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Building and Using Comparable Corpora

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Cover of 'Building and Using Comparable Corpora'

Table of Contents

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    Book Overview
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    Chapter 1 Overviewing Important Aspects of the Last Twenty Years of Research in Comparable Corpora
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    Chapter 2 Mining Parallel Documents Using Low Bandwidth and High Precision CLIR from the Heterogeneous Web
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    Chapter 3 Automatic Comparable Web Corpora Collection and Bilingual Terminology Extraction for Specialized Dictionary Making
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    Chapter 4 Statistical Comparability: Methodological Caveats
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    Chapter 5 Methods for Collection and Evaluation of Comparable Documents
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    Chapter 6 Measuring the Distance Between Comparable Corpora Between Languages
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    Chapter 7 Exploiting Comparable Corpora for Lexicon Extraction: Measuring and Improving Corpus Quality
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    Chapter 8 Statistical Corpus and Language Comparison on Comparable Corpora
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    Chapter 9 Comparable Multilingual Patents as Large-Scale Parallel Corpora
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    Chapter 10 Extracting Parallel Phrases from Comparable Data
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    Chapter 11 Exploiting Comparable Corpora
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    Chapter 12 Paraphrase Detection in Monolingual Specialized/Lay Comparable Corpora
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    Chapter 13 Information Network Construction and Alignment from Automatically Acquired Comparable Corpora
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    Chapter 14 Bilingual Terminology Mining from Language for Special Purposes Comparable Corpora
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    Chapter 15 The Place of Comparable Corpora in Providing Terminological Reference Information to Online Translators: A Strategic Framework
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    Chapter 16 Old Needs, New Solutions: Comparable Corpora for Language Professionals
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    Chapter 17 Exploiting the Incomparability of Comparable Corpora for Contrastive Linguistics and Translation Studies
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Title
Building and Using Comparable Corpora
Published by
Springer Berlin Heidelberg, January 2014
DOI 10.1007/978-3-642-20128-8
ISBNs
978-3-64-220127-1, 978-3-64-220128-8
Editors

Sharoff, Serge, Fung, Pascale, Zweigenbaum, Pierre, Rapp, Reinhard

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 2 4%
Indonesia 1 2%
Malaysia 1 2%
Germany 1 2%
Iran, Islamic Republic of 1 2%
Belgium 1 2%
Portugal 1 2%
Japan 1 2%
Unknown 37 80%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 24%
Student > Master 9 20%
Professor > Associate Professor 5 11%
Lecturer > Senior Lecturer 3 7%
Student > Bachelor 3 7%
Other 14 30%
Unknown 1 2%
Readers by discipline Count As %
Linguistics 15 33%
Computer Science 14 30%
Arts and Humanities 7 15%
Social Sciences 3 7%
Nursing and Health Professions 1 2%
Other 4 9%
Unknown 2 4%