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US$ 69.72
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Graph Learning and Network Science for Natural Language Processing
Published by Taylor & Francis Ltd, 2024
ISBN 10: 1032224576 ISBN 13: 9781032224572
Language: English
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
Seller rating 5 out of 5 stars
US$ 66.85
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US$ 78.41
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Graph Learning and Network Science for Natural Language Processing (Paperback)
Published by Taylor & Francis Ltd, London, 2024
ISBN 10: 1032224576 ISBN 13: 9781032224572
Language: English
Paperback. Condition: new. Paperback. 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. Advances in Graph based Natural Language Processing (NLP) and Information Retrieval (IR) tasks have shown the importance of processing Graph of Words. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Graph Learning and Network Science for Natural Language Processing
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
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Graph Learning and Network Science for Natural Language Processing (Computational Intelligence Techniques)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
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Graph Learning and Network Science for Natural Language Processing (Computational Intelligence Techniques)
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Graph Learning and Network Science for Natural Language Processing
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Add to basketTaschenbuch. Condition: Neu. Neuware - Advances in Graph based Natural Language Processing (NLP) and Information Retrieval (IR) tasks have shown the importance of processing Graph of Words.
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Add to basketPaperback. Condition: Brand New. 272 pages. 9.00x6.00x9.00 inches. In Stock.
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Graph Learning and Network Science for Natural Language Processing (Paperback)
Published by Taylor & Francis Ltd, London, 2024
ISBN 10: 1032224576 ISBN 13: 9781032224572
Language: English
US$ 73.42
Convert currencyUS$ 49.31 shipping from United Kingdom to U.S.A.Quantity: 1 available
Add to basketPaperback. Condition: new. Paperback. 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. Advances in Graph based Natural Language Processing (NLP) and Information Retrieval (IR) tasks have shown the importance of processing Graph of Words. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Graph Learning and Network Science for Natural Language Processing (Paperback)
Published by Taylor & Francis Ltd, London, 2024
ISBN 10: 1032224576 ISBN 13: 9781032224572
Language: English
US$ 126.70
Convert currencyUS$ 37.00 shipping from Australia to U.S.A.Quantity: 1 available
Add to basketPaperback. Condition: new. Paperback. 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. Advances in Graph based Natural Language Processing (NLP) and Information Retrieval (IR) tasks have shown the importance of processing Graph of Words. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Graph Learning and Network Science for Natural Language Processing
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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US$ 140.40
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Condition: As New. Unread book in perfect condition.
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Graph Learning and Network Science for Natural Language Processing
Published by Taylor & Francis Ltd, 2022
ISBN 10: 1032224568 ISBN 13: 9781032224565
Language: English
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
Seller rating 5 out of 5 stars
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Graph Learning and Network Science for Natural Language Processing
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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US$ 164.15
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Graph Learning and Network Science for Natural Language Processing (Computational Intelligence Techniques)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
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US$ 169.70
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Condition: New. 1st edition NO-PA16APR2015-KAP.
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US$ 140.41
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Graph Learning and Network Science for Natural Language Processing
Published by Taylor & Francis Ltd, 2022
ISBN 10: 1032224568 ISBN 13: 9781032224565
Language: English
Seller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Ireland
Seller rating 5 out of 5 stars
First Edition
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Add to basketHardcover. Condition: Brand New. 272 pages. 9.00x6.00x0.81 inches. In Stock.
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US$ 196.73
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Graph Learning and Network Science for Natural Language Processing
Published by Taylor & Francis Ltd Dez 2022, 2022
ISBN 10: 1032224568 ISBN 13: 9781032224565
Language: English
US$ 184.38
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Add to basketBuch. Condition: Neu. Neuware - Advances in Graph based Natural Language Processing (NLP) and Information Retrieval (IR) tasks have shown the importance of processing Graph of Words.
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US$ 178.12
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Add to basketCondition: 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.
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Graph Learning and Network Science for Natural Language Processing
Published by Taylor & Francis Ltd, 2022
ISBN 10: 1032224568 ISBN 13: 9781032224565
Language: English
Condition: New. 2022. 1st Edition. Hardcover. . . . . . Books ship from the US and Ireland.
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PAP. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
