DocumentCode :
3030293
Title :
Research on Answer Extraction Method for Domain Question Answering System(QA)
Author :
Mao, Cun-li ; Li, Li-Na ; Yu, Zheng-tao ; Han, Lu ; Guo, Jian-yi ; Lei, Xiong-Li
Author_Institution :
Sch. of Inf. Eng. & Autom., Kunming Univ. of Sci. & Technol., Kunming, China
Volume :
1
fYear :
2009
fDate :
11-14 Dec. 2009
Firstpage :
79
Lastpage :
83
Abstract :
The domain knowledge has a direct impact on the result of question - answering (Q & A) in the restricted domain question answering system (QA). In this paper, a method of answer extraction for domain Chinese question-and-answer (Q&A) is proposed, which based on the analysis of interrogative sentence and the answer type, carrying on the text retrieval with the help of the domain knowledge and obtaining the relevant paragraphs of the question as the candidate answer. For the question of numeral or list entity type, extracted the question center related domain entity as the answers by adopting the naming entity recognition. For the definition questions, the sentences or paragraphs with higher relevance can be extracted to become the answer based on the relevance ranking between the candidate sentences or paragraphs and questions by combined the computing method of keywords weighting and the method of semantic similarity between the sentences and questions. Experimented on the answer extraction in Yunnan tourism domain, the results show that more remarkable effects have been achieved by adopting the method of answer extraction from domain Chinese question-and-answer.
Keywords :
information retrieval; search engines; Yunnan tourism domain; answer extraction method; domain Chinese question-and-answer; domain question answering system; entity recognition; keywords weighting; relevance ranking; semantic similarity; text retrieval; Computational intelligence; Computer security; Data mining; Educational institutions; Information retrieval; Information security; Knowledge engineering; Pattern matching; Search engines; Snow; Question Answering System (QA); answer extraction; answer types; domain knowledge; question types;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Security, 2009. CIS '09. International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-5411-2
Type :
conf
DOI :
10.1109/CIS.2009.173
Filename :
5376719
Link To Document :
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