Lecture 8 Notes
... across the heap. Either the keys of parent nodes are always greater than or equal to those of the children and the highest key is in the root node (max heap) or the keys of parent nodes are less than or equal to those of the children and the lowest key is in the root node (min heap). Shape property: ...
... across the heap. Either the keys of parent nodes are always greater than or equal to those of the children and the highest key is in the root node (max heap) or the keys of parent nodes are less than or equal to those of the children and the lowest key is in the root node (min heap). Shape property: ...
We define “strongly connected” to mean that for every pair of vertices
... • Our inductive hypothesis would be that MST_edges is a subset of the MST so far. • Our inductive step would be that the next light edge is part of the MST we are trying to build. • We would actually show that if the next light edge were NOT in the MST, then we’d have a contradiction. ...
... • Our inductive hypothesis would be that MST_edges is a subset of the MST so far. • Our inductive step would be that the next light edge is part of the MST we are trying to build. • We would actually show that if the next light edge were NOT in the MST, then we’d have a contradiction. ...
International Journal of Emerging Technologies in Computational
... Definition 1 An uncertain item is an item x ∈ W whose presence in a transaction t ∈ T is defined by an existential probability P (x ∈ t) ∈ (0, 1). A certain item is an item where presence of an item x is either 0 or 1. Definition 2 An uncertain transaction t is a transaction that contains uncertain ...
... Definition 1 An uncertain item is an item x ∈ W whose presence in a transaction t ∈ T is defined by an existential probability P (x ∈ t) ∈ (0, 1). A certain item is an item where presence of an item x is either 0 or 1. Definition 2 An uncertain transaction t is a transaction that contains uncertain ...
Compact combinatorial maps: A volume mesh data structure
... among cells of the mesh using a basic element called dart, and a group of relations between darts. For an orientable 3D manifold, a 3D dart corresponds to a cell tuple (v, e, f, c), where v is a starting vertex of an edge e that lies in a face f of 3-cell c. For 2D orientable surfaces, a 2D dart wou ...
... among cells of the mesh using a basic element called dart, and a group of relations between darts. For an orientable 3D manifold, a 3D dart corresponds to a cell tuple (v, e, f, c), where v is a starting vertex of an edge e that lies in a face f of 3-cell c. For 2D orientable surfaces, a 2D dart wou ...
Path Minima Queries in Dynamic Weighted Trees
... where the input tree is a path. In this problem, we are given an array containing n elements, and we have to find the position of the minimum element within a query range. The following lower bounds are derived from known lower bounds by reduction from the 1D-RMQ problem: (1) In the semigroup model, ...
... where the input tree is a path. In this problem, we are given an array containing n elements, and we have to find the position of the minimum element within a query range. The following lower bounds are derived from known lower bounds by reduction from the 1D-RMQ problem: (1) In the semigroup model, ...
File Structures - School of Computing Science
... The third approach is the network approach associated with the proposals by the Data Base Task Group of CODASYL. Here data items are linked into a network in which any given link between two items exists because it satisfies some condition on the attributes of those items, for example, they share an ...
... The third approach is the network approach associated with the proposals by the Data Base Task Group of CODASYL. Here data items are linked into a network in which any given link between two items exists because it satisfies some condition on the attributes of those items, for example, they share an ...
Bloom Based Filters for Hierachical Data - delab-auth
... • For 2% of the total size of the data, multi-level Bloom filters evaluate path queries for a false positives ratio below 3%, while Simple Blooms fail to recognize the correct paths, no matter how much the filter size increases. • Breadth Blooms work better than Depth Blooms. • Depth Blooms require ...
... • For 2% of the total size of the data, multi-level Bloom filters evaluate path queries for a false positives ratio below 3%, while Simple Blooms fail to recognize the correct paths, no matter how much the filter size increases. • Breadth Blooms work better than Depth Blooms. • Depth Blooms require ...
Lock-Free Data-Structure Iterators
... Unfortunately, existing snapshot algorithms cannot support a (practical) data-structure 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 ten ...
... Unfortunately, existing snapshot algorithms cannot support a (practical) data-structure 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 ten ...
Chapter 17 part 1
... Linked List as an ADT (continued) • The basic operations on linked lists are: (continued) − Retrieve the info contained in the first node − Retrieve the info contained in the last node − Search the list for a given item − Insert an item in the list − Delete an item from the list − Make a copy of th ...
... Linked List as an ADT (continued) • The basic operations on linked lists are: (continued) − Retrieve the info contained in the first node − Retrieve the info contained in the last node − Search the list for a given item − Insert an item in the list − Delete an item from the list − Make a copy of th ...
Quadtree
A quadtree is a tree data structure in which each internal node has exactly four children. Quadtrees are most often used to partition a two-dimensional space by recursively subdividing it into four quadrants or regions. The regions may be square or rectangular, or may have arbitrary shapes. This data structure was named a quadtree by Raphael Finkel and J.L. Bentley in 1974. A similar partitioning is also known as a Q-tree. All forms of quadtrees share some common features: They decompose space into adaptable cells Each cell (or bucket) has a maximum capacity. When maximum capacity is reached, the bucket splits The tree directory follows the spatial decomposition of the quadtree.