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1
Dynamic Suffix Array with Polylogarithmic Queries and Updates ...
Kempa, Dominik; Kociumaka, Tomasz. - : arXiv, 2022
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2
Faster Algorithms for Longest Common Substring ...
Charalampopoulos, Panagiotis; Kociumaka, Tomasz; Pissis, Solon P.. - : Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2021
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3
Breaking the $O(n)$-Barrier in the Construction of Compressed Suffix Arrays ...
Kempa, Dominik; Kociumaka, Tomasz. - : arXiv, 2021
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4
Faster Algorithms for Longest Common Substring ...
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5
Time-Space Tradeoffs for Finding a Long Common Substring ...
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6
Time-Space Tradeoffs for Finding a Long Common Substring ...
Ben-Nun, Stav; Golan, Shay; Kociumaka, Tomasz. - : Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2020
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7
Practical Performance of Space Efficient Data Structures for Longest Common Extensions ...
Dinklage, Patrick; Fischer, Johannes; Herlez, Alexander; Kociumaka, Tomasz; Kurpicz, Florian. - : Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2020
Abstract: For a text T[1,n], a Longest Common Extension (LCE) query lce_T(i,j) asks for the length of the longest common prefix of the suffixes T[i,n] and T[j,n] identified by their starting positions 1 ≤ i,j ≤ n. A classic problem in stringology asks to preprocess a static text T[1,n] over an alphabet of size σ so that LCE queries can be efficiently answered on-line. Since its introduction in the 1980’s, this problem has found numerous applications: in suffix sorting, edit distance computation, approximate pattern matching, regularities finding, string mining, and many more. Text-book solutions offer O(n) preprocessing time and O(1) query time, but they employ memory-heavy data structures, such as suffix arrays, in practice several times bigger than the text itself. Very recently, more space efficient solutions using O(nlogσ) bits of total space or even only O(log n) bits of extra space have been proposed: string synchronizing sets [Kempa and Kociumaka, STOC'19, and Birenzwige et al., SODA'20] and in-place ...
Keyword: longest common prefix; space efficient data structures; text indexing; Theory of computation → Pattern matching
URL: https://drops.dagstuhl.de/opus/volltexte/2020/12905/
https://dx.doi.org/10.4230/lipics.esa.2020.39
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8
Faster Approximate Pattern Matching: A Unified Approach ...
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9
Longest Unbordered Factor in Quasilinear Time
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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10
Longest Unbordered Factor in Quasilinear Time ...
Kociumaka, Tomasz; Kundu, Ritu; Mohamed, Manal. - : Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik GmbH, Wadern/Saarbruecken, Germany, 2018
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11
Longest Unbordered Factor in Quasilinear Time ...
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12
Maximal Unbordered Factors of Random Strings ...
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13
Efficient Index for Weighted Sequences
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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14
Minimal Suffix and Rotation of a Substring in Optimal Time
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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15
Minimal Suffix and Rotation of a Substring in Optimal Time ...
Kociumaka, Tomasz. - : Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik GmbH, Wadern/Saarbruecken, Germany, 2016
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16
Sparse Suffix Tree Construction in Optimal Time and Space ...
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17
Minimal Suffix and Rotation of a Substring in Optimal Time ...
Kociumaka, Tomasz. - : arXiv, 2016
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18
Optimal Dynamic Strings ...
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19
Wavelet Trees Meet Suffix Trees ...
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20
Substring Suffix Selection ...
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