- Linux
- Python 3
- NVIDIA GPU + CUDA cuDNN
Clone this repo.
git clone https://github.com/zfjsail/OAG-entity-alignment.git
cd OAG-entity-alignment
Please install dependencies by
pip install -r requirements.txt
The dataset can be downloaded from BaiduPan (with password 445n) or Aliyun. Unzip the file and put the data directory into project directory.
cd $project_path
export CUDA_VISIBLE_DEVICES='?' # specify which GPU(s) to be used
python processing.py # all pre-processing process
python train_rnn_match.py --n-try 5 --entity-type author # RNN-based matching model for author alignment
If you want to know about all supported baselines, see run.sh
for details.
For entity types, we support three types of entities (affliation, venue, and author) for entity alignment.
For matching models, we support RNN-based, CNN-based, and heterogeneous graph attention network (HGAT) based models.