Detalhes bibliográficos
Ano de defesa: |
2019 |
Autor(a) principal: |
Andrade, Claudio Moisés Valiense
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Orientador(a): |
Rocha Junior, João Batista
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Banca de defesa: |
Não Informado pela instituição |
Tipo de documento: |
Dissertação
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Tipo de acesso: |
Acesso aberto |
Idioma: |
por |
Instituição de defesa: |
Universidade Estadual de Feira de Santana
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Programa de Pós-Graduação: |
Mestrado em Computação Aplicada
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Departamento: |
DEPARTAMENTO DE CIÊNCIAS EXATAS
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País: |
Brasil
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Palavras-chave em Português: |
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Área do conhecimento CNPq: |
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Link de acesso: |
http://tede2.uefs.br:8080/handle/tede/826
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Resumo: |
Spatial data is increasingly present in our daily lives. We use various applications that use this data, such as Google Maps and Uber. There are a huge number of interesting questions that can be performed on these data. For example, a tourist maybe interested in hotels that have a lot of restaurants in its vicinity. This project proposes a new query type named Popularity Based Spatio-Textual Preference Query (PSTPQ), whose main contribution, that can select the best spatial objects taking into account the number of relevant spatio-textual objects, for a given set of query keywords, in its neighborhood. We present algorithms to process this query e ciently and evaluate the algorithms proposed in real datasets. Our experiments show that it is more e cient to use spatial indices (e.g. R-Tree) for distances less than 5 km in relation to textual indexes (e.g. Inverted File). In our experiments, the hybrid index processed the PSTPQ query with better performance. The PSTPQ query has as a di erential take into account the number of reference objects in the spatial neighborhood, in addition to selecting the reference objects from the textual description. |