An Association Rule Mining Method for Spatial Database

T.-C. Lu, C.-C. Chang, and S.W. Changchien (Taiwan)


Association rules, class inheritance, rough set, spatial database mining


Spatial data mining has become a significant topic of research as large amounts of spatial data are collected and deposited into imaging systems. Association rules mining from spatial databases can retrieve the association relationships among spatial objects. It can be very complicated and exhausting because spatial data are usually related to each other in terms of different aspects, such as distance, direction, and topology. In this paper, we shall propose an efficient method for mining association rules from a spatial database. The mining method employs a mining scheme called Class Inheritance Tree (CIT) to efficiently extract the association rules among distinct and recurrent spatial objects.

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