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Stochastic context-free grammar

Known as: SCFG, Probabilistic parsing, Probabilized context-free grammar 
PCFGs extend context-free grammars similar to how hidden Markov models extend regular grammars. Each production is assigned a probability. The… 
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Papers overview

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2010
2010
We extend stochastic context-free grammars such that the probability of applying a production can depend on the length of the… 
2009
2009
This paper presents a model-based approach to dialogue management that is guided by data-driven dialogue act prediction. The… 
2007
2007
In this paper we present preliminary results of investigating the structure of the Penn Treebank and how these results can be… 
2005
2005
We present a document understanding system in which the arrangement of lines of text and block separators within a document are… 
Highly Cited
2001
Highly Cited
2001
In this paper, we present techniques for characterizing complex, multi-tasked activities that require both exemplars and models… 
2001
2001
We present a machine learning algorithm for refining the structure of a stochastic context‐free grammar (SCFG). This algorithm… 
2001
2001
Stochastic models are commonly used in bioinformatics, e.g., hidden Markov models for modeling sequence families or stochastic… 
1998
1998
A genetic algorithm for learning stochastic context-free grammars from finite language samples as described. Solutions to the… 
1994
1994
  • A. FredJ. Leitao
  • 1994
  • Corpus ID: 45697
This paper introduces an improved stochastic context-free language recognizer. The algorithm is basically a best-first search on… 
1992
1992
A novel algorithm for estimating the parameters of a hidden stochastic context-free grammar is presented. In contrast to the…