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  • Broschiertes Buch

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
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Produktbeschreibung
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.
Rezensionen
From the reviews: "The book demonstrates Nivre's impressive ability to explain dependency grammar and dependency parsing clearly and succinctly to a wide audience. ... The logical progression and the clarity with which this is done is one of the many strengths of this book. ... Get Nivre's book; read it; and enjoy it! The excellent and thorough reference list alone is worth it, constituting a good ten percent of the book." (Christer Samuelsson, Computational Linguistics, Vol. 33 (2), 2007)