Inductive Dependency Parsing

  • Joakim Nivre
Part of the Text, Speech and Language Technology book series (TLTB, volume 34)

Table of contents

  1. Front Matter
    Pages i-ix
  2. Pages 1-8
  3. Pages 45-86
  4. Pages 121-174
  5. Pages 175-182
  6. Back Matter
    Pages 183-216

About this book

Introduction

This book provides an in-depth description of the framework of inductive dependency parsing, a methodology for robust and efficient syntactic analysis of unrestricted natural language text. This methodology is based on two essential components: dependency-based syntactic representations and a data-driven approach to syntactic parsing. More precisely, it is based on a deterministic parsing algorithm in combination with inductive machine learning to predict the next parser action.

The book includes a theoretical analysis of all central models and algorithms, as well as a thorough empirical evaluation of memory-based dependency parsing, using data from Swedish and English. Offering the reader a one-stop reference to dependency-based parsing of natural language, it is intended for researchers and system developers in the language technology field, and is also suited for graduate or advanced undergraduate education.

Keywords

Index Parsing algorithms language learning machine learning natural language syntactic

Authors and affiliations

  • Joakim Nivre
    • 1
  1. 1.Växjö UniversitySweden

Bibliographic information

  • DOI https://doi.org/10.1007/1-4020-4889-0
  • Copyright Information Springer Science+Business Media B.V. 2006
  • Publisher Name Springer, Dordrecht
  • eBook Packages Humanities, Social Sciences and Law
  • Print ISBN 978-1-4020-4888-3
  • Online ISBN 978-1-4020-4889-0
  • Series Print ISSN 1386-291X