PlaceProfile: Employing Visual and Cluster Analysis to Profile Regions based on Points of Interest
Autor(a) principal: | |
---|---|
Data de Publicação: | 2021 |
Outros Autores: | , |
Tipo de documento: | Artigo de conferência |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://hdl.handle.net/11449/247584 |
Resumo: | Understanding how commercial and social activities and points of interest are located in a city is essential to plan efficient cities in smart mobility. Over the years, the growth of data sources from distinct online social networks has enabled new perspectives to applications that provide mechanisms to aid in comprehension of how people displaces between different regions within a city. To support enterprises and governments better understand and compare distinct regions of a city, this work proposes a web application called PlaceProfile to perform visual profiling of city areas based on iconographic visualization and to label areas based on clustering algorithms. The visualization results are overlayered on Google Maps to enrich the map layout and aid analyst in understanding region profiling at a glance. Besides, PlaceProfile coordinates a radar chart with areas selected by the user to enable detailed inspection of the frequency of categories of points of interest (POIs). This linked views approach also supports clustering algorithms’ explainability by providing inspections of the attributes used to compute similarities. We employed the proposed approach in a case study in the São Paulo city, Brazil. |
id |
UNSP_f2ec14e05662ad837f465edcfd329835 |
---|---|
oai_identifier_str |
oai:repositorio.unesp.br:11449/247584 |
network_acronym_str |
UNSP |
network_name_str |
Repositório Institucional da UNESP |
repository_id_str |
2946 |
spelling |
PlaceProfile: Employing Visual and Cluster Analysis to Profile Regions based on Points of InterestArea ProfilingClusteringGoogle MapsPOIsSmart CitiesSmart MobilityVisualizationUnderstanding how commercial and social activities and points of interest are located in a city is essential to plan efficient cities in smart mobility. Over the years, the growth of data sources from distinct online social networks has enabled new perspectives to applications that provide mechanisms to aid in comprehension of how people displaces between different regions within a city. To support enterprises and governments better understand and compare distinct regions of a city, this work proposes a web application called PlaceProfile to perform visual profiling of city areas based on iconographic visualization and to label areas based on clustering algorithms. The visualization results are overlayered on Google Maps to enrich the map layout and aid analyst in understanding region profiling at a glance. Besides, PlaceProfile coordinates a radar chart with areas selected by the user to enable detailed inspection of the frequency of categories of points of interest (POIs). This linked views approach also supports clustering algorithms’ explainability by providing inspections of the attributes used to compute similarities. We employed the proposed approach in a case study in the São Paulo city, Brazil.São Paulo State University (UNESP), Presidente PrudenteSão Paulo State University (UNESP), Presidente PrudenteUniversidade Estadual Paulista (UNESP)Christófano, Rafael Mariano [UNESP]Júnior, Wilson Estécio Marcílio [UNESP]Eler, Danilo Medeiros [UNESP]2023-07-29T13:20:05Z2023-07-29T13:20:05Z2021-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject506-514International Conference on Enterprise Information Systems, ICEIS - Proceedings, v. 1, p. 506-514.2184-4992http://hdl.handle.net/11449/2475842-s2.0-85111119358Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengInternational Conference on Enterprise Information Systems, ICEIS - Proceedingsinfo:eu-repo/semantics/openAccess2024-06-18T18:18:36Zoai:repositorio.unesp.br:11449/247584Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T15:49:32.830549Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
PlaceProfile: Employing Visual and Cluster Analysis to Profile Regions based on Points of Interest |
title |
PlaceProfile: Employing Visual and Cluster Analysis to Profile Regions based on Points of Interest |
spellingShingle |
PlaceProfile: Employing Visual and Cluster Analysis to Profile Regions based on Points of Interest Christófano, Rafael Mariano [UNESP] Area Profiling Clustering Google Maps POIs Smart Cities Smart Mobility Visualization |
title_short |
PlaceProfile: Employing Visual and Cluster Analysis to Profile Regions based on Points of Interest |
title_full |
PlaceProfile: Employing Visual and Cluster Analysis to Profile Regions based on Points of Interest |
title_fullStr |
PlaceProfile: Employing Visual and Cluster Analysis to Profile Regions based on Points of Interest |
title_full_unstemmed |
PlaceProfile: Employing Visual and Cluster Analysis to Profile Regions based on Points of Interest |
title_sort |
PlaceProfile: Employing Visual and Cluster Analysis to Profile Regions based on Points of Interest |
author |
Christófano, Rafael Mariano [UNESP] |
author_facet |
Christófano, Rafael Mariano [UNESP] Júnior, Wilson Estécio Marcílio [UNESP] Eler, Danilo Medeiros [UNESP] |
author_role |
author |
author2 |
Júnior, Wilson Estécio Marcílio [UNESP] Eler, Danilo Medeiros [UNESP] |
author2_role |
author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (UNESP) |
dc.contributor.author.fl_str_mv |
Christófano, Rafael Mariano [UNESP] Júnior, Wilson Estécio Marcílio [UNESP] Eler, Danilo Medeiros [UNESP] |
dc.subject.por.fl_str_mv |
Area Profiling Clustering Google Maps POIs Smart Cities Smart Mobility Visualization |
topic |
Area Profiling Clustering Google Maps POIs Smart Cities Smart Mobility Visualization |
description |
Understanding how commercial and social activities and points of interest are located in a city is essential to plan efficient cities in smart mobility. Over the years, the growth of data sources from distinct online social networks has enabled new perspectives to applications that provide mechanisms to aid in comprehension of how people displaces between different regions within a city. To support enterprises and governments better understand and compare distinct regions of a city, this work proposes a web application called PlaceProfile to perform visual profiling of city areas based on iconographic visualization and to label areas based on clustering algorithms. The visualization results are overlayered on Google Maps to enrich the map layout and aid analyst in understanding region profiling at a glance. Besides, PlaceProfile coordinates a radar chart with areas selected by the user to enable detailed inspection of the frequency of categories of points of interest (POIs). This linked views approach also supports clustering algorithms’ explainability by providing inspections of the attributes used to compute similarities. We employed the proposed approach in a case study in the São Paulo city, Brazil. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-01-01 2023-07-29T13:20:05Z 2023-07-29T13:20:05Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/conferenceObject |
format |
conferenceObject |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
International Conference on Enterprise Information Systems, ICEIS - Proceedings, v. 1, p. 506-514. 2184-4992 http://hdl.handle.net/11449/247584 2-s2.0-85111119358 |
identifier_str_mv |
International Conference on Enterprise Information Systems, ICEIS - Proceedings, v. 1, p. 506-514. 2184-4992 2-s2.0-85111119358 |
url |
http://hdl.handle.net/11449/247584 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
International Conference on Enterprise Information Systems, ICEIS - Proceedings |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
506-514 |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808128568549441536 |