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Context Modeling for Text Compression

  • Daniel S. Hirschberg†
  • Debra A. Lelewer‡
Part of the The Kluwer International Series in Engineering and Computer Science book series (SECS, volume 176)

Abstract

Adaptive context modeling has emerged as one of the most promising new approaches to compressing text. A finite-context model is a probabilistic model that uses the context in which input symbols occur (generally a few preceding characters) to determine the number of bits used to code these symbols. We provide an introduction to context modeling and recent research results that incorporate the concept of context modeling into practical data compression algorithms.

Keywords

Memory Requirement Hash Table Data Compression Context Model Internal Memory 
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 Science+Business Media New York 1992

Authors and Affiliations

  • Daniel S. Hirschberg†
    • 1
  • Debra A. Lelewer‡
    • 2
  1. 1.Department of Information and Computer ScienceUniversity of CaliforniaIrvineUSA
  2. 2.Computer Science Dept.California State Polytechnic UniversityPomonaUSA

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