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Da: Ria Christie Collections, Uxbridge, Regno Unito
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Condizione: New. 1st edition NO-PA16APR2015-KAP.
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Da: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlanda
Prima edizione
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Aggiungi al carrelloCondizione: New. 2022. 1st Edition. Hardcover. . . . . .
Lingua: Inglese
Editore: Taylor and Francis Ltd, GB, 2022
ISBN 10: 1032224568 ISBN 13: 9781032224565
Da: Rarewaves.com USA, London, LONDO, Regno Unito
EUR 199,71
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Aggiungi al carrelloHardback. Condizione: New. 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.
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Aggiungi al carrelloHardcover. Condizione: Brand New. 272 pages. 9.00x6.00x0.81 inches. In Stock.
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Aggiungi al carrelloCondizione: New. Dr. Muskan Garg is a Postdoctoral research associate at University of Florida, whose research focuses on the problems in natural language processing, information retrieval, and social media analysis. She received her Masters and PhD from.
Da: Kennys Bookstore, Olney, MD, U.S.A.
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Aggiungi al carrelloBuch. Condizione: Neu. Graph Learning and Network Science for Natural Language Processing | Amit Kumar Gupta (u. a.) | Buch | Computational Intelligence Techniques | Einband - fest (Hardcover) | Englisch | 2022 | Taylor & Francis Ltd | EAN 9781032224565 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.
Lingua: Inglese
Editore: Taylor and Francis Ltd, GB, 2022
ISBN 10: 1032224568 ISBN 13: 9781032224565
Da: Rarewaves.com UK, London, Regno Unito
EUR 188,03
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Aggiungi al carrelloHardback. Condizione: New. 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.
Lingua: Inglese
Editore: Taylor & Francis Ltd Dez 2022, 2022
ISBN 10: 1032224568 ISBN 13: 9781032224565
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 142,70
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Aggiungi al carrelloBuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 256 pp. Englisch.
Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 168,21
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Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 158,18
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Aggiungi al carrelloBuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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.