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System for 3D visualization and data mining of large vascular trees
System for 3D visualization and data mining of large vascular trees

7. Full-Text Indexes in External Memory
7. Full-Text Indexes in External Memory

... The first technique is the Patricia trie [557], which is a close relative of the compact trie. The difference is that, in a Patricia trie, the edge labels contain only the first character (branching character) and the length (skip value) of the corresponding compact trie label. The Patricia trie for th ...
I/O-Efficient Data Structures for Colored Range and Prefix
I/O-Efficient Data Structures for Colored Range and Prefix

6 Access Methods and Query Processing Techniques
6 Access Methods and Query Processing Techniques

... During the past decade, new applications of database technology—with requirements for non-standard data types and novel update and querying capabilities— have emerged that motivate a re-examination of a host of issues related to access methods and query processing techniques. As an example, a range ...
MIT 6.851 Advanced Data Structures
MIT 6.851 Advanced Data Structures

... Slabs that also contain slabs that span either L or R. . . . . . . . . . . . . . . . . . . 77 ...
Linked Lists, Stacks, and Queues
Linked Lists, Stacks, and Queues

... is the only data structure (albeit a simple one) we have so far. In this lecture, we will learn another simple data structure—the linked list—for managing a set. Then, we will utilize a linked list to implement two other slightly more sophisticated structures: the stack and the queue. ...
Chapter 19 - McGraw Hill Higher Education
Chapter 19 - McGraw Hill Higher Education

... Once the data is no longer needed, it should be released back into the heap for later use. This is done using the free function, passing it the same address that was returned by malloc. void free(void*); If allocated data is not freed, the program might run out of heap memory and be unable to contin ...
Linked Lists, stacks and queues
Linked Lists, stacks and queues

... – Some operations on the array have a sub-optimum cost: • Insertions and removals of data in the first position or intermediate positions need data to be moved to consecutive memory positions • Concatenation of arrays: data has to be copied to a new array • Partition of an array in several pieces: d ...
PPT - UNSW
PPT - UNSW

... Bottom-up heap construction is faster than n successive insertions and speeds up the first phase of heap-sort. ...
COMP9024: Data Structures and Algorithms
COMP9024: Data Structures and Algorithms

... Bottom-up heap construction is faster than n successive insertions and speeds up the first phase of heap-sort. ...
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Chap9. Multilevel Indexing and B-Trees
Chap9. Multilevel Indexing and B-Trees

Chapter 19 Java Data Structures
Chapter 19 Java Data Structures

...  If the list is empty, both are null  can create three nodes to store three strings in a list, as follows: ...
Cache-Oblivious B-Trees
Cache-Oblivious B-Trees

... ideal-cache model to analyze the number of memory transfers between each pair of adjacent levels. Because the algorithm is cache-oblivious, it performs well on all levels. See [16] for details. The algorithms in our paper only need a constant number of memory blocks in the cache at once, so any sem ...
The Tree Data Model
The Tree Data Model

... “live” in the memory of the computer. In C, we can create the space for structures for nodes by using the function malloc from the standard library stdlib.h, in which case nodes “float” in memory and are accessible only through pointers. Alternatively, we can create an array of structures and use el ...
Tree: A New Overlay with Deterministic Bounds
Tree: A New Overlay with Deterministic Bounds

... search operations on the structure, divided by the total number of search operations. – Load balancing: it refers to the distribution of data elements on the nodes. The goal of load balancing is to distribute equally the n elements stored in the N nodes of the network (typically N  n). That is, if ...
Keyword Search On Spatial Databases
Keyword Search On Spatial Databases

... We present a method to efficiently answer top-k spatial keyword queries, which is based on the tight integration of data structures and algorithms used in spatial database search and Information Retrieval (IR). In particular, our method consists of building an Information Retrieval R-Tree (IR2Tree), ...
struct node - CSE@IIT Delhi
struct node - CSE@IIT Delhi

... struct node * insert_asc(struct node * r, int value) { struct node *p, *q, *new; new = (struct node *) malloc(sizeof(struct node)); new->data = value; new ->next = NULL; p = r; q = p; while(p!=NULL) { if (p->data >= value) { /* insert before */ if (p==r) { new->next =r; /* insert at start */ return ...
Complete Inverted Files for Efficient Text Retrieval and Analysis
Complete Inverted Files for Efficient Text Retrieval and Analysis

LinkedLists Queues Trees File
LinkedLists Queues Trees File

... – Accessed via a pointer to the first node of the list – Subsequent nodes are accessed via the link-pointer member of the current node – Link pointer in the last node is set to NULL to mark the list’s end ...
U -F union by size link-by-rank
U -F union by size link-by-rank

1 - faraday
1 - faraday

CSci 161
CSci 161

... Arrays, Vectors and ArrayLists allocate space before it is actually needed if a Vector or ArrayList fills up, it will grow this requires allocation of an entirely new contiguous chunk of memory ...
U -F union by size link-by-rank
U -F union by size link-by-rank

Chapter 10: Trees
Chapter 10: Trees

... Note 9. Some books will dene the length of a path as the number of nodes in the path, not the number of edges. This will have an eect on the remaining denitions and the details of many theorems and proofs of these theorems. It is important to know which denition is being used. In these notes, it ...
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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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