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Grammatical trigrams : a probabilistic model of link grammar

著者: John D Lafferty; Daniel D Sleator; Davy Temperley
出版商: Pittsburgh, Pa. : School of Computer Science, Carnegie Mellon University, [1992]
丛书: Research paper (Carnegie Mellon University. School of Computer Science), CMU-CS-92-181.
版本/格式:   图书 : 英语查看所有的版本和格式
数据库:WorldCat
提要:
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  再读一些...
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所有的著者/提供者: John D Lafferty; Daniel D Sleator; Davy Temperley
OCLC号码: 26847322
注意: "To appear in Proc. of the 1992 AAAI Fall Symp. on Probabilistic Approaches to Natural Language."
"September 1992."
描述: 10 p. ; 28 cm.
丛书名: Research paper (Carnegie Mellon University. School of Computer Science), CMU-CS-92-181.
责任: John Lafferty, Daniel Sleator, Davy Temperley.

摘要:

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."

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