A Framework to Answer Questions of Opinion Type

摘要：

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.

关键词： Question Answering Opinion Mining Information Retrieval Classification Clustering

作者: Xiangdong Su Guanglai Gao Yu Tian

作者单位: School of Computer Science Inner Mongolia University Hohhot, China 010021

会议类型: 国际会议

会议名称: 2010 Seventh Web Information System and Applications Conference(第七届全国web信息系统及其应用学术会议)

会议地点: 呼和浩特

会议语种:英文

页码: 166-169

在线出版日期: 2010-08-20（万方平台首次上网日期，不代表论文的发表时间）