weichen3690/logcl

The code of LogCL

LogCL

The code of LogCL

Process data

First, unpack the data files

For the three ICEWS datasets 'ICEWS18', 'ICEWS14', 'ICEWS05-15', 'GDELT', go into the dataset folder in the ./data directory and run the following command to construct the static graph and the query historical subgraph.

cd ./data/
python get_his_subg.py
cd ./<dataset>
python ent2word.py
cd .. 
python get_his_subg.py

Train models

Then the following commands can be used to train the proposed models. By default, dev set evaluation results will be printed when training terminates.

1. Train models

python src/main.py -d ICEWS14 --train-history-len 7 --test-history-len 7 --dilate-len 1 --lr 0.001 --n-layers 2 --evaluate-every 1 --gpu=0 --n-hidden 200 --self-loop --decoder convtranse --encoder uvrgcn --layer-norm --weight 0.5  --entity-prediction --angle 10 --discount 1 --pre-weight 0.9  --pre-type all --add-static-graph  --temperature 0.03

Cite

Please cite our paper if you find this code useful for your research.

@article{chen2023local,
  title={Local-Global History-aware Contrastive Learning for Temporal Knowledge Graph Reasoning},
  author={Chen, Wei and Wan, Huaiyu and Wu, Yuting and Zhao, Shuyuan and Cheng, Jiayaqi and Li, Yuxin and Lin, Youfang},
  journal={arXiv preprint arXiv:2312.01601},
  year={2023}
}