关键词: 问答系统, 问句分类, 支持向量机, 句法特征, 语义特征

Abstract:

At present,Chinese question classification is commonly based on the combinatorial rules between the in-terrogatives and their interrelated words.Because the extraction of the combinatorial rules gready depends on language knowledge and not all combinatorial rules can be listed.the classification performance is not desirable.As the SVM (Support Vector Machine),a machine learning method based on the statistical theory,possesses excellent discriminating effect on small sample classification,this paper establishes a question classification model based on SVM after the analysis and definition of Chinese question types.Th e process of the feature selection for question classification is then described in detail.Finally,a question classification experiment is carried out by introducing coresponding semantic features based on syntactic achieved,which a classification accuracy of 88.7% being achieved,which indicates that Chinese questions can be excellently clsssified by means of SVM with the combina-tion of syntactic features and semantic features.

Key words: question-answering system, ；question classification, support vector machine, syntactic feature, seman-tic feature