交互式问答系统：文献综述
Interactive Question Answering Systems: Literature Review
AI总结：
本综述系统梳理交互式问答系统，提出统一框架与分类法，分析其方法、评估及数据集，并展望未来趋势，附GitHub资源汇总。
摘要：
问答系统被公认为网络上流行且经常有效的信息寻求方式。在此类系统中，信息寻求者可以通过自然语言提出自己的问题，从而获得对其查询的简洁回答。交互式问答是最近提出且日益流行的解决方案，它位于问答系统与对话系统的交叉点。一方面，用户可以用常规语言提问并找到其询问的实际答案；另一方面，如果初始请求存在多个可能答案、答案极少或存在歧义，系统可以将问答会话延长为对话。通过允许用户提出更多问题，交互式问答使用户能够与系统动态交互并获得更精确的结果。本综述对当前文献中流行的交互式问答方法进行了详细概述。首先解释了问答系统的基本原理，从而定义新的符号和分类法，将所有已识别的工作统一在一个框架内。随后，从所提出的方法论、评估方法以及数据集/应用领域等方面，对已发表的交互式问答系统工作进行展示和审视。我们还描述了围绕特定任务和社区提出的问题所呈现的趋势，从而揭示学者未来的研究兴趣。我们的工作还得到了一个GitHub页面的支持，该页面综合了本文献研究涵盖的所有主要主题。https://sisinflab.github.io/interactive-question-answering-systems-survey/
英文摘要：
Question answering systems are recognized as popular and frequently effective means of information seeking on the web. In such systems, information seekers can receive a concise response to their query by presenting their questions in natural language. Interactive question answering is a recently proposed and increasingly popular solution that resides at the intersection of question answering and dialogue systems. On the one hand, the user can ask questions in normal language and locate the actual response to her inquiry; on the other hand, the system can prolong the question-answering session into a dialogue if there are multiple probable replies, very few, or ambiguities in the initial request. By permitting the user to ask more questions, interactive question answering enables users to dynamically interact with the system and receive more precise results. This survey offers a detailed overview of the interactive question-answering methods that are prevalent in current literature. It begins by explaining the foundational principles of question-answering systems, hence defining new notations and taxonomies to combine all identified works inside a unified framework. The reviewed published work on interactive question-answering systems is then presented and examined in terms of its proposed methodology, evaluation approaches, and dataset/application domain. We also describe trends surrounding specific tasks and issues raised by the community, so shedding light on the future interests of scholars. Our work is further supported by a GitHub page with a synthesis of all the major topics covered in this literature study. https://sisinflab.github.io/interactive-question-answering-systems-survey/
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
