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عنوان
Syntactic n-grams in computational linguistics /

پدید آورنده
Grigori Sidorov.

موضوع
Computational linguistics.,Semantic computing.,Computational linguistics.,COMPUTERS-- General.,Semantic computing.

رده
P98

کتابخانه
Center and Library of Islamic Studies in European Languages

محل استقرار
استان: Qom ـ شهر: Qom

Center and Library of Islamic Studies in European Languages

تماس با کتابخانه : 32910706-025

INTERNATIONAL STANDARD BOOK NUMBER

(Number (ISBN
3030147711
(Number (ISBN
303014772X
(Number (ISBN
9783030147716
(Number (ISBN
9783030147723
Erroneous ISBN
3030147703
Erroneous ISBN
9783030147709

TITLE AND STATEMENT OF RESPONSIBILITY

Title Proper
Syntactic n-grams in computational linguistics /
General Material Designation
[Book]
First Statement of Responsibility
Grigori Sidorov.

.PUBLICATION, DISTRIBUTION, ETC

Place of Publication, Distribution, etc.
Cham :
Name of Publisher, Distributor, etc.
Springer,
Date of Publication, Distribution, etc.
2019.

PHYSICAL DESCRIPTION

Specific Material Designation and Extent of Item
1 online resource

SERIES

Series Title
SpringerBriefs in computer science

INTERNAL BIBLIOGRAPHIES/INDEXES NOTE

Text of Note
Includes bibliographical references.

CONTENTS NOTE

Text of Note
Intro; Preface; Introduction; Contents; Part I: Vector Space Model in the Analysis of Similarity between Texts; Chapter 1: Formalization in Computational Linguistics; 1.1 Computational Linguistics; 1.2 Computational Linguistics and Artificial Intelligence; 1.3 Formalization in Computational Linguistics; Chapter 2: Vector Space Model; 2.1 The Main Idea of the Vector Space Model; 2.2 Example of the Vector Space Model; 2.3 Similarity of Objects in the Vector Space Model; 2.4 Cosine Similarity Between Vectors; Chapter 3: Vector Space Model for Texts and the tf-idf Measure
Text of Note
3.1 Features for Text Represented in Vector Space Model3.2 Values of Text Features: tf-idf; 3.3 Term-Document Matrix; 3.4 Traditional n-grams as Features in Vector Space Model; Chapter 4: Latent Semantic Analysis (LSA): Reduction of Dimensions; 4.1 Idea of the Latent Semantic Analysis; 4.2 Examples of the Application of the Latent Semantic Analysis; 4.3 Usage of the Latent Semantic Analysis; Chapter 5: Design of Experiments in Computational Linguistics; 5.1 Machine Learning in Computational Linguistics; 5.2 Basic Concepts in the Design of Experiments; 5.3 Design of Experiments
Text of Note
8.3 Example of Continuous Syntactic n-grams in Spanish8.4 Example of Continuous Syntactic n-grams in English; Chapter 9: Types of Syntactic n-grams According to their Components; 9.1 n-grams of Lexical Elements; 9.2 n-grams of POS Tags; 9.3 n-grams of Syntactic Relations Tags; 9.4 n-grams of Characters; 9.5 Mixed n-grams; 9.6 Classification of n-grams According to their Components; Chapter 10: Continuous and Noncontinuous Syntactic n-grams; 10.1 Continuous Syntactic n-grams; 10.2 Noncontinuous Syntactic n-grams; Chapter 11: Metalanguage of Syntactic n-gram Representation
Text of Note
Chapter 12: Examples of Construction of Non-continuous Syntactic n-grams12.1 Example for Spanish; 12.2 Example for English; Chapter 13: Automatic Analysis of Authorship Using Syntactic n-grams; 13.1 Corpus Preparation for the Automatic Authorship Attribution Task; 13.2 Evaluation of the Authorship Attribution Task Using Syntactic n-grams; Chapter 14: Filtered n-grams; 14.1 Idea of Filtered n-grams; 14.2 Example of Filtered n-grams; 14.3 Filtered n-grams of Characters; Chapter 15: Generalized n-grams; 15.1 Idea of Generalized n-grams; 15.2 Example of Generalized n-grams; Bibliography
Text of Note
Chapter 6: Example of Application of n-grams: Authorship Attribution Using Syllables6.1 Authorship Attribution Task; 6.2 Related Work; 6.3 Syllables and Their Use in Authorship Attribution; 6.4 Untyped and Typed Syllables; 6.5 Datasets; 6.6 Automatic Syllabification; 6.7 Experimental Methodology; 6.8 Experimental Results; Chapter 7: Deep Learning and Vector Space Model; Part II: Non-linear Construction of n-grams; Chapter 8: Syntactic n-grams: The Concept; 8.1 The Idea of Syntactic n-grams; 8.2 Previous Ideas Related to Application of Syntactic Information
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SUMMARY OR ABSTRACT

Text of Note
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.

ACQUISITION INFORMATION NOTE

Source for Acquisition/Subscription Address
Springer Nature
Stock Number
com.springer.onix.9783030147716

OTHER EDITION IN ANOTHER MEDIUM

Title
Syntactic n-grams in computational linguistics.
International Standard Book Number
9783030147709

TOPICAL NAME USED AS SUBJECT

Computational linguistics.
Semantic computing.
Computational linguistics.
COMPUTERS-- General.
Semantic computing.

(SUBJECT CATEGORY (Provisional

COM-- 000000
UYQL
UYQL

DEWEY DECIMAL CLASSIFICATION

Number
006
.
3/5
Edition
23

LIBRARY OF CONGRESS CLASSIFICATION

Class number
P98

PERSONAL NAME - PRIMARY RESPONSIBILITY

Sidorov, Grigori

ORIGINATING SOURCE

Date of Transaction
20200823083956.0
Cataloguing Rules (Descriptive Conventions))
pn

ELECTRONIC LOCATION AND ACCESS

Electronic name
 مطالعه متن کتاب 

[Book]

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