869 resultados para BWW ontology
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Pós-graduação em Ciência da Computação - IBILCE
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Pós-graduação em Ciência da Computação - IBILCE
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Pós-graduação em Ciência da Computação - IBILCE
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Different vocabularies and contexts are barriers to the communication between people or software systems. It is necessary a common understanding in the domain that is talked about, so it can be obtained a correct interpretation of the information. An ontology formally models the structure of a domain and turn explicit the shared understanding in the form of concepts and relations that emerge from its observation. Constitutes a sort of framework used in the mapping to the meaning of the information that is talked about. The formal accuracy in which they are defined, by means of axioms, allow machine processing, implicating in systems interoperability. Structured this way, the knowledge is easily transferred between people or systems from different contexts. Ontologies present several applications nowadays. They are considered the infra-structure to the Semantic Web, which is composed by Web resources with embedded meaning. Thereby, the automatic execution of complex tasks is allowed, with the benefit from the effective communication between Web software agents. Among other applications, they also have been used to structure the knowledge generated from several areas, like Biology and Software Engineering.
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The increase in new electronic devices had generated a considerable increase in obtaining spatial data information; hence these data are becoming more and more widely used. As well as for conventional data, spatial data need to be analyzed so interesting information can be retrieved from them. Therefore, data clustering techniques can be used to extract clusters of a set of spatial data. However, current approaches do not consider the implicit semantics that exist between a region and an object’s attributes. This paper presents an approach that enhances spatial data mining process, so they can use the semantic that exists within a region. A framework was developed, OntoSDM, which enables spatial data mining algorithms to communicate with ontologies in order to enhance the algorithm’s result. The experiments demonstrated a semantically improved result, generating more interesting clusters, therefore reducing manual analysis work of an expert.
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Pós-graduação em Ciência da Computação - IBILCE
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)