Efficient algorithms for the scaled indexing problem
Journal of Algorithms
q-Gram Matching Using Tree Models
IEEE Transactions on Knowledge and Data Engineering
Optimal spaced seeds for faster approximate string matching
Journal of Computer and System Sciences
Improved approximate string matching and regular expression matching on Ziv-Lempel compressed texts
ACM Transactions on Algorithms (TALG)
Blocked pattern matching problem and its applications in proteomics
RECOMB'11 Proceedings of the 15th Annual international conference on Research in computational molecular biology
Finding the position of the k-mismatch and approximate tandem repeats
SWAT'06 Proceedings of the 10th Scandinavian conference on Algorithm Theory
Random access to grammar-compressed strings
Proceedings of the twenty-second annual ACM-SIAM symposium on Discrete Algorithms
Faster approximate pattern matching in compressed repetitive texts
ISAAC'11 Proceedings of the 22nd international conference on Algorithms and Computation
Fast and cache-oblivious dynamic programming with local dependencies
LATA'12 Proceedings of the 6th international conference on Language and Automata Theory and Applications
Time-Space trade-offs for longest common extensions
CPM'12 Proceedings of the 23rd Annual conference on Combinatorial Pattern Matching
Improved approximate string matching and regular expression matching on Ziv-Lempel compressed texts
CPM'07 Proceedings of the 18th annual conference on Combinatorial Pattern Matching
Time-space trade-offs for longest common extensions
Journal of Discrete Algorithms
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We give two algorithms for finding all approximate matches of a pattern in a text, where the edit distance between the pattern and the matching text substring is at most k. The first algorithm, which is quite simple, runs in time $O(\frac{nk^3}{m}+n+m)$ on all patterns except k-break periodic strings (defined later). The second algorithm runs in time $O(\frac{nk^4}{m}+n+m)$ on k-break periodic patterns. The two classes of patterns are easily distinguished in O(m)time.