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Semi Supervised Dependency Parsing by Chen Wenliang (21 results)
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US$ 59.16
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Semi-Supervised Dependency Parsing (Paperback)
Published by Springer Verlag, Singapore, Singapore, 2016
ISBN 10: 9811012342 ISBN 13: 9789811012341
Language: English
Paperback. Condition: new. Paperback. This book presents a comprehensive overview of semi-supervised approaches to dependency parsing. Having become increasingly popular in recent years, one of the main reasons for their success is that they can make use of large unlabeled data together with relatively small labeled data and have shown their advantages in the context of dependency parsing for many languages. Various semi-supervised dependency parsing approaches have been proposed in recent works which utilize different types of information gleaned from unlabeled data. The book offers readers a comprehensive introduction to these approaches, making it ideally suited as a textbook for advanced undergraduate and graduate students and researchers in the fields of syntactic parsing and natural language processing. This book presents a comprehensive overview of semi-supervised approaches to dependency parsing. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Condition: New.
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Semi-Supervised Dependency Parsing (Hardcover)
Published by Springer Verlag, Singapore, Singapore, 2015
ISBN 10: 9812875514 ISBN 13: 9789812875518
Language: English
First Edition
Hardcover. Condition: new. Hardcover. This book presents a comprehensive overview of semi-supervised approaches to dependency parsing. Having become increasingly popular in recent years, one of the main reasons for their success is that they can make use of large unlabeled data together with relatively small labeled data and have shown their advantages in the context of dependency parsing for many languages. Various semi-supervised dependency parsing approaches have been proposed in recent works which utilize different types of information gleaned from unlabeled data. The book offers readers a comprehensive introduction to these approaches, making it ideally suited as a textbook for advanced undergraduate and graduate students and researchers in the fields of syntactic parsing and natural language processing. This book presents a comprehensive overview of semi-supervised approaches to dependency parsing. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Semi-Supervised Dependency Parsing
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Semi-Supervised Dependency Parsing
Seller: Ria Christie Collections, Uxbridge, United Kingdom
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Condition: New. pp. 152.
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Condition: New. pp. 156.
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Add to basketHardcover. Condition: Brand New. 140 pages. 9.25x6.10x0.60 inches. In Stock.
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Semi-Supervised Dependency Parsing
Published by Springer Nature Singapore, 2015
ISBN 10: 9812875514 ISBN 13: 9789812875518
Language: English
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Semi-Supervised Dependency Parsing (Paperback)
Published by Springer Verlag, Singapore, Singapore, 2016
ISBN 10: 9811012342 ISBN 13: 9789811012341
Language: English
US$ 178.33
Convert currencyUS$ 37.00 shipping from Australia to U.S.A.Quantity: 1 available
Add to basketPaperback. Condition: new. Paperback. This book presents a comprehensive overview of semi-supervised approaches to dependency parsing. Having become increasingly popular in recent years, one of the main reasons for their success is that they can make use of large unlabeled data together with relatively small labeled data and have shown their advantages in the context of dependency parsing for many languages. Various semi-supervised dependency parsing approaches have been proposed in recent works which utilize different types of information gleaned from unlabeled data. The book offers readers a comprehensive introduction to these approaches, making it ideally suited as a textbook for advanced undergraduate and graduate students and researchers in the fields of syntactic parsing and natural language processing. This book presents a comprehensive overview of semi-supervised approaches to dependency parsing. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Semi-Supervised Dependency Parsing (Hardcover)
Published by Springer Verlag, Singapore, Singapore, 2015
ISBN 10: 9812875514 ISBN 13: 9789812875518
Language: English
First Edition
US$ 207.32
Convert currencyUS$ 37.00 shipping from Australia to U.S.A.Quantity: 1 available
Add to basketHardcover. Condition: new. Hardcover. This book presents a comprehensive overview of semi-supervised approaches to dependency parsing. Having become increasingly popular in recent years, one of the main reasons for their success is that they can make use of large unlabeled data together with relatively small labeled data and have shown their advantages in the context of dependency parsing for many languages. Various semi-supervised dependency parsing approaches have been proposed in recent works which utilize different types of information gleaned from unlabeled data. The book offers readers a comprehensive introduction to these approaches, making it ideally suited as a textbook for advanced undergraduate and graduate students and researchers in the fields of syntactic parsing and natural language processing. This book presents a comprehensive overview of semi-supervised approaches to dependency parsing. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Add to basketCondition: New. Print on Demand pp. 152.
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Add to basketCondition: New. Print on Demand pp. 156.
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Add to basketCondition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents a comprehensive overview of semi-supervised approaches to dependency parsingBridges the gap between small human-annotated training data and huge raw data for dependency parsingExplains why semi-supervised approaches are well suited.
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US$ 58.01
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Add to basketGebunden. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents a comprehensive overview of semi-supervised approaches to dependency parsingBridges the gap between small human-annotated training data and huge raw data for dependency parsingExplains why semi-supervised approaches are well suited.
