Skip to content

Latest commit

 

History

History
32 lines (28 loc) · 1.29 KB

README.md

File metadata and controls

32 lines (28 loc) · 1.29 KB

L2RP

License

Learning to Rank Items of Minimal Reviews Using Weak Supervision

  • L2RP is a learning to rank technique that can be used in ranking products based on customer reviews. The main idea is to learn a ranking function from products having many reviews to transfer this knolwedge to product categories having less reviews in a weakly supervised setting.
    • More deatils will can be found in the original paper link.

1. Prerequisities

  • Python 3.7
  • Numpy==1.9.1
  • scipy==0.14
  • Tensorflow==1.13.0
  • Keras==1.0.6
  • Scikit-learn==1.18.5
  • Matplotlib==3.2.2
  • Java

2. Getting Started

  • Will be provided soon...

3. License

  • DTOPS is only distributed under Apache-2.0 License Copyright (c) 2020.
  • Contact: Yassien Shaalan

4. Citation

If you use this work, please cite:

{
title={Learning to Rank Items of Minimal Reviews Using Weak Supervision},
author={Shaalan,Yassien, Zhang, J., Chan, J.},
booktitle={PAKDD },
pages={631-643},
year={2018}
}