Question Classification in Chinese Restricted-Domain Based on SVM and Domain Dictionary

摘要：

Question classification is very important for question answering. This paper presents our research work on automatic question classification through support vector machine approaches. Unlike the classification using only bag-of-word features, we exploit the domain knowledge and question-specific stop words in our model, and also present how to enrich bag-of-word approach by implementing feature attributes to facilitate the question categorization. When tested on the questions in cooking domain, our approach reaches an accuracy up to 86.34％, which promisingly outperforms the result of the baseline.

关键词： RDQA question classification SVMs domain knowledge

作者: Ling XIA Zhi TENG Fuji REN

作者单位: Faculty of Engineering,The University of Tokushima Tokushima,770-8506,Japan

会议类型: 国际会议

会议名称: The 2008 IEEE International Conference on Natural Language Processing and Knowledge Engineering(IEEE NLP-KE 2008)(2008IEEE自然语言处理与知识工程国际会议)

会议地点: 北京

会议语种:英文

在线出版日期: 2008-10-19（万方平台首次上网日期，不代表论文的发表时间）