A recommender system for university modules based on graph database technologies

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...

Full description

Saved in:
Bibliographic Details
Main Author: Koh, Jun Jie
Other Authors: Long Cheng
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2023
Subjects:
Online Access:https://hdl.handle.net/10356/172311
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
Description
Summary: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.