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A Statistical Parsing Framework for Sentiment Classification
Statistical Parsing Framework Sentiment Classification
2015/9/15
We present a statistical parsing framework for sentence-level sentiment classification in this article. Unlike previous works that use syntactic parsing results for sentiment analysis, we develop a st...
Wide-Coverage Deep Statistical Parsing Using Automatic Dependency Structure Annotation
Wide-Coverage Deep Statistical Parsing Automatic Dependency Structure Annotation
2015/9/6
A number of researchers have recently conducted experiments comparing “deep” hand-crafted wide-coverage with “shallow” treebank- and machine-learning-based parsers at the level of dependencies, using ...
Wide-Coverage Efficient Statistical Parsing with CCG and Log-Linear Models
Wide-Coverage Statistical Parsing CCG Log-Linear Models
2015/9/2
This article describes a number of log-linear parsing models for an automatically extracted lexicalized grammar. The models are “full” parsing models in the sense that probabilities are defined for co...
Corpus-based statistical parsing relies on using large quantities of annotated text as training examples. Building this kind of resource is expensive and labor-intensive. This work proposes to use sam...
Optimizing Local Probability Models for Statistical Parsing
Local Probability Models Statistical Parsing
2015/6/12
This paper studies the properties and performance of models for estimating local probability distributions which are used as components of larger probabilistic systems — history-based generative parsi...
An Information-Theory-Based Feature Type Analysis for the Modelling of Statistical Parsing
Information-Theory-Based Feature Type Statistical Parsing
2009/2/13
The paper proposes an information-theory-based method for feature types analysis in probabilistic evaluation modelling for statistical parsing. The basic idea is that we use entropy and conditional en...