This is officail code for the Web Conference 2021 paper: Session-aware Linear Item-Item Models for Session-based Recommendation.
We implemented our model based on the session-recommedndation framework session-rec, and you can find the other session-based models and detailed usage on there.
Thank you for sharing the code.
README.md and the comments in source code will be updated, again.
The slides can be found here.
Datasets can be downloaded from:
https://www.dropbox.com/sh/n281js5mgsvao6s/AADQbYxSFVPCun5DfwtsSxeda?dl=0
- Unzip any dataset file to the data folder, i.e., rsc15-clicks.dat will then be in the folder data/rsc15/raw
- Run a configuration with the following command:
For example:
python run_preprocesing.py conf/preprocess/window/rsc15.yml
- Change the expeimental settings and the model hyperparameters using a configuration file
*.yml. - When a configuration file in conf/in has been executed, it will be moved to the folder conf/out.
- Run
run_config.pywith configuaration folder arguments to train and test models.
For example:python run_confg.py conf/in conf/out
- The yml files for slist used in paper can be found in
conf/save_slist
- Python 3
- NumPy
- Pyyaml
- SciPy
- Sklearn
- Pandas
- Psutil