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Natural Language Processing Using Very Large Corpora

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Cover of 'Natural Language Processing Using Very Large Corpora'

Table of Contents

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    Book Overview
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    Chapter 1 Implementation and Evaluation of a German HMM for POS Disambiguation
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    Chapter 2 Improvements in Part-of-Speech Tagging with an Application to German
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    Chapter 3 Unsupervised Learning of Disambiguation Rules for Part-of-Speech Tagging
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    Chapter 4 Tagging French without Lexical Probabilities — Combining Linguistic Knowledge and Statistical Learning
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    Chapter 5 Example-Based Sense Tagging of Running Chinese Text
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    Chapter 6 Disambiguating Noun Groupings with Respect to WordNet Senses
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    Chapter 7 A Comparison of Corpus-Based Techniques for Restoring Accents in Spanish and French Text
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    Chapter 8 Beyond Word N -Grams
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    Chapter 9 Statistical Augmentation of a Chinese Machine-Readable Dictionary
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    Chapter 10 Text Chunking Using Transformation-Based Learning
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    Chapter 11 Prepositional Phrase Attachment Through a Backed-off Model
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    Chapter 12 On the Unsupervised Induction of Phrase-Structure Grammars
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    Chapter 13 Robust Bilingual Word Alignment for Machine Aided Translation
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    Chapter 14 Iterative Alignment of Syntactic Structures for a Bilingual Corpus
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    Chapter 15 Trainable Coarse Bilingual Grammars for Parallel Text Bracketing
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    Chapter 16 Comparative Discourse Analysis of Parallel Texts
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    Chapter 17 Comparing the Retrieval Performance of English and Japanese Text Databases
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    Chapter 18 Inverse Document Frequency (IDF): A Measure of Deviations from Poisson
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Title
Natural Language Processing Using Very Large Corpora
Published by
Springer Netherlands, April 2013
DOI 10.1007/978-94-017-2390-9
ISBNs
978-9-04-815349-7, 978-9-40-172390-9
Editors

Armstrong, Susan, Church, Kenneth, Isabelle, Pierre, Manzi, Sandra, Tzoukermann, Evelyne, Yarowsky, David

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 1 100%

Demographic breakdown

Readers by professional status Count As %
Lecturer 1 100%
Unspecified 1 100%
Readers by discipline Count As %
Unspecified 1 100%
Computer Science 1 100%