Table Question Answering (Table QA) refers to providing precise answers from tables to answer a user's question. In recent years, there have been a lot of works on table QA, but there is a lack of comprehensive surveys on this research topic. Hence, we aim to provide an overview of available datasets and representative methods in table QA. We classify existing methods for table QA into five categories according to their techniques, which include semantic-parsing-based, generative, extractive, matching-based, and retriever-reader-based methods. Moreover, as table QA is still a challenging task for existing methods, we also identify and outline several key challenges and discuss the potential future directions of table QA.
翻译:问题解答表(质答表)是指从表格中提供准确的答案,回答用户的问题。近年来,在表格质量解答表上做了大量工作,但缺乏关于这一研究专题的全面调查。因此,我们力求提供一份有关表格质量解答现有数据集和代表性方法的概览。我们根据表格质量解答现有方法的技术分为五类,其中包括基于语义分离、基因化、采掘、配对和检索器阅读器的方法。此外,由于表格质量解析对于现有方法来说仍是一项艰巨的任务,我们还查明和概述了几个关键挑战,并讨论了表格质量解析的潜在未来方向。