Results 241 to 250 of about 148,669 (285)

A New String Matching Algorithm

International Journal of Computer Mathematics, 2003
In this paper a new exact string-matching algorithm with sub-linear average case complexity has been presented. Unlike other sub-linear string-matching algorithms it never performs more than n text character comparisons while working on a text of length n. It requires only O(mþs) extra pre-processing time and space, where m is the length of the pattern
Mustaq Ahmed, M. Kaykobad, Rezaul Alam Chowdhury   +2 more
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Generic Algorithms for Factoring Strings

2013
In this paper we describe algorithms for factoring words over sets of strings known as circ-UMFFs, generalizations of the well-known Lyndon words based on lexorder, whose properties were first studied in 1958 by Chen, Fox and Lyndon. In 1983 Duval designed an elegant linear-time sequential (RAM) Lyndon factorization algorithm; a corresponding parallel (
David E. Daykin, Jacqueline W. Daykin, Costas S. Iliopoulos, W. F. Smyth   +3 more
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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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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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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 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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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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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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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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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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