问答系统研究综述

问答系统是人工智能和自然语言处理领域中具有广泛发展前景的研究方向之一.早期的问答系统限定以自然语言形式进行提问和回答,近年来,随着多模态知识图谱、多模态预训练模型的发展,支持文字、图片、音频、视频等多种模态间信息查询的广义问答系统逐渐成为新的研究热点,其以多媒体方式展示结果,更加直观、全面.本文根据问答系统任务对象的变化,将问答系统划分为3种类型:专用问答系统、通用问答系统和多模态问答系统.分析了这3种类型的问答系统发展过程中所面临的问题,着重总结每个阶段所采用的关键技术与方法,同时对问答系统在工业上的应用进行了举例说明,并对未来研究方向进行了展望.

Survey on Question Answering System Research

The question answering (Q&A) system is one of the promising research directions in the field of artificial intelligence and natural language processing. Early Q&A systems can only ask and answer in the form of natural language. In recent years, with the development of multimodal knowledge graphs and multimodal pre-training models, generalized Q&A systems supporting information queries of multiple modes such as text, image, audio, and video have gradually become a new research hotspot, and their display of results in a multimedia manner is more intuitive and comprehensive. This study classifies Q&A systems into three types according to their changing task objects: dedicated Q&A systems, general Q&A systems, and multimodal Q&A systems. The problems faced in the development of these three types of Q&A systems are analyzed, and the key technologies and methods used in each stage are highlighted and summarized. In addition, the industrial applications of Q&A systems are exemplified, and future research directions are prospected.