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DSB-tree: an improved spatial data index structure based on SS-tree

机译:DSB树:基于SS树的改进的空间数据索引结构

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Using approximate geometrical expression to construct spatial data index becomes to an effective method because of the complexity of spatial entity. The simple exterior approximate expression could not satisfy the multiple query requirements to the spatial dataset. Obvious distance and topology relationships can be found between spatial data, especially the two or three dimensions spatial data used in GIS. Circle shape is can be constructed and expressed with a low amount of data, and all kinds of operations on distance and topology are exceedingly simple and easy to implement. A novel index structure named double sphere balance tree and abbreviated as DSB-tree is represented with importing maximum enclosed circle (MEC) as interior approximate expression based on SS-tree. Due to the double approximate expression constructed with two circles (MBC and MEC), all the operations of DSB-tree are low cost and more effective. We implement the structure and its basal operations as spatial data index, including insertion, remove and query. Finally, the extensive experiments and their results are given to discuss the performance of the DSB-tree for the NN query.
机译:由于空间实体的复杂性,使用近似几何表达来构造空间数据索引变为有效的方法。简单的外部近似表达式无法满足空间数据集的多个查询要求。在空间数据之间可以找到明显的距离和拓扑关系,尤其是GIS中使用的两种或三维空间数据。圆形可以构造并以少量的数据表示,并且各种操作在距离和拓扑上非常简单且易于实现。名为Double Sphere Stanal树的新颖索引结构并缩写为DSB-TREE,以导入最大封闭的圆(MEC)作为基于SS树的内部近似表达式。由于两个圆圈(MBC和MEC)构造的双近似表达,DSB树的所有操作都是低成本且更有效的。我们将结构及其基础操作实施为空间数据索引,包括插入,删除和查询。最后,提供了广泛的实验及其结果讨论了NN查询的DSB树的性能。

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