Results 11 to 20 of about 177,864 (288)
Information, 2022 Over the last few years, the phenomenon of fake news has become an important issue, especially during the worldwide COVID-19 pandemic, and also a serious risk for the public health.
Giorgio De Magistris +4 more
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Neural Text Classification and Stacked Heterogeneous Embeddings for Named Entity Recognition in SMM4H 2021 [PDF]
Proceedings of the Sixth Social Media Mining for Health (#SMM4H) Workshop and Shared Task, 2021 NAACL ...
Yaseen, Usama, Langer, Stefan
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Named Entity Recognition and News Article Classification: A Lightweight Approach
IEEE AccessThis paper introduces TinyGreekNewsBERT, a 14.1 M-parameter distilled Transformer that performs both Named Entity Recognition (NER) and multiclass news-topic classification in Greek.
Ioannis Katranis +4 more
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Using machine learning to maintain rule-based named-entity recognition and classification systems [PDF]
Proceedings of the 39th Annual Meeting on Association for Computational Linguistics - ACL '01, 2001 This paper presents a method that assists in maintaining a rule-based named-entity recognition and classification system. The underlying idea is to use a separate system, constructed with the use of machine learning, to monitor the performance of the rule-based system.
Georgios Petasis +5 more
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Korean Named Entity Recognition and Classification using Word Embedding Features
Journal of KIISE, 2016 Named Entity Recognition and Classification (NERC) is a task for recognition and classification of named entities such as a person's name, location, and organization. There have been various studies carried out on Korean NERC, but they have some problems, for example lacking some features as compared with English NERC.
Yunsu Choi, Jeongwon Cha
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Towards scalable and cross-lingual specialist language models for oncology [PDF]
Scientific ReportsClinical oncology generates vast, unstructured data that often contain inconsistencies, missing information, and ambiguities, making it difficult to extract reliable insights for data-driven decision-making.
Morteza Rohanian +5 more
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Proceedings of the 13th International Conference on Data Science, Technology and ApplicationsNamed Entity Recognition (NER) and Relation Classification (RC) are important steps in extracting information from unstructured text and formatting it into a machine-readable format. We present a survey of recent deep learning models that address named entity recognition and relation classification, with focus on few-shot learning performance.
Alqaaidi, Sakher Khalil +3 more
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Unified Named Entity Recognition as Word-Word Relation Classification [PDF]
AAAI Conference on Artificial Intelligence, 2021 So far, named entity recognition (NER) has been involved with three major types, including flat, overlapped (aka. nested), and discontinuous NER, which have mostly been studied individually.
Jingye Li +7 more
semanticscholar +1 more source
ANEC: An Amharic Named Entity Corpus and Transformer Based Recognizer
IEEE Access, 2023 Named Entity Recognition is an information extraction task that serves as a pre-processing step for other natural language processing tasks, such as machine translation, information retrieval, and question answering.
Ebrahim Chekol Jibril, A. Cuneyd Tantug
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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
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