A resource-light approach to morpho-syntactic tagging /

While supervised corpus-based methods are highly accurate for different NLP tasks, including morphological tagging, they are difficult to port to other languages because they require resources that are expensive to create. As a result, many languages have no realistic prospect for morpho-syntactic a...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Feldman, Anna
Otros Autores: Hana, Jirka
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Amsterdam ; New York, NY : Rodopi, 2010.
Colección:Language and computers ; no. 70.
Temas:
Grammar, Comparative and general > Morphosyntax.
Computational linguistics.
Language transfer (Language learning)
Cross-language information retrieval.
Morphosyntaxe.
Linguistique informatique.
Transfert (Apprentissage d'une langue)
Recherche multilingue d'information.
computational linguistics.
LANGUAGE ARTS & DISCIPLINES > Grammar & Punctuation.
LANGUAGE ARTS & DISCIPLINES > Linguistics > Syntax.
Computational linguistics
Cross-language information retrieval
Grammar, Comparative and general > Morphosyntax
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Preliminary Material
  • Introduction
  • Common tagging techniques
  • Previous resource-light approaches to NLP
  • Languages, corpora and tagsets
  • Quantifying language properties
  • Resource-light morphological analysis
  • Cross-language morphological tagging
  • Summary and further work
  • Bibliography
  • Tagsets we use
  • Corpora
  • Language properties
  • Citation Index.

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