论文标题
问题回答超过策划和开放的网络来源
Question Answering over Curated and Open Web Sources
论文作者
论文摘要
在过去的几年中，关于自动化问题回答主题（QA）的研究的爆炸激增，涵盖了信息检索，自然语言处理和人工智能的社区。本教程将涵盖质量保证的真正积极成长时期的亮点，以使观众能够掌握目前正在使用的算法家族。我们将基本来源的研究贡献从检索到答案的地方分配：策划的知识图，非结构化文本或混合语料库。我们选择分区的这一维度，因为它在算法设计方面是最歧视的。每个子主题中都涵盖了其他关键维度：例如解决问题的复杂性，以及系统中引入的解释性和互动性程度。我们将以最有希望的质量检查趋势来结束教程，这将有助于进入该领域的新进入者做出最佳决定，以使社区前进。自从2016年Sigir的质量检查QA上一个教程以来，社区发生了很多变化，我们认为，这种及时的概述确实将使大量的会议参与者受益。
The last few years have seen an explosion of research on the topic of automated question answering (QA), spanning the communities of information retrieval, natural language processing, and artificial intelligence. This tutorial would cover the highlights of this really active period of growth for QA to give the audience a grasp over the families of algorithms that are currently being used. We partition research contributions by the underlying source from where answers are retrieved: curated knowledge graphs, unstructured text, or hybrid corpora. We choose this dimension of partitioning as it is the most discriminative when it comes to algorithm design. Other key dimensions are covered within each sub-topic: like the complexity of questions addressed, and degrees of explainability and interactivity introduced in the systems. We would conclude the tutorial with the most promising emerging trends in the expanse of QA, that would help new entrants into this field make the best decisions to take the community forward. Much has changed in the community since the last tutorial on QA in SIGIR 2016, and we believe that this timely overview will indeed benefit a large number of conference participants.
