Fact Checking Knowledge Graphs -- A Survey

IF 28 1区计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS

ACM Computing Surveys Pub Date : 2025-07-19 DOI:10.1145/3749838

Umair Qudus, Michael Röder, Muhammad Saleem, Axel-Cyrille Ngonga Ngomo

引用次数: 0

Abstract

Knowledge graphs are used by a growing number of applications to represent structured data. Hence, evaluating the veracity of assertions in knowledge graphs—dubbed fact checking—is currently a challenge of growing importance. However, manual fact checking is commonly impractical due to the sheer size of knowledge graphs. This paper is a systematic survey of recent works on automatic fact checking with a focus on knowledge graphs. We present recent fact-checking approaches, the varied sources they use as background knowledge, and the features they rely upon. Finally, we draw conclusions pertaining to possible future research directions in fact checking knowledge graphs.

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事实核查知识图谱——一项调查

越来越多的应用程序使用知识图来表示结构化数据。因此，评估知识图中断言的准确性（称为事实检查）是当前日益重要的挑战。然而，由于知识图谱的庞大规模，手动事实检查通常是不切实际的。本文以知识图谱为重点，系统地综述了近年来在自动事实核查方面的研究成果。我们介绍了最近的事实核查方法，它们用作背景知识的各种来源，以及它们所依赖的特征。最后，对知识图谱事实检验的未来研究方向进行了总结。

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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来源期刊

ACM Computing Surveys 工程技术-计算机：理论方法

CiteScore

33.20

自引率

0.60%

发文量

372

审稿时长

12 months

期刊介绍： ACM Computing Surveys is an academic journal that focuses on publishing surveys and tutorials on various areas of computing research and practice. The journal aims to provide comprehensive and easily understandable articles that guide readers through the literature and help them understand topics outside their specialties. In terms of impact, CSUR has a high reputation with a 2022 Impact Factor of 16.6. It is ranked 3rd out of 111 journals in the field of Computer Science Theory & Methods. ACM Computing Surveys is indexed and abstracted in various services, including AI2 Semantic Scholar, Baidu, Clarivate/ISI: JCR, CNKI, DeepDyve, DTU, EBSCO: EDS/HOST, and IET Inspec, among others.