Results 161 to 170 of about 70,442,116 (202)

Bounds on algorithms for string generation

Acta Informatica, 1972
The well-known lower bound of log2 n! on the number of comparisons required to sort n items is extended to cover algorithms, such as replacement selection, which produce a sorted string whose length is a random variable. The case of algorithms which produce several strings is also discussed and these results are then applied to obtain an upper bound on
A. C. McKellar, C. K. Wong
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Parallel String Matching Algorithms

Kybernetes, 1988
The string searching problem is central to many information retrieval and text editing applications. The Brute Force algorithm is inefficient in some cases and in this article four other algorithms are discussed, of which the Boyer‐Moore and the Improved Boyer‐Moore are found to be the fastest.
Evans, D. J., Ghanemi, S.
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A string pattern—matching algorithm

Journal of Systems and Software, 1993
Abstract A string pattern-matching algorithm uses a character string, pattern , to search another character string, text , for the first or all occurrence(s) of the pattern in the text. This article presents a string patternmatching algorithm using a mapping table and an automaton. The number of states of the automaton is equal to the length of the
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A framework to animate string algorithms

Information Processing Letters, 1996
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Ricardo A. Baeza-Yates, Luis O. Fuentes
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Algorithms on Compressed Strings and Arrays

1999
We survey the complexity issues related to several algorithmic problems for compressed one- and two-dimensional texts without explicit decompression: pattern-matching, equality-testing, computation of regularities, subsegment extraction, language membership, and solvability of word equations.
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VECTOR ALGORITHMS FOR APPROXIMATE STRING MATCHING

International Journal of Foundations of Computer Science, 2002
Vector algorithms allow the computation of an output vector r = r1 r2 ⋯ rm given an input vector e = e1 e2 ⋯ em in a bounded number of operations, independent of m the length of the vectors. The allowable operations are usually restricted to bit-wise operations available in processors, including shifts and binary addition with carry.
Anne Bergeron, Sylvie Hamel
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String matching algorithms and automata

1994
In this paper we study the structure of finite automata recognizing sets of the form A*p, for some word p, and use the results obtained to improve the Knuth-Morris-Pratt string searching algorithm. We also determine the average number of nontrivial edges of the above automata.
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On Simon's string searching algorithm

Information Processing Letters, 1993
We give sharp bounds for the problem of string matching when only one head moving from the right to the left of the text is used: \((2-1/m)n\) character comparisons for all the text, and \(\min \{1+ \log_ 2m,\text{Card}(A)\}\) character comparisons on each character of the text, where \(m\) is the length of the pattern, \(n\) the length of the text ...
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PAMA: A FAST STRING MATCHING ALGORITHM

International Journal of Foundations of Computer Science, 2006
String matching is a fundamental operation in computer science, and its performance has great impact on many applications including database query, text processing, DNA and protein sequence analysis. In this paper, we propose a fast string matching algorithm, PAMA (PAttern MAtching). The shift rule used by PAMA not only subsumes both the bad character
Shiyong Lu, Feng Cao, Yi Lu 0015
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Simple Optimal String Matching Algorithm

Journal of Algorithms, 2000
Summary: We present a new string matching algorithm optimal on average (with equiprobability and independence of letters, in \(O(m+ n\log_{|\Sigma|} m/m)\), where \(n\) is the size of the text and \(m\) the size of the searched word, both taken on an alphabet \(\Sigma\)) and linear in the worst case (in \(O(m+ n)\)).
Allauzen, Cyril, Raffinot, Mathieu
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