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2015 | OriginalPaper | Buchkapitel

The xBR\(^+\)-tree: An Efficient Access Method for Points

verfasst von : George Roumelis, Michael Vassilakopoulos, Thanasis Loukopoulos, Antonio Corral, Yannis Manolopoulos

Erschienen in: Database and Expert Systems Applications

Verlag: Springer International Publishing

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Abstract

Spatial indexes, such as those based on Quadtree, are important in spatial databases for efficient execution of queries involving spatial constraints. In this paper, we present improvements of the xBR-tree (a member of the Quadtree family) with modified internal node structure and tree building process, called xBR\(^+\)-tree. We highlight the differences of the algorithms for processing single dataset queries between the xBR and xBR\(^+\)-trees and we demonstrate performance results (I/O efficiency and execution time) of extensive experimentation (based on real and synthetic datasets) on tree building process and processing of single dataset queries, using the two structures. These results show that the two trees are comparable, regarding their building performance, however, the xBR\(^+\)-tree is an overall winner, regarding spatial query processing.

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Fußnoten
1
Note that we used double numbers for coordinates, instead of float numbers used in [10], to be able to represent large number of points in the normalized square space. Due to this change of representation, results for specific datasets that appear in [10] for the xBR-tree differ slightly from the respective results in this paper.
 
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Metadaten
Titel
The xBR-tree: An Efficient Access Method for Points
verfasst von
George Roumelis
Michael Vassilakopoulos
Thanasis Loukopoulos
Antonio Corral
Yannis Manolopoulos
Copyright-Jahr
2015
DOI
https://doi.org/10.1007/978-3-319-22849-5_4