Knowledge graph and knowledge reasoning: A systematic review

Q1 Engineering Journal of Electronic Science and Technology Pub Date : 2022-06-01 DOI:10.1016/j.jnlest.2022.100159

Ling Tian , Xue Zhou , Yan-Ping Wu , Wang-Tao Zhou , Jin-Hao Zhang , Tian-Shu Zhang

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引用次数: 18

Abstract

The knowledge graph (KG) that represents structural relations among entities has become an increasingly important research field for knowledge-driven artificial intelligence. In this survey, a comprehensive review of KG and KG reasoning is provided. It introduces an overview of KGs, including representation, storage, and essential technologies. Specifically, it summarizes several types of knowledge reasoning approaches, including logic rules-based, representation-based, and neural network-based methods. Moreover, this paper analyzes the representation methods of knowledge hypergraphs. To effectively model hyper-relational data and improve the performance of knowledge reasoning, a three-layer knowledge hypergraph model is proposed. Finally, it analyzes the advantages of three-layer knowledge hypergraphs through reasoning and update algorithms which could facilitate future research.

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知识图谱与知识推理:系统综述

知识图(knowledge graph, KG)表示实体之间的结构关系，已成为知识驱动型人工智能日益重要的研究领域。在这项调查中，对KG和KG推理进行了全面的回顾。它介绍了kg的概述，包括表示、存储和基本技术。具体来说，它总结了几种类型的知识推理方法，包括基于逻辑规则的方法、基于表示的方法和基于神经网络的方法。此外，本文还分析了知识超图的表示方法。为了有效地对超关系数据建模，提高知识推理的性能，提出了一种三层知识超图模型。最后，通过推理和更新算法分析了三层知识超图的优势，为今后的研究提供了参考。

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来源期刊

Journal of Electronic Science and Technology Engineering-Electrical and Electronic Engineering

CiteScore

4.30

自引率

0.00%

发文量

1362

审稿时长

99 days

期刊介绍： JEST (International) covers the state-of-the-art achievements in electronic science and technology, including the most highlight areas: ¨ Communication Technology ¨ Computer Science and Information Technology ¨ Information and Network Security ¨ Bioelectronics and Biomedicine ¨ Neural Networks and Intelligent Systems ¨ Electronic Systems and Array Processing ¨ Optoelectronic and Photonic Technologies ¨ Electronic Materials and Devices ¨ Sensing and Measurement ¨ Signal Processing and Image Processing JEST (International) is dedicated to building an open, high-level academic journal supported by researchers, professionals, and academicians. The Journal has been fully indexed by Ei INSPEC and has published, with great honor, the contributions from more than 20 countries and regions in the world.