May 2024

Cracking the Knowledge Code: Hybrid AI for matching Information Systems and Natural Language

This project explores data-driven automatic programming using graph transformers. Unlike traditional programming, where humans define transformations, this method leverages inductive logic programming to learn from data. By feeding the system input and output graphs, it creates a model (program) that generalizes these transformations, automating various tasks. The core of the system is the graph transformer, …

Cracking the Knowledge Code: Hybrid AI for matching Information Systems and Natural Language Read More »

Cracking the Knowledge Code: Hybrid AI for matching Information Systems and Natural Language

This project explores data-driven automatic programming using graph transformers. Unlike traditional programming, where humans define transformations, this method leverages inductive logic programming to learn from data. By feeding the system input and output graphs, it creates a model (program) that generalizes these transformations, automating various tasks. The core of the system is the graph transformer, …

Cracking the Knowledge Code: Hybrid AI for matching Information Systems and Natural Language Read More »

Cracking the Knowledge Code: Hybrid AI for matching Information Systems and Natural Language

This project explores data-driven automatic programming using graph transformers. Unlike traditional programming, where humans define transformations, this method leverages inductive logic programming to learn from data. By feeding the system input and output graphs, it creates a model (program) that generalizes these transformations, automating various tasks. The core of the system is the graph transformer, …

Cracking the Knowledge Code: Hybrid AI for matching Information Systems and Natural Language Read More »

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