Wissensintegration aus Webdaten in eine Graphdatenbank zur Nutzung in RAG-Systemen

A system was developed to automatically extract, model, and store university‑related information from the Technical University of Cologne’s website in a domain‑specific knowledge graph hosted in Neo4j. Large Language Models are used to translate natural‑language questions into structured Cypher queries, enabling a conversational question‑answer interface that reliably retrieves details about study programmes, faculties, and thematic focuses. Evaluation with a reference test set showed high accuracy for structured queries, while answers to personal‑data requests were limited by incomplete or inconsistent source information.