
# FdGars

## Paper
The FdGars model is proposed by the [paper](https://dl.acm.org/citation.cfm?id=3316586) below:
```bibtex
@inproceedings{wang2019fdgars,
  title={Fdgars: Fraudster detection via graph convolutional networks in online app review system},
  author={Wang, Jianyu and Wen, Rui and Wu, Chunming and Huang, Yu and Xion, Jian},
  booktitle={Companion Proceedings of The 2019 World Wide Web Conference},
  pages={310--316},
  year={2019}
}
```


## Brief Introduction

It applies [vanilla GCN](https://arxiv.org/abs/1609.02907) to spam detection problems with handcrafted features.

## Input Format

FdGars has the same input as vanilla GCN. In our toolbox, we take one homo-graph of DBLP dataset as its input.

## TODO List

