Business location recommendation using check-in data

This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2017.

Opis bibliograficzny
Główni autorzy:	Ahmed, Nasim Uddin, Mahmud, Shafayet, Islam, Md. Tawabul, Shoumik, Shadman, Habib, Muhaimin
Kolejni autorzy:	Uddin, Dr. Jia
Format:	Praca dyplomowa
Język:	English
Wydane:	BRAC University 2018
Hasła przedmiotowe:	Check-in data Location recommendation Business location LBSN
Dostęp online:	http://hdl.handle.net/10361/8863

id	10361-8863
record_format	dspace
spelling	10361-88632022-01-26T10:23:14Z Business location recommendation using check-in data Ahmed, Nasim Uddin Mahmud, Shafayet Islam, Md. Tawabul Shoumik, Shadman Habib, Muhaimin Uddin, Dr. Jia Department of Computer Science and Engineering, BRAC University Check-in data Location recommendation Business location LBSN This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2017. Cataloged from PDF version of thesis report. Includes bibliographical references (page 22-23). In this era of Social Networks, large amount of data is generated from the users of social media and mobile applications on day to day basis. This data can be useful for the companies as they provide insight into the location oriented decisions of the businesses and on user behavior patterns in their regular activities. In this thesis work we are interested in the LBSN (Location Based Social network) data which is generated when the Users of social network Interact in the Online Social Networking Platforms and mobile applications by sharing their location data through “check ins” in the various Business locations. This spatial aspect of the LSBN data almost represent an online model of the physical world which can be analyzed to find key insights regarding the business locations. We have used the Geographical and Social distances to partition the city into neighborhoods as place for a new business opportunity. In technique we have used the collaborative neighborhood filtering based on similarity of neighborhoods by establishing correlation between business venues and check in patterns. We have used the New York foursquare data for our experimentation, this experimentation shows promising results for prediction of future business location. Nasim Uddin Ahmed Shafayet Mahmud Md. Tawabul Islam Shadman Shoumik Muhaimin Habib B. Computer Science and Engineering 2018-01-02T06:40:13Z 2018-01-02T06:40:13Z 2017 2017-08 Thesis ID 13101285 ID 14201009 ID 12301043 ID 13101276 ID 16101322 http://hdl.handle.net/10361/8863 en BRAC University thesis are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 23 pages application/pdf BRAC University
institution	Brac University
collection	Institutional Repository
language	English
topic	Check-in data Location recommendation Business location LBSN
spellingShingle	Check-in data Location recommendation Business location LBSN Ahmed, Nasim Uddin Mahmud, Shafayet Islam, Md. Tawabul Shoumik, Shadman Habib, Muhaimin Business location recommendation using check-in data
description	This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2017.
author2	Uddin, Dr. Jia
author_facet	Uddin, Dr. Jia Ahmed, Nasim Uddin Mahmud, Shafayet Islam, Md. Tawabul Shoumik, Shadman Habib, Muhaimin
format	Thesis
author	Ahmed, Nasim Uddin Mahmud, Shafayet Islam, Md. Tawabul Shoumik, Shadman Habib, Muhaimin
author_sort	Ahmed, Nasim Uddin
title	Business location recommendation using check-in data
title_short	Business location recommendation using check-in data
title_full	Business location recommendation using check-in data
title_fullStr	Business location recommendation using check-in data
title_full_unstemmed	Business location recommendation using check-in data
title_sort	business location recommendation using check-in data
publisher	BRAC University
publishDate	2018
url	http://hdl.handle.net/10361/8863
work_keys_str_mv	AT ahmednasimuddin businesslocationrecommendationusingcheckindata AT mahmudshafayet businesslocationrecommendationusingcheckindata AT islammdtawabul businesslocationrecommendationusingcheckindata AT shoumikshadman businesslocationrecommendationusingcheckindata AT habibmuhaimin businesslocationrecommendationusingcheckindata
_version_	1814309689246089216

Business location recommendation using check-in data

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