The implementation of our ICDM 2019 paper "Relation Structure-Aware Heterogeneous Graph Neural Network" RSHN. Slides.
python == 3.6.2
torch == 1.1.0
numpy == 1.16.4
scipy == 1.2.0
torch_geometric == 1.0.0
numba == 0.42.1
The data folder includes our propocessed data for training and testing.
The orginal datasets can be founded from here.
The model folder includes our proposed model "RSHN".
The build_coarsened_line_graph folder includes utils used in model.
The torch_geometeric/nn/conv folder includes the designed convolution layers used in model.
cd model
python RSHN.py --dataset AIFB --lr 0.01 --weight_decay 5e-4 --dim 16 --num_node_layer 2 --num_edge_layer 1 --dropout 0.6 --epoch 50
@inproceedings{zhu2019RSHN
author={Shichao Zhu and Chuan Zhou and Shirui Pan and Xingquan Zhu and Bin Wang},
title={Relation Structure-Aware Heterogeneous Graph Neural Network},
journal={IEEE International Conference On Data Mining (ICDM)},
year={2019}
}