Welcome to the PUT-RecSys-Research organization!
We focus on research and development in the field of recommender systems, explainable AI, and the intersection of reinforcement learning with knowledge-based recommendation. Our projects aim to advance academic understanding and provide practical tools for the recommendation and AI community. 🤖📊

This repository is a Master Thesis project focused on advanced recommender systems. The work explores novel algorithms and evaluation methods for recommendation, with a strong emphasis on explainability and reproducibility. Implementations are provided primarily in Jupyter Notebook and Python, enabling easy experimentation and extension. The project is designed to serve both as a research contribution and as a practical resource for students and practitioners interested in modern recommender systems. Comprehensive documentation and well-structured experiments make it accessible for further academic or industrial research.

For questions, collaboration, or more information, please contact us via our GitHub organization page:
https://github.com/PUT-RecSys-Research