A repository to work on the project assigned at the course Recommender Systems 2024/2025
This repository hosts the project for the Recommender Systems course at the Politecnico di Milano. The project aims to explore and deepen knowledge of Recommender Systems in the context of Artificial Intelligence. Specifically, our goal is to develop a state-of-the-art book recommendation system..
The project is part of a competition reserved for students of the Recommender Systems course. The main objective is to predict and recommend 10 potentially relevant books for each user based on their historical interactions. The evaluation metric used is MAP@10.
Dataset Details: Interactions: ~1.9 million user-book interactions. Users: ~35,000. Books: ~38,000. Features: ~94,000 item features. Split: 80% training, 20% test (random holdout). Participants can implement and test any recommender algorithm in Python, while adhering to restrictions on reusing external code and frameworks.
| Name | GitHub | |
|---|---|---|
| Kalana Kalpitha Kalupahana | kalanakalpitha.kalupahana@mail.polimi.it | kala1221 |
| Andrea Fondacaro | andrea.fondacaro@mail.polimi.it | andrea.fondacaro |