Panda0406 / Zero-shot-knowledge-graph-relational-learning

Generative Adversarial Zero-Shot Relational Learning for Knowledge Graphs

Generative Adversarial Zero-Shot Relational Learning for Knowledge Graphs

PyTorch implementation of zero-shot knowledge graph learning model described in our AAAI 2020 paper Generative Adversarial Zero-Shot Relational Learning for Knowledge Graphs. In this work, we propose a solution for zero-shot knowledge graph relational learning via generative adversarial learning.

Steps to run the experiments

Requirements

• Python 3.6
• >= PyTorch 1.0.0
• tqdm

Datasets and word embeddings

• NELL-ZS: Please download(Baidu Yun with code be85 or Google Drive) and put it into this directory.
• Wiki-ZS: Please download(Baidu Yun with code 9zh5 or Google Drive) and put it into directory ./origin_data.

Training on NELL-ZS dataset

• python trainer.py --pretrain_feature_extractor

Reference

@article{qin2020generative,
  title={Generative Adversarial Zero-Shot Relational Learning for Knowledge Graphs},
  author={Qin, Pengda and Wang, Xin and Chen, Wenhu and Zhang, Chunyun and Xu, Weiran and Wang, William Yang},
  journal={arXiv preprint arXiv:2001.02332},
  year={2020}
}