Intelligent generation and reasoning method for aviation assembly knowledge graph based on joint knowledge embedding learning

doi:10.1016/j.asoc.2025.114140

Intelligent generation and reasoning method for aviation assembly knowledge graph based on joint knowledge embedding learning

2025-10-31

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DOI：10.1016/j.asoc.2025.114140

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• Proposes a knowledge-enhanced LLM framework for aviation assembly, achieving 91.33 % accuracy in knowledge graph generation. • Enables vector-based continuous reasoning with 96.55 % accuracy, overcoming semantic gaps in graph methods. • Develops and validates a knowledge assistance tool using real-world data, replacing traditional manuals. • Provides precise, interpretable guidance for engineers through natural language queries.

Intelligent generation and reasoning method for aviation assembly knowledge graph based on joint knowledge embedding learning

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