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dc.creatorRoumelis G., Vassilakopoulos M., Loukopoulos T., Corral A., Manolopoulos Y.en
dc.description.abstractSpatial 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. © Springer International Publishing Switzerland 2015.en
dc.sourceLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)en
dc.subjectDatabase systemsen
dc.subjectExpert systemsen
dc.subjectQuery languagesen
dc.subjectQuery processingen
dc.subjectBuilding performanceen
dc.subjectQuad treesen
dc.subjectSpatial access methodsen
dc.subjectSpatial constraintsen
dc.subjectSpatial databaseen
dc.subjectSpatial query processingen
dc.subjectSynthetic datasetsen
dc.subjectSpringer Verlagen
dc.titleThe xbr+-tree: An efficient access method for pointsen

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