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of data access
of data access

... to the right sub-tree of a given node depending only on a key value in this node. Using recursive method (going down the tree), after every key value test there is always reduced (approximately) the half of number of elements (from this “wrong” tree half ). This algorithm is more efficient than line ...
Lecture No. 15
Lecture No. 15

... Similarly, in case of strings (words) here, we will increment the counter if it is already present, and will seek the left and right subtrees accordingly, if required. In case of int’s we could easily compare them and see which one is greater but what will happen in case of strings. You must remembe ...
A Simple and Efficient Union-Find
A Simple and Efficient Union-Find

How to Keep Your Neighbours in Order Conor McBride Abstract 1.
How to Keep Your Neighbours in Order Conor McBride Abstract 1.

... alleviate and sometimes obviate the burden of proof. Let us try to bake the invariant in. What should the type of a subtree tell us? If we want to check the invariant at a given node, we shall need some information about the subtrees which we might expect comes from their type. We require that the e ...
Building Trees
Building Trees

Representation transformations of ordered lists
Representation transformations of ordered lists

... representation into another, efficiently? Summarizing this paper, we already know that given an input representation of L, we can produce another representation of it in Θ(n) time, if this other representation is a linear data structure, an AVL or red-black tree. In some cases we have direct transfo ...
Chapter 13 Trees - Margaret M. Fleck
Chapter 13 Trees - Margaret M. Fleck

05_1_Lecture
05_1_Lecture

Array Implementation of Binary Trees
Array Implementation of Binary Trees

...  After the insertion of a new key k, the heap-order property may be violated  Algorithm upheap restores the heap-order property by swapping k along an upward path from the insertion node  Upheap terminates when the key k reaches the root or a node whose parent has a key smaller than or equal to k ...
COMP171H Notes: Hashing
COMP171H Notes: Hashing

R-TREES.  A DYNAMIC  INDEX  STRUCTURE Antomn  Guttman
R-TREES. A DYNAMIC INDEX STRUCTURE Antomn Guttman

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Some Data Structures
Some Data Structures

... type type treenode2 = record value : information parent : ↑treenode2 • where now each node contains only a single pointer leading to its parent. • This representation is about as economical with storage space, but • it is inefficient unless all the operations on the tree involve starting from a node ...
Planar Point Location Using Persistent Search Trees
Planar Point Location Using Persistent Search Trees

... new method that uses space even more efficiently than path copying. It leads to a data structure for persistent sorted sets (but not persistent lists) that has bounds of O(log m) worst-case time per operation and O(1) amortized space per update. ...
Scalable Classification Algorithms
Scalable Classification Algorithms

... D be the original training db and D’ be the new data to be incorporated Run the same tree construction algorithm If D’ is from the same underlying probabilistic distribution, finally splitting criterion will be captured by the coarse splitting criterion. If D’ is sufficiently different, only that pa ...
Lecture 9 Student Notes
Lecture 9 Student Notes

... First we will show how to construct a data-structure that is capable of performing 2-sided range queries while using only linear space. Using this data-structure, it will be possible to construct data-structures for the 3-sided and 4-sided cases which have the desired space bounds. At a high level, ...
Data Structures for Scenes, The Basics of Scene Graphs
Data Structures for Scenes, The Basics of Scene Graphs

Chapter 5 : Trees
Chapter 5 : Trees

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ppt

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Softwaring in Clojure

hyperoctree
hyperoctree

... sorted data This insures that none of the children of the root node receives more than half the points ...
One-Time Binary Search Tree Balancing - Size
One-Time Binary Search Tree Balancing - Size

Finding The Maximum Density Axes Parallel Regions for Weighted
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Chapter 12 Trees - Margaret M. Fleck
Chapter 12 Trees - Margaret M. Fleck

... Formally, a tree is a undirected graph with a special node called the root, in which every node is connected to the root by exactly one path. When a pair of nodes are neighbors in the graph, the node nearest the root is called the parent and the other node is its child. By convention, trees are draw ...
- Backpack
- Backpack

... is stored at the root, and the sub-trees rooted at a node contain larger (smaller) values than does the node itself. A Min-heap viewed as a binary tree and an array. Heaps can be used as an array. For any element at array position I, left child is at ( 2i ), right child is at ( 2i+1 ) and parent is ...
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Interval tree

In computer science, an interval tree is a tree data structure to hold intervals. Specifically, it allows one to efficiently find all intervals that overlap with any given interval or point. It is often used for windowing queries, for instance, to find all roads on a computerized map inside a rectangular viewport, or to find all visible elements inside a three-dimensional scene. A similar data structure is the segment tree.The trivial solution is to visit each interval and test whether it intersects the given point or interval, which requires O(n) time, where n is the number of intervals in the collection. Since a query may return all intervals, for example if the query is a large interval intersecting all intervals in the collection, this is asymptotically optimal; however, we can do better by considering output-sensitive algorithms, where the runtime is expressed in terms of m, the number of intervals produced by the query. Interval trees have a query time of O(log n + m) and an initial creation time of O(n log n), while limiting memory consumption to O(n). After creation, interval trees may be dynamic, allowing efficient insertion and deletion of an interval in O(log n). If the endpoints of intervals are within a small integer range (e.g., in the range [1,...,O(n)]), faster data structures exist with preprocessing time O(n) and query time O(1+m) for reporting m intervals containing a given query point.
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