A recommender system for university modules based on graph database technologies

Abstract

Recommender systems has become ubiquitous in multiple domains, most notably in e-commerce and other Internet-based businesses where users can have access to multiple different choices. Graph databases which started as a way to model and store data as graphs has increasingly become the tool of choice to model and analyze highly connected data to find hidden relationships among data and draw insights from it. Recommender systems have been implemented using graph databases but there have not been any implementations specifically targeting the recommendation of university modules for undergraduate students. Thus, this project aims to implement a personalized recommender system for university modules using graph database technologies. The project will focus on recommending modules at the Nanyang Technological University (NTU) to NTU's undergraduate students.