Results 51 to 60 of about 709,306 (283)
IEEE Access, 2022 The third-generation semiconductor materials (TGSMs) is a frontier scientific domain, where researchers need to consult extensive literature for the entity information on materials, devices, preparation methods, and experimental performances, and sort ...
Xiaobo Jiang, Kun He, Borui Yang
doaj +1 more source
Few-shot classification in Named Entity Recognition Task
, 2018 For many natural language processing (NLP) tasks the amount of annotated data is limited. This urges a need to apply semi-supervised learning techniques, such as transfer learning or meta-learning.
Akhundov Adnan +5 more
core +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT In pediatric patients, T‐cell lymphoblastic lymphoma (T‐LBL) survival exceeds 80%. Relapse remains associated with limited curative options. Frontline treatment is largely extrapolated from T‐cell acute lymphoblastic leukemia (T‐ALL) treatment, reflecting the ongoing debate, whether both entities represent distinct diseases or variants within ...
Marie C. Heider +4 more
wiley +1 more source
Named Entity Recognition Datasets: A Classification Framework
International Journal of Computational Intelligence SystemsNamed entity recognition as a fundamental task plays a crucial role in accomplishing some of the tasks and applications in natural language processing. In the age of Internet information, as far as computer applications are concerned, a huge proportion ...
Ying Zhang, Gang Xiao
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Aerospace, 2023 With the development of the air traffic management system (ATM), the cyber threat for ATM is becoming more and more serious. The recognition of ATM cyber threat entities is an important task, which can help ATM security experts quickly and accurately ...
Chao Liu +5 more
doaj +1 more source
Deep Active Learning for Named Entity Recognition [PDF]
, 2018 Deep learning has yielded state-of-the-art performance on many natural language processing tasks including named entity recognition (NER). However, this typically requires large amounts of labeled data.
Anandkumar, Animashree +4 more
core +1 more source
Neural Named Entity Recognition for Kazakh
, 2023 We present several neural networks to address the task of named entity recognition for morphologically complex languages (MCL). Kazakh is a morphologically complex language in which each root/stem can produce hundreds or thousands of variant word forms.
Tolegen, Gulmira +3 more
openaire +2 more sources
Organoids in pediatric cancer research
FEBS Letters, EarlyView.Organoid technology has revolutionized cancer research, yet its application in pediatric oncology remains limited. Recent advances have enabled the development of pediatric tumor organoids, offering new insights into disease biology, treatment response, and interactions with the tumor microenvironment.
Carla Ríos Arceo, Jarno Drost
wiley +1 more source
Deep learning-based methods for natural hazard named entity recognition
Scientific Reports, 2022 Natural hazard named entity recognition is a technique used to recognize natural hazard entities from a large number of texts. The method of natural hazard named entity recognition can facilitate acquisition of natural hazards information and provide ...
Junlin Sun +3 more
doaj +1 more source
Future Internet, 2023 Due to the advancement of technology, cybercrime has increased considerably, making digital forensics essential for any organisation. One of the most critical challenges is to analyse and classify the information on devices, identifying the relevant and ...
Luis Alberto Martínez Hernández +2 more
doaj +1 more source