DocumentCode
1938341
Title
Research on Chinese FAQ Question Answering System in Restricted Domain
Author
Yu, Zheng-tao ; Qiu, Yan-xia ; Deng, Jin-Hui ; Han, Lu ; Mao, Cun-li ; Meng, Xiang-yan
Author_Institution
Kunming Univ. of Sci. & Technol., Kunming
Volume
7
fYear
2007
fDate
19-22 Aug. 2007
Firstpage
3927
Lastpage
3932
Abstract
FAQ (frequently-asked question) is a good question and answer model to realize business advisory system in restricted domain. A FAQ question answering system model is presented in this paper. With the help of the idea of ontology, a knowledge base is constructed in the domain. With the help of language KDML (Knowledge Database Mark-up Language) of HowNet,the domain ontology and the relationship of it are defined and described, and the fusion of domain knowledge base (domain HowNet) and common knowledge base(HowNet) is realized. On this basis, a question similarity calculation method, which makes use of the characteristics of the domain question and combines lexical relationship, syntactic interdependent relationship and the semantic relationship of domains among question sentences, is implemented. And based on the question similarity calculation, retrieval of related question from the candidate question set and extraction of answers can be implemented with this method. The result of Yunnan tourism question-answer model experiment shows that this method is feasible and effective.
Keywords
information retrieval; knowledge based systems; natural languages; ontologies (artificial intelligence); Chinese FAQ question answering system; KDML; Knowledge Database Mark-up Language; Yunnan tourism question-answer model; business advisory system; domain HowNet; domain ontology; frequently-asked question; Application software; Automation; Computer applications; Cybernetics; Databases; Information processing; Learning systems; Machine learning; Natural languages; Ontologies; Domain ontology; Frequently-asked question; Question similarity; Restricted domain question answering system;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2007 International Conference on
Conference_Location
Hong Kong
Print_ISBN
978-1-4244-0973-0
Electronic_ISBN
978-1-4244-0973-0
Type
conf
DOI
10.1109/ICMLC.2007.4370832
Filename
4370832
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