摘要
This paper outlines the basic concept of knowledge graph and its unique advantages, and explains in detail its approach to processing complex data structures through data integration, relationship discovery and semantic understanding. Knowledge graphs utilize a combination of technologies such as entities, attributes, relationships, and semantic annotations to demonstrate indispensable functionality in standardization processes, and especially excel in achieving semantic connectivity. This paper systematically analyzes the role of knowledge graph in each level using the standards hierarchical model as a framework. In Level 1, knowledge graph supports information extraction and preliminary tagging;in Level 2, it realizes structured and semantic processing of documents;in Level 3, it facilitates complex relationship modeling and executive integration;and it lays the foundation for advanced intelligent applications, autonomous standards governance and dynamic automatic updating in Level 4 and 5. This paper provides an in-depth discussion of its future directions and possible challenges, including key topics such as optimizing the scalability of knowledge graphs and facilitating cross-domain knowledge fusion. It shows that knowledge graphs provide powerful technical support for standards digitization and offer new possibilities for realizing smart manufacturing and cross-domain collaboration.
