Action Sequence Augmentation for Early Graph-based Anomaly Detection

This repository contains the source code for the CIKM'2021 paper:

Action Sequence Augmentation for Early Graph-based Anomaly Detection

by Tong Zhao* (tzhao2@nd.edu), Bo Ni* (bni@alumni.nd.edu), Wenhao Yu, Zhichun Guo, Neil Shah, and Meng Jiang.

Requirements

This code package was developed and tested with Python 3.8.5. Make sure all dependencies specified in the requirements.txt file are satisfied before running the model. This can be achieved by

pip install -r requirements.txt

Example Usage

python -u main.py --dataset reddit --rnn gru --method gcn --graph_num 3

Cite

If you find this repository useful in your research, please cite our paper:

@inproceedings{zhao2021action,
  title={Action Sequence Augmentation for Early Graph-based Anomaly Detection},
  author={Zhao, Tong and Ni, Bo and Yu, Wenhao and Guo, Zhichun and Shah, Neil and Jiang, Meng},
  booktitle={Proceedings of the 30th ACM International Conference on Information \& Knowledge Management},
  pages={},
  year={2021}
}