Domain knowledge graph-based research progress of knowledge representation

• Published in: Neural computing & applications 2021, Vol.33 (2), p.681-690
• Main Authors: Lin, Jinjiao, Zhao, Yanze, Huang, Weiyuan, Liu, Chunfang, Pu, Haitao
• Format: Article
• Language: English
• Subjects: Artificial Intelligence; Computational Biology/Bioinformatics; Computational Science and Engineering; Computer Science; Data Mining and Knowledge Discovery; Domains; Graphical representations; Graphs; Image Processing and Computer Vision; Knowledge bases (artificial intelligence); Knowledge representation; Probability and Statistics in Computer Science; S.I. : DPTA Conference 2019
• ISSN: 0941-0643; 1433-3058
• DOI: 10.1007/s00521-020-05057-5

Domain knowledge graph has become a research topic in the era of artificial intelligence. Knowledge representation is the key step to construct domain knowledge graph. There have been quite a few well-established general knowledge graphs. However, there are still gaps on the domain knowledge graph construction. The research introduces the related concepts of the knowledge representation and analyzes knowledge representation of knowledge graphs by category, which includes some classical general knowledge graphs and several typical domain knowledge graphs. The paper also discusses the development of knowledge representation in accordance with the difference of entities, relationships and properties. It also presents the unsolved problems and future research trends in the knowledge representation of domain knowledge graph study.