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}
}