CFGAN: A Generic Collaborative Filtering Framework based on Generative Adversarial Networks

This repository provides a reference implementation of CFGAN as described in the following papers:

CFGAN: A Generic Collaborative Filtering Framework based on Generative Adversarial Networks Dong-Kyu Chae, Jin-Soo Kang, Sang-Wook Kim, and Jung-Tae Lee 27th ACM Int’l Conf. on Information and Knowledge Management (CIKM 2018)

Overview of CFGAN

Authors

• Dong-Kyu Chae ([email protected])
• Jin-Soo Kang ([email protected])
• Sang-Wook Kim ([email protected])
• Jung-Tae Lee ([email protected])

Requirements

The code has been tested running under Python 3.5. The required packages are as follows:

• tensorflow_gpu

Basic Usage

python python cfgan.py

Cite

We encourage you to cite our paper if you have used the code in your work. You can use the following BibTex citation:

@inproceedings{ChaeKKL18,
  author    = {Dong{-}Kyu Chae and Jin{-}Soo Kang and Sang{-}Wook Kim and Jung{-}Tae Lee},
  title     = {CFGAN: A Generic Collaborative Filtering Framework based on Generative
               Adversarial Networks},
  booktitle = {Proceedings of the 27th ACM International Conference on Information
               and Knowledge Management, (CIKM 2018)},
  pages     = {137--146},
  year      = {2018}
}

GitHub

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