Compression, Indexing, and Retrieval for Massive String Data View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

2010

AUTHORS

Wing-Kai Hon , Rahul Shah , Jeffrey Scott Vitter

ABSTRACT

The field of compressed data structures seeks to achieve fast search time, but using a compressed representation, ideally requiring less space than that occupied by the original input data. The challenge is to construct a compressed representation that provides the same functionality and speed as traditional data structures. In this invited presentation, we discuss some breakthroughs in compressed data structures over the course of the last decade that have significantly reduced the space requirements for fast text and document indexing. One interesting consequence is that, for the first time, we can construct data structures for text indexing that are competitive in time and space with the well-known technique of inverted indexes, but that provide more general search capabilities. Several challenges remain, and we focus in this presentation on two in particular: building I/O-efficient search structures when the input data are so massive that external memory must be used, and incorporating notions of relevance in the reporting of query answers. More... »

PAGES

260-274

References to SciGraph publications

  • 2002-01-29. Compressed Text Databases with Efficient Query Algorithms Based on the Compressed Suffix Array in ALGORITHMS AND COMPUTATION
  • 2007. Implicit Compression Boosting with Applications to Self-indexing in STRING PROCESSING AND INFORMATION RETRIEVAL
  • 2008-07. Improved Approximate String Matching Using Compressed Suffix Data Structures in ALGORITHMICA
  • 2007. A Lempel-Ziv Text Index on Secondary Storage in COMBINATORIAL PATTERN MATCHING
  • 1994-09. Algorithms for parallel memory, I: Two-level memories in ALGORITHMICA
  • 2010. Succinct Dictionary Matching with No Slowdown in COMBINATORIAL PATTERN MATCHING
  • 2005. Rank-Sensitive Data Structures in STRING PROCESSING AND INFORMATION RETRIEVAL
  • 2003. Full-Text Indexes in External Memory in ALGORITHMS FOR MEMORY HIERARCHIES
  • 2007. Space-Efficient Algorithms for Document Retrieval in COMBINATORIAL PATTERN MATCHING
  • 2006. Inverted Files Versus Suffix Arrays for Locating Patterns in Primary Memory in STRING PROCESSING AND INFORMATION RETRIEVAL
  • 2005. Succinct Suffix Arrays Based on Run-Length Encoding in COMBINATORIAL PATTERN MATCHING
  • 2009. On Entropy-Compressed Text Indexing in External Memory in STRING PROCESSING AND INFORMATION RETRIEVAL
  • 2006. Position-Restricted Substring Searching in LATIN 2006: THEORETICAL INFORMATICS
  • 2009. Succinct Index for Dynamic Dictionary Matching in ALGORITHMS AND COMPUTATION
  • 2007-12. Compressed Suffix Trees with Full Functionality in THEORY OF COMPUTING SYSTEMS
  • 2009. Succinct Text Indexing with Wildcards in STRING PROCESSING AND INFORMATION RETRIEVAL
  • 1995-09. On-line construction of suffix trees in ALGORITHMICA
  • 2009-03. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome in GENOME BIOLOGY
  • 2008. Fully-Compressed Suffix Trees in LATIN 2008: THEORETICAL INFORMATICS
  • 2004. Advantages of Backward Searching — Efficient Secondary Memory and Distributed Implementation of Compressed Suffix Arrays in ALGORITHMS AND COMPUTATION
  • Book

    TITLE

    Combinatorial Pattern Matching

    ISBN

    978-3-642-13508-8
    978-3-642-13509-5

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-3-642-13509-5_24

    DOI

    http://dx.doi.org/10.1007/978-3-642-13509-5_24

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1029367197


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