Syntactic Grams: Unlocking the Power of Computational Linguistics

Syntactic n-grams in Computational Linguistics (SpringerBriefs in Computer Science)

by Robert Iannone

5 out of 5

Language	:	English
File size	:	3033 KB
Text-to-Speech	:	Enabled
Screen Reader	:	Supported
Enhanced typesetting	:	Enabled
Print length	:	142 pages
Paperback	:	311 pages
Item Weight	:	10.46 pounds
Dimensions	:	6.1 x 0.71 x 9.25 inches

FREE

In a world increasingly reliant on digital communication, the ability to understand and process human language is becoming more and more crucial. Computational linguistics, a field that combines computer science and linguistics, is at the forefront of this effort, and syntactic grams are one of its most powerful tools.

Syntactic grams are sequences of words that are related to each other in some way. By studying the distribution of syntactic grams in large corpora of text, computational linguists can learn about the structure of language and how it is used. This knowledge can then be used to develop natural language processing (NLP) applications, such as machine translation, text summarization, and question answering.

The Power of Syntactic Grams

Syntactic grams have several key advantages over other methods for studying language. First, they are able to capture the long-range dependencies that exist between words in a sentence. This makes them more powerful than traditional methods, such as n-grams, which only consider the relationships between adjacent words.

Second, syntactic grams are able to encode the syntactic structure of a sentence. This makes them more powerful than methods that simply count the frequency of words, such as word frequency lists.

Third, syntactic grams can be used to represent a wide variety of linguistic phenomena, such as phrases, clauses, and sentences. This makes them a versatile tool for computational linguists working on a wide range of problems.

Applications of Syntactic Grams

Syntactic grams have been used in a wide variety of NLP applications, including:

• Machine translation
• Text summarization
• Question answering
• Language modeling
• Speech recognition
• Information retrieval

Syntactic grams have also been used to study a wide variety of linguistic phenomena, such as:

• Syntax
• Semantics
• Pragmatics
• Discourse analysis
• Language acquisition

Syntactic Grams in Computational Linguistics: A Comprehensive Guide

Syntactic Grams in Computational Linguistics: A Comprehensive Guide is the definitive guide to syntactic grams. Written by leading experts in the field, this book provides a comprehensive overview of the theory and applications of syntactic grams.

The book covers a wide range of topics, including:

• The history of syntactic grams
• The different types of syntactic grams
• The algorithms for extracting syntactic grams from text
• The applications of syntactic grams in NLP

Syntactic Grams in Computational Linguistics: A Comprehensive Guide is an essential resource for anyone working in the field of NLP. This book will provide you with the knowledge and skills you need to use syntactic grams to improve the performance of your NLP applications.

Free Download Your Copy Today!

Syntactic Grams in Computational Linguistics: A Comprehensive Guide is available now from Springer. To Free Download your copy, please visit the following website:

https://www.springer.com/gp/book/9783030641512

Syntactic n-grams in Computational Linguistics (SpringerBriefs in Computer Science)

by Robert Iannone

5 out of 5

Language	:	English
File size	:	3033 KB
Text-to-Speech	:	Enabled
Screen Reader	:	Supported
Enhanced typesetting	:	Enabled
Print length	:	142 pages
Paperback	:	311 pages
Item Weight	:	10.46 pounds
Dimensions	:	6.1 x 0.71 x 9.25 inches

FREE