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Substring Search
In computer science, string-searching algorithms, sometimes called string-matching algorithms, are an important class of string algorithms that try to find a place where one or several strings (also called patterns) are found within a larger string or text. A basic example of string searching is when the pattern and the searched text are arrays of elements of an alphabet (finite set) Σ. Σ may be a human language alphabet, for example, the letters ''A'' through ''Z'' and other applications may use a ''binary alphabet'' (Σ = ) or a ''DNA alphabet'' (Σ = ) in bioinformatics. In practice, the method of feasible string-search algorithm may be affected by the string encoding. In particular, if a variable-width encoding is in use, then it may be slower to find the ''N''th character, perhaps requiring time proportional to ''N''. This may significantly slow some search algorithms. One of many possible solutions is to search for the sequence of code units instead, but doing so may produ ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Computer Science
Computer science is the study of computation, automation, and information. Computer science spans theoretical disciplines (such as algorithms, theory of computation, information theory, and automation) to Applied science, practical disciplines (including the design and implementation of Computer architecture, hardware and Computer programming, software). Computer science is generally considered an area of research, academic research and distinct from computer programming. Algorithms and data structures are central to computer science. The theory of computation concerns abstract models of computation and general classes of computational problem, problems that can be solved using them. The fields of cryptography and computer security involve studying the means for secure communication and for preventing Vulnerability (computing), security vulnerabilities. Computer graphics (computer science), Computer graphics and computational geometry address the generation of images. Progr ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Powerset Construction
In the theory of computation and automata theory, the powerset construction or subset construction is a standard method for converting a nondeterministic finite automaton (NFA) into a deterministic finite automaton (DFA) which recognizes the same formal language. It is important in theory because it establishes that NFAs, despite their additional flexibility, are unable to recognize any language that cannot be recognized by some DFA. It is also important in practice for converting easier-to-construct NFAs into more efficiently executable DFAs. However, if the NFA has ''n'' states, the resulting DFA may have up to 2''n'' states, an exponentially larger number, which sometimes makes the construction impractical for large NFAs. The construction, sometimes called the Rabin–Scott powerset construction (or subset construction) to distinguish it from similar constructions for other types of automata, was first published by Michael O. Rabin and Dana Scott in 1959. Intuition To simulate t ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Boyer–Moore String-search Algorithm
In computer science, the Boyer–Moore string-search algorithm is an efficient string-searching algorithm that is the standard benchmark for practical string-search literature. It was developed by Robert S. Boyer and J Strother Moore in 1977. The original paper contained static tables for computing the pattern shifts without an explanation of how to produce them. The algorithm for producing the tables was published in a follow-on paper; this paper contained errors which were later corrected by Wojciech Rytter in 1980. The algorithm preprocesses the string being searched for (the pattern), but not the string being searched in (the text). It is thus well-suited for applications in which the pattern is much shorter than the text or where it persists across multiple searches. The Boyer–Moore algorithm uses information gathered during the preprocess step to skip sections of the text, resulting in a lower constant factor than many other string search algorithms. In general, the al ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Rabin–Karp Algorithm
In computer science, the Rabin–Karp algorithm or Karp–Rabin algorithm is a string-searching algorithm created by that uses hashing to find an exact match of a pattern string in a text. It uses a rolling hash to quickly filter out positions of the text that cannot match the pattern, and then checks for a match at the remaining positions. Generalizations of the same idea can be used to find more than one match of a single pattern, or to find matches for more than one pattern. To find a single match of a single pattern, the expected time of the algorithm is linear in the combined length of the pattern and text, although its worst-case time complexity is the product of the two lengths. To find multiple matches, the expected time is linear in the input lengths, plus the combined length of all the matches, which could be greater than linear. In contrast, the Aho–Corasick algorithm can find all matches of multiple patterns in worst-case time and space linear in the input length ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Algorithm
In mathematics and computer science, an algorithm () is a finite sequence of rigorous instructions, typically used to solve a class of specific Computational problem, problems or to perform a computation. Algorithms are used as specifications for performing calculations and data processing. More advanced algorithms can perform automated deductions (referred to as automated reasoning) and use mathematical and logical tests to divert the code execution through various routes (referred to as automated decision-making). Using human characteristics as descriptors of machines in metaphorical ways was already practiced by Alan Turing with terms such as "memory", "search" and "stimulus". In contrast, a Heuristic (computer science), heuristic is an approach to problem solving that may not be fully specified or may not guarantee correct or optimal results, especially in problem domains where there is no well-defined correct or optimal result. As an effective method, an algorithm ca ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Approximate String Matching
In computer science, approximate string matching (often colloquially referred to as fuzzy string searching) is the technique of finding strings that match a pattern approximately (rather than exactly). The problem of approximate string matching is typically divided into two sub-problems: finding approximate substring matches inside a given string and finding dictionary strings that match the pattern approximately. Overview The closeness of a match is measured in terms of the number of primitive operations necessary to convert the string into an exact match. This number is called the edit distance between the string and the pattern. The usual primitive operations are: * insertion: ''cot'' → ''coat'' * deletion: ''coat'' → ''cot'' * substitution: ''coat'' → ''cost'' These three operations may be generalized as forms of substitution by adding a NULL character (here symbolized by *) wherever a character has been deleted or inserted: * insertion: ''co*t'' → ''coat'' * delet ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Trigram Search
Trigram search is a method of searching for text when the exact syntax or spelling of the target object is not precisely known or when queries may be regular expressions. It finds objects which match the maximum number of three consecutive character strings (i.e. trigrams) in the entered search terms, which are generally near matches. Two strings with many shared trigrams can be expected to be very similar. Trigrams also allow for efficiently creating indexes for searches that are regular expressions or match the text inexactly. Indexes can significantly accelerate searches. A threshold for number of trigram matches can be specified as a cutoff point, after which a result is no longer considered a match. Using trigrams for accelerating searches is a technique used in some systems for code searching, in situations in which queries that are regular expressions may be useful, in search engines such as Elasticsearch, as well as in databases such as PostgreSQL.{{Cite web , date=2022-05-1 ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Depth-first Search
Depth-first search (DFS) is an algorithm for traversing or searching tree or graph data structures. The algorithm starts at the root node (selecting some arbitrary node as the root node in the case of a graph) and explores as far as possible along each branch before backtracking. Extra memory, usually a stack, is needed to keep track of the nodes discovered so far along a specified branch which helps in backtracking of the graph. A version of depth-first search was investigated in the 19th century by French mathematician Charles Pierre Trémaux as a strategy for solving mazes. Properties The time and space analysis of DFS differs according to its application area. In theoretical computer science, DFS is typically used to traverse an entire graph, and takes time where , V, is the number of vertices and , E, the number of edges. This is linear in the size of the graph. In these applications it also uses space O(, V, ) in the worst case to store the stack of vertices on th ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Suffix Array
In computer science, a suffix array is a sorted array of all suffixes of a string. It is a data structure used in, among others, full-text indices, data-compression algorithms, and the field of bibliometrics. Suffix arrays were introduced by as a simple, space efficient alternative to suffix trees. They had independently been discovered by Gaston Gonnet in 1987 under the name ''PAT array'' . gave the first in-place \mathcal(n) time suffix array construction algorithm that is optimal both in time and space, where ''in-place'' means that the algorithm only needs \mathcal(1) additional space beyond the input string and the output suffix array. Enhanced suffix arrays (ESAs) are suffix arrays with additional tables that reproduce the full functionality of suffix trees preserving the same time and memory complexity. The suffix array for a subset of all suffixes of a string is called sparse suffix array. Multiple probabilistic algorithms have been developed to minimize the additiona ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Suffix Tree
In computer science, a suffix tree (also called PAT tree or, in an earlier form, position tree) is a compressed trie containing all the suffixes of the given text as their keys and positions in the text as their values. Suffix trees allow particularly fast implementations of many important string operations. The construction of such a tree for the string S takes time and space linear in the length of S. Once constructed, several operations can be performed quickly, for instance locating a substring in S, locating a substring if a certain number of mistakes are allowed, locating matches for a regular expression pattern etc. Suffix trees also provide one of the first linear-time solutions for the longest common substring problem. These speedups come at a cost: storing a string's suffix tree typically requires significantly more space than storing the string itself. History The concept was first introduced by . Rather than the suffix S ..n/math>, Weiner stored in his trie the ''pref ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Substring Index
In computer science, a substring index is a data structure which gives substring search in a text or text collection in sublinear time. If you have a document S of length n, or a set of documents D=\ of total length n, you can locate all occurrences of a pattern P in o(n) time. (See Big O notation.) The phrase full-text index is also often used for an index of all substrings of a text. But is ambiguous, as it is also used for regular word indexes such as inverted files and document retrieval. See full text search. Substring indexes include: * Suffix tree * Suffix array * N-gram index, an inverted file for all N-grams of the text * Compressed suffix arrayR. Grossi and J. S. VitterCompressed Suffix Arrays and Suffix Trees, with Applications to Text Indexing and String Matching ''SIAM Journal on Computing,'' 35(2), 2005, 378-407. * FM-index * LZ-index References {{reflist Algorithms on strings String data structures Database index techniques Substring indices, ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Bitap Algorithm
The bitap algorithm (also known as the shift-or, shift-and or Baeza-Yates–Gonnet algorithm) is an approximate string matching algorithm. The algorithm tells whether a given text contains a substring which is "approximately equal" to a given pattern, where approximate equality is defined in terms of Levenshtein distance if the substring and pattern are within a given distance ''k'' of each other, then the algorithm considers them equal. The algorithm begins by precomputing a set of bitmasks containing one bit for each element of the pattern. Then it is able to do most of the work with bitwise operations, which are extremely fast. The bitap algorithm is perhaps best known as one of the underlying algorithms of the Unix utility agrep, written by Udi Manber, Sun Wu, and Burra Gopal. Manber and Wu's original paper gives extensions of the algorithm to deal with fuzzy matching of general regular expressions. Due to the data structures required by the algorithm, it performs best on pa ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
