Topic
Edit distance
About: Edit distance is a research topic. Over the lifetime, 2887 publications have been published within this topic receiving 71491 citations.
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IBM1
TL;DR: A Named Entities transliteration mining system using Finite State Automata (FSA) and a baseline system that utilizes the Editex technique to measure the length-normalized phonetic based edit distance between the two words is compared.
Abstract: We propose a Named Entities transliteration mining system using Finite State Automata (FSA). We compare the proposed approach with a baseline system that utilizes the Editex technique to measure the length-normalized phonetic based edit distance between the two words. We submitted three standard runs in NEWS2010 shared task and ranked first for English to Arabic (WM-EnAr) and obtained an F-measure of 0.915, 0.903, and 0.874 respectively.
25 citations
TL;DR: The vertices of the polygons are suggested as the primitives of the attributed strings so that the benefits of split and merge operations are placed in the dynamic programming algorithm for the edit distance evaluation without an extra computation-cost.
25 citations
29 Aug 2005
TL;DR: This paper considers a generalization of sorting by reversals (SBR), k-SBR, and allows each symbol to appear at most k times in each string, for some k≥ 1, and develops a simple O(k2)-approximation algorithm running in time O( k · n).
Abstract: For a string A=a1... an, a reversalρ(i,j), 1≤ i
25 citations
TL;DR: For a string A =a"1...a"n, a reversal@r(i,j), 1==1. The main result of as discussed by the authors is an O(k^2)-approximation algorithm running in time O(n).
25 citations
09 Oct 1994
TL;DR: A modified normalized edit distance is presented that expresses the edit distance between two strings X and Y in a more adequate and intuitive way, reflecting the human decision process during comparisons.
Abstract: In this paper, we discuss the weighted edit distance and two well known normalizations, one based on editing path lengths and one based on the string lengths. We investigate the limitations of these approaches as well as the restrictions on the associated weight function including the triangular inequality. As a solution to the problems pointed out, we present a modified normalized edit distance. The new approach expresses the edit distance between two strings X and Y in a more adequate and intuitive way, reflecting the human decision process during comparisons. A further advantage is that this new distance measure is efficiently computable in O(|X|/spl times/|Y|) instead of O(|X|/spl times/|Y|/spl times/min (|X|,|Y|)) for the other normalizations.
25 citations