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案件記録

THRESHOLD-BASED ADAPTIVE ONTOLOGY AND KNOWLEDGE GRAPH MODIFICATION USING GENERATIVE ARTIFICIAL INTELLIGENCE

発明審査中
1閲覧数
20請求項 · 3 独立
§ Ⅰ

案件概要

発明者

James Myers; Ganesh Prasad BHAT; Tariq Husayn Maonah; Mariusz Saternus; Daniel Lewandowski; Biraj Krushna Rath; Stuart Murray; Philip Davies; Nigil Satish Jeyashekar; Miriam Silver; Payal Jain

IPC分類

G6N 20/20

CPC分類

G6N20/20

Systems and methods described herein enable adaptive, threshold-based modification of node maps representing ontologies, knowledge graphs, or code development pipelines using generative artificial intelligence. The disclosed platform can retrieve a node map and generate one or more candidate perturbations that modify nodes or relationships within the node map. The disclosed platform can evaluate the effect of the perturbations by comparing respective outputs against ground-truth data. Perturbations can be automatically determined based on changes in external datasets, compliance policies, or operational requirements. The perturbations can be implemented when a computed perturbation quality value satisfies a threshold quality criterion. As such, the system enables efficient, policy-compliant evolution of relational system architectures in dynamic environments.

原文(中国語)

Systems and methods described herein enable adaptive, threshold-based modification of node maps representing ontologies, knowledge graphs, or code development pipelines using generative artificial intelligence. The disclosed platform can retrieve a node map and generate one or more candidate perturbations that modify nodes or relationships within the node map. The disclosed platform can evaluate the effect of the perturbations by comparing respective outputs against ground-truth data. Perturbations can be automatically determined based on changes in external datasets, compliance policies, or operational requirements. The perturbations can be implemented when a computed perturbation quality value satisfies a threshold quality criterion. As such, the system enables efficient, policy-compliant evolution of relational system architectures in dynamic environments.

外部リソース