Search results
Results from the WOW.Com Content Network
Range minimum query reduced to the lowest common ancestor problem.. Given an array A[1 … n] of n objects taken from a totally ordered set, such as integers, the range minimum query RMQ A (l,r) =arg min A[k] (with 1 ≤ l ≤ k ≤ r ≤ n) returns the position of the minimal element in the specified sub-array A[l …
In computer science, an optimal binary search tree (Optimal BST), sometimes called a weight-balanced binary tree, [1] 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.
The function inorderNext [2]: 60 returns an in-order-neighbor of node, either the in-order-successor (for dir=1) or the in-order-predecessor (for dir=0), and the updated stack, so that the binary search tree may be sequentially in-order-traversed and searched in the given direction dir further on.
A planar graph and its minimum spanning tree. Each edge is labeled with its weight, which here is roughly proportional to its length. A minimum spanning tree (MST) or minimum weight spanning tree is a subset of the edges of a connected, edge-weighted undirected graph that connects all the vertices together, without any cycles and with the minimum possible total edge weight. [1]
An augmented tree can be built from a simple ordered tree, for example a binary search tree or self-balancing binary search tree, ordered by the 'low' values of the intervals. An extra annotation is then added to every node, recording the maximum upper value among all the intervals from this node down.
The treap was first described by Raimund Seidel and Cecilia R. Aragon in 1989; [1] [2] its name is a portmanteau of tree and heap. It is a Cartesian tree in which each key is given a (randomly chosen) numeric priority. As with any binary search tree, the inorder traversal order of the nodes is the same as the sorted order of the keys. The ...
The necessary distinction can be made by first partitioning the edges; i.e., defining the binary tree as triplet (V, E 1, E 2), where (V, E 1 ∪ E 2) is a rooted tree (equivalently arborescence) and E 1 ∩ E 2 is empty, and also requiring that for all j ∈ { 1, 2 }, every node has at most one E j child. [14]
In graph theory and theoretical computer science, the longest path problem is the problem of finding a simple path of maximum length in a given graph.A path is called simple if it does not have any repeated vertices; the length of a path may either be measured by its number of edges, or (in weighted graphs) by the sum of the weights of its edges.