Faster pattern matching with character classes using prime number encoding
Chaim Linhart,Ron Shamir +1 more
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TLDR
An FFT-based algorithm is presented that uses a novel prime-numbers encoding scheme, which is logn/logm times faster than the fastest extant approaches, which are based on boolean convolutions, and speeds up solutions to approximate matching with character classes problems.About:
This article is published in Journal of Computer and System Sciences.The article was published on 2009-05-01 and is currently open access. It has received 17 citations till now. The article focuses on the topics: 3-dimensional matching & Optimal matching.read more
Citations
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Book ChapterDOI
Generalised Matching
TL;DR: A related problem the authors term pattern matching with string classes which they show to be solvable efficiently and an optimisation variant of generalised matching which gives a polynomial-time min $(1,\sqrt{k/OPT})$-approximation algorithm for fixed k.
Posted Content
Space Lower Bounds for Online Pattern Matching
TL;DR: In this article, the authors present space lower bounds for online pattern matching under a number of different distance measures, including edit and swap, Hamming, L 1, L 2, L 3, L 4, L 5, L 6, L 7, L 8, L 9, L 10, L 11, L 12, L 14, L 15, L 16, L 17, L 18, L 19, L 20, L 21, L 22, L 23, L 24, L 28, L 30, L 31, L 32, L 34, L
Journal ArticleDOI
Space lower bounds for online pattern matching
TL;DR: A dichotomy between distance functions that have wildcard-like properties and those that do not is shown and there exist space bounds of @W(logm) and O(log^2m) bits.
Journal ArticleDOI
Exploiting word-level parallelism for fast convolutions and their applications in approximate string matching
TL;DR: A method for performing convolutions efficiently in a word RAM model of computation, having a word size of w = ?
Book ChapterDOI
Fast Convolutions and Their Applications in Approximate String Matching
TL;DR: A method for performing boolean convolutions efficiently in word RAM model of computation, having a word size of w={\it \Omega(\log n)$ bits, is developed, which is applied to approximate string matching under Hamming distance.
References
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Book
Algorithms on Strings, Trees and Sequences: Computer Science and Computational Biology
TL;DR: In this paper, the authors introduce suffix trees and their use in sequence alignment, core string edits, alignments and dynamic programming, and extend the core problems to extend the main problems.
Journal ArticleDOI
Fast Pattern Matching in Strings
TL;DR: An algorithm is presented which finds all occurrences of one given string within another, in running time proportional to the sum of the lengths of the strings, showing that the set of concatenations of even palindromes, i.e., the language $\{\alpha \alpha ^R\}^*$, can be recognized in linear time.
Journal ArticleDOI
A fast string searching algorithm
TL;DR: The algorithm has the unusual property that, in most cases, not all of the first i.” in another string, are inspected.