by Gabrielle Taylor, Mousumi Akter, and Sicheng Li
This project was part of our COMP6970: Information Retrieval Course.
The main goal of this project was to build a transparent and explainable recommendation system framework. We implemented set-based explainable recommendation system framework based on the paper. Then, I (Mousumi) have also proposed a novel rank-based explainable technique for recommendation system. Through extensive experiments on popular Movielens 20M Dataset, I have found out that our proposed rank-based explainable recommendation system is comparable with the current state of the art set-based explainable recommendation system.
git clone https://github.com/Mousumi44/Recommendation-System-Project.git
cd Recommendation-System-Project
python ExplainableRecommender.py
Presentation of the project can be found in the following link: