Introducing efficient parallelism into approximate string matching and a new serial algorithm
STOC '86 Proceedings of the eighteenth annual ACM symposium on Theory of computing
Algorithms on strings, trees, and sequences: computer science and computational biology
Algorithms on strings, trees, and sequences: computer science and computational biology
A Linear-Time Algorithm for Computing Characteristic Strings
ISAAC '94 Proceedings of the 5th International Symposium on Algorithms and Computation
Polynomial-Time Algorithms for Computing Characteristic Strings
CPM '94 Proceedings of the 5th Annual Symposium on Combinatorial Pattern Matching
CPM '97 Proceedings of the 8th Annual Symposium on Combinatorial Pattern Matching
Fast distance multiplication of unit-Monge matrices
SODA '10 Proceedings of the twenty-first annual ACM-SIAM symposium on Discrete Algorithms
An Almost Quadratic Time Algorithm for Sparse Spliced Alignment
Theory of Computing Systems
Note: A fast algorithm for multiplying min-sum permutations
Discrete Applied Mathematics
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Given two strings S and T, together with an integer representing the similarity bound, the characteristic string problem consists in finding the shortest substrings of T such that S has no substrings similar to them, in the sense that one string is similar to another if the amount of ‘dissimilarities' between them is less than or equal to the similarity bound. Under the similarity criterion that uses Levenshtain distance to measure the amount of dissimilarities between two strings, this problem is known to be solvable in cubic time and linear space. The present article proposes a new algorithm for this problem that performs in almost quadratic time and almost linear space, under a certain class of similarity criteria, including the similarity criterion based on Levenshtain distance.