TY  - BOOK
AU  - Garg,Muskan
AU  - Gupta,Amit Kumar
AU  - Prasad,Rajesh
TI  - GRAPH LEARNING AND NETWORK SCIENCE FOR NATURAL LANGUAGE PROCESSING
T2  - Computational intelligence techniques
SN  - 9781000789300
AV  - QA76.9.N38 
U1  - 006.35 23
PY  - 2022///
CY  - [S.l.]
PB  - CRC PRESS
KW  - Natural language processing (Computer science)
KW  - Graph theory
KW  - System analysis
KW  - BUSINESS & ECONOMICS / Statistics
KW  - bisacsh
KW  - COMPUTERS / Database Management / Data Mining
KW  - COMPUTERS / Machine Theory
N2  - 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
UR  - https://www.taylorfrancis.com/books/9781003272649
UR  - http://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf
ER  -