  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.
