Name: Unleashing the Power of Syntactic N-Grams: A Solution for Explainable Cognitive Linguistics (en Inglés)
Price: 93650.00 CLP
Availability: InStock
Author: Calvo, Hiram
ISBN: 9789994980116

portada Unleashing the Power of Syntactic N-Grams: A Solution for Explainable Cognitive Linguistics (en Inglés)

Formato

Libro Físico

Autor

Hiram Calvo

Editorial

Eliva Press

Idioma

Inglés

N° páginas

214

Encuadernación

Tapa Blanda

Dimensiones

22.9 x 15.2 x 1.1 cm

Peso

0.29 kg.

ISBN13

9789994980116

Categorías

Tecnología de la información: cuestiones generales

Unleashing the Power of Syntactic N-Grams: A Solution for Explainable Cognitive Linguistics (en Inglés)

Hiram Calvo (Autor) · Eliva Press · Tapa Blanda

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Origen: Estados Unidos (Costos de importación incluídos en el precio)

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Reseña del libro "Unleashing the Power of Syntactic N-Grams: A Solution for Explainable Cognitive Linguistics (en Inglés)"

Recently Natural Language Processing has seen the rise of computationally expensive (although effective) technologies to deal with the nuances of language. While traditional approaches seem to be less popular nowadays, there are several advantages that these may provide. In particular, n-gram-based models foster the explainability of Artificial Intelligence-based algorithms. This is why this book was conceived.Recent studies applied to related areas (Sidorov, 2013) show that syntactic n-grams can help to improve several tasks, since they consider not only the expressions' words, but also their part of speech and the long distance connections that they can capture. A disadvantage of syntactic n-grams might be the need of a parser, which can be slow and may not be available for all languages, so that the benefits of using this additional resource should be clear. In this work we present an in-depth research in order to present the strengths and weaknesses of using syntactic n-grams in a variety of applications. Some of them have been benefited from this approach, while others have just been scantly explored. Among others, we present several techniques for textual entailment, error correction, and fake news detection. Different kinds of syntactic n-grams (sn-grams) are evaluated: dependency-based sn-grams, and constituent-based sn-grams. We also evaluate these variants along with continuous and non-continuous sn-grams. We expect that this book helps our readers to appreciate the benefits of using n-grams and syntactic n-grams in a number of applications; those detailed in this book, and many others to be found in the vast field of Computational Linguistics.