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Knowledge graph construction for intelligent cockpits based on large language models.

Haomin Dong1,2, Wenbin Wang2, Zhenjiang Sun2

  • 1School of Mechanical and Aerospace Engineering, Jilin University, Changchun, 130025, China.

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This study introduces GLM-TripleGen, a novel knowledge graph construction model for intelligent cockpits. It accurately captures user behavior and enhances system understanding, overcoming limitations of traditional methods.

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Area of Science:

  • Human-Computer Interaction
  • Artificial Intelligence
  • Knowledge Representation

Background:

  • Intelligent cockpits require advanced user behavior inference for proactive interaction.
  • Traditional methods face scalability, generalization, and accuracy issues, leading to pseudo-demand functions.
  • Knowledge graphs (KGs) offer a solution for organizing complex information and understanding user needs.

Purpose of the Study:

  • To develop a novel knowledge graph construction (KGC) model, GLM-TripleGen, for analyzing intelligent cockpit states and behaviors.
  • To precisely mine latent relationships between cockpit states and user behaviors.
  • To address challenges in entity recognition and relationship extraction within cockpit data.

Main Methods:

  • Introduced GLM-TripleGen, a domain-specific KGC model for intelligent cockpits.
  • Constructed an instruction-following dataset tailored to vehicle states and in-cockpit interactions.
  • Employed the Low-Rank Adaptation (LoRA) method for efficient model fine-tuning and parameter optimization.

Main Results:

  • GLM-TripleGen demonstrated superior performance compared to state-of-the-art KGC methods.
  • The model accurately generated normalized cockpit triple units.
  • Achieved robust performance and strong generalization capabilities with unknown entities and relationships.

Conclusions:

  • GLM-TripleGen effectively addresses the challenges of KGC in intelligent cockpit domains.
  • The model enhances the system's ability to understand user behavior and contextual information.
  • GLM-TripleGen offers a robust and adaptable solution for knowledge graph construction in evolving intelligent systems.