Graph Learning and Network Science for Natural Language Processing Hardback
Edited by Muskan (Amity University Rajasthan, India) Garg, Amit Kumar (Amity University Rajasthan, India) Gupta, Rajesh (MIT ADT University, Maharashtra) Prasad
Part of the Computational Intelligence Techniques series
Hardback
Description
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 NLPCovers recent computational intelligence techniques for graph-based neural network modelsDiscusses advances in random walk-based techniques, semantic webs, and lexical networksExplores recent research into NLP for graph-based streaming dataReviews advances in knowledge graph embedding and ontologies for NLP approachesThis book is aimed at researchers and graduate students in computer science, natural language processing, and deep and machine learning.
Information
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Out of stock
- Format:Hardback
- Pages:256 pages, 29 Tables, black and white; 87 Line drawings, black and white; 1 Halftones, black and whi
- Publisher:Taylor & Francis Ltd
- Publication Date:28/12/2022
- Category:
- ISBN:9781032224565
Information
-
Out of stock
- Format:Hardback
- Pages:256 pages, 29 Tables, black and white; 87 Line drawings, black and white; 1 Halftones, black and whi
- Publisher:Taylor & Francis Ltd
- Publication Date:28/12/2022
- Category:
- ISBN:9781032224565
