DocumentCode
2261256
Title
Study on similarity of simple questions based on the catering field
Author
Dong, Qijun ; Shi, Shuicai ; Wang, Hongwei ; Lv, Xueqiang
Author_Institution
Chinese Inf. Process Res. Center, BISTU, Beijing, China
fYear
2009
fDate
24-27 Sept. 2009
Firstpage
1
Lastpage
5
Abstract
The similarity between sentences is a theoretical basis and key technology to the question answering system. The method presented in this paper is as follows. Firstly, the dependency question sets are obtained and the key words are extracted from the major components of the question sentences and the target question form the related libraries, and then the candidate question sets are obtained through comparing their field words and key words. Secondly, take the HowNet as the semantic knowledge resource to compute the semantic similarity; and lastly the sentences with the largest similarity are returned. This accuracy of the method to calculate the similarity between the simple sentences is up to 85% in catering field. The experimental results show that the approach presented in this paper achieves good results in specific areas.
Keywords
catering industry; computational linguistics; information retrieval; information retrieval systems; natural language processing; HowNet semantic knowledge resource; candidate question set; catering field word; dependency question set; keyword extraction; library; natural language processing; question answering system; question sentence semantic similarity; Data mining; Information analysis; Information processing; Libraries; Marine animals; Natural language processing; Shape; Skeleton; Surface treatment; Tagging; HowNet; interdependence; the catering field; the similarity between sentences;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Language Processing and Knowledge Engineering, 2009. NLP-KE 2009. International Conference on
Conference_Location
Dalian
Print_ISBN
978-1-4244-4538-7
Electronic_ISBN
978-1-4244-4540-0
Type
conf
DOI
10.1109/NLPKE.2009.5313852
Filename
5313852
Link To Document