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Computational and Corpus-Based Phraseology

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Cover of 'Computational and Corpus-Based Phraseology'

Table of Contents

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    Book Overview
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    Chapter 1 Corpus Methods in a Digitized World
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    Chapter 2 The IdiomSearch Experiment: Extracting Phraseology from a Probabilistic Network of Constructions
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    Chapter 3 Collocational Constructions in Translated Spanish: What Corpora Reveal
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    Chapter 4 Constructions in Parallel Corpora: A Quantitative Approach
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    Chapter 5 Mechanisms of Meaning
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    Chapter 6 Putting the Horses Before the Cart: Identifying Multiword Expressions Before Translation
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    Chapter 7 A Web of Analogies: Depictive and Reaction Object Constructions in Modern English and French Fiction
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    Chapter 8 Brazilian Recipes in Portuguese and English: The Role of Phraseology for Translation
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    Chapter 9 Pragmatic Parameters for Contrastive Analyses of the Equivalence of Eventive Specialized Phraseological Units
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    Chapter 10 Phraseological Units and Subtitling in Television Series: A Case Study The Big Bang Theory
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    Chapter 11 A Semantic Approach to the Inclusion of Complex Nominals in English Terminographic Resources
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    Chapter 12 Eye of a Needle in a Haystack
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    Chapter 13 Predicate-Argument Analysis to Build a Phraseology Module and to Increase Conceptual Relation Expressiveness
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    Chapter 14 Phrasal Settings in Which the Definite and Indefinite Articles Appear to Be Interchangeable in English: An Exploratory Study
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    Chapter 15 Deverbal Nouns in Czech Light Verb Constructions
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    Chapter 16 Contribution Towards a Corpus-Based Phraseology Minimum
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    Chapter 17 Estimating Lexical Availability of European Portuguese Proverbs
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    Chapter 18 Verbal Multiword Expressions in Slovene
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    Chapter 19 Using Parallel Corpora to Study the Translation of Legal System-Bound Terms: The Case of Names of English and Spanish Courts
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    Chapter 20 Towards Better Representation of Phraseological Meaning in Dictionaries for Learners
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    Chapter 21 Designing a Learner’s Dictionary with Phraseological Disambiguators
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    Chapter 22 Individual Differences in L2 Processing of Multi-word Phrases: Effects of Working Memory and Personality
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    Chapter 23 Verbal Phraseology: An Analysis of Cognitive Verbs in Linguistics, Engineering and Medicine Academic Papers
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    Chapter 24 Cultural Models and Motivation of Idioms with the Component ‘Heart’ in Croatian
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    Chapter 25 Variation of Adjectival Slots in kao (‘as’) Similes in Croatian: A Cognitive Linguistic Account
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    Chapter 26 Cognitive Processing of Multiword Expressions in Native and Non-native Speakers of English: Evidence from Gaze Data
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    Chapter 27 Verb-Object Compounds and Idioms in Chinese
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    Chapter 28 Korean Morphological Collocations: Theoretical and Descriptive Implications
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    Chapter 29 Towards Comprehensive Computational Representations of Arabic Multiword Expressions
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    Chapter 30 Frequency Consolidation Among Word N-Grams
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    Chapter 31 Combining Dependency Parsing and a Lexical Network Based on Lexical Functions for the Identification of Collocations
Attention for Chapter 22: Individual Differences in L2 Processing of Multi-word Phrases: Effects of Working Memory and Personality
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Chapter title
Individual Differences in L2 Processing of Multi-word Phrases: Effects of Working Memory and Personality
Chapter number 22
Book title
Computational and Corpus-Based Phraseology
Published by
Springer, Cham, November 2017
DOI 10.1007/978-3-319-69805-2_22
Book ISBNs
978-3-31-969804-5, 978-3-31-969805-2
Authors

Elma Kerz, Daniel Wiechmann

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X Demographics

The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 16 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 31%
Student > Master 2 13%
Researcher 2 13%
Student > Doctoral Student 1 6%
Lecturer > Senior Lecturer 1 6%
Other 2 13%
Unknown 3 19%
Readers by discipline Count As %
Linguistics 7 44%
Computer Science 3 19%
Arts and Humanities 1 6%
Social Sciences 1 6%
Unknown 4 25%