Abstract:

As a high-level form of information retrieval, the Question Answering system（QA）can quickly and accurately provide users with the required information services. After giving a question, an accurate answer will be given accordingly, which makes it become a more and more attention research direction  in the field of natural language processing. Question Classification（QC）is the most important part of question analysis and processing in the QA, and its classification accuracy will directly affect the overall performance of the QA. In recent years, the rapid development of machine learning and deep learning technologies has greatly promoted the research and development of QC, which has strong feasibility and superiority in question classification. This paper summarizes and analyzes the domestic and foreign research status of QC, question classification standard system, question feature extraction, traditional machine learning classification methods and recently popular deep learning classification methods, and elaborates the current status of QC. This paper expounds research difficulties in QC, and makes preliminary prospects for future research and development directions.

Key words: question answering system, question classification, classification system, machine learning, deep learning

摘要：

问答系统作为信息检索的一种高阶形式，能够迅速、精准地为用户提供所需的信息服务，在给定一个问题后，会相应地给出准确的答案，这使得它在自然语言处理领域成为一个越发受人关注的研究方向。问句分类作为问答系统中的问题分析和处理的首要环节，是问答系统中尤为重要的一部分，其分类精度会直接影响到问答系统的性能。近些年来，机器学习和深度学习等技术的快速发展极大地促进了问句分类的研究和发展，其在问句分类上具有较强的可行性和优越性。为此就问句分类的国内外研究现状、问句分类标准体系、问句特征抽取、传统的机器学习分类方法和近来流行的深度学习分类方法进行总结和分析，阐述了问句分类当前所面临的一些研究难点，并对未来的研究和发展方向做了初步展望。

关键词: 问答系统, 问句分类, 分类体系, 机器学习, 深度学习