Adaptive Knowledge Graph Generation Based on Conceptual Patterns

Abstract

This thesis introduces an adaptive knowledge graph generation system designed to address the challenges of managing and analysing the vast amounts of unstructured data, while mitigating the known limitations of Large Language Models (LLMs), such as hallucinations, vagueness, and a lack of interpretability.