Legommenders
A modular framework for recommender systems
![Legommenders](https://github.com/Jyonn/Legommenders/raw/master/Legommenders.png)
Updates
Jan. 23, 2024
- Legommenders partially supports the flatten sequential recommendation model.
- New models are added, including: MaskNet, GDCN, etc.
Oct. 16, 2023
- We clean the code and convert names of the item-side parameters.
Oct. 5, 2023
- The first recommender system package, Legommenders, with a modular-design is released!
- Legommenders involves a set of recommender system algorithms, including:
- Matching based methods: NAML, NRMS, LSTUR, etc.
- Ranking based methods: DCN, DeepFM, PNN, etc.
Citations
Legommenders have served as a fundamental framework for several research projects, including ONCE, SPAR,GreenRec, and UIST.
If you find Legommenders useful in your research, please consider citing our project:
@online{legommenders,
author = {Liu, Qijiong},
title = {Legommenders: A Modular Framework for Recommender Systems},
year = {2023},
url = {https://github.com/Jyonn/Legommenders}
}