Detalhes bibliográficos
Ano de defesa: |
2008 |
Autor(a) principal: |
Natale, Leandro Pupo
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Orientador(a): |
Mustaro, Pollyana Notargiacomo
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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 Presbiteriana Mackenzie
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Programa de Pós-Graduação: |
Não Informado pela instituição
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Departamento: |
Não Informado pela instituição
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País: |
Não Informado pela instituição
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Palavras-chave em Português: |
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Palavras-chave em Inglês: |
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Área do conhecimento CNPq: |
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Link de acesso: |
http://dspace.mackenzie.br/handle/10899/24399
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Resumo: |
In recent years the technological advances have allowed the improvement, streamlining processes, activities simplification and the establishment of new forms of communication between people. They also reached the government sphere and its activities, bringing benefits with respect to access information and enabling greater interaction between citizens through services C2C (Citizen to Citizen). Based on these aspects, this research is guided in the use of the social networks analysis to achieve the mapping of relationships and interactions between citizens under the government focus, in order to extract and represent that knowledge in metadata to build an ontology. Through the use the UML notation and the Java platform, it was modeled and developed a prototype of a computer system that manages and manipulates a social network, using metadata to store the social ties in the ontological database. This allows the social network to be expanded dynamically through a semantic analysis of the data held in each new citizen inserted in the network. In a complementary manner, by means of algorithms adapted the graphs theory, the prototype provides every citizen the path to pass through to find other people with common interests and needs in, revealing the result of the search graphically. The prototype also displays graphically the different social ties among citizens, so that government agencies can quantitatively analyze the information present in the social network. |