A Chinese question-answering system with question classification and answer clustering

We propose an approach for Chinese question analysis and answer extraction. A general question analysis process contains keyword extraction and question classification. Question classification plays a crucial role in automatic question answering. To implement the question classification, we have carried out experiments with Support Vector Machines (SVM) using four kinds of features: words, part of speech (POS), named entity, semantic. And the answer extraction is converted into a clustering problem. The experimental results show the excellent performance of the proposed approach.