ACCM

This is our implementation for the paper:

Shaoyun Shi, Min Zhang, Yiqun Liu, and Shaoping Ma. 2018. Attention-based Adaptive Model to Unify Warm and Cold Starts Recommendation. In CIKM'18.

Please cite our paper if you use our codes. Thanks!

Author: Shaoyun Shi (shisy13 AT gmail.com)

@inproceedings{shi2018attention,
  title={Attention-based Adaptive Model to Unify Warm and Cold Starts Recommendation},
  author={Shi, Shaoyun and Zhang, Min and Liu, Yiqun and Ma, Shaoping},
  booktitle={Proceedings of the 27th ACM International Conference on Information and Knowledge Management},
  pages={127--136},
  year={2018},
  organization={ACM}
}

Environments

Python 3.5.2

Packages: See in requirements.txt

tensorflow_gpu==1.4.0
pandas==0.23.1
numpy==1.14.5
tqdm==4.23.4

Datasets

• ml-100k: The origin dataset can be found here. The processed ml-100k dataset is in ./dataset. The codes for processing the data are in ./src/ml-100k.py.

Example to run the codes

> cd ACCM
> mkdir model
> cd src

# ACCM with Cold-Sampling
> python CSACCM.py --warm_ratio 0.9

# ACCM without Cold-Sampling
> python CSACCM.py --warm_ratio 1.0

Note that other codes ending with *Model.py are inherited by CSACCM.py