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Acoustic features of dysphonic speech vs normal speech in New Zealand English speakers
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| 82 |
Modeling verb valency in a computational grammar for Portuguese in the HPSG formalism ; Modelação da valência verbal numa gramática computacional do português no formalismo HPSG
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In: Domínios de Lingu@gem; Ahead of Print; 1-63 ; 1980-5799 (2022)
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| 83 |
Causal and Semantic Relations in L2 Text Processing: An Eye-Tracking Study
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Nahatame, Shingo. - : University of Hawaii National Foreign Language Resource Center, 2022. : Center for Language & Technology, 2022
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| 84 |
Recognition of Urdu sign language: a systematic review of the machine learning classification
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In: PeerJ Comput Sci (2022)
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| 85 |
Multi-label emotion classification of Urdu tweets
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In: PeerJ Comput Sci (2022)
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| 86 |
Eine agentenbasierte Architektur für Programmierung mit gesprochener Sprache
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| 87 |
Word Frequency Analysis of Community Reaction to Religious Violence on Social Media
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In: School of Computer Science & Engineering Faculty Publications (2022)
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| 88 |
(Re)shaping online narratives: when bots promote the message of President Trump during his first impeachment
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In: PeerJ Comput Sci (2022)
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| 89 |
A systematic literature review on spam content detection and classification
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In: PeerJ Comput Sci (2022)
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| 90 |
People’s expectations and experiences of big data collection in the Saudi context
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In: PeerJ Comput Sci (2022)
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Abstract:
Big data and machine learning technologies facilitate various business intelligence activities for businesses. However, personal data collection can generate adverse effects on consumers. Big data collection can compromise people’s sense of autonomy, harming digital privacy, transparency and trust. This research investigates personal data collection, control, awareness, and privacy regulation on people’s autonomy in Saudi. This study used a hybrid analytical model that incorporates symmetrical and asymmetrical analysis via fuzzy set qualitative comparative analysis (fsQCA) to analyze consumer sense of autonomy regarding big data collection. The symmetrical shows that ‘Control’ had the most significant influence on people’s autonomy, followed by ‘Big data collection’ and ‘Awareness’. The fsQCA shows 84% of the variation, explaining the people’s autonomy.
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Keyword:
Computational Linguistics
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URL: https://doi.org/10.7717/peerj-cs.926
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9044354/
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| 91 |
Developing and evaluating cybersecurity competencies for students in computing programs
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In: PeerJ Comput Sci (2022)
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| 92 |
Multitask Pointer Network for Multi-Representational Parsing
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| 93 |
CorpusExplorer ; Eine Software zur korpuspragmatischen Analyse
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| 94 |
Horse or pony? Visual Typicality and Lexical Frequency Affect Variability in Object Naming
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In: Proceedings of the Society for Computation in Linguistics (2022)
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| 95 |
Masked language models directly encode linguistic uncertainty
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In: Proceedings of the Society for Computation in Linguistics (2022)
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| 96 |
Learning Stress Patterns with a Sequence-to-Sequence Neural Network
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In: Proceedings of the Society for Computation in Linguistics (2022)
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| 97 |
Modeling human-like morphological prediction
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In: Proceedings of the Society for Computation in Linguistics (2022)
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| 98 |
The interaction between cognitive ease and informativeness shapes the lexicons of natural languages
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In: Proceedings of the Society for Computation in Linguistics (2022)
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| 99 |
What is so Plautine about Plautine Language? Computers and the Style of Early Latin Drama
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In: Peter Barrios-Lech (2022)
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| 100 |
How Well Do LSTM Language Models Learn Filler-gap Dependencies?
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In: Proceedings of the Society for Computation in Linguistics (2022)
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