About: Optimal binary search tree

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In computer science, an optimal binary search tree (Optimal BST), sometimes called a weight-balanced binary tree, is a binary search tree which provides the smallest possible search time (or expected search time) for a given sequence of accesses (or access probabilities). Optimal BSTs are generally divided into two types: static and dynamic.

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rdf:type	plant
rdfs:label	Optimal binary search tree (en)
rdfs:comment	In computer science, an optimal binary search tree (Optimal BST), sometimes called a weight-balanced binary tree, is a binary search tree which provides the smallest possible search time (or expected search time) for a given sequence of accesses (or access probabilities). Optimal BSTs are generally divided into two types: static and dynamic. (en)
sameAs	Optimal binary search tree Optimal binary search tree
dbp:wikiPageUsesTemplate	dbt:CS-Trees dbt:Main dbt:Mvar dbt:Reflist dbt:Tmath dbt:Data_structures dbt:Unsolved
Subject	Binary trees Search trees
gold:hypernym	Tree
prov:wasDerivedFrom	http://en.wikipedia.org/wiki/Optimal_binary_search_tree?oldid=1068814105&ns=0
Wikipage page ID	42382810 (xsd:integer)
page length (characters) of wiki page	18220 (xsd:nonNegativeInteger)
Wikipage revision ID	1068814105 (xsd:integer)
has abstract	In computer science, an optimal binary search tree (Optimal BST), sometimes called a weight-balanced binary tree, is a binary search tree which provides the smallest possible search time (or expected search time) for a given sequence of accesses (or access probabilities). Optimal BSTs are generally divided into two types: static and dynamic. In the static optimality problem, the tree cannot be modified after it has been constructed. In this case, there exists some particular layout of the nodes of the tree which provides the smallest expected search time for the given access probabilities. Various algorithms exist to construct or approximate the statically optimal tree given the information on the access probabilities of the elements. In the dynamic optimality problem, the tree can be modified at any time, typically by permitting tree rotations. The tree is considered to have a cursor starting at the root which it can move or use to perform modifications. In this case, there exists some minimal-cost sequence of these operations which causes the cursor to visit every node in the target access sequence in order. The splay tree is conjectured to have a constant competitive ratio compared to the tree in all cases, though this has not yet been proven. (en)
foaf:isPrimaryTopicOf	http://en.wikipedia.org/wiki/Optimal_binary_search_tree
is Wikipage redirect of	Optimum binary search tree Static optimality Dynamic optimality
is Link from a Wikipage to another Wikipage of	Adriano Garsia Binary tree Geometry of binary search trees Key-independent optimality Michelle L. Wachs Garsia–Wachs algorithm Hash table Interleave lower bound Dynamic optimality

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