A Maximum Entropy approach to Natural Language Processing

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A Maximum Entropy approach to Natural Language Processing (1996)

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by Adam L. Berger , Stephen A. Della Pietra , Vincent J. Della Pietra

Venue:	COMPUTATIONAL LINGUISTICS
Citations:	1365 - 5 self

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@ARTICLE{Berger96amaximum,
    author = {Adam L. Berger and Stephen A. Della Pietra and Vincent J. Della Pietra},
    title = {A Maximum Entropy approach to Natural Language Processing},
    journal = {COMPUTATIONAL LINGUISTICS},
    year = {1996},
    volume = {22},
    pages = {39--71}
}

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Abstract

The concept of maximum entropy can be traced back 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.

Keyphrases

natural language processing maximum entropy approach maximum entropy multiple thread pattern recognition maximum entropy model widescale application statistical estimation biblical time statistical modeling maximum-likelihood approach example several problem real world problem

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