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2018 | OriginalPaper | Chapter

Computing Burrows-Wheeler Similarity Distributions for String Collections

Authors : Felipe A. Louza, Guilherme P. Telles, Simon Gog, Liang Zhao

Published in: String Processing and Information Retrieval

Publisher: Springer International Publishing

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Abstract

In this article we present practical and theoretical improvements to the computation of the Burrows-Wheeler similarity distribution for all pairs of strings in a collection. Our algorithms take advantage of the Burrows-Wheeler transform (BWT) computed for the concatenation of all strings, instead of the pairwise construction of BWTs performed by the straightforward approach, and use compressed data structures that allow reductions of running time while still keeping a small memory footprint, as shown by a set of experiments with real datasets.

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previous chapter Optimal In-Place Suffix Sorting

next chapter Better Heuristic Algorithms for the Repetition Free LCS and Other Variants

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Title: Computing Burrows-Wheeler Similarity Distributions for String Collections
Authors: Felipe A. Louza
Guilherme P. Telles
Simon Gog
Liang Zhao
Publisher: Springer International Publishing
Book: String Processing and Information Retrieval
Print ISBN: 978-3-030-00478-1

Electronic ISBN: 978-3-030-00479-8

Copyright Year: 2018
DOI: https://doi.org/10.1007/978-3-030-00479-8_23

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