SLIST

Update 02/18/2022: Please check this link for an improved version of SLIST

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.
Thanks for sharing the code. README.md and the comments in source code will be updated, again.

The slides can be found here or here.

Dataset

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

Basic Usage

• 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.py with configuaration folder arguments to train and test models.
  For example: python run_confg.py conf/in conf/out

Running SLIST

• The yml files for slist used in paper can be found in conf/save_slist

Requirements

• Python 3
• NumPy
• Pyyaml
• SciPy
• Sklearn
• Pandas
• Psutil

Citation

Please cite our papaer:

@inproceedings{DBLP:conf/www/ChoiKLSL21,
  author    = {Minjin Choi and
               Jinhong Kim and
               Joonseok Lee and
               Hyunjung Shim and
               Jongwuk Lee},
  editor    = {Jure Leskovec and
               Marko Grobelnik and
               Marc Najork and
               Jie Tang and
               Leila Zia},
  title     = {Session-aware Linear Item-Item Models for Session-based Recommendation},
  booktitle = {{WWW} '21: The Web Conference 2021, Virtual Event / Ljubljana, Slovenia,
               April 19-23, 2021},
  pages     = {2186--2197},
  publisher = {{ACM} / {IW3C2}},
  year      = {2021},
  url       = {https://doi.org/10.1145/3442381.3450005},
  doi       = {10.1145/3442381.3450005},
  timestamp = {Mon, 07 Jun 2021 14:20:06 +0200},
  biburl    = {https://dblp.org/rec/conf/www/ChoiKLSL21.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}