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Uniquely represented data structures for computational geometry
Uniquely represented data structures for computational geometry

Clustering-Based Similarity Search in Metric Spaces with Sparse
Clustering-Based Similarity Search in Metric Spaces with Sparse

... Something that most of the algorithms we have mentioned have in common is that both pivots and cluster centers are usually selected at random. However, it is evident that the specific set of selected reference objects has a strong influence in the efficiency of the search. The number of objects, the ...
cp unit 5
cp unit 5

... sequence. Under the simplest form, each node is composed of a datum and a reference (in other words, a link) to the next node in the sequence; more complex variants add additional links. This structure allows for efficient insertion or removal of elements from any position in the sequence. The princ ...
Fast mining frequent itemsets using Nodesets
Fast mining frequent itemsets using Nodesets

Lock-Free Data-Structure Iterators
Lock-Free Data-Structure Iterators

... iterator. Three problems hinder such use. First, atomic snapshot objects are designed for pre-allocated and well-defined memory registers. Therefore, they are not applicable to concurrent data structures that tend to grow and shrink when nodes are added or removed. Second, the UPDATE operation in th ...
Abstract Efficient Data Structures for Tamper-Evident Logging
Abstract Efficient Data Structures for Tamper-Evident Logging

linked lists in python - KSU Web Home
linked lists in python - KSU Web Home

... items, each of which is stored in a node. Each node in a stack includes a data block and one or more links. A stack has only one end: the top of the stack. The main characteristics of a stack are: • Nodes can only be inserted at the top of the stack (TOS) • Nodes can only be removed from the top of ...
The amortized cost of finding the minimum
The amortized cost of finding the minimum

... (expected) cost of insert and delete operations is at most t, then the worst-case (expected) cost of find-min is Ω(n/22t ). We build on the approach of Brodal et al. [5] and resolve the more natural amortized version of the problem. More specifically, we show that if the amortized (expected) cost o ...
kd Range Search with Binary Patricia Tries
kd Range Search with Binary Patricia Tries

Document
Document

AN OVERVIEW OF QUADTREES, OCTREES, AND RELATED
AN OVERVIEW OF QUADTREES, OCTREES, AND RELATED

... The term quadtree is used to describe a class of hierarchical data structures whose common property is that they are based on the principle of recursive decomposition of space. They can be differentiated on the following bases: (1) the type of data that they represent, (2) the principle guiding the ...
Suffix Trees on Words
Suffix Trees on Words

... ancestor of the two nodes should be inserted, if it is not already there. This is done by searching up the tree from the last inserted word until reaching a node that has smaller height within the word trie. 4. If necessary, insert the internal (lowest common ancestor) node, and insert the leaf node ...
The HV-tree: a Memory Hierarchy Aware Version Index
The HV-tree: a Memory Hierarchy Aware Version Index

Dynamic point-region quadtrees for particle simulations
Dynamic point-region quadtrees for particle simulations

... The pseudo-code of the refine procedure called within the step method is given in Algorithm 3. The refine procedure continuously refines the nodes until the maximum refinement level is reached or no node containing more than one point is left. The refine procedure may trigger a coarsening process if the ...
Design, Implementation and Evaluation of Efficient Data
Design, Implementation and Evaluation of Efficient Data

... sets are the most crucial factor that affects the performance of a computer based system. During the past decade or so, most systems have begun to provide a standard set of high performance data structures either as system libraries or via direct support in the programming languages. Some legacy sys ...
Threaded Trees Institute of Lifelong Learning, University of Delhi
Threaded Trees Institute of Lifelong Learning, University of Delhi

... You must have got a taste of all these well known and well used traversal methods in the previous chapters. Breadth first uses queue data structure and Depth first traversals use stacks heavily either implicitly in recursive implementation or explicitly in iterative implementation. Depth first trave ...
notes
notes

lec2
lec2

... – Except for the root, all nodes have degree between 1/4b and b – Root has degree between 2 and b • B-tree with leaf parameter k  (B) – O(N/B) space – Height O(log b NB ) – O( 1 k ) amortized leaf rebalance operations – O( b1k log b NB ) amortized internal node rebalance operations • B-tree with ...
NewUnit2Lists
NewUnit2Lists

... The above implementations are not synchronized. It requires external mechanisms for synchronizing access by multiple threads to the same list. Unit2: ADT Lists ...
The SprayList: A Scalable Relaxed Priority Queue
The SprayList: A Scalable Relaxed Priority Queue

... Our solution is to have the DeleteMin operations traverse the SkipList, not along the list, but via a tightly controlled random walk from its head. We call this operation a spray. Roughly, at each SkipList level, a thread flips a random coin to decide how many nodes to skip ahead at that level. In e ...
Implementing a Simulated Directed Acyclic Word Graph for
Implementing a Simulated Directed Acyclic Word Graph for

QSplat: A Multiresolution Point Rendering System for Large Meshes Szymon Rusinkiewicz
QSplat: A Multiresolution Point Rendering System for Large Meshes Szymon Rusinkiewicz

The Rainbow Skip Graph: A Fault-Tolerant Constant
The Rainbow Skip Graph: A Fault-Tolerant Constant

Wait-Free Linked-Lists
Wait-Free Linked-Lists

... that node has been inserted, success is reported. While the above description outlines the general process of inserting a node, the actual algorithm is a lot more complex, and requires care to avoid problematic races that can make things go wrong. In addition, there is also a potential ABA problem t ...
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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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