Topic
Approximate string matching
About: Approximate string matching is a research topic. Over the lifetime, 1903 publications have been published within this topic receiving 62352 citations. The topic is also known as: fuzzy string-searching algorithm & fuzzy string-matching algorithm.
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TL;DR: The vertices of the polygons are suggested as the primitives of the attributed strings so that the benefits of split and merge operations are placed in the dynamic programming algorithm for the edit distance evaluation without an extra computation-cost.
25 citations
TL;DR: This work has developed a new longest common prefix array-sampled representation, optimized to work with the backward search method inherently used by the FM-Index, which led to both a fast and a space-efficient approach.
Abstract: Motivation: Maximal Exact Matches, or just MEMs, are a powerful tool in the context of multiple sequence alignment and approximate string matching. The most efficient algorithms to collect them are based on compressed indexes that rely on LCP array centered data structures. However, their space efficient representations make use of encoding techniques that are very expensive from a computational point of view. With the deluge of data generated by highthroughput sequencing, new approaches need to be developed in order to deal with larger genomic sequences. Results: In this work we have developed a new LCP array sampled representation, optimized to work with the backward search method inherently used by the FM-Index. Unlike previous implementations that sacrifice running time to have smaller space, ours lead to both a fast and very space efficient approach. This implementation was used by the new software slaMEM, developed to efficiently retrieve MEMs. The results show that the new algorithm is competitive against existing state of the art approaches. Availability and Implementation: The software is implemented in C and is operating system independent. The source code is freely available for download at http://github.com/fjdf/slaMEM/ under the GPLv3 license. Contact: atf@inesc-id.pt Supplementary information: Supplementary data is available at Bioinformatics online.
25 citations
29 Aug 2005
TL;DR: This paper considers a generalization of sorting by reversals (SBR), k-SBR, and allows each symbol to appear at most k times in each string, for some k≥ 1, and develops a simple O(k2)-approximation algorithm running in time O( k · n).
Abstract: For a string A=a1... an, a reversalρ(i,j), 1≤ i
25 citations
TL;DR: A lightweight approach to recognize gestures with Kinect by utilizing approximate string matching, which encodes the movements of the joints as sequences of characters in order to simplify the gesture recognition as a widely studied string matching problem.
25 citations
TL;DR: An Introductory Course on Communication Complexity and Formal Languages and Concurrent Behaviours and Probabilistic Parsing.
Abstract: Basic Notation and Terminology.- Open Problems on Partial Words.- Alignments and Approximate String Matching.- An Introductory Course on Communication Complexity.- Formal Languages and Concurrent Behaviours.- Cellular Automata - A Computational Point of View.- Probabilistic Parsing.- DNA-Based Memories: A Survey.
25 citations