Treffer: An NLP-driven e-learning platform with LLMs and graph databases for personalised guidance.

Information is ubiquitously available at our fingertips, transforming the way we learn, work and engage with the world around us. The challenge is not just accessing data but discerning its relevance and utility. This constant flow of information demands selective attention and strategic thinking about how we integrate new findings for professional growth. In this context, we propose an e-learning platform that recommends career paths based on user-uploaded PDFs. Our solution extracts keywords with Natural Language Processing (NLP). Using OpenAI, we enable interaction with the PDF files, allowing the user to ask questions and receive summaries. Then, we generate embeddings and index them with Facebook AI Similarity Search (FAISS). Next, we use a dataset of job listings and, with BERT, skills and technologies are extracted. An interconnected graph using a graph database system (Neo4j) based on these skills and technologies is built. Keywords from the uploaded documents are analyzed and matched to skills, leading to job recommendations or guidance on additional skills needed to secure employment. Mean Reciprocal Rank (MRR) is calculated to compare the results of different job recommendation systems. [ABSTRACT FROM AUTHOR]

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