A business zone recommender system based on Facebook and urban planning data

We present ZoneRec—a zone recommendation system for physical businesses in an urban city,which uses both public business data from Facebook and urban planning data. The systemconsists of machine learning algorithms that take in a business’ metadata and outputs a list ofrecommended zones to establish...

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Main Authors:	LIN, Jovian, OENTARYO, Richard Jayadi, LIM, Ee Peng, VU, Casey, VU, Adrian Wei Liang, and PRASETYO, Philips Kokoh
Format:	text
Language:	English
Published:	Institutional Knowledge at Singapore Management University 2016
Subjects:	Facebook Social media Business Location recommendation Databases and Information Systems
Online Access:	https://ink.library.smu.edu.sg/sis_research/3460 https://ink.library.smu.edu.sg/context/sis_research/article/4461/viewcontent/154___A_Business_Zone_Recommender_System_Based_on_Facebook_and_Urban_Planning_Data.pdf
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Institution:	Singapore Management University
Language:	English

id	sg-smu-ink.sis_research-4461
record_format	dspace
spelling	sg-smu-ink.sis_research-44612018-06-22T01:36:36Z A business zone recommender system based on Facebook and urban planning data LIN, Jovian OENTARYO, Richard Jayadi LIM, Ee Peng VU, Casey VU, Adrian Wei Liang and PRASETYO, Philips Kokoh We present ZoneRec—a zone recommendation system for physical businesses in an urban city,which uses both public business data from Facebook and urban planning data. The systemconsists of machine learning algorithms that take in a business’ metadata and outputs a list ofrecommended zones to establish the business in. We evaluate our system using data of foodbusinesses in Singapore and assess the contribution of different feature groups to therecommendation quality. 2016-03-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/3460 info:doi/10.1007/978-3-319-30671-1_47 https://ink.library.smu.edu.sg/context/sis_research/article/4461/viewcontent/154___A_Business_Zone_Recommender_System_Based_on_Facebook_and_Urban_Planning_Data.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Facebook Social media Business Location recommendation Databases and Information Systems
institution	Singapore Management University
building	SMU Libraries
continent	Asia
country	Singapore Singapore
content_provider	SMU Libraries
collection	InK@SMU
language	English
topic	Facebook Social media Business Location recommendation Databases and Information Systems
spellingShingle	Facebook Social media Business Location recommendation Databases and Information Systems LIN, Jovian OENTARYO, Richard Jayadi LIM, Ee Peng VU, Casey VU, Adrian Wei Liang and PRASETYO, Philips Kokoh A business zone recommender system based on Facebook and urban planning data
description	We present ZoneRec—a zone recommendation system for physical businesses in an urban city,which uses both public business data from Facebook and urban planning data. The systemconsists of machine learning algorithms that take in a business’ metadata and outputs a list ofrecommended zones to establish the business in. We evaluate our system using data of foodbusinesses in Singapore and assess the contribution of different feature groups to therecommendation quality.
format	text
author	LIN, Jovian OENTARYO, Richard Jayadi LIM, Ee Peng VU, Casey VU, Adrian Wei Liang and PRASETYO, Philips Kokoh
author_facet	LIN, Jovian OENTARYO, Richard Jayadi LIM, Ee Peng VU, Casey VU, Adrian Wei Liang and PRASETYO, Philips Kokoh
author_sort	LIN, Jovian
title	A business zone recommender system based on Facebook and urban planning data
title_short	A business zone recommender system based on Facebook and urban planning data
title_full	A business zone recommender system based on Facebook and urban planning data
title_fullStr	A business zone recommender system based on Facebook and urban planning data
title_full_unstemmed	A business zone recommender system based on Facebook and urban planning data
title_sort	business zone recommender system based on facebook and urban planning data
publisher	Institutional Knowledge at Singapore Management University
publishDate	2016
url	https://ink.library.smu.edu.sg/sis_research/3460 https://ink.library.smu.edu.sg/context/sis_research/article/4461/viewcontent/154___A_Business_Zone_Recommender_System_Based_on_Facebook_and_Urban_Planning_Data.pdf
_version_	1770573223576993792

A business zone recommender system based on Facebook and urban planning data

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