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Enhancing the Process of Knowledge Discovery in Geographic Databases Using Geo-Ontologies
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Author(s): Vania Bogorny (Universidade Federal do Rio Grande do Sul (UFRGS), Brazil), Paulo Martins Engel (Transnational University of Limburg, Belgium)and Luis Otavio Alavares (Transnational University of Limburg, Belgium)
Copyright: 2008
Pages: 22
Source title:
Data Mining with Ontologies: Implementations, Findings, and Frameworks
Source Author(s)/Editor(s): Hector Oscar Nigro (Universidad Nacional del Centro de la Provincia de Buenos Aires, Argentina), Sandra Elizabeth Gonzalez Cisaro (Universidad Nacional del Centro de la Provincia de Buenos Aires, Argentina)and Daniel Hugo Xodo (Universidad Nacional del Centro de la Provincia de Buenos Aires, Argentina)
DOI: 10.4018/978-1-59904-618-1.ch009
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Abstract
This chapter introduces the problem of mining frequent geographic patterns and spatial association rules from geographic databases. In the geographic domain most discovered patterns are trivial, non-novel, and non-interesting, which simply represent natural geographic associations intrinsic to geographic data. A large amount of natural geographic associations are explicitly represented in geographic database schemas and geo-ontologies, which have not been used so far in frequent geographic pattern mining. Therefore, this chapter presents a novel approach to extract patterns from geographic databases using geo-ontologies as prior knowledge. The main goal of this chapter is to show how the large amount of knowledge represented in geo-ontologies can be used to avoid the extraction of patterns that are previously known as non-interesting.
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