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 …
Automatic de-identification of textual documents in the electronic health record: a review of recent research
Abstract Background In the United States, the Health Insurance Portability and
Accountability Act (HIPAA) protects the confidentiality of patient data and requires the …
Accountability Act (HIPAA) protects the confidentiality of patient data and requires the …
Global pointer: Novel efficient span-based approach for named entity recognition
J Su, A Murtadha, S Pan, J Hou, J Sun… - arXiv preprint arXiv …, 2022 - arxiv.org
Named entity recognition (NER) task aims at identifying entities from a piece of text that
belong to predefined semantic types such as person, location, organization, etc. The state-of …
belong to predefined semantic types such as person, location, organization, etc. The state-of …
De-identification of patient notes with recurrent neural networks
Objective: Patient notes in electronic health records (EHRs) may contain critical information
for medical investigations. However, the vast majority of medical investigators can only …
for medical investigations. However, the vast majority of medical investigators can only …
Named entity recognition and classification on historical documents: A survey
After decades of massive digitisation, an unprecedented amount of historical documents is
available in digital format, along with their machine-readable texts. While this represents a …
available in digital format, along with their machine-readable texts. While this represents a …
Prediction of combined terrestrial evapotranspiration index (CTEI) over large river basin based on machine learning approaches
Drought is a fundamental physical feature of the climate pattern worldwide. Over the past
few decades, a natural disaster has accelerated its occurrence, which has significantly …
few decades, a natural disaster has accelerated its occurrence, which has significantly …
[PDF][PDF] Natural language processing methods for language modeling
DM Nemeskey - 2020 - hlt.bme.hu
The field of natural language processing (NLP) is contemporaneous with computers.
Machine translation systems were developed as early as the 1950s, and the widespread …
Machine translation systems were developed as early as the 1950s, and the widespread …
Challenges and open problems of legal document anonymization
Data sharing is a central aspect of judicial systems. The openly accessible documents can
make the judiciary system more transparent. On the other hand, the published legal …
make the judiciary system more transparent. On the other hand, the published legal …
Named entity recognition by using XLNet-BiLSTM-CRF
R Yan, X Jiang, D Dang - Neural Processing Letters, 2021 - Springer
Named entity recognition (NER) is the basis for many natural language processing (NLP)
tasks such as information extraction and question answering. The accuracy of the NER …
tasks such as information extraction and question answering. The accuracy of the NER …
HuSpaCy: an industrial-strength Hungarian natural language processing toolkit
Although there are a couple of open-source language processing pipelines available for
Hungarian, none of them satisfies the requirements of today's NLP applications. A language …
Hungarian, none of them satisfies the requirements of today's NLP applications. A language …