Multinomial likelihood with Bi-Weighting (Mult-BiW)

This is our Tensorflow implementation for the paper:

Tianyu Zhu, Jiandong Ding, Yansong Shi, Guoqing Chen, Jian-Yun Nie. "Mitigating Popularity Bias in Recommendation with Global Listwise Learning and Progressive Bi-Weighting."

Introduction

Mult-BiW is a framework for popularity debiasing in item recommendation.

Citation

Environment Requirement

The code has been tested running under Python 3.8. The required packages are as follows:

• tensorflow == 2.8.0+
• numpy == 1.23.0+
• scipy == 1.8.0+
• pandas == 1.5.0+

Example to Run the Codes

python MF.py --dataset amazon --lr 1e-4 --l2_reg 1e-6 --alpha -1.0 --eta 1.0
python LightGCN.py --dataset amazon --lr 1e-3 --l2_reg 1e-6 --alpha -1.0 --eta 1.0 --num_layer 2