Efficient string matching with k mismatches
Theoretical Computer Science
Approximate string matching: a simpler faster algorithm
Proceedings of the ninth annual ACM-SIAM symposium on Discrete algorithms
An Extension of the String-to-String Correction Problem
Journal of the ACM (JACM)
Verifying candidate matches in sparse and wildcard matching
STOC '02 Proceedings of the thiry-fourth annual ACM symposium on Theory of computing
Information Processing Letters
Information and Computation
FOCS '97 Proceedings of the 38th Annual Symposium on Foundations of Computer Science
On the complexity of the Extended String-to-String Correction Problem
STOC '75 Proceedings of seventh annual ACM symposium on Theory of computing
Faster algorithms for string matching with k mismatches
Journal of Algorithms - Special issue: SODA 2000
Dictionary matching and indexing with errors and don't cares
STOC '04 Proceedings of the thirty-sixth annual ACM symposium on Theory of computing
Pattern matching with address errors: rearrangement distances
SODA '06 Proceedings of the seventeenth annual ACM-SIAM symposium on Discrete algorithm
Swap and mismatch edit distance
Algorithmica
Linear pattern matching algorithms
SWAT '73 Proceedings of the 14th Annual Symposium on Switching and Automata Theory (swat 1973)
Approximate swap and mismatch edit distance
SPIRE'07 Proceedings of the 14th international conference on String processing and information retrieval
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Finding the similarity between two sequences is a major problem in computer science. It is motivated by many issues from computational biology as well as from information retrieval and image processing. These fields take into account possible corruptions of the data caused by genome rearrangements, typing mistakes, and more. Therefore, many applications do not require merely complete resemblance of the sequences, but rather an approximate matching. We consider mismatches and swaps as natural mistakes which are allowed in a meagre number. The edit distance problem with swap and mismatch operations was solved in O(nmlogm) time. Yet, the problem of string matching with at most k swaps and mismatches errors was open. In this paper, we present an algorithm that finds all locations where the pattern has at most k mismatch and swap errors in time O(nklogm).