review · ACM Computing Surveys · 1989

Modeling for text compression

Cited by 262Open access

Abstract

The best schemes for text compression use large models to help them predict which characters will come next. The actual next characters are coded with respect to the prediction, resulting in compression of information. Models are best formed adaptively, based on the text seen so far. This paper surveys successful strategies for adaptive modeling that are suitable for use in practical text compression systems. The strategies fall into three main classes: finite-context modeling, in which the last few characters are used to condition the probability distribution for the next one; finite-state modeling, in which the distribution is conditioned by the current state (and which subsumes finite-context modeling as an important special case); and dictionary modeling, in which strings of characters are replaced by pointers into an evolving dictionary. A comparison of different methods on the same sample texts is included, along with an analysis of future research directions.

Cite this paper

APA 7

Bell, T., Witten, I. H., & Cleary, J. G. (1989). Modeling for text compression. ACM Computing Surveys, 21(4), 557–591. https://doi.org/10.1145/76894.76896

MLA 9

Bell, Tim, et al. “Modeling for text compression.” ACM Computing Surveys, vol. 21, no. 4, 1989, pp. 557–91, https://doi.org/10.1145/76894.76896.

Chicago

Bell, Tim, Ian H. Witten, and John G. Cleary. 1989. “Modeling for text compression.” ACM Computing Surveys 21 (4): 557–91. https://doi.org/10.1145/76894.76896.

Harvard

Bell, T., Witten, I.H. and Cleary, J.G. (1989) ‘Modeling for text compression’, ACM Computing Surveys, 21(4), pp. 557–591. Available at: https://doi.org/10.1145/76894.76896.

BibTeX

@article{bell1989modeling,
  title = {{Modeling for text compression}},
  author = {Bell, Tim and Witten, Ian H. and Cleary, John G.},
  journal = {ACM Computing Surveys},
  volume = {21},
  number = {4},
  pages = {557--591},
  year = {1989},
  doi = {10.1145/76894.76896}
}

Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.