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Recent Advances in Text-to-Pattern Distance Algorithms
[chapter]

2020
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Lecture Notes in Computer Science
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Computing text-to-pattern distances is a fundamental problem in pattern matching. Given a text of length n and a pattern of length m, we are asked to output the distance between the pattern and every n-substring of the text. A basic variant of this problem is computation of Hamming distances, that is counting the number of mismatches (different characters aligned), for each alignment. Other popular variants include 1 distance (Manhattan distance), 2 distance (Euclidean distance) and general p

doi:10.1007/978-3-030-51466-2_32
fatcat:67g3nam6o5elfc6xeup7mqw7fi