shashankg7 / sigir_2022_BISER

Main contributors for this code

Jae-woong Lee and Seongmin Park (https://github.com/psm1206)

Preliminaries

Set up your user Python environment as follows:

python==3.7.7 tqdm joblib bottleneck numpy==1.16.2 pandas==0.24.2 scikit-learn==0.20.3 tensorflow==1.15.0 (cpu) mlflow==1.4.0 pyyaml==5.1

How to run

1. Set a model's hyperparameters you want in main.py. The adjustable hyperparameters are as follows.

   • model name {mf, relmf, uae, iae, proposed}
   • dataset {coat, yahoo}
   • learning rate
   • regularization term
   • hidden dimension
   • batch size
   • etc.
   • In case of our proposed method, the best hyperparmeters are fixed in the code.

2. Run main.py with the hyperparameters you set.

   • e.g.,
   • MF: main.py --model_name mf --dataset coat --lr 0.005 --reg 1e-9 --hidden 128 --batch_size 1024
   • Proposed: main.py --model_name proposed --dataset coat

3. You can see the results in the './log' folder.

Example to run in Coat dataset

MF

python main.py -m mf --dataset coat -lr 0.005 -reg 1e-9 -hidden 128 --batch_size 1024 -ran 10

RelMF

python main.py -m relmf --dataset coat -lr 0.005 -reg 1e-5 -hidden 128 --batch_size 1024 -ran 10

UAE

python main.py -m uae --dataset coat -lr 0.1 -reg 1e-6 -hidden 50 --batch_size 1 -ran 10

IAE

python main.py -m iae --dataset coat -lr 0.2 -reg 1e-7 -hidden 50 --batch_size 1 -ran 10

CJMF

python main.py -m cjmf --dataset coat -lr 0.005 -reg 1e-9 -hidden 128 --batch_size 1024 -ran 10

MACR

python main.py -m macr --dataset coat -lr 0.01 -reg 1e-5 -hidden 64 --batch_size 2048 -ran 10

BISER

python main.py -m proposed --dataset coat -ran 10

Example to run in Yahoo! R3 dataset

MF

python main.py -m mf --dataset yahoo -lr 0.001 -reg 1e-7 -hidden 64 --batch_size 1024 -ran 5

RelMF

python main.py -m relmf --dataset yahoo -lr 0.001 -reg 1e-7 -hidden 64 --batch_size 1024 -ran 5

UAE

python main.py -m uae --dataset yahoo -lr 0.01 -reg 0.0 -hidden 200 --batch_size 1 -ran 5

IAE

python main.py -m iae --dataset yahoo -lr 0.05 -reg 0.0 -hidden 200 --batch_size 1 -ran 5

CJMF

python main.py -m cjmf --dataset yahoo -lr 0.001 -reg 1e-6 -hidden 64 --batch_size 1024 -ran 5

MACR

python main.py -m macr --dataset yahoo -lr 0.001 -reg 1e-7 -hidden 64 --batch_size 8192 -ran 5

BISER

python main.py -m proposed --dataset yahoo -ran 5