Authors:
- 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)
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Front Matter
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Vector Space Model in the Analysis of Similarity between Texts
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Front Matter
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Non-linear Construction of n-grams
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Front Matter
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Back Matter
About this book
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
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Instituto Politécnico Nacional, Centro de Investigación en Computación, Mexico City, Mexico
Grigori Sidorov
About the author
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