This is the source code of our ICDE 2024 paper "Firzen: Firing Strict Cold-start Items with Heterogeneous and Homogeneous Graphs for Recommendation".
conda create -n Firzen python=3.8 anaconda
conda activate Firzen
# Please install PyTorch according to your CUDA version.
conda install pytorch==1.13.0 pytorch-cuda=11.7 -c pytorch -c nvidia
pip install -r requirements.txt
Our model is evaluated on Amazon Beauty, Amazon Cell Phones and Accessories, Amazon Clothing Shoes and Jewelry datasets.
You can download our processed datasets and unzip them to your data folder:
- Baidu Yun Pan: 1207
# Amazon_Beauty
python run_itemcoldstart.py --dataset=Amazon_Beauty --model=Firzen --config_files=configs/knowledge_rec_beauty.yaml
# Amazon_Cell_Phones_and_Accessories
python run_itemcoldstart.py --dataset=Amazon_Cell_Phones_and_Accessories --model=Firzen --config_files=configs/knowledge_rec_cell_phones.yaml
# Amazon_Clothing_Shoes_and_Jewelry
python run_itemcoldstart.py --dataset=Amazon_Clothing_Shoes_and_Jewelry --model=Firzen --config_files=configs/knowledge_rec_clothing.yaml
Our code references the following projects. Many thanks to the authors.