Research on the Construction of Aerospace Quality Knowledge System and Proactive Services

Aiming at the requirement of knowledge service in space quality management, this paper studies and proposes a solution based on knowledge graph and proactive service mechanism. Through the construction of structured knowledge graph, the effective organization and integration of complex quality management information is realized. This paper also introduces non-graph knowledge processing technology to extend the knowledge coverage. Scenario-based recommendation mechanism combines user portrait, context information and deep learning algorithm to achieve accurate knowledge push, including fuzzy matching and incomplete data information push methods. Through the case verification of space model quality problem zeroing, the system has achieved remarkable results in improving the speed of user knowledge acquisition, the relevance of recommended content and the efficiency of problem solving. The results show that this scheme has a good application prospect in the optimization of aerospace quality management process.