L2RP

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}

}