Tailoring Educational Resources Retrieval via Confidentiality-Preserving RAG

This paper investigates EM-driven query decomposition techniques for optimizing educational resource retrieval under confidentiality constraints.
The study highlights the balance between personalization and data protection in AI-driven learning environments.

Recommended citation: Boratto L., Congiu F., Fenu G., Marras M. (2025). Tailoring Educational Resources Retrieval via Confidentiality-Preserving RAG. In Proceedings of SIREM 2025. http://academicpages.github.io/files/tailoring-educational-rag.pdf