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The Competitive Advantage of the Indian and Korean Film Industries: An Empirical Analysis Using Natural Language Processing Methods
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In: Applied Sciences; Volume 12; Issue 9; Pages: 4592 (2022)
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62 |
Information Processing by Selective Machines
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In: Proceedings; Volume 81; Issue 1; Pages: 122 (2022)
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eHealth Engagement on Facebook during COVID-19: Simplistic Computational Data Analysis
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In: International Journal of Environmental Research and Public Health; Volume 19; Issue 8; Pages: 4615 (2022)
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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 Gender Bias in Contextualized Embeddings
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In: Computer Sciences & Mathematics Forum; Volume 3; Issue 1; Pages: 3 (2022)
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66 |
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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AraConv: Developing an Arabic Task-Oriented Dialogue System Using Multi-Lingual Transformer Model mT5
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In: Applied Sciences; Volume 12; Issue 4; Pages: 1881 (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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Contextual Semantic-Guided Entity-Centric GCN for Relation Extraction
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In: Mathematics; Volume 10; Issue 8; Pages: 1344 (2022)
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MetaboListem and TABoLiSTM: Two Deep Learning Algorithms for Metabolite Named Entity Recognition
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In: Metabolites; Volume 12; Issue 4; Pages: 276 (2022)
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Abstract:
Reviewing the metabolomics literature is becoming increasingly difficult because of the rapid expansion of relevant journal literature. Text-mining technologies are therefore needed to facilitate more efficient literature reviews. Here we contribute a standardised corpus of full-text publications from metabolomics studies and describe the development of two metabolite named entity recognition (NER) methods. These methods are based on Bidirectional Long Short-Term Memory (BiLSTM) networks and each incorporate different transfer learning techniques (for tokenisation and word embedding). Our first model (MetaboListem) follows prior methodology using GloVe word embeddings. Our second model exploits BERT and BioBERT for embedding and is named TABoLiSTM (Transformer-Affixed BiLSTM). The methods are trained on a novel corpus annotated using rule-based methods, and evaluated on manually annotated metabolomics articles. MetaboListem (F1-score 0.890, precision 0.892, recall 0.888) and TABoLiSTM (BioBERT version: F1-score 0.909, precision 0.926, recall 0.893) have achieved state-of-the-art performance on metabolite NER. A training corpus with full-text sentences from >1000 full-text Open Access metabolomics publications with 105,335 annotated metabolites was created, as well as a manually annotated test corpus (19,138 annotations). This work demonstrates that deep learning algorithms are capable of identifying metabolite names accurately and efficiently in text. The proposed corpus and NER algorithms can be used for metabolomics text-mining tasks such as information retrieval, document classification and literature-based discovery and are available from the omicsNLP GitHub repository.
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Keyword:
deep learning; named entity recognition; natural language processing
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URL: https://doi.org/10.3390/metabo12040276
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Extraction of the Relations among Significant Pharmacological Entities in Russian-Language Reviews of Internet Users on Medications
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In: Big Data and Cognitive Computing; Volume 6; Issue 1; Pages: 10 (2022)
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X-Transformer: A Machine Translation Model Enhanced by the Self-Attention Mechanism
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In: Applied Sciences; Volume 12; Issue 9; Pages: 4502 (2022)
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Evaluation of Chinese Natural Language Processing System Based on Metamorphic Testing
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In: Mathematics; Volume 10; Issue 8; Pages: 1276 (2022)
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Retrieval-Based Transformer Pseudocode Generation
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In: Mathematics; Volume 10; Issue 4; Pages: 604 (2022)
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An Explainable Fake News Detector Based on Named Entity Recognition and Stance Classification Applied to COVID-19
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In: Information; Volume 13; Issue 3; Pages: 137 (2022)
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Data of the Shared Task on the Disambiguation of German Verbal Idioms at KONVENS 2021 ...
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Data of the Shared Task on the Disambiguation of German Verbal Idioms at KONVENS 2021 ...
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Hebrew Transformed: Machine Translation of Hebrew Using the Transformer Architecture
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Scripted-sentence learning in Spanish speakers (Quique et al., 2022) ...
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Scripted-sentence learning in Spanish speakers (Quique et al., 2022) ...
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