Exploring human activity behavior and mobility data in carpooling
Autor(a) principal: | |
---|---|
Data de Publicação: | 2014 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFPE |
Texto Completo: | https://repositorio.ufpe.br/handle/123456789/11850 |
Resumo: | The analysis of human movements has been the subject of several studies since the 70s. In recent years, the exponential growth of location aware devices must allow the study of the behavior of the individuals’ mobility from their trajectories collected. However, a significant part of the available literature is focused on the development of techniques for analyzing trajectories of people from a purely geometric point of view, while a smaller part, but increasingly group is looking at the semantic aspects of mobility. This work presents a contribution to the latest trend, and is concerned with the definition of semantic regularity profiles and the applicability of these concepts to the practice of carpooling. We propose a semantic regularity profile based on the entropy of the spatial and temporal frequency of visits to certain categories of places. We analyze the user’s behavior with respect to regularity and irregularity, identifying users who are more or less loyal to certain locations, in contrast to the irregularity of visiting different places. In a different point of view, an analysis over the place perspective was also performed. A web tool was developed to show on map, for each place of a given category, the computed information about the loyal behavior of their visitors. From the study about regularity, we have evidences that some human activities are not strictly associated to a unique POI (Point of Interest) and neither to a specific schedule of the day. Bringing to the carpooling context, in some situations it is worth for a person to change his destination or the time to perform an activity if there is a possibility of ride for him due all the benefits involved with the carpooling practice. This dissertation also presents a novel matching method for carpooling that is oriented to the passenger’s intended activity, aiming to boost the possibilities of rides. Three algorithms for carpool matching are proposed, which manipulates differently the spatial and temporal dimensions. Using a real data set of trajectories, we conducted experiments and our results showed that the proposed matching algorithms improved the traditional carpooling approach in +46.84% when the spatial dimension was considered, in +50.89% when the temporal dimension was prioritized and in +82.30% when both dimensions were tackled. |
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Lira, Vinícius Cezar Monteiro de LiraTedesco, PatríciaTimes, Valéria Cesário2015-03-10T19:43:51Z2015-03-10T19:43:51Z2014-08-28https://repositorio.ufpe.br/handle/123456789/11850The analysis of human movements has been the subject of several studies since the 70s. In recent years, the exponential growth of location aware devices must allow the study of the behavior of the individuals’ mobility from their trajectories collected. However, a significant part of the available literature is focused on the development of techniques for analyzing trajectories of people from a purely geometric point of view, while a smaller part, but increasingly group is looking at the semantic aspects of mobility. This work presents a contribution to the latest trend, and is concerned with the definition of semantic regularity profiles and the applicability of these concepts to the practice of carpooling. We propose a semantic regularity profile based on the entropy of the spatial and temporal frequency of visits to certain categories of places. We analyze the user’s behavior with respect to regularity and irregularity, identifying users who are more or less loyal to certain locations, in contrast to the irregularity of visiting different places. In a different point of view, an analysis over the place perspective was also performed. A web tool was developed to show on map, for each place of a given category, the computed information about the loyal behavior of their visitors. From the study about regularity, we have evidences that some human activities are not strictly associated to a unique POI (Point of Interest) and neither to a specific schedule of the day. Bringing to the carpooling context, in some situations it is worth for a person to change his destination or the time to perform an activity if there is a possibility of ride for him due all the benefits involved with the carpooling practice. This dissertation also presents a novel matching method for carpooling that is oriented to the passenger’s intended activity, aiming to boost the possibilities of rides. Three algorithms for carpool matching are proposed, which manipulates differently the spatial and temporal dimensions. Using a real data set of trajectories, we conducted experiments and our results showed that the proposed matching algorithms improved the traditional carpooling approach in +46.84% when the spatial dimension was considered, in +50.89% when the temporal dimension was prioritized and in +82.30% when both dimensions were tackled.engUniversidade Federal de PernambucoAttribution-NonCommercial-NoDerivs 3.0 Brazilhttp://creativecommons.org/licenses/by-nc-nd/3.0/br/info:eu-repo/semantics/openAccessHuman Mobility BehaviorRegularityLoyaltyCarpoolingExploring human activity behavior and mobility data in carpoolinginfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisreponame:Repositório Institucional da UFPEinstname:Universidade Federal de Pernambuco (UFPE)instacron:UFPETHUMBNAILDISSERTAÇÃO Vinicius Cezar Monteiro de Lira.pdf.jpgDISSERTAÇÃO Vinicius Cezar Monteiro de Lira.pdf.jpgGenerated Thumbnailimage/jpeg1339https://repositorio.ufpe.br/bitstream/123456789/11850/5/DISSERTA%c3%87%c3%83O%20Vinicius%20Cezar%20Monteiro%20de%20Lira.pdf.jpg85b486e6844ab8bb131cdbde9de3e24bMD55ORIGINALDISSERTAÇÃO Vinicius Cezar Monteiro de Lira.pdfDISSERTAÇÃO Vinicius Cezar Monteiro de Lira.pdfDissertação de mestradoapplication/pdf4006584https://repositorio.ufpe.br/bitstream/123456789/11850/1/DISSERTA%c3%87%c3%83O%20Vinicius%20Cezar%20Monteiro%20de%20Lira.pdf5d1301329fabe34879780b3b17bb1e8aMD51CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; 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dc.title.pt_BR.fl_str_mv |
Exploring human activity behavior and mobility data in carpooling |
title |
Exploring human activity behavior and mobility data in carpooling |
spellingShingle |
Exploring human activity behavior and mobility data in carpooling Lira, Vinícius Cezar Monteiro de Lira Human Mobility Behavior Regularity Loyalty Carpooling |
title_short |
Exploring human activity behavior and mobility data in carpooling |
title_full |
Exploring human activity behavior and mobility data in carpooling |
title_fullStr |
Exploring human activity behavior and mobility data in carpooling |
title_full_unstemmed |
Exploring human activity behavior and mobility data in carpooling |
title_sort |
Exploring human activity behavior and mobility data in carpooling |
author |
Lira, Vinícius Cezar Monteiro de Lira |
author_facet |
Lira, Vinícius Cezar Monteiro de Lira |
author_role |
author |
dc.contributor.author.fl_str_mv |
Lira, Vinícius Cezar Monteiro de Lira |
dc.contributor.advisor1.fl_str_mv |
Tedesco, Patrícia Times, Valéria Cesário |
contributor_str_mv |
Tedesco, Patrícia Times, Valéria Cesário |
dc.subject.por.fl_str_mv |
Human Mobility Behavior Regularity Loyalty Carpooling |
topic |
Human Mobility Behavior Regularity Loyalty Carpooling |
description |
The analysis of human movements has been the subject of several studies since the 70s. In recent years, the exponential growth of location aware devices must allow the study of the behavior of the individuals’ mobility from their trajectories collected. However, a significant part of the available literature is focused on the development of techniques for analyzing trajectories of people from a purely geometric point of view, while a smaller part, but increasingly group is looking at the semantic aspects of mobility. This work presents a contribution to the latest trend, and is concerned with the definition of semantic regularity profiles and the applicability of these concepts to the practice of carpooling. We propose a semantic regularity profile based on the entropy of the spatial and temporal frequency of visits to certain categories of places. We analyze the user’s behavior with respect to regularity and irregularity, identifying users who are more or less loyal to certain locations, in contrast to the irregularity of visiting different places. In a different point of view, an analysis over the place perspective was also performed. A web tool was developed to show on map, for each place of a given category, the computed information about the loyal behavior of their visitors. From the study about regularity, we have evidences that some human activities are not strictly associated to a unique POI (Point of Interest) and neither to a specific schedule of the day. Bringing to the carpooling context, in some situations it is worth for a person to change his destination or the time to perform an activity if there is a possibility of ride for him due all the benefits involved with the carpooling practice. This dissertation also presents a novel matching method for carpooling that is oriented to the passenger’s intended activity, aiming to boost the possibilities of rides. Three algorithms for carpool matching are proposed, which manipulates differently the spatial and temporal dimensions. Using a real data set of trajectories, we conducted experiments and our results showed that the proposed matching algorithms improved the traditional carpooling approach in +46.84% when the spatial dimension was considered, in +50.89% when the temporal dimension was prioritized and in +82.30% when both dimensions were tackled. |
publishDate |
2014 |
dc.date.issued.fl_str_mv |
2014-08-28 |
dc.date.accessioned.fl_str_mv |
2015-03-10T19:43:51Z |
dc.date.available.fl_str_mv |
2015-03-10T19:43:51Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://repositorio.ufpe.br/handle/123456789/11850 |
url |
https://repositorio.ufpe.br/handle/123456789/11850 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
Attribution-NonCommercial-NoDerivs 3.0 Brazil http://creativecommons.org/licenses/by-nc-nd/3.0/br/ info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Attribution-NonCommercial-NoDerivs 3.0 Brazil http://creativecommons.org/licenses/by-nc-nd/3.0/br/ |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
Universidade Federal de Pernambuco |
publisher.none.fl_str_mv |
Universidade Federal de Pernambuco |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da UFPE instname:Universidade Federal de Pernambuco (UFPE) instacron:UFPE |
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