STAR-GCN
The MXNet implementation of STAR-GCN: Stacked and Reconstructed Graph Convolutional Networks for Recommender Systems in IJCAI 2019
Prerequisite
Requirements
- MXNet Version 1.5.0
- Please build from source
- Compile the customized segment operator kernel according to README
- GraphSampler
- Compile the graphsampler API according to README
- GluonNLP
pip install gluonnlp
pip install spacy
python -m spacy download en
Installation
Install the mxgraph python package
python setup.py develop
Training
The training scripts are in the experiments directory. The chosen hyperparameters are stored in yml files in the cfg dirctory.
For example, to train the MovieLens-100k in the transductive setting, we can run
cd experiments/cfg
python ../STAR_GCN.py --ctx gpu0 --cfg transductive_ml-100k.yml
Cite
Please cite our paper if you use this code in your own work:
@inproceedings{zhang2019star,
title = {STAR-GCN: Stacked and Reconstructed Graph Convolutional Networks for Recommender Systems},
author = {Zhang, Jiani and Shi, Xingjian and Zhao, Shenglin and King, Irwin},
booktitle = {The 28th International Joint Conference on Artificial Intelligence},
pages = {4264--4270},
year = {2019}
}