1997
DOI: 10.1016/s0031-3203(96)00101-x
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Pattern recognition of strings with substitutions, insertions, deletions and generalized transpositions

Abstract: We study the problem of recognizing a string Y which is the noisy version of some unknown string X * chosen from a finite dictionary, H. The traditional case which has been extensively studied in the literature is the one in which Y contains substitution, insertion and deletion (SID) errors. Although some work has been done to extend the traditional set of edit operations to include the straightforward transposition of adjacent characters 2[14] the problem is unsolved when the transposed characters are themsel… Show more

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Cited by 35 publications
(17 citation statements)
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“…The algorithm is given in Algorithm 2. [11] Algorithm 2 Optimal string alignment distance Input: Strings s1, s2 with |s1| = m and |s2| = n; insertion/deletion cost cost id , substitution cost cost sub , transposition cost costtrans Output: OSAD of s1 and s2 1: Initialize matrix M of dimensions m by n, with: 2:…”
Section: Appendixmentioning
confidence: 99%
“…The algorithm is given in Algorithm 2. [11] Algorithm 2 Optimal string alignment distance Input: Strings s1, s2 with |s1| = m and |s2| = n; insertion/deletion cost cost id , substitution cost cost sub , transposition cost costtrans Output: OSAD of s1 and s2 1: Initialize matrix M of dimensions m by n, with: 2:…”
Section: Appendixmentioning
confidence: 99%
“…By the term "edit distance between two strings of characters", we mean the minimum number of operations such as replace, delete, insert, transpose that are required to transform one string into another string [1], [2], [4], [5], [6], [8]. Levenshtein distance is one such edit distance which measures the distance between two strings of characters.…”
Section: Matching Strategymentioning
confidence: 99%
“…The edit distance ed( ) between two strings is defined as the minimum number of character insertions, deletions and substitutions needed to convert one to another. The problem of approximate string matching [11] is typically divided into two sub-problems first one is, finding approximate sub string matches inside a given string and second one is finding dictionary strings that match the pattern approximately [12]. We are dealing with the second type of the approximate string matching problem.…”
Section: Approximate String Matchingmentioning
confidence: 99%