GhostAnderson/NISER

A reimplementation of Paper NISER: Normalized Item and Session Representations to Handle Popularity Bias.

NISER

Paper data and code

This is the code for the Paper: NISER: Normalized Item and Session Representations to Handle Popularity Bias. We have implemented our methods in Pytorch.

Here are two datasets we used in our paper. After downloaded the datasets, you can put them in the folder datasets/:

• YOOCHOOSE: http://2015.recsyschallenge.com/challenge.html or https://www.kaggle.com/chadgostopp/recsys-challenge-2015

• DIGINETICA: http://cikm2016.cs.iupui.edu/cikm-cup or https://competitions.codalab.org/competitions/11161

There is a small dataset sample included in the folder datasets/, which can be used to test the correctness of the code.

Requirements

• Python 3
• PyTorch 1.8.1

Reimplementation Performance

Hit@20: 53.34

MRR@20: 18.99