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Journal ArticleDOI

Correcting Counter-Automaton-Recognizable Languages

Robert A. Wagner, +1 more
- 01 Aug 1978 - 
- Vol. 7, Iss: 3, pp 357-375
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TLDR
Using a linear-time algorithm for solving single-origin graph shortest distance problems, it is shown how to correct a string of length n into the language accepted by a counter automaton in time proportional to $n^2 $ on a RAM with unit operation cost function.
Abstract
Correction of a string x into a language L is the problem of finding a string $y \in L$ to which x can be edited at least cost. The edit operations considered here are single-character deletions, single-character insertions, and single-character substitutions, each at an independent cost that does not depend on context. Employing a linear-time algorithm for solving single-origin graph shortest distance problems, it is shown how to correct a string of length n into the language accepted by a counter automaton in time proportional to $n^2 $ on a RAM with unit operation cost function. The algorithm is uniform over counter automata and edit cost functions; and it is shown how the correction time depends on the size of the automaton, the nature of the cost function, and the correction cost itself. For less general cases, potentially faster algorithms are described, including a linear-time algorithm for the case that very little correction is necessary and that the automaton’s counter activity is determined by ...

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Citations
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Journal ArticleDOI

Fast text searching: allowing errors

TL;DR: T h e string-matching problem is a very c o m m o n problem; there are many extensions to t h i s problem; for example, it may be looking for a set of patterns, a pattern w i t h "wi ld cards," or a regular expression.
Book ChapterDOI

Algorithms for finding patterns in strings

TL;DR: This chapter discusses the algorithms for solving string-matching problems that have proven useful for text-editing and text-processing applications and several innovative, theoretically interesting algorithms have been devised that run significantly faster than the obvious brute-force method.

An Application of Pattern Matching in Intrusion Detection

TL;DR: A generalized model for matching intrusion signatures based on Colored Petri Nets is presented, and some of its properties are derived.
Book

Ten Lectures on Statistical and Structural Pattern Recognition

TL;DR: This lecture discusses context-free languages, their 2-D generalisation, related tasks, and the relationship of statistical and structural recognition to regular languages and corresponding pattern recognition tasks.
Journal ArticleDOI

Approximate matching of regular expressions

TL;DR: An algorithm to solve the problem in time O(MN), where M and N are the lengths of A and R, and requires only O(N) space to deliver just the score of the best alignment, superior to an earlier algorithm by Wagner and Seiferas.
References
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Journal ArticleDOI

The String-to-String Correction Problem

TL;DR: An algorithm is presented which solves the string-to-string correction problem in time proportional to the product of the lengths of the two strings.
Book

Compiler construction for digital computers

David Gries
TL;DR: The techniques involved in writing compilers for high-level languages such as FORTRAN or PL/1, as well as semantic routines, are described.
Journal ArticleDOI

A Minimum Distance Error-Correcting Parser for Context-Free Languages

TL;DR: An algorithm is presented that will parse any input string to completion finding the fewest possible number of errors on a random access computer.
Journal ArticleDOI

Order-n correction for regular languages

TL;DR: The method presented requires time proportional to the number of characters in α.
Journal ArticleDOI

Syntax-directed least-errors analysis for context-free languages: a practical approach

TL;DR: A least-errors recognizer is developed informally using the well-known recognizer of Earley, along with elements of Bellman's dynamic programming, and takes a general class of context-free grammars as drivers and any finite string as input.