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Experimental IR Meets Multilinguality, Multimodality, and Interaction

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Cover of 'Experimental IR Meets Multilinguality, Multimodality, and Interaction'

Table of Contents

  1. Altmetric Badge
    Book Overview
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    Chapter 1 What Happened in CLEF $$\ldots $$ For a While?
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    Chapter 2 Crosslingual Depression Detection in Twitter Using Bilingual Word Alignments
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    Chapter 3 Studying the Variability of System Setting Effectiveness by Data Analytics and Visualization
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    Chapter 4 Stance Detection in Web and Social Media: A Comparative Study
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    Chapter 5 TwitCID: A Collection of Data Sets for Studies on Information Diffusion on Social Networks
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    Chapter 6 Sonny, Cerca! Evaluating the Impact of Using a Vocal Assistant to Search at School
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    Chapter 7 Generating Cross-Domain Text Classification Corpora from Social Media Comments
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    Chapter 8 Efficient Answer-Annotation for Frequent Questions
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    Chapter 9 Improving Ranking for Systematic Reviews Using Query Adaptation
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    Chapter 10 Analyzing the Adequacy of Readability Indicators to a Non-English Language
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    Chapter 11 How Many Labels? Determining the Number of Labels in Multi-Label Text Classification
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    Chapter 12 Using Audio Transformations to Improve Comprehension in Voice Question Answering
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    Chapter 13 A User Modeling Shared Challenge Proposal
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    Chapter 14 How Lexical Gold Standards Have Effects on the Usefulness of Text Analysis Tools for Digital Scholarship
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    Chapter 15 Personality Facets Recognition from Text
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    Chapter 16 Unsupervised System Combination for Set-Based Retrieval with Expectation Maximization
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    Chapter 17 An Ensemble Approach to Cross-Domain Authorship Attribution
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    Chapter 18 Evaluation of Deep Species Distribution Models Using Environment and Co-occurrences
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    Chapter 19 Interactive Learning-Based Retrieval Technique for Visual Lifelogging
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    Chapter 20 An Effective Deep Transfer Learning and Information Fusion Framework for Medical Visual Question Answering
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    Chapter 21 Language Modeling in Temporal Mood Variation Models for Early Risk Detection on the Internet
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    Chapter 22 Medical Image Labelling and Semantic Understanding for Clinical Applications
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    Chapter 23 To Check or Not to Check: Syntax, Semantics, and Context in the Language of Check-Worthy Claims
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    Chapter 24 Overview of [email protected] 2019: Sequel in the Systematic Reproducibility Realm
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    Chapter 25 Overview of the CLEF-2019 CheckThat! Lab: Automatic Identification and Verification of Claims
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    Chapter 26 Overview of the CLEF eHealth Evaluation Lab 2019
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    Chapter 27 Overview of eRisk 2019 Early Risk Prediction on the Internet
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    Chapter 28 ImageCLEF 2019: Multimedia Retrieval in Medicine, Lifelogging, Security and Nature
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    Chapter 29 Overview of LifeCLEF 2019: Identification of Amazonian Plants, South & North American Birds, and Niche Prediction
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    Chapter 30 Overview of PAN 2019: Bots and Gender Profiling, Celebrity Profiling, Cross-Domain Authorship Attribution and Style Change Detection
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    Chapter 31 Overview of the CLEF 2019 Personalised Information Retrieval Lab (PIR-CLEF 2019)
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    Chapter 32 Overview of CLEF 2019 Lab ProtestNews: Extracting Protests from News in a Cross-Context Setting
Attention for Chapter 7: Generating Cross-Domain Text Classification Corpora from Social Media Comments
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Chapter title
Generating Cross-Domain Text Classification Corpora from Social Media Comments
Chapter number 7
Book title
Experimental IR Meets Multilinguality, Multimodality, and Interaction
Published by
Springer, Cham, September 2019
DOI 10.1007/978-3-030-28577-7_7
Book ISBNs
978-3-03-028576-0, 978-3-03-028577-7

Benjamin Murauer, Günther Specht, Murauer, Benjamin, Specht, Günther

Twitter Demographics

The data shown below were collected from the profiles of 3 tweeters 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 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Librarian 1 13%
Student > Ph. D. Student 1 13%
Lecturer > Senior Lecturer 1 13%
Student > Master 1 13%
Unknown 4 50%
Readers by discipline Count As %
Computer Science 4 50%
Unknown 4 50%