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A weight-balanced tree is a binary search tree that stores the sizes of subtrees in the nodes. That is, a node has fields key, of any ordered type; value (optional, only for mappings) left, right, pointer to node; size, of type integer. By definition, the size of a leaf (typically represented by a nil pointer) is zero.
If the key isn’t found in memory, the search moves to the disk components, starting with the first level (C1) and continuing through deeper levels (C2, C3, etc.). Each disk level is also sorted, allowing for efficient searches using methods like binary search or tree search. Newer levels are checked first because they contain the most recent ...
Smart term-weighting triple notation Term frequency () Document frequency (,) Document length normalization (,); b: Binary weight x: n: Disregards the collection frequency
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.
Most operations on a binary search tree (BST) take time directly proportional to the height of the tree, so it is desirable to keep the height small. A binary tree with height h can contain at most 2 0 +2 1 +···+2 h = 2 h+1 −1 nodes. It follows that for any tree with n nodes and height h: +
Database tables and indexes may be stored on disk in one of a number of forms, including ordered/unordered flat files, ISAM, heap files, hash buckets, or B+ trees. Each form has its own particular advantages and disadvantages. The most commonly used forms are B-trees and ISAM.
A binary search of a sorted table with N records, for example, can be done in roughly ⌈ log 2 N ⌉ comparisons. If the table had 1,000,000 records, then a specific record could be located with at most 20 comparisons: ⌈ log 2 (1,000,000) ⌉ = 20. Large databases have historically been kept on disk drives.
In computer science, a search data structure [citation needed] is any data structure that allows the efficient retrieval of specific items from a set of items, such as a specific record from a database. The simplest, most general, and least efficient search structure is merely an unordered sequential list of all the items.