A survey on deep learning for named entity recognition
Named entity recognition (NER) is the task to identify mentions of rigid designators from text
belonging to predefined semantic types such as person, location, organization etc. NER …
belonging to predefined semantic types such as person, location, organization etc. NER …
Recent named entity recognition and classification techniques: a systematic review
Textual information is becoming available in abundance on the web, arising the requirement
of techniques and tools to extract the meaningful information. One of such an important …
of techniques and tools to extract the meaningful information. One of such an important …
Portuguese named entity recognition using BERT-CRF
Recent advances in language representation using neural networks have made it viable to
transfer the learned internal states of a trained model to downstream natural language …
transfer the learned internal states of a trained model to downstream natural language …
A survey on semantic processing techniques
Semantic processing is a fundamental research domain in computational linguistics. In the
era of powerful pre-trained language models and large language models, the advancement …
era of powerful pre-trained language models and large language models, the advancement …
Named entity recognition and relation detection for biomedical information extraction
The number of scientific publications in the literature is steadily growing, containing our
knowledge in the biomedical, health, and clinical sciences. Since there is currently no …
knowledge in the biomedical, health, and clinical sciences. Since there is currently no …
An analytical study of information extraction from unstructured and multidimensional big data
Process of information extraction (IE) is used to extract useful information from unstructured
or semi-structured data. Big data arise new challenges for IE techniques with the rapid …
or semi-structured data. Big data arise new challenges for IE techniques with the rapid …
Applications of transformer-based language models in bioinformatics: a survey
The transformer-based language models, including vanilla transformer, BERT and GPT-3,
have achieved revolutionary breakthroughs in the field of natural language processing …
have achieved revolutionary breakthroughs in the field of natural language processing …
Nested named entity recognition: a survey
With the rapid development of text mining, many studies observe that text generally contains
a variety of implicit information, and it is important to develop techniques for extracting such …
a variety of implicit information, and it is important to develop techniques for extracting such …
[HTML][HTML] Comparing news articles and tweets about COVID-19 in Brazil: sentiment analysis and topic modeling approach
T de Melo, CMS Figueiredo - JMIR Public Health and …, 2021 - publichealth.jmir.org
Background: The COVID-19 pandemic is severely affecting people worldwide. Currently, an
important approach to understand this phenomenon and its impact on the lives of people …
important approach to understand this phenomenon and its impact on the lives of people …
Dual adversarial neural transfer for low-resource named entity recognition
We propose a new neural transfer method termed Dual Adversarial Transfer Network
(DATNet) for addressing low-resource Named Entity Recognition (NER). Specifically, two …
(DATNet) for addressing low-resource Named Entity Recognition (NER). Specifically, two …