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An effective algorithm for string correction using generalized edit distances  I. Description of the . . .
, 1981
"... This paper deals with the problem of estimating a transmitted string X, from the corresponding received string Y, which is a noisy version of X,. We assume that Y contains*any number of substitution, insertion, and deletion errors, and that no two consecutive symbols of X, were deleted in transmissi ..."
Abstract

Cited by 19 (11 self)
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This paper deals with the problem of estimating a transmitted string X, from the corresponding received string Y, which is a noisy version of X,. We assume that Y contains*any number of substitution, insertion, and deletion errors, and that no two consecutive symbols of X, were deleted in transmission. We have shown that for channels which cause independent errors, and whose error probabilities exceed those of noisy strings studied in the literature [ 121, at least 99.5 % of the erroneous strings will not contain two consecutive deletion errors. The best estimate X * of X, is defined as that element of H which minimizes the generalized Levenshtein distance D ( X/Y) between X and Y. Using dynamic programming principles, an algorithm is presented which yields X+ without computing individually the distances between every word of H and Y. Though this algorithm requires more memory, it can be shown that it is, in general, computationally less complex than all other existing algorithms which perform the same task.
An Effective Algorithm for String Cowection Using Generaliied Edit Distances II. Computational Complexity of the Algorithm and Some Applications*
"... This paper deals with the problem of estimating an unknown transmitted string X, belonging to a finite dictionary H from its observable noisy version Y. In the first part of this paper [IS] we have developed an algorithm, referred to as ~go~t ~ I, to find the string Xi fH which minimizes the general ..."
Abstract
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This paper deals with the problem of estimating an unknown transmitted string X, belonging to a finite dictionary H from its observable noisy version Y. In the first part of this paper [IS] we have developed an algorithm, referred to as ~go~t ~ I, to find the string Xi fH which minimizes the generalized Levenshtein distance D ( X,/Y). In this part of the paper we study the computations complexity of Algorithm I, and illustrate qu~titatively the advantage Algorithm I has over the standard technique and other algorithms. Its superiority has been shown for various dictionaries, including the one consisting of the 102 1 most common English words of length greater than unity [23]. A comparison between Algorithm I and other algorithms used to correct misspelled words of a regular language is also made here. Some applications of Algorithm I are also discussed. I.