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Cross-Lingual Transfer Learning for Arabic Task-Oriented Dialogue Systems Using Multilingual Transformer Model mT5
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In: Mathematics; Volume 10; Issue 5; Pages: 746 (2022)
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Measuring Terminology Consistency in Translated Corpora: Implementation of the Herfindahl-Hirshman Index
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In: Information; Volume 13; Issue 2; Pages: 43 (2022)
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Comparative Study of Multiclass Text Classification in Research Proposals Using Pretrained Language Models
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In: Applied Sciences; Volume 12; Issue 9; Pages: 4522 (2022)
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The Role of Task Complexity and Dominant Articulatory Routines in the Acquisition of L3 Spanish
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In: Languages; Volume 7; Issue 2; Pages: 90 (2022)
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Leveraging Frozen Pretrained Written Language Models for Neural Sign Language Translation
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In: Information; Volume 13; Issue 5; Pages: 220 (2022)
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Analyzing COVID-19 Medical Papers Using Artificial Intelligence: Insights for Researchers and Medical Professionals
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In: Big Data and Cognitive Computing; Volume 6; Issue 1; Pages: 4 (2022)
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Abstract:
Since the beginning of the COVID-19 pandemic almost two years ago, there have been more than 700,000 scientific papers published on the subject. An individual researcher cannot possibly get acquainted with such a huge text corpus and, therefore, some help from artificial intelligence (AI) is highly needed. We propose the AI-based tool to help researchers navigate the medical papers collections in a meaningful way and extract some knowledge from scientific COVID-19 papers. The main idea of our approach is to get as much semi-structured information from text corpus as possible, using named entity recognition (NER) with a model called PubMedBERT and Text Analytics for Health service, then store the data into NoSQL database for further fast processing and insights generation. Additionally, the contexts in which the entities were used (neutral or negative) are determined. Application of NLP and text-based emotion detection (TBED) methods to COVID-19 text corpus allows us to gain insights on important issues of diagnosis and treatment (such as changes in medical treatment over time, joint treatment strategies using several medications, and the connection between signs and symptoms of coronavirus, etc.).
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Keyword:
BERT; COVID-19; knowledge extraction; knowledge graphs; NER; NLP; text-based emotion detection (TBED); transfer learning
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URL: https://doi.org/10.3390/bdcc6010004
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27 |
The Effects of Event Depictions in Second Language Phrasal Vocabulary Learning
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30 |
ETHNOCULTURAL AND SOCIOLINGUISTIC FACTORS IN TEACHING RUSSIAN AS A FOREIGN LANGUAGE ...
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The Effects of Event Depictions in Second Language Phrasal Vocabulary Learning ...
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34 |
Toward an Epistemic Web
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In: 197 ; RatSWD Working Paper Series ; 22 (2022)
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StaResGRU-CNN with CMedLMs: a stacked residual GRU-CNN with pre-trained biomedical language models for predictive intelligence
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An Empirical Study of Factors Affecting Language-Independent Models
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„A Hund is er scho’“. Die Migration eines Ausdrucks und seine bayerisch-ungarische Transfergeschichte
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Neural-based Knowledge Transfer in Natural Language Processing
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Chinese Idioms: Stepping Into L2 Student’s Shoes
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In: Acta Linguistica Asiatica, Vol 12, Iss 1 (2022) (2022)
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