This HTML5 document contains 21 embedded RDF statements represented using HTML+Microdata notation.

The embedded RDF content will be recognized by any processor of HTML5 Microdata.

Namespace Prefixes

PrefixIRI
dcthttp://purl.org/dc/terms/
yago-reshttp://yago-knowledge.org/resource/
dbohttp://dbpedia.org/ontology/
foafhttp://xmlns.com/foaf/0.1/
dbthttp://dbpedia.org/resource/Template:
rdfshttp://www.w3.org/2000/01/rdf-schema#
freebasehttp://rdf.freebase.com/ns/
rdfhttp://www.w3.org/1999/02/22-rdf-syntax-ns#
owlhttp://www.w3.org/2002/07/owl#
n12http://en.wikipedia.org/wiki/
dbphttp://dbpedia.org/property/
dbchttp://dbpedia.org/resource/Category:
provhttp://www.w3.org/ns/prov#
xsdhhttp://www.w3.org/2001/XMLSchema#
goldhttp://purl.org/linguistics/gold/
dbrhttp://dbpedia.org/resource/

Statements

Subject Item
dbr:Optimal_binary_search_tree
rdf:type
dbo:Plant
rdfs:label
Optimal binary search tree
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.
owl:sameAs
yago-res:Optimal_binary_search_tree freebase:m.0105pbnn
dbp:wikiPageUsesTemplate
dbt:Unsolved dbt:Reflist dbt:Data_structures dbt:CS-Trees dbt:Tmath dbt:Mvar dbt:Main
dct:subject
dbc:Search_trees dbc:Binary_trees
gold:hypernym
dbr:Tree
prov:wasDerivedFrom
n12:Optimal_binary_search_tree?oldid=1068814105&ns=0
dbo:wikiPageID
42382810
dbo:wikiPageLength
18220
dbo:wikiPageRevisionID
1068814105
dbo: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.
foaf:isPrimaryTopicOf
n12:Optimal_binary_search_tree