A comparison of approximate string matching algorithms
Software—Practice & Experience
Efficient text fingerprinting via Parikh mapping
Journal of Discrete Algorithms
Fast algorithms for finding disjoint subsequences with extremal densities
Pattern Recognition
Necklaces, convolutions, and X + Y
ESA'06 Proceedings of the 14th conference on Annual European Symposium - Volume 14
Computing rank-convolutions with a mask
ACM Transactions on Algorithms (TALG)
Scaled and permuted string matching
Information Processing Letters
On table arrangements, scrabble freaks, and jumbled pattern matching
FUN'10 Proceedings of the 5th international conference on Fun with algorithms
Gapped permutation patterns for comparative genomics
WABI'06 Proceedings of the 6th international conference on Algorithms in Bioinformatics
Sub-quadratic time and linear space data structures for permutation matching in binary strings
Journal of Discrete Algorithms
On Approximate Jumbled Pattern Matching in Strings
Theory of Computing Systems - Special Issue: Fun with Algorithms
Disjoint segments with maximum density
ICCS'05 Proceedings of the 5th international conference on Computational Science - Volume Part II
New algorithms for binary jumbled pattern matching
Information Processing Letters
Binary jumbled string matching for highly run-length compressible texts
Information Processing Letters
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We present a novel approach for computing all maximum consecutive subsums in a sequence of positive integers in near linear time. Solutions for this problem over binary sequences can be used for reporting existence (and possibly one occurrence) of Parikh vectors in a bit string. Recently, several attempts have been tried to build indexes for all Parikh vectors of a binary string in subquadratic time. However, to the best of our knowledge, no algorithm is know to date which can beat by more than a polylogarithmic factor the natural Θ(n2) exhaustive procedure. Our result implies an approximate construction of an index for all Parikh vectors of a binary string in O(n1+η) time, for any constant η0. Such index is approximate, in the sense that it leaves a small chance for false positives, i.e., Parikh vectors might be reported which are not actually present in the string. No false negative is possible. However, we can tune the parameters of the algorithm so that we can strictly control such a chance of error while still guaranteeing strong sub-quadratic running time.