/BundleMage

Primary LanguagePython

BundleMage

This project is a PyTorch implementation of BundleMage (PLOS ONE 2023).

Prerequisties

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.

Datasets

We use 3 datasets in our work: Youshu, Netease, and Steam. We include the preprocessed datasets in the repository: data/{data_name}.

Running the code

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.

Citation

@article{10.1371/journal.pone.0280630,
    author = {Hyunsik Jeon and 
              Jun{-}Gi Jang and 
              Taehun Kim and
              U Kang},
    journal = {PLOS ONE},
    publisher = {Public Library of Science},
    title = {Accurate Bundle Matching and Generation via Multitask Learning with Partially Shared Parameters},
    year = {2023},
    month = {01}
}