Results 21 to 30 of about 7,549,002 (298)
A Cognitive Approach in Onomastics: Some Notes on Metaphorical Place-Names
In the framework of cognitive linguistics, metaphor is considered as a general cognitive mechanism that plays a fundamental role in human thinking and understanding, in the creation of our social, cultural, and psychological reality, while also impacting
Katalin Reszegi
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This study aims to investigate metaphorical representation in Javanese food names in terms of linguistic forms, metaphorical element distribution, similarity basis, source domains, and sociocultural factors underlying their existence. This study employed
Hendrokumoro +2 more
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This research is conducted to measure how participants’ understanding to a source domain of metaphor will help them to better interpret metaphor in “Titanium” song by using the Conceptual Metaphor Theory (CMT).
Muhammad Adam
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A Jesuit Perspective on Metaphors for COVID-19 in the Online Journal Thinking Faith
This article investigated how metaphors for COVID-19 were framed in a Catholic-based journal Thinking Faith. Data, consisting of 107 metaphors, were collected from the online journal and were analyzed within the Jesuit perspectives.
Truly Almendo Pasaribu +2 more
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Curriculum Manager for Source Selection in Multi-source Domain Adaptation [PDF]
The performance of Multi-Source Unsupervised Domain Adaptation depends significantly on the effectiveness of transfer from labeled source domain samples. In this paper, we proposed an adversarial agent that learns a dynamic curriculum for source samples, called Curriculum Manager for Source Selection (CMSS).
Luyu Yang +3 more
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Analysis of Visual and Verbal Rhetorical Strategies in Advertising Discourse From Cognitive Perspective [PDF]
Pictorial metaphor is a form of rhetorical tropes depicted in images that have a powerful persuasion in advertising. The visual devices in advertising are considered to be an essential, interrelated, meaningful, and culturally embodied characteristic of ...
Reham Sayed Sedeeq
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Source Free Unsupervised Graph Domain Adaptation [PDF]
Graph Neural Networks (GNNs) have achieved great success on a variety of tasks with graph-structural data, among which node classification is an essential one. Unsupervised Graph Domain Adaptation (UGDA) shows its practical value of reducing the labeling
Zhang, Dongmei +7 more
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Recently, neural networks have shown promising results for named entity recognition(NER), which needs a number of labeled data to for model training. When meeting a new domain (target domain) for NER, there is no or a few labeled data, which makes domain
Chuanbo Liu +3 more
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Domain consistency regularization for unsupervised multi-source domain adaptive classification
Deep learning-based multi-source unsupervised domain adaptation (MUDA) has been actively studied in recent years. Compared with single-source unsupervised domain adaptation (SUDA), domain shift in MUDA exists not only between the source and target ...
Zhang, Xiaobing +7 more
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