An Overview of Nonparametric Bayesian Models and Applications to Natural Language Processing
by
Narges Sharif-razavian
,
Andreas Zollmann
| Citations: | 1 - 0 self |
BibTeX
@MISC{Sharif-razavian_anoverview,
author = {Narges Sharif-razavian and Andreas Zollmann},
title = {An Overview of Nonparametric Bayesian Models and Applications to Natural Language Processing},
year = {}
}
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Abstract
This paper provides an overview of nonparametric Bayesian models relevant to natural language processing (NLP) tasks. We first introduce Bayesian parametric methods, followed by nonparametric Bayesian modeling based on the most common nonparametric prior, the Dirichlet Process. We give characterizations of the Dirichlet Process via the Polya urn scheme, the related Chinese restaurant metaphor, and the stick-breaking construction. We will also introduce two generalizations
