GraphRAG: Revolutionizing University Admissions Q&A Systems

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This report covers a student research project on developing an automated web-based Q&A system utilizing GraphRAG and large language models to achieve creative, accurate responses. Objectives included reaching a 75% accuracy rate, tested on university queries, achieving an 80% success rate compared to traditional systems. Key technologies involved knowledge graphs, embeddings, and augmented retrieval methods. Challenges included expanding applicability beyond a single university, handling...