Statistical models for language representation
ISSN: 2745-2220, 2382-3399
Année de publication: 2013
Titre de la publication: Avances tecnológicos en ingeniería
Volumen: 1
Número: 1
Pages: 29-39
Type: Article
D'autres publications dans: Revista ONTARE
Objectifs de Développement Durable
Résumé
ONTARE. REVISTA DE INVESTIGACIÓN DE LA FACULTAD DE INGENIERÍA This paper discuses several models for the computational representation of language. First, some n-gram models that are based on Markov models are introduced. Second, a family of models known as the exponential models is taken into account. This family in particular allows the incorporation of several features to model. Third, a recent current of research, the probabilistic Bayesian approach, is discussed. In this kind of models, language is modeled as a probabilistic distribution. Several distributions and probabilistic processes, such as the Dirichlet distribution and the Pitman- Yor process, are used to approximate the linguistic phenomena. Finally, the problem of sparseness of the language and its common solution known as smoothing is discussed.