Syntactic n-grams in Computational Linguistics PDF Download
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Author: Grigori Sidorov
Publisher: Springer
ISBN: 3030147711
Category : Computers
Languages : en
Pages : 92
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Book Description
This book is about a new approach in the field of computational linguistics related to the idea of constructing n-grams in non-linear manner, while the traditional approach consists in using the data from the surface structure of texts, i.e., the linear structure. In this book, we propose and systematize the concept of syntactic n-grams, which allows using syntactic information within the automatic text processing methods related to classification or clustering. It is a very interesting example of application of linguistic information in the automatic (computational) methods. Roughly speaking, the suggestion is to follow syntactic trees and construct n-grams based on paths in these trees. There are several types of non-linear n-grams; future work should determine, which types of n-grams are more useful in which natural language processing (NLP) tasks. This book is intended for specialists in the field of computational linguistics. However, we made an effort to explain in a clear manner how to use n-grams; we provide a large number of examples, and therefore we believe that the book is also useful for graduate students who already have some previous background in the field.
Author: Grigori Sidorov
Publisher: Springer
ISBN: 3030147711
Category : Computers
Languages : en
Pages : 92
Get Book Here
Book Description
This book is about a new approach in the field of computational linguistics related to the idea of constructing n-grams in non-linear manner, while the traditional approach consists in using the data from the surface structure of texts, i.e., the linear structure. In this book, we propose and systematize the concept of syntactic n-grams, which allows using syntactic information within the automatic text processing methods related to classification or clustering. It is a very interesting example of application of linguistic information in the automatic (computational) methods. Roughly speaking, the suggestion is to follow syntactic trees and construct n-grams based on paths in these trees. There are several types of non-linear n-grams; future work should determine, which types of n-grams are more useful in which natural language processing (NLP) tasks. This book is intended for specialists in the field of computational linguistics. However, we made an effort to explain in a clear manner how to use n-grams; we provide a large number of examples, and therefore we believe that the book is also useful for graduate students who already have some previous background in the field.
Author: Grigori Sidorov
Publisher:
ISBN: 9783030147723
Category : Computational linguistics
Languages : en
Pages :
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Book Description
This book is about a new approach in the field of computational linguistics related to the idea of constructing n-grams in non-linear manner, while the traditional approach consists in using the data from the surface structure of texts, i.e., the linear structure. In this book, we propose and systematize the concept of syntactic n-grams, which allows using syntactic information within the automatic text processing methods related to classification or clustering. It is a very interesting example of application of linguistic information in the automatic (computational) methods. Roughly speaking, the suggestion is to follow syntactic trees and construct n-grams based on paths in these trees. There are several types of non-linear n-grams; future work should determine, which types of n-grams are more useful in which natural language processing (NLP) tasks. This book is intended for specialists in the field of computational linguistics. However, we made an effort to explain in a clear manner how to use n-grams; we provide a large number of examples, and therefore we believe that the book is also useful for graduate students who already have some previous background in the field.
Author: Hiram Calvo
Publisher: Eliva Press
ISBN: 9789994980116
Category :
Languages : sv
Pages : 214
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Book Description
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.
Author: Patrick Juola
Publisher: Now Publishers Inc
ISBN: 160198118X
Category : Authorship, Disputed
Languages : en
Pages : 116
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Book Description
Authorship Attribution surveys the history and present state of the discipline, presenting some comparative results where available. It also provides a theoretical and empirically-tested basis for further work. Many modern techniques are described and evaluated, along with some insights for application for novices and experts alike.
Author: Brian Roark
Publisher: Oxford University Press, USA
ISBN: 0199274770
Category : Computers
Languages : en
Pages : 337
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Book Description
"The authors discuss the nature and uses of syntactic parsers and examine the problems and opportunities of parsing algorithms for finite-state, context-free, and various context-sensitive grammars.
Author: Wenliang Chen
Publisher: Springer
ISBN: 9812875522
Category : Language Arts & Disciplines
Languages : en
Pages : 149
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Book Description
This book presents a comprehensive overview of semi-supervised approaches to dependency parsing. Having become increasingly popular in recent years, one of the main reasons for their success is that they can make use of large unlabeled data together with relatively small labeled data and have shown their advantages in the context of dependency parsing for many languages. Various semi-supervised dependency parsing approaches have been proposed in recent works which utilize different types of information gleaned from unlabeled data. The book offers readers a comprehensive introduction to these approaches, making it ideally suited as a textbook for advanced undergraduate and graduate students and researchers in the fields of syntactic parsing and natural language processing.
Author: Dan Jurafsky
Publisher: Pearson Education India
ISBN: 9788131716724
Category :
Languages : en
Pages : 912
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Book Description
Author: Christian E. Larsen
Publisher:
ISBN:
Category : Applied linguistics
Languages : en
Pages : 204
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Book Description
Author: Emily M. Bender
Publisher: Morgan & Claypool Publishers
ISBN: 1627050124
Category : Computers
Languages : en
Pages : 186
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Book Description
Many NLP tasks have at their core a subtask of extracting the dependencies—who did what to whom—from natural language sentences. This task can be understood as the inverse of the problem solved in different ways by diverse human languages, namely, how to indicate the relationship between different parts of a sentence. Understanding how languages solve the problem can be extremely useful in both feature design and error analysis in the application of machine learning to NLP. Likewise, understanding cross-linguistic variation can be important for the design of MT systems and other multilingual applications. The purpose of this book is to present in a succinct and accessible fashion information about the morphological and syntactic structure of human languages that can be useful in creating more linguistically sophisticated, more language-independent, and thus more successful NLP systems. Table of Contents: Acknowledgments / Introduction/motivation / Morphology: Introduction / Morphophonology / Morphosyntax / Syntax: Introduction / Parts of speech / Heads, arguments, and adjuncts / Argument types and grammatical functions / Mismatches between syntactic position and semantic roles / Resources / Bibliography / Author's Biography / General Index / Index of Languages
Author: Sandra Kübler
Publisher: Morgan & Claypool Publishers
ISBN: 1598295969
Category : Computers
Languages : en
Pages : 128
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Book Description
Dependency-based methods for syntactic parsing have become increasingly popular in natural language processing in recent years. This book gives a thorough introduction to the methods that are most widely used today. After an introduction to dependency grammar and dependency parsing, followed by a formal characterization of the dependency parsing problem, the book surveys the three major classes of parsing models that are in current use: transition-based, graph-based, and grammar-based models. It continues with a chapter on evaluation and one on the comparison of different methods, and it closes with a few words on current trends and future prospects of dependency parsing. The book presupposes a knowledge of basic concepts in linguistics and computer science, as well as some knowledge of parsing methods for constituency-based representations. Table of Contents: Introduction / Dependency Parsing / Transition-Based Parsing / Graph-Based Parsing / Grammar-Based Parsing / Evaluation / Comparison / Final Thoughts
