Article ID Journal Published Year Pages File Type
10366675 Information and Software Technology 2005 12 Pages PDF
Abstract
Spatial data mining has been identified as an important task for understanding and use of spatial data- and knowledge-bases. In this paper, we present a new approach to discover strong multilevel spatial association rules in spatial databases based on partitioning the set of rows with respect to the spatial relations denoted as relation table R. Meanwhile, the introduction of the equivalence partition tree makes the discovery of multilevel spatial association rules easy and efficient. Experiments show that the new algorithm is efficient.
Related Topics
Physical Sciences and Engineering Computer Science Human-Computer Interaction
Authors
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