A standard citation relationship identification system and method based on a gravity model
By using gravity models and federated learning techniques, the citation relationships of standards are quantified, which solves the problems of ambiguity and foreign dependence in the development of traditional standards, and realizes the optimization of an efficient and scientific standard system and independent development, thereby improving the standardization level of the robotics industry.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- SHANGHAI INST OF QUALITY & STANDARDIZATION
- Filing Date
- 2025-10-20
- Publication Date
- 2026-07-21
AI Technical Summary
Traditional standard development relies on expert experience and lacks quantitative analysis tools, resulting in a vague standard system, difficulty in identifying gaps in the field, high dependence on foreign standards, and time-consuming manual analysis that is prone to missing key reference paths.
A standard citation relationship identification system based on a gravity model is adopted. By quantifying the citation strength between standards, analyzing the evolution of topics and time series characteristics, and combining federated learning technology, cross-enterprise standard data collaborative analysis is achieved, and a data-driven standard system optimization path is constructed.
It significantly improves the efficiency of standard system optimization, reduces the risk of dependence on foreign standards, enhances the scientific and forward-looking nature of standard development, achieves cross-institutional collaboration and data security, and provides efficient visualization interaction and decision support.
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