An ontology-based business semantic modeling method and system

By using ontology-based semantic segmentation and graph structure organization, combined with the improved OneKE model and ReAct algorithm, the accuracy and consistency issues of semantic modeling in existing technologies are solved, achieving efficient semantic modeling and governance.

CN122433739APending Publication Date: 2026-07-21SHUZHIYUN (BEIJING) TECHNOLOGY CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
SHUZHIYUN (BEIJING) TECHNOLOGY CO LTD
Filing Date
2026-04-22
Publication Date
2026-07-21

AI Technical Summary

Technical Problem

Existing data modeling methods struggle to accurately identify the true relationships between business concepts and attributes in complex business scenarios. Semantic candidate results are often confused or missing, mapping relationships are incomplete or mismatched, semantic model structures are incomplete and inconsistent, and semantic governance is inefficient.

Method used

An ontology-based approach is adopted to generate a set of semantic fragments and a set of data structures through semantic fragment segmentation and structural parsing. The improved OneKE model is used to extract semantics through a term hierarchy stacking mechanism. The GraphRAG algorithm is combined to construct a semantic association graph, and the ReAct algorithm is used to construct candidate mapping paths. Finally, a business semantic ontology structure and a set of mapping relationships are generated, and semantic verification and abnormal path backtracking are performed.

Benefits of technology

It improves the accuracy of semantic extraction and the completeness of associations, enhances the consistency of mapping relationships and semantic governance capabilities, and ensures the accuracy and usability of the semantic model.

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Abstract

The application discloses a kind of based on ontology's business semantic modeling method and system, comprising: S1, obtain business text data and data structure information;S2, input semantic fragment set into improved OneKE model, introduce term bit rank migration stack mechanism, generate semantic candidate set;S3, graph structure organization processing is executed using GraphRAG algorithm, and semantic correlation graph is generated;S4, business semantic ontology structure and mapping relationship set are generated by ReAct algorithm;S5, construct semantic model;S6, generate semantic governance result based on semantic model;S7, to business semantic ontology structure and mapping relationship set executes update processing, obtains the semantic model after updating, and exports business semantic modeling result.The application has the advantages of high semantic extraction accuracy, strong semantic correlation relationship integrity, high mapping relationship consistency and strong semantic governance capability.
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