Research on question classification for Automatic Question Answering
Shihua Xu, Gang Cheng, Fang Kong · 2016
Automatic Question Answering (QA) is a hot topic in both Natural Language Processing (NLP) and Information Retrieval (IR). And question classification is the key step of a successful automatic QA system. In this paper, an SVM-based approach is firstly proposed as our baseline system. Then two additional features, i.e., top-words and dependency relations, are introduced to improve the performance of our baseline system. Experiments on the UIUC corpus show that the introduced features can improve our baseline system significantly. In comparison with the state-of-the-art system, our proposed approach also achieves better performance.