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Author: Grigori Sidorov Publisher: Springer ISBN: 3030147711 Category : Computers Languages : en Pages : 92
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
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 :
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.
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
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: Wenliang Chen Publisher: Springer ISBN: 9812875522 Category : Language Arts & Disciplines Languages : en Pages : 144
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: Ildar Batyrshin Publisher: Springer Nature ISBN: 3030898172 Category : Computers Languages : en Pages : 433
Book Description
The two-volume set LNAI 13067 and 13068 constitutes the proceedings of the 20th Mexican International Conference on Artificial Intelligence, MICAI 2021, held in Mexico City, Mexico, in October 2021. The total of 58 papers presented in these two volumes was carefully reviewed and selected from 129 submissions. The first volume, Advances in Computational Intelligence, contains 30 papers structured into three sections: – Machine and Deep Learning – Image Processing and Pattern Recognition – Evolutionary and Metaheuristic Algorithms The second volume, Advances in Soft Computing, contains 28 papers structured into two sections: – Natural Language Processing – Intelligent Applications and Robotics
Author: Alexander Gelbukh Publisher: Springer ISBN: 3642372473 Category : Computers Languages : en Pages : 576
Book Description
This two-volume set, consisting of LNCS 7816 and LNCS 7817, constitutes the thoroughly refereed proceedings of the 13th International Conference on Computer Linguistics and Intelligent Processing, CICLING 2013, held on Samos, Greece, in March 2013. The total of 91 contributions presented was carefully reviewed and selected for inclusion in the proceedings. The papers are organized in topical sections named: general techniques; lexical resources; morphology and tokenization; syntax and named entity recognition; word sense disambiguation and coreference resolution; semantics and discourse; sentiment, polarity, subjectivity, and opinion; machine translation and multilingualism; text mining, information extraction, and information retrieval; text summarization; stylometry and text simplification; and applications.
Author: Anna Feldman Publisher: BRILL ISBN: 904202769X Category : Language Arts & Disciplines Languages : en Pages : 199
Book Description
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 annotation in the foreseeable future. The method presented in this book aims to overcome this problem by significantly limiting the necessary data and instead extrapolating the relevant information from another, related language. The approach has been tested on Catalan, Portuguese, and Russian. Although these languages are only relatively resource-poor, the same method can be in principle applied to any inflected language, as long as there is an annotated corpus of a related language available. Time needed for adjusting the system to a new language constitutes a fraction of the time needed for systems with extensive, manually created resources: days instead of years. This book touches upon a number of topics: typology, morphology, corpus linguistics, contrastive linguistics, linguistic annotation, computational linguistics and Natural Language Processing (NLP). Researchers and students who are interested in these scientific areas as well as in cross-lingual studies and applications will greatly benefit from this work. Scholars and practitioners in computer science and linguistics are the prospective readers of this book.
Author: Emily M. Bender Publisher: Springer Nature ISBN: 3031021509 Category : Computers Languages : en Pages : 166
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: Grigori Sidorov
Author: Grigori Sidorov
Author: Grigori Sidorov
Author: Hiram Calvo
Author: Patrick Juola
Author: Dan Jurafsky
Author: Wenliang Chen
Author: Ildar Batyrshin
Author: Alexander Gelbukh
Author: Anna Feldman
Author: Emily M. Bender