A Framework to Answer Questions of Opinion Type

Author

Su, Xiangdong ; Gao, Guanglai ; Tian, Yu

Author_Institution

Sch. of Comput. Sci., Inner Mongolia Univ., Hohhot, China

fYear

2010

fDate

20-22 Aug. 2010

Firstpage

166

Lastpage

169

Abstract

In this paper, we propose a framework to answer questions of opinion type. The data source is the web pages returned from the search engine. By using Bayes Classifier, the main texts on the pages are classified into three categories at sentence level: positive review, negative review and neutral review. K-means method is used to cluster the sentences of positive review and negative review respectively. The final answers are extracted from the sentence groups after clustering and presented in the form of quaternion. We design a system to test this framework. The experimental results show that it is effective.

Keywords

Bayes methods; Web sites; feature extraction; pattern classification; pattern clustering; query processing; search engines; text analysis; Bayes classifier; K-means method; Web page; answer extraction; data source; negative review; neutral review; opinion type; positive review; question answering; search engine; Book reviews; Computers; Conferences; Data mining; Feature extraction; Quaternions; Web pages; Classification; Clustering; Information Retrieval; Opinion Mining; Question Answering;

fLanguage

English

Publisher

ieee

Conference_Titel

Web Information Systems and Applications Conference (WISA), 2010 7th

Conference_Location

Hohhot

Print_ISBN

978-1-4244-8440-9

Type

conf

DOI

10.1109/WISA.2010.22

Filename

5581311