Efficient discovery of multilevel spatial association rules using partitions
Efficient discovery of multilevel spatial association rules using partitions
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DOI：
10.1016/j.infsof.2004.03.007
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发表时间：
2005-10
期刊：
影响因子：
--
通讯作者：
Lizhen Wang;Kunqing Xie;Tao Chen;Xiuli Ma
中科院分区：
文献类型：
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作者：
Lizhen Wang;Kunqing Xie;Tao Chen;Xiuli Ma
空间数据挖掘已被确定为理解和使用空间数据和知识库的一项重要任务。本文提出了一种新的方法来发现强多级空间关联规则的空间数据库的基础上划分的行集的空间关系表示为关系表R。同时，等价划分树的引入使得多级空间关联规则的发现变得简单而有效。实验表明，该算法是有效的。
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.