Safety behavior regulation matching method and system based on large model and knowledge graph

By constructing a multimodal large model and a knowledge graph-based method for matching security behavior regulations, this approach addresses the issues of missing compliance associations, insufficient scenario generalization capabilities, and model reliability in existing technologies. It enables automatic matching of security behaviors and compliance tracing, thereby improving recognition accuracy and management efficiency.

CN121682318APending Publication Date: 2026-03-17BEIJING UNIV OF TECH
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Patent Information

Application Number
CN202511890821.1
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-12-15
Publication Date
2026-03-17

AI Technical Summary

Technical Problem

Existing security behavior recognition technologies suffer from several drawbacks in high-risk areas, including a lack of compliance correlation, insufficient scenario generalization ability, defects in dynamic risk assessment, and model reliability issues. These problems result in low efficiency and high false positive rates in compliance tracing.

Method used

We adopt a security behavior regulation matching method based on large models and knowledge graphs. By constructing multimodal large models and multimodal knowledge graphs, we can achieve automatic matching and compliance traceability of security behaviors. We combine security domain standards to construct multimodal knowledge graphs, use multimodal large models to process security specification manuals, and set up security scenario thinking chain templates to achieve full-process automation from behavior recognition to regulation matching.

Benefits of technology

It significantly improves the accuracy of identifying unsafe behaviors in complex scenarios, ensures the accuracy, traceability, and compliance of output results, shortens compliance traceability time, improves management efficiency, reduces the false judgment rate, and realizes full-process automation of security management.

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Abstract

The invention provides a safety behavior regulation matching method and system based on a large model and a knowledge graph, and relates to the technical field of safety intelligent management, and the method comprises the steps: enabling a multi-modal large model to receive a field image, and generating a behavior description and a candidate regulation direction; the multi-modal large model extracts visual features from a field image based on a thinking chain template, retrieves a multi-modal knowledge graph based on the visual features and behavior description, and screens a candidate term range based on the visual features and candidate term directions; the multi-modal large model screens candidate regulations from a relational database on the basis of the direction of the candidate regulations, converts the candidate regulations into multi-modal semantic vectors on the basis of visual features and behavior description, and screens the candidate regulations from a vector database; the multi-modal large model is based on a multi-modal knowledge graph, and the most matched security behavior regulation and image-text-regulation cross-modal interpretation are output. The method breaks through the limitation of single-mode recognition, improves the recognition precision of complex scenes, and achieves the cross-mode recognition of safety behaviors and the precise matching of regulations.
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