Semantic Comprehension of Questions in Q&A System for Chinese Language Based on Semantic Element Combination

Question understanding is an extremely important part of the question and answer (Q&A) system, which is the basis of subsequent information retrieval and answer extraction. In order to improve the semantic understanding of question, we propose a method of understanding the question based on the combination of semantic element for Chinese language. Firstly, the method uses lexical and rules recognition to extract the semantic elements of questions and recognizes the functions according to the preprocessing pattern. Secondly, combining the dependency analysis tree structure of the question and the function type, it can produce the semantic elements. Finally, a normalized semantic expression was generated. We extract the user questions in Baidu-Zhidao as the test set. The result shows that the accuracy of the proposed method is 97.8%, so the semantics of the Chinese language questions can be effectively understood by this method.