Overview
- Presents a comprehensive overview of semi-supervised approaches to dependency parsing
- Bridges the gap between small human-annotated training data and huge raw data for dependency parsing
- Explains why semi-supervised approaches are well suited to dependency parsing
- Clarifies the differences between the three levels of information for semi-supervised dependency parsing
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Table of contents(10 chapters)
About this book
Authors and Affiliations
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Soochow University, Suzhou, China
Wenliang Chen, Min Zhang
Bibliographic Information
Book Title: Semi-Supervised Dependency Parsing
Authors: Wenliang Chen, Min Zhang
DOI: https://doi.org/10.1007/978-981-287-552-5
Publisher: Springer Singapore
eBook Packages: Humanities, Social Sciences and Law, Social Sciences (R0)
Copyright Information: Springer Science+Business Media Singapore 2015
Hardcover ISBN: 978-981-287-551-8Published: 27 July 2015
Softcover ISBN: 978-981-10-1234-1Published: 23 October 2016
eBook ISBN: 978-981-287-552-5Published: 16 July 2015
Edition Number: 1
Number of Pages: VIII, 144
Number of Illustrations: 48 b/w illustrations, 13 illustrations in colour
Topics: Computational Linguistics