Restaurant recommendation app using real-time / Mohd Hazlee Seruji

Finding a place to eat can be a problem for certain people. Sometimes when going out with family or a group of friends, it is hard for us to decide a place to eat. Usually it is because we are not aware of the most of the restaurants near us. In the end, we usually end up eating at the same place ov...

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Main Author: Seruji, Mohd Hazlee
Format: Thesis
Language:English
Published: 2017
Online Access:https://ir.uitm.edu.my/id/eprint/64336/1/64336.PDF
https://ir.uitm.edu.my/id/eprint/64336/
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spelling my.uitm.ir.643362023-11-05T04:58:03Z https://ir.uitm.edu.my/id/eprint/64336/ Restaurant recommendation app using real-time / Mohd Hazlee Seruji Seruji, Mohd Hazlee Finding a place to eat can be a problem for certain people. Sometimes when going out with family or a group of friends, it is hard for us to decide a place to eat. Usually it is because we are not aware of the most of the restaurants near us. In the end, we usually end up eating at the same place over and over again. Therefore, this problem has sparked an idea for the development of Foodster, the restaurant-recommendation app using real-time location. This application allows the user to find nearby restaurants based on his current location. This app doesn't require any login thus allowing the ease of access to anyone who uses it. By using Foursquare Venue Database as the information provider for the restaurants, this application have vast amount of restaurant it has access to. Each data retrieved from Foursquare is then filtered based on the venue's category and ratings. This allows the user to choose their preferred restaurant based on what they feel like eating. On the restaurant page, user can tap on the venue of the restaurant on the map that allows the user to find the route to their preferred restaurant. With this application, people will have easier access to choose which restaurant they would like to have their next meal. Instead of just showing the locations of restaurant, this app also shows places for shopping and outdoor activities which can be choosen on the filter page. 2017 Thesis NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/64336/1/64336.PDF Restaurant recommendation app using real-time / Mohd Hazlee Seruji. (2017) Degree thesis, thesis, Universiti Teknologi MARA (UiTM).
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
language English
description Finding a place to eat can be a problem for certain people. Sometimes when going out with family or a group of friends, it is hard for us to decide a place to eat. Usually it is because we are not aware of the most of the restaurants near us. In the end, we usually end up eating at the same place over and over again. Therefore, this problem has sparked an idea for the development of Foodster, the restaurant-recommendation app using real-time location. This application allows the user to find nearby restaurants based on his current location. This app doesn't require any login thus allowing the ease of access to anyone who uses it. By using Foursquare Venue Database as the information provider for the restaurants, this application have vast amount of restaurant it has access to. Each data retrieved from Foursquare is then filtered based on the venue's category and ratings. This allows the user to choose their preferred restaurant based on what they feel like eating. On the restaurant page, user can tap on the venue of the restaurant on the map that allows the user to find the route to their preferred restaurant. With this application, people will have easier access to choose which restaurant they would like to have their next meal. Instead of just showing the locations of restaurant, this app also shows places for shopping and outdoor activities which can be choosen on the filter page.
format Thesis
author Seruji, Mohd Hazlee
spellingShingle Seruji, Mohd Hazlee
Restaurant recommendation app using real-time / Mohd Hazlee Seruji
author_facet Seruji, Mohd Hazlee
author_sort Seruji, Mohd Hazlee
title Restaurant recommendation app using real-time / Mohd Hazlee Seruji
title_short Restaurant recommendation app using real-time / Mohd Hazlee Seruji
title_full Restaurant recommendation app using real-time / Mohd Hazlee Seruji
title_fullStr Restaurant recommendation app using real-time / Mohd Hazlee Seruji
title_full_unstemmed Restaurant recommendation app using real-time / Mohd Hazlee Seruji
title_sort restaurant recommendation app using real-time / mohd hazlee seruji
publishDate 2017
url https://ir.uitm.edu.my/id/eprint/64336/1/64336.PDF
https://ir.uitm.edu.my/id/eprint/64336/
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score 13.214268