update usage and requirements

Author: FenyuHu

README.md

@@ -2,5 +2,36 @@
 ## Description
 This is the repository for the IJCAI-19 paper [Hierarchical Graph Convolutional Networks for Semi-supervised Node Classification](https://arxiv.org/pdf/1902.06667.pdf).
 
-## Stay Tuned!
-We will release all relevant codes and datasets ASAP!
+## Requirements
+
+- Tensorflow (1.9.0)
+- networkx
+
+## Usage
+
+You can conduct node classification experiments on citation network (Cora, Citeseer or Pubmed) with the following commands:
+
+```bash
+python train.py --dataset cora --epochs 60 --early_stopping 1000 --coarsen_level 4 --dropout 0.85 --weight_decay 7e-4 --hidden 32 --node_wgt_embed_dim 8 --seed1 156 --seed2 136
+```
+
+```bash
+python train.py --dataset citeseer --epochs 200 --early_stopping 60 --coarsen_level 4 --dropout 0.85 --weight_decay 7e-4 --hidden 30 --node_wgt_embed_dim 15 --seed1 156 --seed2 156
+```
+
+```bash
+python train.py --dataset pubmed --epochs 250 --early_stopping 1000 --coarsen_level 4 --dropout 0.85 --weight_decay 7e-4 --hidden 30 --node_wgt_embed_dim 8 --seed1 156 --seed2 136
+```
+
+## Cite
+Please cite our paper if you use this code in your own work:
+
+```
+@inproceedings{hgcn_ijcai19,
+    title = {Hierarchical Graph Convolutional Networks for Semi-supervised Node Classification},
+    author = {Fenyu Hu and Yanqiao Zhu and Shu Wu and Liang Wang and Tieniu Tan},
+    booktitle = {Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, (IJCAI)},
+    year = {2019},
+    url = {https://arxiv.org/abs/1902.06667}
+}
+```