Mobility Data under Analysis a Complex Network Perspective from Interactions Among Trajectories to Movements among Points Interest
Autor(a) principal: | |
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Data de Publicação: | 2012 |
Tipo de documento: | Dissertação |
Idioma: | por |
Título da fonte: | Biblioteca Digital de Teses e Dissertações da UFC |
Texto Completo: | http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=7837 |
Resumo: | The explosion of personal positioning devices like GPS-enabled smartphones has enabled the collection and storage of a huge amount of positioning data in the form of trajectories. Thereby, trajectory data have brought many research challenges in the process of recovery, storage and knowledge discovery in mobility as well as new applications to support our society in mobility terms. Other research area that has been receiving great attention nowadays is the area of complex network or science of networks. Complex network is the first approach to model complex system that are present in the real world, such as economic markets, the Internet, World Wide Web and disease spreading to name a few. It has been applied in different field, like Computer Science, Biology and Physics. Therefore, complex networks have demonstrated a great potential to investigate the behavior of complex systems through their entities and the relationships that exist among them. The present dissertation, therefore, aims at exploiting approaches to analyze mobility data using a perspective of complex networks. The first exploited approach stands for the trajectories as the main entities of the networks connecting each other through a similarity function. The second, in turn, focuses on points of interest that are visited by people, which perform some activities in these points. In addition, this dissertation also exploits the proposed methodologies in order to develop a software tool to support users in mobility analysis using complex network techniques. |
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Biblioteca Digital de Teses e Dissertações da UFC |
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info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisMobility Data under Analysis a Complex Network Perspective from Interactions Among Trajectories to Movements among Points Interest2012-02-10Josà AntÃnio Fernandes de Macedo00028098700http://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4737328P5VÃnia Maria Ponte Vidal17344948320http://lattes.cnpq.br/9431229866203038Marco AntÃnio Casanova29997810759http://lattes.cnpq.br/0400232298849115Chiara RensoNÃo tem89444337200http://lattes.cnpq.br/2100592282487417Igo Ramalho BrilhanteUniversidade Federal do CearÃPrograma de PÃs-GraduaÃÃo em CiÃncia da ComputaÃÃoUFCBRComplex Network Mobility TrajectoryCIENCIA DA COMPUTACAOThe explosion of personal positioning devices like GPS-enabled smartphones has enabled the collection and storage of a huge amount of positioning data in the form of trajectories. Thereby, trajectory data have brought many research challenges in the process of recovery, storage and knowledge discovery in mobility as well as new applications to support our society in mobility terms. Other research area that has been receiving great attention nowadays is the area of complex network or science of networks. Complex network is the first approach to model complex system that are present in the real world, such as economic markets, the Internet, World Wide Web and disease spreading to name a few. It has been applied in different field, like Computer Science, Biology and Physics. Therefore, complex networks have demonstrated a great potential to investigate the behavior of complex systems through their entities and the relationships that exist among them. The present dissertation, therefore, aims at exploiting approaches to analyze mobility data using a perspective of complex networks. The first exploited approach stands for the trajectories as the main entities of the networks connecting each other through a similarity function. The second, in turn, focuses on points of interest that are visited by people, which perform some activities in these points. In addition, this dissertation also exploits the proposed methodologies in order to develop a software tool to support users in mobility analysis using complex network techniques.http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=7837application/pdfinfo:eu-repo/semantics/openAccessporreponame:Biblioteca Digital de Teses e Dissertações da UFCinstname:Universidade Federal do Cearáinstacron:UFC2019-01-21T11:20:50Zmail@mail.com - |
dc.title.pt.fl_str_mv |
Mobility Data under Analysis a Complex Network Perspective from Interactions Among Trajectories to Movements among Points Interest |
title |
Mobility Data under Analysis a Complex Network Perspective from Interactions Among Trajectories to Movements among Points Interest |
spellingShingle |
Mobility Data under Analysis a Complex Network Perspective from Interactions Among Trajectories to Movements among Points Interest Igo Ramalho Brilhante Complex Network Mobility Trajectory CIENCIA DA COMPUTACAO |
title_short |
Mobility Data under Analysis a Complex Network Perspective from Interactions Among Trajectories to Movements among Points Interest |
title_full |
Mobility Data under Analysis a Complex Network Perspective from Interactions Among Trajectories to Movements among Points Interest |
title_fullStr |
Mobility Data under Analysis a Complex Network Perspective from Interactions Among Trajectories to Movements among Points Interest |
title_full_unstemmed |
Mobility Data under Analysis a Complex Network Perspective from Interactions Among Trajectories to Movements among Points Interest |
title_sort |
Mobility Data under Analysis a Complex Network Perspective from Interactions Among Trajectories to Movements among Points Interest |
author |
Igo Ramalho Brilhante |
author_facet |
Igo Ramalho Brilhante |
author_role |
author |
dc.contributor.advisor1.fl_str_mv |
Josà AntÃnio Fernandes de Macedo |
dc.contributor.advisor1ID.fl_str_mv |
00028098700 |
dc.contributor.advisor1Lattes.fl_str_mv |
http://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4737328P5 |
dc.contributor.referee1.fl_str_mv |
VÃnia Maria Ponte Vidal |
dc.contributor.referee1ID.fl_str_mv |
17344948320 |
dc.contributor.referee1Lattes.fl_str_mv |
http://lattes.cnpq.br/9431229866203038 |
dc.contributor.referee2.fl_str_mv |
Marco AntÃnio Casanova |
dc.contributor.referee2ID.fl_str_mv |
29997810759 |
dc.contributor.referee2Lattes.fl_str_mv |
http://lattes.cnpq.br/0400232298849115 |
dc.contributor.referee3.fl_str_mv |
Chiara Renso |
dc.contributor.referee3Lattes.fl_str_mv |
NÃo tem |
dc.contributor.authorID.fl_str_mv |
89444337200 |
dc.contributor.authorLattes.fl_str_mv |
http://lattes.cnpq.br/2100592282487417 |
dc.contributor.author.fl_str_mv |
Igo Ramalho Brilhante |
contributor_str_mv |
Josà AntÃnio Fernandes de Macedo VÃnia Maria Ponte Vidal Marco AntÃnio Casanova Chiara Renso |
dc.subject.por.fl_str_mv |
Complex Network Mobility Trajectory |
topic |
Complex Network Mobility Trajectory CIENCIA DA COMPUTACAO |
dc.subject.cnpq.fl_str_mv |
CIENCIA DA COMPUTACAO |
dc.description.abstract.por.fl_txt_mv |
The explosion of personal positioning devices like GPS-enabled smartphones has enabled the collection and storage of a huge amount of positioning data in the form of trajectories. Thereby, trajectory data have brought many research challenges in the process of recovery, storage and knowledge discovery in mobility as well as new applications to support our society in mobility terms. Other research area that has been receiving great attention nowadays is the area of complex network or science of networks. Complex network is the first approach to model complex system that are present in the real world, such as economic markets, the Internet, World Wide Web and disease spreading to name a few. It has been applied in different field, like Computer Science, Biology and Physics. Therefore, complex networks have demonstrated a great potential to investigate the behavior of complex systems through their entities and the relationships that exist among them. The present dissertation, therefore, aims at exploiting approaches to analyze mobility data using a perspective of complex networks. The first exploited approach stands for the trajectories as the main entities of the networks connecting each other through a similarity function. The second, in turn, focuses on points of interest that are visited by people, which perform some activities in these points. In addition, this dissertation also exploits the proposed methodologies in order to develop a software tool to support users in mobility analysis using complex network techniques. |
description |
The explosion of personal positioning devices like GPS-enabled smartphones has enabled the collection and storage of a huge amount of positioning data in the form of trajectories. Thereby, trajectory data have brought many research challenges in the process of recovery, storage and knowledge discovery in mobility as well as new applications to support our society in mobility terms. Other research area that has been receiving great attention nowadays is the area of complex network or science of networks. Complex network is the first approach to model complex system that are present in the real world, such as economic markets, the Internet, World Wide Web and disease spreading to name a few. It has been applied in different field, like Computer Science, Biology and Physics. Therefore, complex networks have demonstrated a great potential to investigate the behavior of complex systems through their entities and the relationships that exist among them. The present dissertation, therefore, aims at exploiting approaches to analyze mobility data using a perspective of complex networks. The first exploited approach stands for the trajectories as the main entities of the networks connecting each other through a similarity function. The second, in turn, focuses on points of interest that are visited by people, which perform some activities in these points. In addition, this dissertation also exploits the proposed methodologies in order to develop a software tool to support users in mobility analysis using complex network techniques. |
publishDate |
2012 |
dc.date.issued.fl_str_mv |
2012-02-10 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
status_str |
publishedVersion |
format |
masterThesis |
dc.identifier.uri.fl_str_mv |
http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=7837 |
url |
http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=7837 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Federal do Cearà |
dc.publisher.program.fl_str_mv |
Programa de PÃs-GraduaÃÃo em CiÃncia da ComputaÃÃo |
dc.publisher.initials.fl_str_mv |
UFC |
dc.publisher.country.fl_str_mv |
BR |
publisher.none.fl_str_mv |
Universidade Federal do Cearà |
dc.source.none.fl_str_mv |
reponame:Biblioteca Digital de Teses e Dissertações da UFC instname:Universidade Federal do Ceará instacron:UFC |
reponame_str |
Biblioteca Digital de Teses e Dissertações da UFC |
collection |
Biblioteca Digital de Teses e Dissertações da UFC |
instname_str |
Universidade Federal do Ceará |
instacron_str |
UFC |
institution |
UFC |
repository.name.fl_str_mv |
-
|
repository.mail.fl_str_mv |
mail@mail.com |
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1643295159817863168 |