A Study on the Construction of Extenics Database Based on LLM+Neo4j - An Example of Plant Landing Designs

As an important method for solving complex contradictions and generating innovative strategies, Extenics has broad potential in design deepening and engineering applications. However, traditional methods rely on manual modeling and lack systematic data support and intelligent mechanisms. This paper combines the large language model (LLM) and the Neo4j graph database to realize automatic recognition of knowledge structure, relationship modeling and strategy reasoning. The system parses the natural language structure through LLM, builds a semantic graph with the help of Neo4j, and completes the closed-loop reasoning of goal construction, contradiction identification and strategy generation. Taking the plant landing design as an example, the practicality and logic of this method are verified. The study shows that this method not only enhances the structural expression of Extenics, but also provides a new path for cross-domain intelligent modeling and design support.