valeriawong/trademark_appeals

TF-IDF & XGBoost for Trademark Appeals forecasting with 68% accuracy

Trademark_Appeals

TF-IDF & XGBoost for Trademark Appeals

This is a python code for the paper "Intelligent Forecasting of Trademark Registration Appeal with TF-IDF and XGBoost"

If you want to run the code, you need to install the packages by running:

pip install -r requirements.txt

to run the code

python main.py

You can find the model in the folder "output" which is 68% accuracy on the test set.

If you want to get access to dataset,pls contact our corresponding author's email at [email protected] or [email protected]

you can fork and running the raw code directly on kaggle

If you find this work useful for your research and applications, please cite using this BibTeX:

@inproceedings{wang2024trademarkappeals,
    title={Intelligent Forecasting of Trademark Registration Appeal with TF-IDF and XGBoost},
    author={Qun Wang, ShuHao Qian, JiaHuan Yan, Hao Wang, XiaoTao Guo},
    booktitle={IC2023},
    year={2024}
}