This is the code for paper "Multi-representations Space Separation based Graph-level Anomaly-aware Detection".
Some of datasets are put in ./dataset folder. Due to the large file size limitation, some datasets are not uploaded in this project. You may download them from https://chrsmrrs.github.io/datasets/docs/datasets/.
Details in the requirements.txt.
Run the following code to test on dataset AIDS. For datasets with node attributes, feature chooses default, otherwise deg-num. If you want to add the test set into the training set as well, append the parameter "--includingTest" to the command.
python main.py --datadir dataset\AIDS --DS AIDS --feature default
@inproceedings{Lin_2023,
series={SSDBM 2023},
title={Multi-representations Space Separation based Graph-level Anomaly-aware Detection},
url={http://dx.doi.org/10.1145/3603719.3603739},
DOI={10.1145/3603719.3603739},
booktitle={35th International Conference on Scientific and Statistical Database Management},
publisher={ACM},
author={Lin, Fu and Gong, Haonan and Li, Mingkang and Wang, Zitong and Zhang, Yue and Luo, Xuexiong},
year={2023},
month=jul,
collection={SSDBM 2023}
}