- http://experiment.worldcat.org/entity/work/data/29987363#Topic/models
- http://experiment.worldcat.org/entity/work/data/29987363#Topic/grammars
- http://id.loc.gov/authorities/subjects/sh88002425
- http://experiment.worldcat.org/entity/work/data/29987363#Topic/axes
- http://experiment.worldcat.org/entity/work/data/29987363#Topic/parameters
- http://experiment.worldcat.org/entity/work/data/29987363#Topic/motivation
- http://experiment.worldcat.org/entity/work/data/29987363#Topic/algorithms
- http://id.worldcat.org/fast/1034365
- http://experiment.worldcat.org/entity/work/data/29987363#Topic/estimates
- http://experiment.worldcat.org/entity/work/data/29987363#Topic/entropy
- http://experiment.worldcat.org/entity/work/data/29987363#Topic/language
- http://experiment.worldcat.org/entity/work/data/29987363#Topic/computer_programming_and_software
- http://experiment.worldcat.org/entity/work/data/29987363#Topic/paper
- http://experiment.worldcat.org/entity/work/data/29987363#Topic/context_free_grammars
- http://experiment.worldcat.org/entity/work/data/29987363#Topic/natural_language

- http://experiment.worldcat.org/entity/work/data/29987363#Organization/carnegie_mellon_univ_pittsburgh_pa_school_of_computer_science
- http://worldcat.org/entity/person/id/2632506503
- http://worldcat.org/entity/person/id/2716276967
- http://worldcat.org/entity/person/id/2739578722
- http://worldcat.org/entity/person/id/2636069094
- http://worldcat.org/entity/person/id/2716597111
- http://worldcat.org/entity/person/id/2692941597

- "In this paper we present a new class of language models. This class derives from link grammar a context-free formalism for the description of natural language. We describe an algorithm for determining maximum-likelihood estimates of the parameters of these models. The language models which we present differ from previous models based on stochastic context-free grammars in that they are highly lexical. In particular they include the familiar n-gram models as a natural subclass The motivation for considering this class is to estimate the contribution which grammar can make to reducing the relative entropy of natural language."@en
- "Abstract: "In this paper we present a new class of language models. This class derives from link grammar, a context-free formalism for the description of natural language. We describe an algorithm for determining maximum-likelihood estimates of the parameters of these models. The language models which we present differ from previous models based on stochastic context-free grammars in that they are highly lexical. In particular, they include the familiar n-gram models as a natural subclass. The motivation for considering this class is to estimate the contribution which grammar can make to reducing the relative entropy of natural language.""@en