Skip Navigation

The Computer Journal 1997 40(2 and 3):67-75; doi:10.1093/comjnl/40.2_and_3.67
© 1997 by British Computer Society
This Article
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrow Search for citing articles in:
ISI Web of Science (23)
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Cleary, J. G.
Right arrow Articles by Teahan, W. J.
Right arrow Search for Related Content
Social Bookmarking
 Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

Unbounded Length Contexts for PPM

J. G. Cleary and W. J. Teahan

Department of Computer Science, University of Waikato, Hamilton, New Zealand Email: jcleary{at}cs.waikato.ac.nz, wjt{at}cs.waikato.ac.nz

The PPM data compression scheme has set the performance standard in lossless compression of text throughout the past decade. PPM is a finite-context statistical modelling technique that can be viewed as blending together several fixed-order context models to predict the next character in the input sequence. This paper gives a brief introduction to PPM, and describes a variant of the algorithm, called PPM*, which exploits contexts of unbounded length. Although requiring considerably greater computational resources (in both time and space), this reliably achieves compression superior to the benchmark PPMC version. Its major contribution is that it shows that the full information available by considering all substrings of the input string can be used effectively to generate high-quality predictions. Hence, it provides a useful tool for exploring the bounds of compression.


Received June 28, 1996. revised July 25, 1997.


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?




Disclaimer:
Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.