elisacomposta / recommender-systems-challenge

Recommender Systems challenge about book recommentations.

Recommender Systems Challenge 2023

This repository contains the code for the Recommender Systems challenge (Politecnico di Milano, 2023-2024), made on Kaggle.

The application domain is book recommendation, and the goal of the competition is to discover which items a user will interact with.
The datasets contains interactions of users with books: if the user attributed to the book a rating of at least 4, the interaction is present in the dataset with value 1.

Recommender

The final recommender used in the challenge is an hybrid of:

• SLIM Elastic Net
• RP3beta

obtained merging the two similarity matrices using a weighted sum.

All the models have been trained using both Kaggle and Colab notebooks.

Evaluation

The evaluation metric used for the competition is MAP@10.

• Public leaderboard score: 0.14042 (18^th / 63)
• Private leaderboard score: 0.13984 (20^th / 63)

Credits

The code in this repository was built upon the course repository, which provides the implementation of recommenders and utility code.

Team

Simone Scevaroli & Elisa Composta