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Tesi etd-05232013-000551


Thesis type
Tesi di dottorato di ricerca
Author
OTTAVIANO, GIUSEPPE
URN
etd-05232013-000551
Title
Space-Efficient Data Structures for Collections of Textual Data
Settore scientifico disciplinare
INF/01
Corso di studi
INFORMATICA
Commissione
tutor Prof. Grossi, Roberto
Parole chiave
  • strings
  • sequences
  • semi-structured data
  • compression
  • succinct data structures
Data inizio appello
07/06/2013;
Consultabilità
completa
Riassunto analitico
This thesis focuses on the design of succinct and compressed data structures for collections of string-based data, specifically sequences of semi-structured documents in textual format, sets of strings, and sequences of strings. The study of such collections is motivated by a large number of applications both in theory and practice.<br>For textual semi-structured data, we introduce the concept of semi-index, a succinct construction that speeds up the access to documents encoded with textual semi-structured formats, such as JSON and XML, by storing separately a compact description of their parse trees, hence avoiding the need to re-parse the documents every time they are read.<br>For string dictionaries, we describe a data structure based on a path decomposition of the compacted trie built on the string set. The tree topology is encoded using succinct data structures, while the node labels are compressed using a simple dictionary-based scheme. We also describe a variant of the path-decomposed trie for scored string sets, where each string has a score. This data structure can support efficiently top-k completion queries, that is, given a string p and an integer k, return the k highest scored strings among those prefixed by p.<br>For sequences of strings, we introduce the problem of compressed indexed sequences of strings, that is, representing indexed sequences of strings in nearly-optimal compressed space, both in the static and dynamic settings, while supporting supports random access, searching, and counting operations, both for exact matches and prefix search. We present a new data structure, the Wavelet Trie, that solves the problem by combining a Patricia trie with a wavelet tree. The Wavelet Trie improves on the state-of-the-art compressed data structures for sequences by supporting a dynamic alphabet and prefix queries.<br>Finally, we discuss the issue of the practical implementation of the succinct primitives used throughout the thesis for the experiments. These primitives are implemented as part of a publicly available library, Succinct, using state-of-the-art algorithms along with some improvements.
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