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Cross-Situational Learning Towards Robot Grounding
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In: https://hal.archives-ouvertes.fr/hal-03628290 ; 2022 (2022)
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Cross-Situational Learning Towards Robot Grounding
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In: https://hal.archives-ouvertes.fr/hal-03628290 ; 2022 (2022)
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AI for mapping multi-lingual academic papers to the United Nations' Sustainable Development Goals (SDGs) ...
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AI for mapping multi-lingual academic papers to the United Nations' Sustainable Development Goals (SDGs) ...
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AI for mapping multi-lingual academic papers to the United Nations' Sustainable Development Goals (SDGs) ...
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AI for mapping multi-lingual academic papers to the United Nations' Sustainable Development Goals (SDGs) ...
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Reproducibility of the Experimental Result of BERT for Evidence Retrieval and Claim Verification ...
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Reproducibility of the Experimental Result of BERT for Evidence Retrieval and Claim Verification ...
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Lexicon-Based vs. Bert-Based Sentiment Analysis: A Comparative Study in Italian
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In: Electronics; Volume 11; Issue 3; Pages: 374 (2022)
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MIss RoBERTa WiLDe: Metaphor Identification Using Masked Language Model with Wiktionary Lexical Definitions
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In: Applied Sciences; Volume 12; Issue 4; Pages: 2081 (2022)
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Detection of Chinese Deceptive Reviews Based on Pre-Trained Language Model
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In: Applied Sciences; Volume 12; Issue 7; Pages: 3338 (2022)
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S-NER: A Concise and Efficient Span-Based Model for Named Entity Recognition
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In: Sensors; Volume 22; Issue 8; Pages: 2852 (2022)
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A Multitask Learning Framework for Abuse Detection and Emotion Classification
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In: Algorithms; Volume 15; Issue 4; Pages: 116 (2022)
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Visual and Phonological Feature Enhanced Siamese BERT for Chinese Spelling Error Correction
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In: Applied Sciences; Volume 12; Issue 9; Pages: 4578 (2022)
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An Empirical Comparison of Portuguese and Multilingual BERT Models for Auto-Classification of NCM Codes in International Trade
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In: Big Data and Cognitive Computing; Volume 6; Issue 1; Pages: 8 (2022)
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A Lite Romanian BERT: ALR-BERT
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In: Computers; Volume 11; Issue 4; Pages: 57 (2022)
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Performance Study on Extractive Text Summarization Using BERT Models
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In: Information; Volume 13; Issue 2; Pages: 67 (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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Leveraging Part-of-Speech Tagging Features and a Novel Regularization Strategy for Chinese Medical Named Entity Recognition
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In: Mathematics; Volume 10; Issue 9; Pages: 1386 (2022)
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Realistic Image Generation from Text by Using BERT-Based Embedding
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In: Electronics; Volume 11; Issue 5; Pages: 764 (2022)
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