An Overview of Knowledge Graph Reasoning: Key Technologies and Applications

被引:19
作者
Chen, Yonghong [1 ]
Li, Hao [2 ]
Li, Han [1 ]
Liu, Wenhao [1 ]
Wu, Yirui [2 ]
Huang, Qian [2 ]
Wan, Shaohua [3 ]
机构
[1] Yangzhou Collaborat Innovat Res Inst Co Ltd, Yangzhou 225006, Peoples R China
[2] Hohai Univ, Coll Comp & Informat, Nanjing 211100, Peoples R China
[3] Univ Elect Sci & Technol China, Shenzhen Inst Adv Study, Chengdu 611731, Peoples R China
基金
国家重点研发计划; 中国国家自然科学基金;
关键词
knowledge reasoning; knowledge graph; rule reasoning; distributed representation; neural network;
D O I
10.3390/jsan11040078
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In recent years, with the rapid development of Internet technology and applications, the scale of Internet data has exploded, which contains a significant amount of valuable knowledge. The best methods for the organization, expression, calculation, and deep analysis of this knowledge have attracted a great deal of attention. The knowledge graph has emerged as a rich and intuitive way to express knowledge. Knowledge reasoning based on knowledge graphs is one of the current research hot spots in knowledge graphs and has played an important role in wireless communication networks, intelligent question answering, and other applications. Knowledge graph-oriented knowledge reasoning aims to deduce new knowledge or identify wrong knowledge from existing knowledge. Different from traditional knowledge reasoning, knowledge reasoning methods oriented to knowledge graphs are more diversified due to the concise, intuitive, flexible, and rich knowledge expression forms in knowledge graphs. Based on the basic concepts of knowledge graphs and knowledge graph reasoning, this paper introduces the latest research progress in knowledge graph-oriented knowledge reasoning methods in recent years. Specifically, according to different reasoning methods, knowledge graph reasoning includes rule-based reasoning, distributed representation-based reasoning, neural network-based reasoning, and mixed reasoning. These methods are summarized in detail, and the future research directions and prospects of knowledge reasoning based on knowledge graphs are discussed and prospected.
引用
收藏
页数:26
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