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In data processing R*-trees are a variant of R-trees used for indexing spatial information. R*-trees have slightly higher construction cost than standard R-trees, as the data may need to be reinserted; but the resulting tree will usually have a better query performance. Like the standard R-tree, it can store both point and spatial data.
Quadtree compression of an image step by step. Left shows the compressed image with the tree bounding boxes while the right shows just the compressed image A quadtree is a tree data structure in which each internal node has exactly four children.
The key idea is to use the bounding boxes to decide whether or not to search inside a subtree. In this way, most of the nodes in the tree are never read during a search. Like B-trees, R-trees are suitable for large data sets and databases, where nodes can be paged to memory when needed, and the whole tree cannot be kept in main memory. Even if ...
The term prioritized arrives from the introduction of four priority-leaves that represents the most extreme values of each dimensions, included in every branch of the tree. Before answering a window-query by traversing the sub-branches, the prioritized R-tree first checks for overlap in its priority nodes. The sub-branches are traversed (and ...
A rapidly exploring random tree (RRT) is an algorithm designed to efficiently search nonconvex, high-dimensional spaces by randomly building a space-filling tree.The tree is constructed incrementally from samples drawn randomly from the search space and is inherently biased to grow towards large unsearched areas of the problem.
The performance of R-trees depends on the quality of the algorithm that clusters the data rectangles on a node. Hilbert R-trees use space-filling curves, and specifically the Hilbert curve, to impose a linear ordering on the data rectangles. There are two types of Hilbert R-trees: one for static databases, and one for dynamic databases. In both ...
size(r) = the number of nodes in the sub-tree rooted at node r (including r). rank(r) = log 2 (size(r)). Φ = the sum of the ranks of all the nodes in the tree. Φ will tend to be high for poorly balanced trees and low for well-balanced trees. To apply the potential method, we first calculate ΔΦ: the change in the potential caused by a splay ...
An R+ tree is a method for looking up data using a location, often (x, y) coordinates, and often for locations on the surface of the Earth.Searching on one number is a solved problem; searching on two or more, and asking for locations that are nearby in both x and y directions, requires craftier algorithms.