问答式检索技术及评测研究综述

Research on Question Answering & Evaluation: A Survey

问答式检索系统(简称问答系统)是集自然语言处理技术和信息检索技术于一身的新一代搜索引擎。它的出现旨在提供更有力的信息获取工具,以应对信息爆炸带来的严重挑战。经过这几年的发展,问答系统已经成为自然语言处理领域和信息检索领域的一个重要分支和新兴的研究热点,其“通过系统化、大规模地定量评测推动研究向前发展”的发展轨迹,以及某些成功的启示,如基于字符表层的文本分析技术(模板技术)的有效性,快速、浅层自然语言处理技术的必要性,都极大地推动了自然语言处理研究的发展,促进了NLP研究与应用的紧密结合。回顾问答系统研究的历史,总结问答技术的研究现状,将有助于这方面工作向前发展。

Question Answering (QA) is the next generation of search engine which is related to natural language processing, information retrieval and etc. QA aims at providing more powerful information access tools to help users overcome the problem of information overloading. In the last decade, QA has become an important subfield of NLP and IR. Its development track, i.e. accelerating research via systematical and large scale evaluation, and some successful experiences, such as the effectiveness of partial-parsing techniques based on character surface and the importance of fast NLP tools, have made it a great and most important impetus to the research of NLP. Moreover, QA has built a more effective connection between NLP research and NLP application. It will be helpful to review the history and investigate state of the art of QA.