Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10366675 | Information and Software Technology | 2005 | 12 Pages |
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.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Human-Computer Interaction
Authors
Lizhen Wang, Kunqing Xie, Tao Chen, Xiuli Ma,