Unofficial implementation of the algorithm described in the paper Federated Collaborative Filtering for Privacy-Preserving Personalized Recommendation System by Muhammad Ammad-ud-din et al.
This Python implementation is mainly based on sparse computations performed with the library scipy.
The results of this implementation with the datasets MovieLens 1M, Amazon Digital Music, LibraryThing and Foursquare are available within the following papers:
- FedeRank: User Controlled Feedback with Federated Recommender Systems (ECIR 2021)
- How to put users in control of their data in federated top-N recommendation with learning to rank (SAC 2021)
Please, be aware that this is not a stable implementation. So, your suggestions are welcome!