Graph Learning and Network Science for Natural Language Processing (Hardcover)

Advances in graph-based natural language processing (NLP) and information retrieval tasks have shown the importance of processing using the Graph of Words method. This book covers recent concrete information, from the basics to advanced level, about graph-based learning, such as neural network-based approaches, computational intelligence for learning parameters and feature reduction, and network science for graph-based NPL. It also contains information about language generation based on graphical theories and language models. Features: Presents a comprehensive study of the interdisciplinary graphical approach to NLP Covers recent computational intelligence techniques for graph-based neural network models Discusses advances in random walk-based techniques, semantic webs, and lexical networks Explores recent research into NLP for graph-based streaming data Reviews advances in knowledge graph embedding and ontologies for NLP approaches This book is aimed at researchers and graduate students in computer science, natural language processing, and deep and machine learning.

General

Imprint:	Taylor & Francis
Country of origin:	United Kingdom
Series:	Computational Intelligence Techniques
Release date:	December 2022
First published:	2023
Editors:	Muskan Garg • Amit Kumar Gupta • Rajesh Prasad
Dimensions:	229 x 152 x 20mm (L x W x T)
Format:	Hardcover
Pages:	256
ISBN-13:	978-1-03-222456-5
Categories:	Books > Computing & IT > Applications of computing > Databases > General Books > Computing & IT > Applications of computing > Artificial intelligence > Natural language & machine translation Promotions
LSN:	1-03-222456-8
Barcode:	9781032224565

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