Results 21 to 30 of about 3,266 (219)

Few-shot Named Entity Ｒecognition for Medical Text

Journal of Harbin University of Science and Technology, 2021
Aiming at the problem that medical text named entity recognition lacks sufficient labeled data，a newly named entity recognition deep neural network and data enhancement method is proposed.
QIN Jian, HOU Jian-xin, XIE Yi-ning, HE Yong-jun   +3 more
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Research Progress of Named Entity Recognition Based on Large Language Model [PDF]

Jisuanji kexue yu tansuo
Named entity recognition aims to identify named entities and their types from unstructured text, which is an important basic task in natural language processing technologies such as question answering system, machine translation and knowledge graph. With
LIANG Jia, ZHANG Liping, YAN Sheng, ZHAO Yubo, ZHANG Yawen
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Named entity recognition in resumes

CoRR, 2023
Named entity recognition (NER) is used to extract information from various documents and texts such as names and dates. It is important to extract education and work experience information from resumes in order to filter them. Considering the fact that all information in a resume has to be entered to the companys system manually, automatizing this ...
Ege Kesim, Aysu Deliahmetoglu
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Nested named entity recognition [PDF]

Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing Volume 1 - EMNLP '09, 2009
Many named entities contain other named entities inside them. Despite this fact, the field of named entity recognition has almost entirely ignored nested named entity recognition, but due to technological, rather than ideological reasons. In this paper, we present a new technique for recognizing nested named entities, by using a discriminative ...
Jenny Rose Finkel, Christopher D. Manning   +1 more
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Automatic Construction of Chinese Nested Named Entity Recognition Corpus Based on Wikipedia [PDF]

Jisuanji gongcheng, 2018
Traditional supervised learning method needs to label the corpus in a certain scale,which limits its domain adaptability.Therefore,a method of automatically constructing a Chinese nested named entity recognition corpus from Chinese Wikipedia entries is ...
LI Yanqun,HE Yunqi,QIAN Longhua,ZHOU Guodong
doaj   +1 more source

Federated Named Entity Recognition

CoRR, 2022
We present an analysis of the performance of Federated Learning in a paradigmatic natural-language processing task: Named-Entity Recognition (NER). For our evaluation, we use the language-independent CoNLL-2003 dataset as our benchmark dataset and a Bi-LSTM-CRF model as our benchmark NER model.
Joel Mathew, Dimitris Stripelis, José Luis Ambite   +2 more
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MphayaNER: Named Entity Recognition for Tshivenda [PDF]

CoRR, 2023
Named Entity Recognition (NER) plays a vital role in various Natural Language Processing tasks such as information retrieval, text classification, and question answering. However, NER can be challenging, especially in low-resource languages with limited annotated datasets and tools.
Rendani Mbuvha, David Ifeoluwa Adelani, Tendani Mutavhatsindi, Tshimangadzo Rakhuhu, Aluwani Mauda, Tshifhiwa Joshua Maumela, Andisani Masindi, Seani Rananga, Vukosi Marivate, Tshilidzi Marwala   +9 more
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Multi-feature Chinese named entity recognition

四川大学学报. 自然科学版, 2022
The task of named entity recognition is to locate the entities in the text and classify them into predefined categories. The current mainstream Chinese named entity recognition models are characterbased named entity recognition models which word ...
XU Xiao-Bo, WANG Tao, KANG Rui, ZHOU Gang, LI Tian-Ning   +4 more
doaj  

Named entity recognition method based on multi-granularity cognition

四川大学学报. 自然科学版, 2022
In the field of data scarcity, the performance of named entity recognition is limited by the expression of underfitting word features. The named entity recognition effect can be improved by introducing conventional multitask learning methods, but ...
LI Pan-Feng, CHEN Ying-Jue, ZHONG Ling-Yun, LIN Feng   +3 more
doaj  

Evaluation of Named Entity Recognition Algorithms in Short Texts

CLEI Electronic Journal, 2017
: One of the major consequences of the growth of social networks has been the generation of huge volumes of content. The text that is generated in social networks constitutes a new type of content, that is short, informal, lacking grammar in some cases,
Edgar Casasola Murillo, Raquel Fonseca
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