Journal ArticleDOI
Approximate Pattern Matching with the L 1 , L 2 and L ∞ Metrics
Ohad Lipsky,Ely Porat +1 more
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TLDR
The problem of String Matching with mismatches to have weighted mismatches is generalized and an O(nlog 4m) algorithm is presented that approximates the results of this problem up to a factor of O(log’m) in the case that the weight function is a metric.Abstract:
Given an alphabet Σ={1,2,…,|Σ|} text string T∈Σn and a pattern string P∈Σm , for each i=1,2,…,n−m+1 define L p (i) as the p-norm distance when the pattern is aligned below the text and starts at position i of the text. The problem of pattern matching with L p distance is to compute L p (i) for every i=1,2,…,n−m+1. We discuss the problem for d=1,2,∞. First, in the case of L 1 matching (pattern matching with an L 1 distance) we show a reduction of the string matching with mismatches problem to the L 1 matching problem and we present an algorithm that approximates the L 1 matching up to a factor of 1+e, which has an $O(\frac{1}{\varepsilon^{2}}n\log m\log|\Sigma|)$ run time. Then, the L 2 matching problem (pattern matching with an L 2 distance) is solved with a simple O(nlog m) time algorithm. Finally, we provide an algorithm that approximates the L ∞ matching up to a factor of 1+e with a run time of $O(\frac{1}{\varepsilon}n\log m\log|\Sigma|)$. We also generalize the problem of String Matching with mismatches to have weighted mismatches and present an O(nlog 4 m) algorithm that approximates the results of this problem up to a factor of O(log m) in the case that the weight function is a metric.read more
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Proceedings ArticleDOI
Towards Unified Approximate Pattern Matching for Hamming and L_1 Distance
TL;DR: A smooth time trade-off is provided by exhibiting an O~((m+k sqrt{m})* n/m) time algorithm, and a matching conditional lower bound is added, showing that a significantly faster combinatorial algorithm is not possible, unless the combinatorially matrix multiplication conjecture fails.
Book
Pattern Matching in Compressed Texts and Images
TL;DR: This monograph surveys and appraises techniques for pattern matching in compressed text and images, and identifies the important relationship between pattern matching and compression, and proposes some performance measures for compressed pattern matching algorithms.
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A subquadratic approximation scheme for partition
TL;DR: The subject of this paper is the time complexity of approximating Knapsack, Subset Sum, Partition, and some other related problems, and the main result is an $\widetilde{O}(n+1/\varepsilon^{5/3})$ time randomized FPTAS for Partitions, which is derived from a certain relaxed form of a randomized F PTAS for Sub set Sum.
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Optimal rank and select queries on dictionary-compressed text
TL;DR: In this article, the problem of supporting queries on a string $S$ of length $n$ within a space bounded by the size of a string attractor for the query was studied.
Journal ArticleDOI
Efficient computations of l 1 and l ∞ rearrangement distances
TL;DR: It is shown that the problem can be approximated in linear time for general patterns, and efficient exact solutions for different variants of the problem are provided, as well as a faster approximation.
References
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Introduction to Algorithms
TL;DR: The updated new edition of the classic Introduction to Algorithms is intended primarily for use in undergraduate or graduate courses in algorithms or data structures and presents a rich variety of algorithms and covers them in considerable depth while making their design and analysis accessible to all levels of readers.
Journal Article
Binary codes capable of correcting deletions, insertions, and reversals
Journal ArticleDOI
Introduction to algorithms: 4. Turtle graphics
TL;DR: In this article, a language similar to logo is used to draw geometric pictures using this language and programs are developed to draw geometrical pictures using it, which is similar to the one we use in this paper.