Feature Decomposition for Reducing Negative Transfer: a Novel Multi-task Learning Model for Recommender System
Model Architecture
![hustlin_erd](https://github.com/mrchor/FDN/raw/master/model_architecture.png)
Bibtex:
@article{zhou2023feature,
title={Feature Decomposition for Reducing Negative Transfer: A Novel Multi-task Learning Method for Recommender System (Student Abstract)},
author={Zhou, Jie and Yu, Qian and Luo, Chuan and Zhang, Jing},
year={2023},
}
Project structure
├── code
├── aliccp
├── FDN.py
├── MMoE.py
├── PLE.py
├── run.sh
├── synthetic_dataset
├── FDN.py
├── MMoE.py
├── PLE.py
├── run.sh
├── data
├── aliccp
├── train_data
├── train_data.csv
├── test_data
├── test_data.csv
├── vocab
├── ID feature index files
├── reader.py
├── synthetic_dataset
├── train_data
├── test_data
├── synthesis_dataset_generation.py
├── README.md
Quick start
cd code/aliccp
sh run.sh
Synthetic DataSet
cd code/synthetic_dataset
sh run.sh
Acknowledgement
- The work is also supported by the National Natural Science Foundation of China (No. 62202025 and 62002012).