Results 51 to 60 of about 316,892 (282)
HMM based Korean Named Entity Recognition [PDF]
Journal of Systemics, Cybernetics and Informatics, 2003 In this paper, we present a named entity recognition model for Korean Language. Named entity recognition is an essential and important process of Question Answering and Information Extraction system.
Yi-Gyu Hwang +2 more
doaj
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
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.
Gulmira Tolegen +3 more
openaire +2 more sources
Named Entity Recognition as Dependency Parsing [PDF]
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020 Accepted by ACL ...
Juntao Yu, Bernd Bohnet, Massimo Poesio
openaire +2 more sources
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Background Central nervous system (CNS) inflammatory demyelinating syndromes, including multiple sclerosis (MS), aquaporin‐4 antibody–positive neuromyelitis optica spectrum disorder (AQP4 + NMOSD), and myelin oligodendrocyte glycoprotein (MOG) antibody–associated disease (MOGAD), occasionally overlap.
Bade Gulec +6 more
wiley +1 more source
Local Feature Enhancement for Nested Entity Recognition Using a Convolutional Block Attention Module
Applied Sciences, 2023 Named entity recognition involves two main types: nested named entity recognition and flat named entity recognition. The span-based approach treats nested entities and flat entities uniformly by classifying entities on a span representation. However, the
Jinxin Deng +4 more
doaj +1 more source
A named entity recognition dataset for Turkish
2016 24th Signal Processing and Communication Application Conference (SIU), 2016 Named entity recognition is one of the important topics in the research area of natural language processing. Named entity recognition studies conducted on Turkish texts are quite limited, compared to the studies on other languages. Besides, the lack of common data sets makes the comparison of different approaches harder.
Dilek Küçük +2 more
openaire +3 more sources
Neural Architectures for Named Entity Recognition [PDF]
Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2016 State-of-the-art named entity recognition systems rely heavily on hand-crafted features and domain-specific knowledge in order to learn effectively from the small, supervised training corpora that are available. In this paper, we introduce two new neural architectures---one based on bidirectional LSTMs and conditional random fields, and the other that ...
Lample, Guillaume +4 more
openaire +3 more sources
Retractions in Rheumatology: Trends, Causes, and Implications for Research Integrity
Arthritis Care &Research, EarlyView.Objective We aimed to describe the trends and main reasons for study retraction in rheumatology literature. Methods We reviewed the Retraction Watch database to identify retracted articles in rheumatology. We recorded the main study characteristics, authors’ countries, reasons for retraction, time from publication to retraction, and trends over time ...
Anna Maria Vettori, Michele Iudici
wiley +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