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Semi-supervised dependency parsing

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Semi-supervised dependency parsing/ by Wenliang Chen, Min Zhang.
Author:	Chen, Wenliang.
other author:	Zhang, Min.
Published:	Singapore :Springer Singapore : : 2015.,
Description:	viii, 144 p. :ill. (some col.), digital ; : 24 cm.;
Contained By:	Springer eBooks
Subject:	Natural language processing (Computer science) -
Online resource:	http://dx.doi.org/10.1007/978-981-287-552-5
ISBN:	9789812875525 (electronic bk.)

Semi-supervised dependency parsing
Chen, Wenliang.

Semi-supervised dependency parsing[electronic resource] /by Wenliang Chen, Min Zhang. - Singapore :Springer Singapore :2015. - viii, 144 p. :ill. (some col.), digital ;24 cm.

1 Introduction -- 2 Dependency Parsing Models -- 3 Overview of Semi-supervised Dependency Parsing Approaches -- 4 Training with Auto-parsed Whole Trees -- 5 Training with Lexical Information -- 6 Training with Bilexical Dependencies -- 7 Training with Subtree Structures -- 8 Training with Dependency Language Models -- 9 Training with Meta Features -- 10 Closing Remarks.

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.

ISBN: 9789812875525 (electronic bk.)

Standard No.: 10.1007/978-981-287-552-5doiSubjects--Topical Terms:

641811
Natural language processing (Computer science)

LC Class. No.: QA76.9.N38

Dewey Class. No.: 006.35

Semi-supervised dependency parsing
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505 0 $a 1 Introduction -- 2 Dependency Parsing Models -- 3 Overview of Semi-supervised Dependency Parsing Approaches -- 4 Training with Auto-parsed Whole Trees -- 5 Training with Lexical Information -- 6 Training with Bilexical Dependencies -- 7 Training with Subtree Structures -- 8 Training with Dependency Language Models -- 9 Training with Meta Features -- 10 Closing Remarks.
520 $a 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.
650 0 $a Natural language processing (Computer science) $3 641811
650 0 $a Grammar, Comparative and general $x Parsing. $3 783095
650 0 $a Mathematical linguistics. $3 677864
650 0 $a Dependency grammar. $3 803169
650 1 4 $a Linguistics. $3 557829
650 2 4 $a Computational Linguistics. $3 670080
700 1 $a Zhang, Min. $3 885335
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