Support Vector Machines for Text Categorization in Chinese Question Classification

Authors:
Xu-Dong Lin;Hong Peng;Bo Liu
Affiliations:
South China University of Technology, China;South China University of Technology, China;South China University of Technology, China
Venue:
WI '06 Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence
Year:
2006

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Abstract

Question classification plays a crucial important role in the question answering system because categorizing a given question is beneficial to identify an answer in the documents. The goal of question classification is to accurately assign labels to question based on expected answer type. Recently, many machine learning algorithms are used for question classification. However many research results show that SVM perform best in this task, because it is well known to work well for nonlinear, sparse, high dimensional problems. In this experiment, we perform the One-against-One SVM algorithm and a feature extraction method of Chinese questions to get high classification accuracy.