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A Maximum Entropy Approach to Natural Language Processing

by: Adam L. Berger, Stephen Della Pietra, and Vincent J. Della Pietra

In: Computational Linguistics, Vol. 22, Nr. 1 (1996) , p. 39-71.

Abstract

The concept of maximum entropy can be traced along multiple threads to Biblical times. Only recently, however, have computers become powerful enough to permit the widescale application of this concept to real world problems in statistical estimation and pattern recognition. In this paper, we describe a method for statistical modeling based on maximum entropy. We present a maximum-likelihood approach for automatically constructing maximum entropy models and describe how to implement this approach efficiently, using as examples several problems in natural language processing.

BibTeX record

@article{Berger:1996,
  abstract = {The concept of maximum entropy can be traced along multiple threads to Biblical times. Only recently, however, have computers become powerful enough to permit the widescale application of this concept to real world problems in statistical estimation and pattern recognition. In this paper, we describe a method for statistical modeling based on maximum entropy. We present a maximum-likelihood approach for automatically constructing maximum entropy models and describe how to implement this approach efficiently, using as examples several problems in natural language processing.},
  added-at = {2007-12-14T02:35:56.000+0100},
  author = {Berger, Adam L. and Pietra, Stephen Della and Pietra, Vincent J. Della},
  biburl = {http://www.bibsonomy.org/bibtex/272155af0cbabd478137fbd06d3bbc4af/diego_ma},
  interhash = {e7f7835dc81d2f7c28d3371df9cdaebe},
  intrahash = {72155af0cbabd478137fbd06d3bbc4af},
  journal = {Computational Linguistics},
  keywords = {maxent machine_translation},
  number = 1,
  pages = {39-71},
  timestamp = {2007-12-14T02:35:56.000+0100},
  title = {A Maximum Entropy Approach to Natural Language Processing},
  volume = 22,
  year = 1996
}

Endnote record