This invention describes an AI system designed to combine information from many different databases, even if they are structured differently. It first converts each database's information into a "knowledge graph," which is like a map of how the data is connected. These maps are then fed into two separate AI learning models to identify correlations between data fields across the databases. The system then produces two integrated knowledge graphs showing these connections, ultimately creating a single, unified knowledge graph that brings all the correlated information together.
Why it matters: Filed before the widespread adoption of highly capable large language models (LLMs), which excel at understanding and correlating diverse data structures. The claims cover using AI to find correlations between database fields, a task significantly enhanced by current LLM capabilities in schema matching and data integration.
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