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GRAPH LEARNING AND NETWORK SCIENCE FOR NATURAL LANGUAGE PROCESSING

Contributor(s): Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: Computational intelligence techniquesPublisher: [S.l.] : CRC PRESS, 2022Description: 1 Online-RessourceISBN:
  • 9781000789300
  • 1000789306
  • 9781003272649
  • 1003272649
  • 9781000789508
  • 1000789500
Subject(s): Additional physical formats: 1032224568 | 9781032224565 | 9781000789508 | 1032224568 | 9781032224565 | Erscheint auch als: 9781000789508 Druck-Ausgabe | Erscheint auch als: 1032224568 Druck-AusgabeLOC classification:
  • QA76.9.N38
Online resources: Summary: 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 learningPPN: PPN: 1882643844Package identifier: Produktsigel: ZDB-4-NLEBK | BSZ-4-NLEBK-KAUB
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