Database 2 -- Lecture II - Faculty of Computer Science
... Expensive maintenance of the physical records storage to maintain the sorted order. – Technique used for insertion based on Overflow Blocks. 1. If there is space in the block insert the new record there in the right place; 2. Otherwise, insert the new record in an Overflow Blocks. In order to mainta ...
... Expensive maintenance of the physical records storage to maintain the sorted order. – Technique used for insertion based on Overflow Blocks. 1. If there is space in the block insert the new record there in the right place; 2. Otherwise, insert the new record in an Overflow Blocks. In order to mainta ...
Heaviest Induced Ancestors and Longest Common Substrings
... In their paper “Range Searching over Tree Cross Products”, Buchsbaum, Goodrich and Westbrook [4] considered how, given a forest of trees T1 , . . . , Td and a subset E of the cross product of the trees’ node sets, we can preprocess the trees such that later, given a d-tuple u consisting of one node ...
... In their paper “Range Searching over Tree Cross Products”, Buchsbaum, Goodrich and Westbrook [4] considered how, given a forest of trees T1 , . . . , Td and a subset E of the cross product of the trees’ node sets, we can preprocess the trees such that later, given a d-tuple u consisting of one node ...
10-queues-priority
... Node: comparison drawn as a circle Leaf: rectangle representing final node ordering Root node: top node in the figure Branch: straight line connecting two nodes Path: sequence of branches between nodes ...
... Node: comparison drawn as a circle Leaf: rectangle representing final node ordering Root node: top node in the figure Branch: straight line connecting two nodes Path: sequence of branches between nodes ...
Prime Box Parallel Search Algorithm
... was related to Trie structure. In Trie structure each node of the trie tree is an array, such that one character from each string is stored in an array at each level. A trie tree is presented in Figure 1 for the strings “ace”, “fade”, “face” and “fact”. Here each node is represented by an array at d ...
... was related to Trie structure. In Trie structure each node of the trie tree is an array, such that one character from each string is stored in an array at each level. A trie tree is presented in Figure 1 for the strings “ace”, “fade”, “face” and “fact”. Here each node is represented by an array at d ...
linked lists in python - KSU Web Home
... A queue is a dynamical data structure that stores a collection of data items or nodes and that has two ends: the head and the tail. The basic restrictions on manipulating a queue are: • Nodes or data items are inserted at the tail of the queue • Nodes or data items are removed from the head of the q ...
... A queue is a dynamical data structure that stores a collection of data items or nodes and that has two ends: the head and the tail. The basic restrictions on manipulating a queue are: • Nodes or data items are inserted at the tail of the queue • Nodes or data items are removed from the head of the q ...
Document
... Priority Queues (Revisited) (cont’d.) • Remove an element from the priority queue – Assume priority queue implemented as a heap • Copy last element of the list into first array position • Reduce list length by one • Restore heap in the list ...
... Priority Queues (Revisited) (cont’d.) • Remove an element from the priority queue – Assume priority queue implemented as a heap • Copy last element of the list into first array position • Reduce list length by one • Restore heap in the list ...
Web Page Cleaning for Web Mining through Feature Weighting
... blocks; and (2) the system knows a priori which blocks are the same blocks in different Web pages. As we will see, partitioning a Web page and identifying corresponding blocks in different pages are actually two critical problems in Web page cleaning. Our system is able to perform these tasks automa ...
... blocks; and (2) the system knows a priori which blocks are the same blocks in different Web pages. As we will see, partitioning a Web page and identifying corresponding blocks in different pages are actually two critical problems in Web page cleaning. Our system is able to perform these tasks automa ...
Double-Ended Priority Queues
... FIGURE 8.10: Interval heap of Figure 8.8 after one node is added. ...
... FIGURE 8.10: Interval heap of Figure 8.8 after one node is added. ...
Linked lists, skip lists
... When you delete a node, it has ½ chance of being level 2, ¼ chance of being level 4, etc., so you don't break the probabilistic behaviour The probability distribution of levels is the same before and after ...
... When you delete a node, it has ½ chance of being level 2, ¼ chance of being level 4, etc., so you don't break the probabilistic behaviour The probability distribution of levels is the same before and after ...
Randomized partition trees for nearest neighbor search
... defeatist search takes time just O(no + log(n/no )), which is O(log n) for constant no . The problem is that q’s nearest neighbor may well lie in a different cell, for instance when the data happen to be concentrated near cell boundaries. Consequently, the failure probability of this scheme can be u ...
... defeatist search takes time just O(no + log(n/no )), which is O(log n) for constant no . The problem is that q’s nearest neighbor may well lie in a different cell, for instance when the data happen to be concentrated near cell boundaries. Consequently, the failure probability of this scheme can be u ...
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.