on information retrieval techniques because of sparseness of training data. Based on various information retrieval techniques, we propose an answer snippet retrieval model for question-answering systems of medical documents. The proposed model first searches candidate answer sentences from medical documents using a cluster-based retrieval technique. Then, it generates reliable answer snippets using a re-ranking model of the candidate answer sentences based on various sentence retrieval techniques. In the experiments with BioASQ 4b, the proposed model showed better performances (MAP of 0.0604) than the previous models.

Contents

요약
Abstract
1. 서론
2. 관련연구
3. 의학 문서용 정답 스닛핏 검색 모델
4. 실험 및 평가
5. 결론
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