Semi-Supervised Dependency Parsing (Paperback, Softcover reprint of the original 1st ed. 2015)

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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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Product Description

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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Product Details

General

Imprint

Springer Verlag, Singapore

Country of origin

Singapore

Release date

October 2016

Availability

Expected to ship within 10 - 15 working days

First published

2015

Authors

,

Dimensions

235 x 155 x 8mm (L x W x T)

Format

Paperback

Pages

144

Edition

Softcover reprint of the original 1st ed. 2015

ISBN-13

978-981-10-1234-1

Barcode

9789811012341

Categories

LSN

981-10-1234-2



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