Similarity between compressed strings

J. W Kim, A. Amihood, G. M Landau, K Park

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review


Problem Definition The problem of computing similarity between two strings is concerned with comparing two strings using some scoring metric. There exist various scoring metrics and a popular one is the Levenshtein distance (or edit distance) metric. The standard solution for the Levenshtein distance metric was proposed by Wagner and Fischer [13], which is based on dynamic programming. Other widely used scoring metrics are the longest common subsequence metric, the weighted edit distance metric, and the affine gap penalty metric. The affine gap penalty metric is the most general, and it is a quite complicated metric to deal with. Table 1 shows the differences between the four metrics. The problem con ...
Original languageAmerican English
Title of host publicationEncyclopedia of Algorithms
EditorsMing-Yang Kao Professor of Computer Science
PublisherSpringer US
ISBN (Print)978-0-387-30162-4
StatePublished - 2008


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