一种多源异构数据对齐方法和系统
By establishing a knowledge graph of multi-source heterogeneous data, the entity parameters in power operation are analyzed and reconstructed, solving the data silo problem, achieving efficient data alignment and consistency, and improving the accuracy and efficiency of power system operation.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- SHENZHEN COMTOP INFORMATION TECH
- Filing Date
- 2025-06-20
- Publication Date
- 2026-07-17
AI Technical Summary
Existing methods for aligning heterogeneous multi-source data in power operations are ineffective in handling differences in time scale, data format, and semantic expression among different types of data. This results in data not being accurately correlated, affecting the accurate assessment of power system operating status and the accuracy and efficiency of power dispatch decisions.
By establishing a knowledge graph of multi-source heterogeneous data, extracting entity parameter sets, analyzing the similarity of entity parameters and reconstructing the knowledge graph, using semantic similarity evaluation models and relation path similarity calculation models, calculating the influence factors of common attributes and relation parameters, and combining entity alignment indicators to complete data alignment.
It improves the alignment efficiency and accuracy of multi-source heterogeneous data, solves the data silo problem, enhances the data consistency and availability of power grid operation, and provides data support for smart grid construction and power equipment condition monitoring.
Smart Images
Figure CN120561612B_ABST