Skip to content

Code for CIKM 2021 paper: Differentially Private Federated Knowledge Graphs Embedding (https://arxiv.org/abs/2105.07615)

Notifications You must be signed in to change notification settings

Nidhogg-lyz/FKGE

 
 

Repository files navigation

To do:

Data release: The datasets we used for experiments have been uploaded.

You can run the baseline experiments through the following code: 'python Config.py baseline 300 100 1.0 -1', where you can replace baseline with strategy_1 or strategy_2 to conduct the experiments with respect to FKGE.

And the other parameters denotes epoches, dimension, gan_ratio and pred_id respectively.

@inproceedings{Peng-2021-DPFKGE,
  title={Differentially Private Federated Knowledge Graphs Embedding},
  author={Hao Peng and
          Haoran Li and
          Yangqiu Song and
          Vincent W. Zheng and
          Jianxin Li},
  booktitle={CIKM 2021},
  year={2021},
  url={https://arxiv.org/abs/2105.07615}
}

About

Code for CIKM 2021 paper: Differentially Private Federated Knowledge Graphs Embedding (https://arxiv.org/abs/2105.07615)

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 76.3%
  • C 12.6%
  • C++ 9.6%
  • Shell 1.5%