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Syntactic n-grams in Computational Linguistics

  • Book
  • © 2019

Overview

Authors:
  1. Grigori Sidorov

    1. Instituto Politécnico Nacional, Centro de Investigación en Computación, Mexico City, Mexico

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  • Provides a new approach in the field of computational linguistics related to the idea of constructing n-grams in non-linear manner
  • Proposes and systematises the concept of syntactic n-grams
  • Intended for specialists in the field of computational linguistics

Part of the book series: SpringerBriefs in Computer Science (BRIEFSCOMPUTER)

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Table of contents (15 chapters)

  1. Front Matter

    Pages i-ix
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  2. Vector Space Model in the Analysis of Similarity between Texts

    1. Front Matter

      Pages 1-1
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    2. Formalization in Computational Linguistics

      • Grigori Sidorov
      Pages 3-4

    3. Vector Space Model

      • Grigori Sidorov
      Pages 5-10

    4. Vector Space Model for Texts and the tf-idf Measure

      • Grigori Sidorov
      Pages 11-15

    5. Latent Semantic Analysis (LSA): Reduction of Dimensions

      • Grigori Sidorov
      Pages 17-19

    6. Design of Experiments in Computational Linguistics

      • Grigori Sidorov
      Pages 21-26

    7. Example of Application of n-grams: Authorship Attribution Using Syllables

      • Grigori Sidorov
      Pages 27-39

    8. Deep Learning and Vector Space Model

      • Grigori Sidorov
      Pages 41-43

  3. Non-linear Construction of n-grams

    1. Front Matter

      Pages 45-45
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    2. Syntactic n-grams: The Concept

      • Grigori Sidorov
      Pages 47-58

    3. Types of Syntactic n-grams According to their Components

      • Grigori Sidorov
      Pages 59-61

    4. Continuous and Noncontinuous Syntactic n-grams

      • Grigori Sidorov
      Pages 63-67

    5. Metalanguage of Syntactic n-gram Representation

      • Grigori Sidorov
      Pages 69-70

    6. Examples of Construction of Non-continuous Syntactic n-grams

      • Grigori Sidorov
      Pages 71-78

    7. Automatic Analysis of Authorship Using Syntactic n-grams

      • Grigori Sidorov
      Pages 79-80

    8. Filtered n-grams

      • Grigori Sidorov
      Pages 81-84

    9. Generalized n-grams

      • Grigori Sidorov
      Pages 85-86

  4. Back Matter

    Pages 87-92
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Keywords

About this book

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 ina 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.

Authors and Affiliations

  • Instituto Politécnico Nacional, Centro de Investigación en Computación, Mexico City, Mexico

    Grigori Sidorov

About the author

Grigori Sidorov is full Professor and researcher at the "Centro de Investigación en Computación" (Center for Computing Research, CIC),which is part of the "Instituto Politécnico Nacional" (National Polytechnic Institute), IPN in Mexico city, Mexico.

Bibliographic Information

  • Book Title: Syntactic n-grams in Computational Linguistics

  • Authors: Grigori Sidorov

  • Series Title: SpringerBriefs in Computer Science

  • DOI: https://doi.org/10.1007/978-3-030-14771-6

  • Publisher: Springer Cham

  • eBook Packages: Computer Science, Computer Science (R0)

  • Copyright Information: The Author(s), under exclusive licence to Springer Nature Switzerland AG 2019

  • Softcover ISBN: 978-3-030-14770-9Published: 11 April 2019

  • eBook ISBN: 978-3-030-14771-6Published: 02 April 2019

  • Series ISSN: 2191-5768

  • Series E-ISSN: 2191-5776

  • Edition Number: 1

  • Number of Pages: IX, 92

  • Number of Illustrations: 5 b/w illustrations, 10 illustrations in colour

  • Topics: Natural Language Processing (NLP), Computational Linguistics

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