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A Framework for Dynamizing Succinct Data Structures

  • Ankur Gupta
  • Wing-Kai Hon
  • Rahul Shah
  • Jeffrey Scott Vitter
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4596)

Abstract

We present a framework to dynamize succinct data structures, to encourage their use over non-succinct versions in a wide variety of important application areas. Our framework can dynamize most state-of-the-art succinct data structures for dictionaries, ordinal trees, labeled trees, and text collections. Of particular note is its direct application to XML indexing structures that answer subpath queries [2]. Our framework focuses on achieving information-theoretically optimal space along with near-optimal update/query bounds.

As the main part of our work, we consider the following problem central to text indexing: Given a text T over an alphabet Σ, construct a compressed data structure answering the queries char(i), rank s (i), and select s (i) for a symbol s ∈ Σ. Many data structures consider these queries for static text T [5,3,16,4]. We build on these results and give the best known query bounds for the dynamic version of this problem, supporting arbitrary insertions and deletions of symbols in T.

Specifically, with an amortized update time of O(n ε ), any static succinct data structure D for T, taking t(n) time for queries, can be converted by our framework into a dynamic succinct data structure that supports rank s (i), select s (i), and char(i) queries in O(t(n) + loglogn) time, for any constant ε> 0. When |Σ| = polylog(n), we achieve O(1) query times. Our update/query bounds are near-optimal with respect to the lower bounds from [13].

Keywords

Label Tree Dynamic Text Text Indexing Text Collection Wavelet Tree 
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-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Ankur Gupta
    • 1
  • Wing-Kai Hon
    • 2
  • Rahul Shah
    • 1
  • Jeffrey Scott Vitter
    • 1
  1. 1.Department of Computer Sciences, Purdue University, West Lafayette, IN 47907–2107USA
  2. 2.Department of Computer Science, National Tsing Hua University, HsinchuTaiwan

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