Generation of New Type of Question Features Based on Bag-of-Words Binding

Aiming at difficulties from lack of rich syntax and semantic features for Chinese question classification, a method is proposed to automatically generate new types of features based on bag-of-words binding in this work. Considering the basic features of bag-of-words(BOW), part of speech(POS), word sense(WS) and others, new types of features could be generated by binding them with bag-of-words respectively, named as W/POS, W/WS, etc. Experiment has been implemented with SVM classifier and the Chinese question set provided by Harbin Institute of Technology. The results show that, compared with the basic features of POS, WS and others, the classification accuracies of bag-of-words binding features of W/POS, W/WS and others get significantly increase. Furthermore, the classification accuracy of the combined bag-of-words binding features for 77 question categories could be up to 82.333%, which indicates the effectiveness of the proposed method for question classification.