search algorithm - ορισμός. Τι είναι το search algorithm
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Τι (ποιος) είναι search algorithm - ορισμός

ANY ALGORITHM WHICH SOLVES THE SEARCH PROBLEM, NAMELY, TO RETRIEVE INFORMATION STORED WITHIN SOME DATA STRUCTURE, OR CALCULATED IN THE SEARCH SPACE OF A PROBLEM DOMAIN, EITHER WITH DISCRETE OR CONTINUOUS VALUES
Search algorithms; Search Algorithm; Informed search algorithm; Search Algorithms; Searching algorithms; Uninformed search algorithm; Informed search; Keyword Search Method; Searching algorithm; Array search; Adversarial search; Search ranking algorithm; Ranking Algorithm; Applications of search algorithms; Quantum search algorithm
  • Visual representation of a [[hash table]], a [[data structure]] that allows for fast retrieval of information.

search algorithm         
<theory> Any algorithm for identifying a solution to a problem (a search problem) out of a space of potential solutions by considering several potential solutions until one is found that meets certain criteria. See A* search, beam search, best-first search, breadth-first search, depth-first search. (2007-11-03)
A* search algorithm         
  • The A* algorithm finding a path of railroads between Washington, D.C. and Los Angeles.
  • Illustration of A* search for finding a path between two points on a graph. From left to right, a heuristic that prefers points closer to the goal is used increasingly.
  • An example of A* algorithm in action (nodes are cities connected with roads, h(x) is the straight-line distance to the target point) Green: Start, Blue: Target, Orange: Visited
  • A* pathfinding algorithm navigating around a randomly-generated maze
  • A* was invented by researchers working on Shakey the Robot's path planning.
ALGORITHM USED FOR PATHFINDING AND GRAPH TRAVERSAL
A Star Search Algorithm; A star search algorithm; A-star algorithm; A-star search algorithm; A* algorithm; A* search; A-star; A Star; A star search; TBA*; New Bidirectional A*
A* (pronounced "A-star") is a graph traversal and path search algorithm, which is used in many fields of computer science due to its completeness, optimality, and optimal efficiency. One major practical drawback is its O(b^d) space complexity, as it stores all generated nodes in memory.
Binary search algorithm         
  • Binary search can be adapted to compute approximate matches. In the example above, the rank, predecessor, successor, and nearest neighbor are shown for the target value <math>5</math>, which is not in the array.
  • binary-search
  • The worst case is reached when the search reaches the deepest level of the tree, while the best case is reached when the target value is the middle element.
  • tree]] representing binary search. The array being searched here is <math>[20, 30, 40, 50, 80, 90, 100]</math>, and the target value is <math>40</math>.
  • [[Binary search tree]]s are searched using an algorithm similar to binary search.
  • Visualization of [[exponential search]]ing finding the upper bound for the subsequent binary search
  • In [[fractional cascading]], each array has pointers to every second element of another array, so only one binary search has to be performed to search all the arrays.
  • Visualization of [[interpolation search]] using linear interpolation. In this case, no searching is needed because the estimate of the target's location within the array is correct. Other implementations may specify another function for estimating the target's location.
  • In noisy binary search, there is a certain probability that a comparison is incorrect.
  • [[Uniform binary search]] stores the difference between the current and the two next possible middle elements instead of specific bounds.
SEARCH ALGORITHM IN SORTED LISTS THAT OPERATES BY DECREASING THE SEARCH SPACE BY HALF EACH PASS
Binary chop; Binary search; Bsearch; Binary Search; Half-interval search; Half-interval search method; Half interval search method
In computer science, binary search, also known as half-interval search, logarithmic search, or binary chop, is a search algorithm that finds the position of a target value within a sorted array. Binary search compares the target value to the middle element of the array.

Βικιπαίδεια

Search algorithm

In computer science, a search algorithm is an algorithm designed to solve a search problem. Search algorithms work to retrieve information stored within particular data structure, or calculated in the search space of a problem domain, with either discrete or continuous values.

Although search engines use search algorithms, they belong to the study of information retrieval, not algorithmics.

The appropriate search algorithm often depends on the data structure being searched, and may also include prior knowledge about the data. Search algorithms can be made faster or more efficient by specially constructed database structures, such as search trees, hash maps, and database indexes.

Search algorithms can be classified based on their mechanism of searching into three types of algorithms: linear, binary, and hashing. Linear search algorithms check every record for the one associated with a target key in a linear fashion. Binary, or half-interval, searches repeatedly target the center of the search structure and divide the search space in half. Comparison search algorithms improve on linear searching by successively eliminating records based on comparisons of the keys until the target record is found, and can be applied on data structures with a defined order. Digital search algorithms work based on the properties of digits in data structures by using numerical keys. Finally, hashing directly maps keys to records based on a hash function.

Algorithms are often evaluated by their computational complexity, or maximum theoretical run time. Binary search functions, for example, have a maximum complexity of O(log n), or logarithmic time. In simple terms, the maximum number of operations needed to find the search target is a logarithmic function of the size of the search space.