Proceedings of the 1990 ACM SIGMOD International Conference on Management of Data 1990
DOI: 10.1145/93597.98741
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The R*-tree: an efficient and robust access method for points and rectangles

Abstract: The R-tree, one of the most popular access methods for rectangles, IS based on the heurlstlc optlmlzatlon of the area of the enclosmg rectangle m each mner node By running numerous experiments m a standardized testbed under highly varying data, queries and operations, we were able to design the R*-tree which mcorporates a combined optlmlzatlon of area, margin and overlap of each enclosmg rectangle m the directory Using our standardized testbed m an exhaustive performance comparison, It turned out that the R*-t… Show more

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Cited by 2,746 publications
(1,392 citation statements)
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“…The variants include R+ Tree [3], R* Tree [4], Packed R-Tree [6], Buffer R-Tree [8], Priority RTree [24], X-Tree [10] and Multi Small Index [33]. Each differs from one another in their construction.…”
Section: Variations Based On Process Changementioning
confidence: 99%
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“…The variants include R+ Tree [3], R* Tree [4], Packed R-Tree [6], Buffer R-Tree [8], Priority RTree [24], X-Tree [10] and Multi Small Index [33]. Each differs from one another in their construction.…”
Section: Variations Based On Process Changementioning
confidence: 99%
“…The aspects are minimization of overlap, area covered by the directory nodes (dead space should be minimum), margin (square gives the minimum margin for the given area) and maximizing storage utilization. The variant R* [4] is built by incorporating a few changes in concepts to the basic R-Tree. The changes are 1) while choosing sub-tree, if the node is nonleaf and points to the leaf then minimum overlap (area is considered only during tie) enlargement is considered.…”
Section: R*-treementioning
confidence: 99%
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“…1 Without a properly designed indexing structure, the retrieval of information may be reduced to a linear exhaustive search. On the other hand, a good indexing structure will make t h e retrieval accurate and computationally e cient.…”
Section: Introductionmentioning
confidence: 99%
“…The Rtree [12] was initially proposed as an extension to the B-Tree structure for handling multidimensional data. Many variants of the R-Tree, such as R + -Tree [27] and R -Tree [4] have been studied. They differ in the algorithm that is used for insertion, specifically in splitting a node of the tree when its subtree is filled.…”
Section: Nearest Neighbor Queriesmentioning
confidence: 99%