Research on Knowledge Graph Modeling Method for Financial Audit of Power Grid Enterprises

With the rapid development of social economy, the financial audit of power grid enterprises has become one of the important components of the economic supervision system. This paper proposes a knowledge graph modeling method for the internal audit of power grid enterprises, and uses deep learning technology to mine the causal relationship between structured data and unstructured data. Knowledge graph makes audit data easier to understand by structurally describing concepts, entities and their relationships in objective data information. With the advantage of knowledge graph semantic network, it can effectively mine the hidden value of massive audit data and the correlation between data. At the same time, the deep learning technology is introduced into the knowledge graph component to extract data features from the multivariate and heterogeneous data of the audit system and mine the relationship between data, which can effectively improve the internal audit level of enterprises.On the basis of previous theoretical work, this paper proposes a set of knowledge graph construction algorithm based on deep learning, and through the comparison with the knowledge graph based on relationship detection, it is verified by experiments that the proposed method has the advantages of large amount of information recognition and high recognition accuracy.