An efficient uniform-cost normalized edit distance algorithm

AN Arslan, O Egecioglu - 6th International Symposium on …, 1999 - ieeexplore.ieee.org
AN Arslan, O Egecioglu
6th International Symposium on String Processing and Information …, 1999ieeexplore.ieee.org
A common model for computing the similarity of two strings X and Y of lengths m, and n
respectively with m/spl ges/n, is to transform X into Y through a sequence of three types of
edit operations: insertion, deletion, and substitution. The model assumes a given cost
function which assigns a non-negative real weight to each edit operation. The amortized
weight for a given edit sequence is the ratio of its weight to its length, and the minimum of
this ratio over all edit sequences is the normalized edit distance. Existing algorithms for …
A common model for computing the similarity of two strings X and Y of lengths m, and n respectively with m/spl ges/n, is to transform X into Y through a sequence of three types of edit operations: insertion, deletion, and substitution. The model assumes a given cost function which assigns a non-negative real weight to each edit operation. The amortized weight for a given edit sequence is the ratio of its weight to its length, and the minimum of this ratio over all edit sequences is the normalized edit distance. Existing algorithms for normalized edit distance computation with proven complexity bounds require O(mn/sup 2/) time in the worst-case. We give an O(mn log n)-time algorithm for the problem when the cost function is uniform, i.e., the weight of each edit operation is constant within the same type, except substitutions can have different weights depending on whether they are matching or non-matching.
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