Abstract:

Question classification aims at classifying the types of questions automatically, and this is a basic task of the question answering system. We propose a classification method for semi-supervised questions with answers. Firstly, we combine answer features with question features to realize sample expressions. Then we train a question classifier on labeled questions using label propagation algorithm to annotate the category of unlabeled questions automatically. The questions of initial annotation and automatic annotation are merged with each other as training samples, and the maximum entropy model is adopted to classify the testing samples. Experimental results demonstrate that the classification method for semisupervised questions with answers in this paper can make full use of the unlabeled samples to improve the performance, and it outperforms other benchmark methods.

Key words: question answering system;question classification;answer aiding;semi-supervised classification;label propagation