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Paperback. Condition: New.
Condition: New. pp. 152.
Condition: New. pp. 156.
Hardcover. Condition: Brand New. 140 pages. 9.25x6.10x0.60 inches. In Stock.
Language: English
Published by Springer Nature Singapore, 2015
ISBN 10: 9812875514 ISBN 13: 9789812875518
Seller: Buchpark, Trebbin, Germany
Condition: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | 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.
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Seller: Majestic Books, Hounslow, United Kingdom
Condition: New. Print on Demand pp. 152.
Seller: Majestic Books, Hounslow, United Kingdom
Condition: New. Print on Demand pp. 156.
Seller: Biblios, Frankfurt am main, HESSE, Germany
Condition: New. PRINT ON DEMAND pp. 152.
Seller: Biblios, Frankfurt am main, HESSE, Germany
Condition: New. PRINT ON DEMAND pp. 156.
Seller: moluna, Greven, Germany
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.
Seller: moluna, Greven, Germany
Gebunden. 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.