Indexing and Querying XML Data for Regular Path Expressions
... from a chapter element should be followed to find out whether there exists any figure element as a descendant. This step needs to be repeated for all chapter elements in XML database. This implies that it is absolutely necessary to examine every possible path from each chapter elements to all leaf n ...
... from a chapter element should be followed to find out whether there exists any figure element as a descendant. This step needs to be repeated for all chapter elements in XML database. This implies that it is absolutely necessary to examine every possible path from each chapter elements to all leaf n ...
R-trees: Introduction
... The paper entitled “The ubiquitous B-tree” by Comer was published in ACM Computing Surveys in 1979 [49]. Actually, the keyword “B-tree” was standing as a generic term for a whole family of variations, namely the B∗ -tree, the B+ -tree and several other variants [111]. The title of the paper might ha ...
... The paper entitled “The ubiquitous B-tree” by Comer was published in ACM Computing Surveys in 1979 [49]. Actually, the keyword “B-tree” was standing as a generic term for a whole family of variations, namely the B∗ -tree, the B+ -tree and several other variants [111]. The title of the paper might ha ...
24slide - KSU Web Home
... trick is to create a new larger array to replace the current array if the current array cannot hold new elements in the list. Initially, an array, say data of Object[] type, is created with a default size. When inserting a new element into the array, first ensure there is enough room in the array. I ...
... trick is to create a new larger array to replace the current array if the current array cannot hold new elements in the list. Initially, an array, say data of Object[] type, is created with a default size. When inserting a new element into the array, first ensure there is enough room in the array. I ...
Space-Efficient Data Structures for Top-k
... • Lexicographic order → strings starting with given prefix in a contiguous range • If we can find the max in a range, it is top-1 • Range is split in two subranges, can proceed recursively using a priority queue to retrieve top-k ...
... • Lexicographic order → strings starting with given prefix in a contiguous range • If we can find the max in a range, it is top-1 • Range is split in two subranges, can proceed recursively using a priority queue to retrieve top-k ...
11 Data Structures
... start with no nodes and then grow as new nodes are needed. A node can be easily deleted without moving other nodes, as would be the case with an array. For example, a linked list could be used to hold the records of students in a school. Each quarter or semester, new students enroll in the school an ...
... start with no nodes and then grow as new nodes are needed. A node can be easily deleted without moving other nodes, as would be the case with an array. For example, a linked list could be used to hold the records of students in a school. Each quarter or semester, new students enroll in the school an ...
Priority Queues (Heaps)
... extra array for the items exiting the heap. • We can avoid this problem as follows: – After each deleteMin, the heap shrinks by 1. – Thus the cell that was last in the heap can be used to store the element that was just deleted. – Using this strategy, after the last deleteMin, the array will contain ...
... extra array for the items exiting the heap. • We can avoid this problem as follows: – After each deleteMin, the heap shrinks by 1. – Thus the cell that was last in the heap can be used to store the element that was just deleted. – Using this strategy, after the last deleteMin, the array will contain ...
Data Structure and File Processing Chapter 2 Linked Lists
... • Step one: Compare the search item with the current node in the list. If the info of the current node is greater than or equal to the search item, stop the search; otherwise, make the next node the current node • Step two: Repeat Step one until either an item in the list that is greater than or equ ...
... • Step one: Compare the search item with the current node in the list. If the info of the current node is greater than or equal to the search item, stop the search; otherwise, make the next node the current node • Step two: Repeat Step one until either an item in the list that is greater than or equ ...
Fully Persistent B-Trees - Department of Computer Science
... number of updated elements of the ephemeral structure. However, a persistent node of size Θ(B) can correspond to Θ(B) versions of an ephemeral node. In order to find the appropriate version during navigation in the persistent node, as many version-ids must be compared in the version list, using the ...
... number of updated elements of the ephemeral structure. However, a persistent node of size Θ(B) can correspond to Θ(B) versions of an ephemeral node. In order to find the appropriate version during navigation in the persistent node, as many version-ids must be compared in the version list, using the ...
Eindhoven University of Technology MASTER An experimental
... Insertion CPU time - LPR-tree. . . . . . . . . . . . . . . . . . . . . . . . . Insertion CPU time - R∗ tree. . . . . . . . . . . . . . . . . . . . . . . . . . Insertion average CPU time - LP R tree vs. R∗ tree. . . . . . . . . . . . . Insertion I/O's - LP R tree. . . . . . . . . . . . . . . . . . . ...
... Insertion CPU time - LPR-tree. . . . . . . . . . . . . . . . . . . . . . . . . Insertion CPU time - R∗ tree. . . . . . . . . . . . . . . . . . . . . . . . . . Insertion average CPU time - LP R tree vs. R∗ tree. . . . . . . . . . . . . Insertion I/O's - LP R tree. . . . . . . . . . . . . . . . . . . ...
Insert after specified number of nodes
... weaknesses, but they happen to be strong where arrays are weak. The array's features all follow from its strategy of allocating the memory for all its elements in one block of memory. Linked lists use an entirely different strategy. As we will see, linked lists allocate memory for each element separ ...
... weaknesses, but they happen to be strong where arrays are weak. The array's features all follow from its strategy of allocating the memory for all its elements in one block of memory. Linked lists use an entirely different strategy. As we will see, linked lists allocate memory for each element separ ...
Linear-Space Data Structures for Range Frequency Queries on
... to any arbitrary element and fπ0 to τ (an approximate value of fπ ), such that τ − t00 ≤ fπ < τ . Upon terminating the following algorithm, we obtain the exact values of π and fπ as π 0 and fπ0 respectively. Scan the elements in Bm from left to right and let k denote the current index. While k is an ...
... to any arbitrary element and fπ0 to τ (an approximate value of fπ ), such that τ − t00 ≤ fπ < τ . Upon terminating the following algorithm, we obtain the exact values of π and fπ as π 0 and fπ0 respectively. Scan the elements in Bm from left to right and let k denote the current index. While k is an ...
Efficient Similarity Search for Hierarchical Data in Large Databases
... bounding relationship immediately holds for the edit distance ED(t1 , t2 ) of two trees t1 and t2 , too. It should be noticed that the above considerations do not only hold for the edit distance but also for the degree-2 edit distance. Therefore, the following theorem allows us also to use leaf-dist ...
... bounding relationship immediately holds for the edit distance ED(t1 , t2 ) of two trees t1 and t2 , too. It should be noticed that the above considerations do not only hold for the edit distance but also for the degree-2 edit distance. Therefore, the following theorem allows us also to use leaf-dist ...
the lecture notes from the Foundations of Computer Science module
... meaning and can be performed with a finite amount of effort in a finite length of time”. As such, an algorithm must be precise enough to be understood by human beings. However, in order to be executed by a computer, we need a program that is written in a rigorous formal language; and since computers ...
... meaning and can be performed with a finite amount of effort in a finite length of time”. As such, an algorithm must be precise enough to be understood by human beings. However, in order to be executed by a computer, we need a program that is written in a rigorous formal language; and since computers ...
Data Structures and Other Objects Using C++
... Pseudocode for Inserting Nodes Otherwise (if the new node will not be first): then a reference named current must be placed on the list This special node is called the selected node and the new node is inserted right after the selected node. ...
... Pseudocode for Inserting Nodes Otherwise (if the new node will not be first): then a reference named current must be placed on the list This special node is called the selected node and the new node is inserted right after the selected node. ...
A Locality Preserving Cache-Oblivious Dynamic Dictionary
... their update cost increases to O(logB N + B ). Subseqently, Rahman, Cole, and Raman [35] presented and implemented a cache-oblivious dynamic dictionary based on exponential search trees [7, 8, 40] that supports insert and delete in O (logB N + log log N ) memory transfers and supports nger-type res ...
... their update cost increases to O(logB N + B ). Subseqently, Rahman, Cole, and Raman [35] presented and implemented a cache-oblivious dynamic dictionary based on exponential search trees [7, 8, 40] that supports insert and delete in O (logB N + log log N ) memory transfers and supports nger-type res ...
Finger Search Trees - Department of Computer Science
... finger searches in O(log d) time and updates in O(1) time, assuming that only O(1) moveable fingers are maintained. Moving a finger d positions requires O(log d) time. This work was refined by Huddleston and Mehlhorn [28]. Tsakalidis [46] presented a solution based on AVL-trees, and Kosarajo [31] pr ...
... finger searches in O(log d) time and updates in O(1) time, assuming that only O(1) moveable fingers are maintained. Moving a finger d positions requires O(log d) time. This work was refined by Huddleston and Mehlhorn [28]. Tsakalidis [46] presented a solution based on AVL-trees, and Kosarajo [31] pr ...
Logarithmic Lower Bounds in the Cell-Probe Model
... ing tu = tq = ts = O lg(b/δ) . The data structure runs on a Random Access Machine, is deterministic, and achieves worst-case bounds. Our upper bounds can handle a slightly harder version of the problem, where update(i, ∆) has the effect A[i] ← A[i] + ∆. Thus, we are not restricting each A[i] to δ bi ...
... ing tu = tq = ts = O lg(b/δ) . The data structure runs on a Random Access Machine, is deterministic, and achieves worst-case bounds. Our upper bounds can handle a slightly harder version of the problem, where update(i, ∆) has the effect A[i] ← A[i] + ∆. Thus, we are not restricting each A[i] to δ bi ...
singly linked list - KFUPM Resources v3
... if (head == tail && el.equals(head.info)) // if only one head = tail = null; // node on the list; else if (el.equals(head.info)) // if > one node on list; head = head.next; // and el is in the head node; else { // if more than one node in list SLLNode pred, tmp;// and el is in a nonhead node;
for ...
... if (head == tail && el.equals(head.info)) // if only one head = tail = null; // node on the list; else if (el.equals(head.info)) // if > one node on list; head = head.next; // and el is in the head node; else { // if more than one node in list SLLNode