Our paper can be accessed here.

The code requires Python 3.7+ and the HuggingFace Transformers library transformers==4.1.0. The detailed requirements can be found in requirements.txt. Note that specific versions of torch_scatter, torch_sparse, torch might be needed to work with different Cuda versions.

The data can be accessed through Dropbox.

Edit the training scripts run_amazon.sh and run_books.sh to specify path to data and the output. Then execute the scripts to run the experiments.

Please follow the given datasets to format your data. Then create a training script to run the experiments.

Please cite the following paper if you found our dataset or framework useful. Thanks!

@inproceedings{zhang2021ltrn,
  author = {Zhang, Xinyang and Zhang, Chenwei and Dong, Luna Xin and Shang, Jingbo and Han, Jiawei},
  title = {Minimally Supervised Structure Rich Text Categorization by Learning on Text-Rich Networks},
  year = {2021},
  booktitle = {Proceedings of The Web Conference 2021},
  location = {Ljubljana, Slovenia},
  series = {WWW '21}
}