Construction and Application of Knowledge Graph of Government Policy Based on Deep Neural Network

With the advent of the era of big data, the development of Deep learning technology has driven the research of smart government. The introduction of Knowledge Graph provides a new way for the development of smart government, and also provides a new way to understand the relevant objects of government policy texts, which has important academic and practical value. Based on the principle of solving the actual needs of smart government, we use the framework of Bert-BiLSTM-CRF model constructs the knowledge graph of government policy and discuss the whole process of the construction of government policy Knowledge Graph from the acquisition and processing of policy document data, the identification of government policy entities, the knowledge fusion of policy entities and the storage of Knowledge Graph. The Knowledge Graph of government policy based on practical problems lays a foundation for the in-depth study of smart government, which is an important application of deep learning technology and knowledge representation technology in the field of policy text research. At the same time, it can provide practical services for demand groups (government, enterprises, individuals, etc.).