DocumentCode :
247023
Title :
An Improved Method of Interrogative Sentence Similarity Compute and Application in Q&A System
Author :
Yang Jing ; Zhu Qi ; Xu Haizhou
Author_Institution :
Sch. of Electr. & Electron. Eng., East China Jiaotong Univ., Nanchang, China
fYear :
2014
fDate :
8-10 Nov. 2014
Firstpage :
209
Lastpage :
212
Abstract :
Sentence similarity compute is an important part in question answering system based on frequency asking questions. The accuracy of the existing sentence similarity algorithm needs to be improved, so this paper presents a revised question similarity compute method. We combine the word order feature with vector space model algorithm. When we use the VSM to compute the question similarity, we propose a method of extracting topic and focus. The difference between this method and the traditional approach is that this method doesn´t depend on interrogative. Topic and focus can reflect the purport of a question. By identifying it can we better understand the question, and consider the impact of the topic and focus in questions similarity compute. At last, by designing experiment to compare it with other methods, the experiment shows that this method can improve the accuracy.
Keywords :
design of experiments; question answering (information retrieval); text analysis; Q&A system; VSM; designing experiment; focus extraction; interrogative sentence similarity compute; question answering system; question similarity compute method; sentence similarity algorithm; topic exraction; vector space model algorithm; word order feature; Accuracy; Computational modeling; Educational institutions; Feature extraction; Knowledge discovery; Semantics; Vectors; interrogative sentence similarity compute; question answering system; topic and focus; vector space model; word order;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC), 2014 Ninth International Conference on
Conference_Location :
Guangdong
Type :
conf
DOI :
10.1109/3PGCIC.2014.62
Filename :
7024583
Link To Document :
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