python setup.py install
- Python 3.7
- TensorFlow (2.0)
- pandas
To reproduce the experiments mentioned in the paper you can run the following commands:
Douban
python train.py -d douban --accum stack -do 0.7 -nleft -nb 2 -e 200 --features --feat_hidden 64 --testing
Flixster
python train.py -d flixster --accum stack -do 0.7 -nleft -nb 2 -e 200 --features --feat_hidden 64 --testing
Yahoo Music
python train.py -d yahoo_music --accum stack -do 0.7 -nleft -nb 2 -e 200 --features --feat_hidden 64 --testing
##Dataset Description
Because uploading to github has a file size limit, all four datasets were deleted. Readers can use the code to download the relevant datasets by themselves.