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Dynamic Suffix Array with Polylogarithmic Queries and Updates ...
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Breaking the $O(n)$-Barrier in the Construction of Compressed Suffix Arrays ...
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Time-Space Tradeoffs for Finding a Long Common Substring ...
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Time-Space Tradeoffs for Finding a Long Common Substring ...
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Practical Performance of Space Efficient Data Structures for Longest Common Extensions ...
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Longest Unbordered Factor in Quasilinear Time
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Kociumaka, Tomasz; Kundu, Ritu; Mohamed, Manal. - : Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, 2018. : LIPIcs - Leibniz International Proceedings in Informatics. 29th International Symposium on Algorithms and Computation (ISAAC 2018), 2018
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Efficient Index for Weighted Sequences
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Barton, Carl; Kociumaka, Tomasz; Pissis, Solon P.. - : Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, 2016. : LIPIcs - Leibniz International Proceedings in Informatics. 27th Annual Symposium on Combinatorial Pattern Matching (CPM 2016), 2016
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Minimal Suffix and Rotation of a Substring in Optimal Time
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Kociumaka, Tomasz. - : Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, 2016. : LIPIcs - Leibniz International Proceedings in Informatics. 27th Annual Symposium on Combinatorial Pattern Matching (CPM 2016), 2016
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Minimal Suffix and Rotation of a Substring in Optimal Time ...
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Kociumaka, Tomasz. - : Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik GmbH, Wadern/Saarbruecken, Germany, 2016
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Sparse Suffix Tree Construction in Optimal Time and Space ...
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Minimal Suffix and Rotation of a Substring in Optimal Time ...
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Wavelet Trees Meet Suffix Trees ...
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Abstract:
We present an improved wavelet tree construction algorithm and discuss its applications to a number of rank/select problems for integer keys and strings. Given a string of length n over an alphabet of size $σ\leq n$, our method builds the wavelet tree in $O(n \log σ/ \sqrt{\log{n}})$ time, improving upon the state-of-the-art algorithm by a factor of $\sqrt{\log n}$. As a consequence, given an array of n integers we can construct in $O(n \sqrt{\log n})$ time a data structure consisting of $O(n)$ machine words and capable of answering rank/select queries for the subranges of the array in $O(\log n / \log \log n)$ time. This is a $\log \log n$-factor improvement in query time compared to Chan and Pătraşcu and a $\sqrt{\log n}$-factor improvement in construction time compared to Brodal et al. Next, we switch to stringological context and propose a novel notion of wavelet suffix trees. For a string w of length n, this data structure occupies $O(n)$ words, takes $O(n \sqrt{\log n})$ time to construct, and ... : 33 pages, 5 figures; preliminary version published at SODA 2015 ...
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Keyword:
68P05 Primary, 68W05 Secondary; Data Structures and Algorithms cs.DS; E.1; F.2.2; FOS Computer and information sciences
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URL: https://arxiv.org/abs/1408.6182 https://dx.doi.org/10.48550/arxiv.1408.6182
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