Abstract
Knowledge graph has been a research hotspot in the field of knowledge services in recent years. Constructing a power grid knowledge graph with a reasonable hierarchy and structure is an important driving force to promote intelligent education in the grid field and the development and innovation of grid technology. Based on the analysis of the gaps between the requirements of data understanding and the technologies of the knowledge graph, a 2-layer power grid knowledge graph framework is designed for data visualization and analysis. Then the weighted average of the word vector similarity is used to match the technical framework with the acquired power grid education resource entities to build a more complete grid technology knowledge graph, making knowledge expression closer to the structure of human cognition. One case study based on this structure is performed, which shows how this power grid knowledge graph works and the effectiveness of it in power grid education resource management. The research provides an efficient analysis and mining environment for the development of research and education intelligence in the field of power grids.
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