Sequential Scenario-Specific Meta Learner for Online Recommendation
Zhengxiao Du, Xiaowei Wang, Hongxia Yang, Jingren Zhou, Jie Tang
Accepted to KDD 2019 Applied Data Science Track!
Under construction. Expect a stable release of cleaner code in June
Clone this repo.
git clone https://github.com/THUDM/ScenarioMeta
cd ScenarioMetaPlease install dependencies by
pip install -r requirements.txtThree public datasets are used for experiments. The Taobao Cloud Theme Click Dataset is released by us.
You can download the preprocessed datasets from the link in OneDrive or by running python scripts/download_preprocessed_data.py.
If you're in regions where OneDrive is not available (e.g. Mainland China), try to download from Tsinghua Cloud by running python scripts/download_preprocessed_data.py --tsinghua.
For training, simply run python src/main.py with necessary parameters.
Different configurations for datasets in the paper are stored under the configs/ directory. Launch a experiment with --config to specify the configuration file, --root_directory to specify the path to the preprocessed data, --comment to specify the experiment name which will be used in logging and --gpu to speficy the gpu id to use.
Please cite our paper if you use the code or datasets in your own work:
@article{du2019scenariometa,
title={Sequential Scenario-Specific Meta Learner for Online Recommendation},
author={Du, Zhengxiao and Wang, Xiaowei and Yang, Hongxia and Zhou, Jingren and Tang, Jie},
journal={arXiv preprint arXiv:1906.00391},
year={2019}
}