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Semi-supervised dependency parsing
~
Chen, Wenliang.
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Semi-supervised dependency parsing
Record Type:
Electronic resources : 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.
[NT 15003449]:
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.
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:
565309
Natural language processing (Computer science)
LC Class. No.: QA76.9.N38
Dewey Class. No.: 006.35
Semi-supervised dependency parsing
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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.
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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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Humanities, Social Sciences and Law (Springer-11648)
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EB QA76.9.N38 C518 2015
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