Data recommendation engine for a web–based research community social network platform

Social media platforms have gained a large amount of attention as there are many social media applications available for people to use. Some of the social media applications available includes WhatsApp, YouTube, Facebook, Instagram, Twitter, LinkedIn and many others. Based on the statistics of socia...

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Main Author: Tay, Wee Meng
Other Authors: Cong Gao
Format: Final Year Project
Language:English
Published: 2019
Subjects:
Online Access:http://hdl.handle.net/10356/76974
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-769742023-03-03T20:38:44Z Data recommendation engine for a web–based research community social network platform Tay, Wee Meng Cong Gao School of Computer Science and Engineering DRNTU::Engineering::Computer science and engineering Social media platforms have gained a large amount of attention as there are many social media applications available for people to use. Some of the social media applications available includes WhatsApp, YouTube, Facebook, Instagram, Twitter, LinkedIn and many others. Based on the statistics of social network penetration in Singapore as of the third quarter of 2017, the top five social media applications are WhatsApp (73%), YouTube (71%), Facebook (70%), Instagram (44%) and Facebook Messenger (42%) (Statista, 2018). The objective of this Final Year Project (FYP) was to develop a mobile–based intelligent social platform application called AcKuu for different users to share and interact with regards to research and academic activities. The mobile–based intelligent social platform application will include a data–driven recommendation engine. This report consists of the detailed Methodology, Prototype Design and Implementation and Results of the mobile–based intelligent social platform application and the data–driven recommendation engine. The mobile–based intelligent social platform application was developed using Android Studio and the data–driven recommendation engine will make use of collaborative filtering algorithm. Overall, the basic functionalities for the mobile–based intelligent social platform application was developed. For the data–driven recommendation engine, dataset was collected and processed for training. Bachelor of Engineering (Computer Science) 2019-04-28T13:30:11Z 2019-04-28T13:30:11Z 2019 Final Year Project (FYP) http://hdl.handle.net/10356/76974 en Nanyang Technological University 47 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Computer science and engineering
spellingShingle DRNTU::Engineering::Computer science and engineering
Tay, Wee Meng
Data recommendation engine for a web–based research community social network platform
description Social media platforms have gained a large amount of attention as there are many social media applications available for people to use. Some of the social media applications available includes WhatsApp, YouTube, Facebook, Instagram, Twitter, LinkedIn and many others. Based on the statistics of social network penetration in Singapore as of the third quarter of 2017, the top five social media applications are WhatsApp (73%), YouTube (71%), Facebook (70%), Instagram (44%) and Facebook Messenger (42%) (Statista, 2018). The objective of this Final Year Project (FYP) was to develop a mobile–based intelligent social platform application called AcKuu for different users to share and interact with regards to research and academic activities. The mobile–based intelligent social platform application will include a data–driven recommendation engine. This report consists of the detailed Methodology, Prototype Design and Implementation and Results of the mobile–based intelligent social platform application and the data–driven recommendation engine. The mobile–based intelligent social platform application was developed using Android Studio and the data–driven recommendation engine will make use of collaborative filtering algorithm. Overall, the basic functionalities for the mobile–based intelligent social platform application was developed. For the data–driven recommendation engine, dataset was collected and processed for training.
author2 Cong Gao
author_facet Cong Gao
Tay, Wee Meng
format Final Year Project
author Tay, Wee Meng
author_sort Tay, Wee Meng
title Data recommendation engine for a web–based research community social network platform
title_short Data recommendation engine for a web–based research community social network platform
title_full Data recommendation engine for a web–based research community social network platform
title_fullStr Data recommendation engine for a web–based research community social network platform
title_full_unstemmed Data recommendation engine for a web–based research community social network platform
title_sort data recommendation engine for a web–based research community social network platform
publishDate 2019
url http://hdl.handle.net/10356/76974
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