Detalhes bibliográficos
| Ano de defesa: |
2016 |
| Autor(a) principal: |
SANTANA, Amon Veiga |
| Orientador(a): |
CAMPOS, Jorge Alberto Prado de |
| Banca de defesa: |
Não Informado pela instituição |
| Tipo de documento: |
Dissertação
|
| Tipo de acesso: |
Acesso aberto |
| Idioma: |
por |
| Instituição de defesa: |
Universidade Salvador
|
| Programa de Pós-Graduação: |
Sistemas e Computação
|
| Departamento: |
Sistemas e Computação
|
| País: |
Brasil
|
| Palavras-chave em Português: |
|
| Palavras-chave em Inglês: |
|
| Área do conhecimento CNPq: |
|
| Link de acesso: |
http://teste.tede.unifacs.br:8080/tede/handle/tede/412
|
Resumo: |
Trajectories of moving objects (people, animals and goods) have been an active research topic for over a decade. The classical approach for trajectory analyse of these objects is mainly based in large amounts of data acquired from positioning devices, such GPS receivers. The trajectory data based in GPS data has the advantage of high special granularity and a relative accuracy. These data, however, don’t carry any type of semantic. More recently, has grown the number of applications that uses georeferenced social interactions as source of information to generate people’s trajectory. The social network interaction usage brings some drawbacks, such as low spatial granularity and accuracy. That means that these data are sparsed and have a high level of uncertainty. The social interactions usage advantage is the high potential to incorporate semantic to the users’ trajectories. This work propose a scaffold for the reconstruction of travel histories using heterogeneous social track sources. We consider social tracks the posts in social networks, GPS positioning data, location history data generated by cloud services or any other user activity that register his geographic position. This scaffold is composed by a conceptual and a data model to represent the individual’s travel histories, including all his movements, transportation means used, places visited and its meanings; algorithms to the detection and categorization of stops and movements; strategies and definitions to the identification of the transportation mean used in the movements; and the development of an application that allows registered users authorize the usage of his social tracks to rebuild his travel histories. These travel histories cover the transportations used, the visits he has made, how long he has stayed in each place, the social repercussion that each visit has generated and other semantic data that together, can tell a complete history. The integration of heterogeneous location information source was shown as a promising approach to the creation of a knowledge base to studies and applications related to knowledge extraction based in semantic enriched trajectories. The test realized with the prototype showed that the model is a feasible to supply this gap in the context of touristic travels. |
