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AVL Trees Extra - Classes
AVL Trees Extra - Classes

Lists
Lists

Program Outcomes
Program Outcomes

... 5. List out few of the applications of tree data-structure? 6. List out few of the applications that make use of Multilinked Structures? 7. What is the bucket size, when the overlapping and collision occur at same time? 8. What are the Collision Resolution Techniques and the methods used in each of ...
PLSD210(ii) - University of Michigan
PLSD210(ii) - University of Michigan

CPS120: Introduction to Computer Science
CPS120: Introduction to Computer Science

DFS-Assignment_List-2013
DFS-Assignment_List-2013

... 2. What are the properties of Binary Tree? OR Define Binary Tree and write its properties. OR Explain any 2 properties of Binary tree. 3. Write recursive algorithm for inorder and postorder traversal. OR Explain inorder, postorder and preorder traversal of binary tree with example. 4. Write an algor ...
Heaps and Greedy Algorithms
Heaps and Greedy Algorithms

i, j - eLisa UGM
i, j - eLisa UGM

... Complex ADTs Although several simple ADTs, such as integer, real, character, pointer and so on, have been implemented and are available for use in most languages, many useful complex ADTs are not. As we will see in this chapter, we need a list ADT, a stack ADT, a queue ADT and so on. To be efficien ...
Efficient Substructure Discovery from Large Semi
Efficient Substructure Discovery from Large Semi

Chapter 9
Chapter 9

ch3-linked list
ch3-linked list

... precede the coding process for a project. Then, in the later stage, the implementation may start with specific data structure.  First, specify each task in terms of inputs and outputs.  Be concerned with what the program should do. For example, if an item is needed to accomplish some tasks, the it ...
CS 130 A: Data Structures and Algorithms
CS 130 A: Data Structures and Algorithms

A Contention-Friendly Binary Search Tree
A Contention-Friendly Binary Search Tree

... contention and speed up concurrent operations that access (or modify) the abstraction. More specifically, we propose a partially internal binary search tree data structure implementing a key-value store, decoupling the operations that modify the abstraction (we call these abstract operations) from o ...
Basic Data Structures
Basic Data Structures

... • Implemented using a heap, underneath • When want priority without having to enter/sort • Good when new stuff will come in over time, rather than all read at beginning ...
PPT
PPT

... BST Operations: Delete ● Why will case 2 always go to case 0 or case 1? ● A: because when x has 2 children, its ...
Document
Document

...  Redistribute Its siblings node (a child of the same parent node) can transfer one of its keys to the current node.  Concatenate Its siblings does not have an extra key to share. In that case both these nodes are merged into a single node (together with a key from a parent) and pointers updated ac ...
Heaviest Induced Ancestors and Longest Common Substrings
Heaviest Induced Ancestors and Longest Common Substrings

... space. Since these data structures are over sampled skyline lists, querying them indicates only which (log n)length block in a complete extended list contain the pair that would be returned by a query on a corresponding complete skyline list. We can recover any (log n)-length block of a complete ext ...
Improving the Performance of Data Cube Queries Using Families of
Improving the Performance of Data Cube Queries Using Families of

... about CubiST and how it can be integrated with relational warehouse systems are provided in [6]. The original CubiST provides a useful framework for answering cube queries. However, CubiST does NOT efficiently answer queries on data cubes containing hierarchies on the dimensional values. In those ca ...
A Survey of Hierarchical Partitioning Methods for Vector Images
A Survey of Hierarchical Partitioning Methods for Vector Images

... Irregularly shaped spatial objects in two or more dimensions, stored in uni-dimensional computer file address space, pose special problems in retrieval. The tesselated data model skirts the problem by viewing objects as part of a universal phenomenon, varying only in degree, and imposing regular, re ...
Data Structures Lecture 1
Data Structures Lecture 1

... Array Lists, Linked Lists, and Doubly Linked Lists ...
Binary Trees
Binary Trees

... - if in list, for a uniform distribution of keys, average search time is N/2 - if not in list, it is N o sorted: average search time is N/2 if found, N/2 if not found (the win!) o we ignore issue of duplicates ...
data structure
data structure

... next to be served. Thus queues release their elements in order of arrival. Accountants have used queues since long before the existence of computers. They call a queue a” FIFO” list. Which stands for “First- In, first-out. “ this section presents two implementations for queues : the array based queu ...
File - University of Limerick
File - University of Limerick

... we do a partitioning, we must insert the partitioning arc and the subfigures such that a further data point will find the correct subfigure. What is distinctive about this insertion is the way we insert figures into the tree before any of the points within them. This paper continues a work written u ...
Syntactic realization with data
Syntactic realization with data

Fnu Pooja
Fnu Pooja

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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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