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학술지 Effects of Answer Weight Boosting in Strategy-driven Question Answering
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저자
오효정, 맹성현, 장명길
발행일
201201
출처
Information Processing & Management, v.48 no.1, pp.83-93
ISSN
0306-4573
출판사
Elsevier
DOI
https://dx.doi.org/10.1016/j.ipm.2011.01.010
협약과제
10MS2400, 웹 QA 기술개발, 장명길
초록
With the advances in natural language processing (NLP) techniques and the need to deliver more fine-grained information or answers than a set of documents, various QA techniques have been developed corresponding to different question and answer types. A comprehensive QA system must be able to incorporate individual QA techniques as they are developed and integrate their functionality to maximize the system's overall capability in handling increasingly diverse types of questions. To this end, a new QA method was developed to learn strategies for determining module invocation sequences and boosting answer weights for different types of questions. In this article, we examine the roles and effects of the answer verification and weight boosting method, which is the main core of the automatically generated strategy-driven QA framework, in comparison with a strategy-less, straightforward answer-merging approach and a strategy-driven but with manually constructed strategies. © 2011 Elsevier Ltd. All rights reserved.
키워드
Answer verification and weight boosting, Question answering, Strategy-driven QA
KSP 제안 키워드
Natural Language Processing, QA system, boosting method, fine-grained, question answering