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What is Search Algorithm mean?
In computer science, a search algorithm is an algorithm (typically involving a multitude of other, more specific algorithms ) which solves a search problem. Search algorithms work to retrieve information stored within some data structure, or calculated in the search space of a problem domain, either with discrete or continuous values.
While the search problems described above and web search are both problems in information retrieval, they are generally studied as separate subfields and are solved and evaluated differently. Web search problems are generally focused on filtering and finding documents that are most relevant to human queries. Classic search algorithms are typically evaluated on how fast they can find a solution, and whether that solution is guaranteed to be optimal. Though information retrieval algorithms must be fast, the quality of ranking, and whether good results have been left out and bad results included, is more important.
The appropriate search algorithm often depends on the data structure being searched, and may also include prior knowledge about the data. Some database structures are specially constructed to make search algorithms faster or more efficient, such as a search tree, hash map, or a database index.
Search algorithms can be classified based on their mechanism of searching into 3 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 that use 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. This means that the maximum number of operations needed to find the search target is a logarithmic function of the size of the search space.
referencePosted on 19 Dec 2024, this text provides information on Miscellaneous in Softwares related to Softwares. Please note that while accuracy is prioritized, the data presented might not be entirely correct or up-to-date. This information is offered for general knowledge and informational purposes only, and should not be considered as a substitute for professional advice.
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