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News RSS with stock recommender

This project is about the development of window applications for News RSS with Stock Recommendations involves sentence matching techniques and provide the recommend stock. This project aims to empower new graduates and institutional investors financially while imparting knowledge and expertise on de...

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Bibliographic Details
Main Author: Chin, Zhi Yi
Format: Final Year Project / Dissertation / Thesis
Published: 2024
Subjects:
T Technology (General)
TD Environmental technology. Sanitary engineering
Online Access:http://eprints.utar.edu.my/7023/1/fyp_IB_2024_CZY.pdf
http://eprints.utar.edu.my/7023/
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id my-utar-eprints.7023
record_format eprints
spelling my-utar-eprints.70232025-02-27T07:26:25Z News RSS with stock recommender Chin, Zhi Yi T Technology (General) TD Environmental technology. Sanitary engineering This project is about the development of window applications for News RSS with Stock Recommendations involves sentence matching techniques and provide the recommend stock. This project aims to empower new graduates and institutional investors financially while imparting knowledge and expertise on developing window applications. The goal of this project is to overcome the analysis of news data to locate relevant news and provide listed companies in Bursa Malaysia. By providing real-time news updates, automatic suggestions, and educational materials, the initiative will improve the effectiveness of the recommendation process and serve as a perfect entry point for anyone wishing to start investing. The project uses a combination of text mining approaches to extract meaningful information from massive amounts of news data. Moreover, accessibility and usability are given top priority in the application's user-centric design, guaranteeing that both inexperienced and expert investors may easily utilize its features. The project seeks to develop a robust and user-friendly platform that can give rapid and precise stock recommendations to all users through exhaustive testing and upgraded enhancements. Lastly, outlines the goals of the project, its approach, and the anticipated effects on users. It highlights how the project can free up a significant amount of users' valuable time while also enabling people to make informed investment decisions while browsing and reading the news in a constantly changing financial environment. 2024-06 Final Year Project / Dissertation / Thesis NonPeerReviewed application/pdf http://eprints.utar.edu.my/7023/1/fyp_IB_2024_CZY.pdf Chin, Zhi Yi (2024) News RSS with stock recommender. Final Year Project, UTAR. http://eprints.utar.edu.my/7023/
institution Universiti Tunku Abdul Rahman
building UTAR Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tunku Abdul Rahman
content_source UTAR Institutional Repository
url_provider http://eprints.utar.edu.my
topic T Technology (General)
TD Environmental technology. Sanitary engineering
spellingShingle T Technology (General)
TD Environmental technology. Sanitary engineering
Chin, Zhi Yi
News RSS with stock recommender
description This project is about the development of window applications for News RSS with Stock Recommendations involves sentence matching techniques and provide the recommend stock. This project aims to empower new graduates and institutional investors financially while imparting knowledge and expertise on developing window applications. The goal of this project is to overcome the analysis of news data to locate relevant news and provide listed companies in Bursa Malaysia. By providing real-time news updates, automatic suggestions, and educational materials, the initiative will improve the effectiveness of the recommendation process and serve as a perfect entry point for anyone wishing to start investing. The project uses a combination of text mining approaches to extract meaningful information from massive amounts of news data. Moreover, accessibility and usability are given top priority in the application's user-centric design, guaranteeing that both inexperienced and expert investors may easily utilize its features. The project seeks to develop a robust and user-friendly platform that can give rapid and precise stock recommendations to all users through exhaustive testing and upgraded enhancements. Lastly, outlines the goals of the project, its approach, and the anticipated effects on users. It highlights how the project can free up a significant amount of users' valuable time while also enabling people to make informed investment decisions while browsing and reading the news in a constantly changing financial environment.
format Final Year Project / Dissertation / Thesis
author Chin, Zhi Yi
author_facet Chin, Zhi Yi
author_sort Chin, Zhi Yi
title News RSS with stock recommender
title_short News RSS with stock recommender
title_full News RSS with stock recommender
title_fullStr News RSS with stock recommender
title_full_unstemmed News RSS with stock recommender
title_sort news rss with stock recommender
publishDate 2024
url http://eprints.utar.edu.my/7023/1/fyp_IB_2024_CZY.pdf
http://eprints.utar.edu.my/7023/
_version_ 1825817830496403456
score 13.244413

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