Systematic review of question answering over knowledge bases

IET Softw. Pub Date : 2021-06-24 DOI:10.1049/sfw2.12028
Arnaldo Pereira, A. Trifan, Rui Pedro Lopes, J. L. Oliveira
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引用次数: 13

Abstract

Over the years, a growing number of semantic data repositories havebeen made available on the web. However, this has created new challenges in exploiting these resources efficiently. Querying services require knowledge beyond the typical user’s expertise, which is a critical issue in adopting semantic information solutions. Several proposals to overcome this dif-ficulty have suggested using question answering (QA) systems to provide user ‐ friendly interfaces and allow natural language use. Because question answering over knowledge bases (KBQAs) is a very active research topic, a comprehensive view of the field is essential. The purpose of this study was to conduct a systematic review of methods and systems for KBQAs to identify their main advantages and limitations. The inclusion criteria rationale was English full ‐ text articles published since 2015 on methods and systems for KBQAs. Sixty ‐ six articles were reviewed to describe their underlying reference architectures.
对知识库的问题回答进行系统的审查
多年来,web上提供了越来越多的语义数据存储库。然而,这给有效开发这些资源带来了新的挑战。查询服务需要超出典型用户专业知识的知识,这是采用语义信息解决方案的关键问题。为了克服这一困难,一些建议建议使用问答(QA)系统来提供用户友好的界面并允许自然语言的使用。由于知识库问答(KBQAs)是一个非常活跃的研究课题,因此对该领域有一个全面的看法是必不可少的。本研究的目的是对kbqa的方法和系统进行系统回顾,以确定其主要优点和局限性。纳入标准的依据是2015年以来发表的关于kbqa方法和系统的英文全文文章。我们回顾了66篇文章来描述他们的底层参考架构。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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