This project is a PyTorch implementation of BundleMage (submitted to PLOS ONE).
Our implementation is based on Python 3.6 and Pytorch 1.8.1. Please see the full list of packages required to our codes in requirements.txt.
We use 3 datasets in our work: Youshu, Netease, and Steam.
We include the preprocessed datasets in the repository: data/{data_name}.
You can run the code by python main.py with arguments --data and --task.
Set --data argument as one among 'youshu', 'netease', and 'steam'.
Set --task argument as 'mat' for bundle matching, or as 'gen' for bundle generation.
We provide demo.sh, which reproduces the experiments of our work for bundle matching and generation.