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Semi-Supervised Dependency Parsing

Min Zhang, Wenliang Chen

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Springer Singapore img Link Publisher

Geisteswissenschaften, Kunst, Musik / Allgemeine und Vergleichende Sprachwissenschaft

Beschreibung

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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Schlagwörter

Semi-supervised dependency parsing, Dependency trees, Semi-supervised Learning, Parsing performance, Syntactic Parsing, Dependency parsing, Big Data for Parsing, Partial Tree Structures, Natural language processing