scholarly journals A graph-theoretic model to solve the approximate string matching problem allowing for translocations

2013 ◽  
Vol 23 ◽  
pp. 143-156
Author(s):  
Pritom Ahmed ◽  
A.S.M. Shohidull Islam ◽  
M. Sohel Rahman
2014 ◽  
Vol 513-517 ◽  
pp. 1017-1020
Author(s):  
Bing Liu ◽  
Dan Han ◽  
Shuang Zhang

String matching is one of the most typical problems in computer science. Previous studies mainly focused on accurate string matching problem. However, with the rapid development of the computer and Internet as well as the continuously rising of new issues, people find that it has very important theoretical value and practical meaning to research and design efficient approximate string matching algorithms. Approximate string matching is also called string matching that allows errors, which mainly aims to find the pattern string in the text and database and allows k differences between the pattern string and its occurring forms in the text. For the problem of approximate string matching, though a number of algorithms have been proposed, there are fewer studies which focus on large size of alphabet . Most of experts are interested in small or middle size of alphabet . For large size of , especially for Chinese characters and Asian phonetics, there are fewer efficient algorithms. For the above reasons, this paper focuses on the approximate Chinese strings matching problem based on the pinyin input method.


1992 ◽  
Vol 35 (5) ◽  
pp. 524-526 ◽  
Author(s):  
A. A. Bertossi ◽  
F. Luccio ◽  
L. Pagli ◽  
E. Lodi

2017 ◽  
Author(s):  
Hongyi Xin ◽  
Jeremie Kim ◽  
Sunny Nahar ◽  
Can Alkan ◽  
Onur Mutlu

AbstractMotivationApproximate String Matching is a pivotal problem in the field of computer science. It serves as an integral component for many string algorithms, most notably, DNA read mapping and alignment. The improved LV algorithm proposes an improved dynamic programming strategy over the banded Smith-Waterman algorithm but suffers from support of a limited selection of scoring schemes. In this paper, we propose the Leaping Toad problem, a generalization of the approximate string matching problem, as well as LEAP, a generalization of the Landau-Vishkin’s algorithm that solves the Leaping Toad problem under a broader selection of scoring schemes.ResultsWe benchmarked LEAP against 3 state-of-the-art approximate string matching implementations. We show that when using a bit-vectorized de Bruijn sequence based optimization, LEAP is up to 7.4x faster than the state-of-the-art bit-vector Levenshtein distance implementation and up to 32x faster than the state-of-the-art affine-gap-penalty parallel Needleman Wunsch Implementation.AvailabilityWe provide an implementation of LEAP in C++ at github.com/CMU-SAFARI/[email protected], [email protected] or [email protected]


Algorithmica ◽  
1994 ◽  
Vol 12 (4-5) ◽  
pp. 327-344 ◽  
Author(s):  
W. I. Chang ◽  
E. L. Lawler

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