Efficient representation of integer sets
... An AVL tree (or height-balanced tree) [Knu98] is a self-balancing binary search tree. The balance factor of a node is the difference between the height of its subtrees. An AVL tree is considered balanced if every node has a balance factor of, at most, one. A node with any other balance factor is con ...
... An AVL tree (or height-balanced tree) [Knu98] is a self-balancing binary search tree. The balance factor of a node is the difference between the height of its subtrees. An AVL tree is considered balanced if every node has a balance factor of, at most, one. A node with any other balance factor is con ...
Linked Lists (Chapter 6)
... • To enhance greater flexibility of movement, the linked representation could include two links in every node, each of which points to the nodes on either side of the given node • Such a linked representation known as doubly linked list • Each node has one or more data fields but only two link field ...
... • To enhance greater flexibility of movement, the linked representation could include two links in every node, each of which points to the nodes on either side of the given node • Such a linked representation known as doubly linked list • Each node has one or more data fields but only two link field ...
Lecture 21
... • Pick an edge e1 = (u, v) in that tree that’s not in Kruskal’s. • Consider the point in Kruskal’s algorithm where u’s set and v’s set were about to be connected. Kruskal selected some edge to connect them: call it e2 . • But, e2 must have at most the same cost as e1 (otherwise Kruskal would have se ...
... • Pick an edge e1 = (u, v) in that tree that’s not in Kruskal’s. • Consider the point in Kruskal’s algorithm where u’s set and v’s set were about to be connected. Kruskal selected some edge to connect them: call it e2 . • But, e2 must have at most the same cost as e1 (otherwise Kruskal would have se ...
assignment no:10
... sorted in ascending/ Descending order, Also find how many maximum comparisons may require for finding any keyword. Make use of appropriate data structures. AIM:To get a Dictionary that stores keywords & its meanings, provide facility for adding new keywords, deleting keywords, & updating values of a ...
... sorted in ascending/ Descending order, Also find how many maximum comparisons may require for finding any keyword. Make use of appropriate data structures. AIM:To get a Dictionary that stores keywords & its meanings, provide facility for adding new keywords, deleting keywords, & updating values of a ...
List of Practicals - Guru Tegh Bahadur Institute of Technology
... each node of the linked list should store information about the lab with name of the lab and number of computers in that lab. Separate functions should be designed to insert and display information in the queue. Trees 24. Create a Binary Tree (Display using Graphics) perform Tree traversals (Preorde ...
... each node of the linked list should store information about the lab with name of the lab and number of computers in that lab. Separate functions should be designed to insert and display information in the queue. Trees 24. Create a Binary Tree (Display using Graphics) perform Tree traversals (Preorde ...
Dr-Margush-06-07_LinkedLists
... of the collection • A linked list uses Nodes with a data value and one or more links (references) to other Nodes ...
... of the collection • A linked list uses Nodes with a data value and one or more links (references) to other Nodes ...
Talk - CSE, IIT Bombay
... 1. First compute a result list for each query group 2. Add virtual links for join conditions 3. Compute the compactness of a subset of all potential answers of the query in order to return the top-k results 1. Compute a list of results for each of query keywords and concept-value ...
... 1. First compute a result list for each query group 2. Add virtual links for join conditions 3. Compute the compactness of a subset of all potential answers of the query in order to return the top-k results 1. Compute a list of results for each of query keywords and concept-value ...
the lecture notes from the Foundations of Computer Science module
... numerous data structures ranging from familiar arrays and lists to complex types of trees, heaps and graphs, and we will see how their choice affects the efficiency of the algorithms based upon them. Often we want to talk about data strictures without having to worry about all the implementational d ...
... numerous data structures ranging from familiar arrays and lists to complex types of trees, heaps and graphs, and we will see how their choice affects the efficiency of the algorithms based upon them. Often we want to talk about data strictures without having to worry about all the implementational d ...
Dual-Sorted Inverted Lists *
... weights, these techniques can still be adapted, by considering that most documents in a list have small weight values, and within the same weight one can still sort the documents by increasing identifier. A problem with the current state of the art is that a serious IR system must support both types ...
... weights, these techniques can still be adapted, by considering that most documents in a list have small weight values, and within the same weight one can still sort the documents by increasing identifier. A problem with the current state of the art is that a serious IR system must support both types ...
Binary Search Trees
... • The algorithm chooses the key in the middle of A[0:n1], which is located at A[Middle], where Middle=(0+(n-1))/2, and compares the search key K and A[Middle]. • If K==A[Middle], the search terminates successfully. • If K < A[Middle] then further search is conducted among the keys to the left of A[M ...
... • The algorithm chooses the key in the middle of A[0:n1], which is located at A[Middle], where Middle=(0+(n-1))/2, and compares the search key K and A[Middle]. • If K==A[Middle], the search terminates successfully. • If K < A[Middle] then further search is conducted among the keys to the left of A[M ...
Lecture 3: Index Representation and Tolerant Retrieval Overview IR
... At query time: hash query term, locate entry in fixed-width array ...
... At query time: hash query term, locate entry in fixed-width array ...
insertFront - WSU EECS - Washington State University
... Other Considerations for Data Structures? (1) ...
... Other Considerations for Data Structures? (1) ...
Binary search tree
In computer science, binary search trees (BST), sometimes called ordered or sorted binary trees, are a particular type of containers: data structures that store ""items"" (such as numbers, names and etc.) in memory. They allow fast lookup, addition and removal of items, and can be used to implement either dynamic sets of items, or lookup tables that allow finding an item by its key (e.g., finding the phone number of a person by name).Binary search trees keep their keys in sorted order, so that lookup and other operations can use the principle of binary search: when looking for a key in a tree (or a place to insert a new key), they traverse the tree from root to leaf, making comparisons to keys stored in the nodes of the tree and deciding, based on the comparison, to continue searching in the left or right subtrees. On average, this means that each comparison allows the operations to skip about half of the tree, so that each lookup, insertion or deletion takes time proportional to the logarithm of the number of items stored in the tree. This is much better than the linear time required to find items by key in an (unsorted) array, but slower than the corresponding operations on hash tables.They are a special case of the more general B-tree with order equal to two.