Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/156672
Title: Machine learning for new friends recommendation in NTU
Authors: Kang, Danson Kang Yit
Keywords: Engineering::Computer science and engineering
Issue Date: 2022
Publisher: Nanyang Technological University
Source: Kang, D. K. Y. (2022). Machine learning for new friends recommendation in NTU. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/156672
Abstract: NiceToMeetU (NTmU) was developed as a friend recommendation system to help undergraduate students in Nanyang Technological University (NTU) to make new friends on campus. While the project is a continuous effort, my work involves mainly creating a software application for users. Previous work aimed to improve the matching algorithm using machine learning, which included: - Construction of user-profiles through questionnaires, which helped to collect textual data from users. - Deep learning approaches such as the Bidirectional Encoder Representations from Transformers (BERT). - Web application designed to collect more featuring data from our users including movies and music. My FYP focuses on delivering a user-friendly mobile application that encourages user usage of the NTmU platform. While there was initially a previous mobile application built, it still lacked certain functionality like the forum and chat. As such, the opportunity to leverage these functionalities as tools to collect textual data, as well as a more compelling reason to increase their screentime on NTmU, was missed out on.
URI: https://hdl.handle.net/10356/156672
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)

Files in This Item:
File Description SizeFormat 
Amended FYP report (Danson Kang Yit Siang).pdf
  Restricted Access
1.53 MBAdobe PDFView/Open

Page view(s)

13
Updated on May 18, 2022

Download(s)

3
Updated on May 18, 2022

Google ScholarTM

Check

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.