Private Recommender Systems: How Can Users Build Their Own Fair Recommender Systems without Log Data? (SDM 2022)
We consider how a user of a web service can build their own recommender system. Many recommender systems on the Internet are still unfair/undesirable for some users, in which case the users need to leave the service or unwillingly continue to use the system. Our proposed concept, private recommender systems, provides a way for the users to resolve this dilemma.
Paper: https://arxiv.org/abs/2105.12353
💿 Dependency
$ pip install -r requirements.txt
$ sudo apt install wget unzip
🗃️ Download and Preprocess Datasets
You can download and preprocess data by the following command. It may take time.
hetrec.npy is the Last.fm dataset. home_and_kitchen.npy is the Amazon dataset. adult_*.npy and adult_*.npz are the