Article Details

Title · Authors · Abstract · Keywords · DOI · References

Research Review of Knowledge Graph Construction

YANG Yanyun1, HU Jun2

(1.Jiangxi Open University, Nanchang 330046, China; 2.Jiangxi Flight University, Nanchang 330088, China)

Section：Computer Technology · Vol. 2025, Issue 8 · Pages：117-125,131 · 2096-4706（2025）08-0117-10 · CLC number：TP391 · Document code：A · DOI：10.19850/j.cnki.2096-4706.2025.08.022

Abstract

As a structured semantic knowledge base, the Knowledge Graph plays a key role in many fields such as information retrieval, intelligent question answering, and recommendation systems. This paper reviews the three core components of Knowledge Graph construction, information extraction, knowledge fusion, and knowledge reasoning. Information extraction technology has developed from rule-based methods to Machine Learning model, and then to Deep Learning model. It is currently evolving towards a joint Entity Relationship Extraction model that reduces error propagation and improves accuracy. In the part of knowledge fusion, the strategies of entity linking and knowledge merging are discussed, and the problem of entity recognition is solved by entity disambiguation and entity alignment. The section on knowledge reasoning analyzes the reasoning methods based on rules, representation learning and Deep Learning, and its application in new knowledge discovery and error information correction. Finally, the challenges in the construction process are pointed out, and suggestions for future research directions are proposed to promote the development of knowledge graph research and application.

Keywords

Knowledge Graph; information extraction; knowledge fusion; knowledge reasoning; Deep Learning

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Funding

Science and Technology Project of Jiangxi Provincial Department of Education (GJJ215702); Jiangxi Flight University Series of Scientific Research Projects (2024YB01)

About the authors

Yang Yanyun (April 1995-), female, Han ethnicity, from Zhangjiakou, Hebei Province, China, teaching assistant, master's student, research direction: natural language processing, data mining, software development; Hu Jun (September 1996-), male, Han ethnicity, from Fuzhou, Jiangxi Province, teaching assistant, master's student, research direction: data mining.