Succinct Non-overlapping Indexing

Conference paper
First Online:
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9133)

Abstract

Given a text \(\mathsf {T}\) having \(n\) characters, we consider the non-overlapping indexing problem defined as follows: pre-process \(\mathsf {T}\) into a data-structure, such that whenever a pattern \(P\) comes as input, we can report a maximal set of non-overlapping occurrences of \(P\) in \(\mathsf {T}\). The best known solution for this problem takes linear space, in which a suffix tree of \(\mathsf {T}\) is augmented with \(O(n)\)-word data structures. A query \(P\) can be answered in optimal \(O(|P|+\mathsf {nocc})\) time, where \(\mathsf {nocc}\) is the output size [Cohen and Porat, ISAAC 2009]. We present the following new result: let \(\mathsf {CSA}\) (not necessarily a compressed suffix array) be an index of \(\mathsf {T}\) that can compute (i) the suffix range of \(P\) in \(\mathsf {search}(P)\) time, and (ii) a suffix array or an inverse suffix array value in \(\mathsf {t_{SA}}\) time; then by using \(\mathsf {CSA}\) alone, we can answer a query \(P\) in \(O(\mathsf {search}(P)+ \mathsf {nocc}\cdot \mathsf {t_{SA}})\) time. Additionally, we present an improved result for a generalized version of this problem called range non-overlapping indexing.

Keywords

Query Time Suffix Tree Suffix Array Output Size Short Pattern 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Arnab Ganguly
    • 1
  • Rahul Shah
    • 1
  • Sharma V. Thankachan
    • 2
  1. 1.School of Electrical Engineering and Computer ScienceLouisiana State UniversityBaton RougeUSA
  2. 2.School of Computational Science and EngineeringGeorgia Institute of TechnologyAtlantaUSA

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