中文摘要：

为解决在开放领域问题回答问题中语料规模较小、难以满足问题分类训练需要的问题,用主动学习方法来构建中文问题分类数据集.根据主动学习的方法进行中文问题类别标注,并且通过主动式特征选择方法来提升性能.实验结果表明：在使用主动学习方法时可以快速收敛到最佳准确率（85%）,在使用人工标注特征下特征集明显的减小.基于主动学习的标注方法在需要较小人工标注同时取得很好的分类性能,并且在一定程度上还可以明显提高问题分类的准确率.

英文摘要：

The current corpora of question classification are relatively small and difficult to meet the practical needs of Question Answering system,so that we use active learning methods to construct a Chinese question classification dataset and for question labeling.In addition,we improve the performance of labeling with feature selection.Experimental results show that by using active learning we can quickly converge at the best accuracy（85%） and by using manual tagging we can have small feature set size.The active learning-based labeling method achieved very good classification performance with less manual annotation tagging,which can significantly improve the accuracy of classification to some degree.