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Cluster Expansions and Iterative Scaling for Maximum Entropy Language Models

1995/09/09 by John D. Lafferty, Lafferty, John D., Bernhard Suhm +1
Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #cmp-lg #cs.CL

paper · pdf · doi:10.48550/arxiv.cmp-lg/9509003

8 pages, uuencoded and compressed postscript

arxiv created 1995/09/09 · arxiv updated 2009/11/30

Abstract

The maximum entropy method has recently been successfully introduced to a variety of natural language applications. In each of these applications, however, the power of the maximum entropy method is achieved at the cost of a considerable increase in computational requirements. In this paper we present a technique, closely related to the classical cluster expansion from statistical mechanics, for reducing the computational demands necessary to calculate conditional maximum entropy language models.

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