Results 71 to 80 of about 379,251 (377)

ChineseCTRE: A Model for Geographical Named Entity Recognition and Correction Based on Deep Neural Networks and the BERT Model

ISPRS International Journal of Geo-Information, 2023
Social media is widely used to share real-time information and report accidents during natural disasters. Named entity recognition (NER) is a fundamental task of geospatial information applications that aims to extract location names from natural ...
Wei Zhang, Jingtao Meng, Jianhua Wan, Chengkun Zhang, Jiajun Zhang, Yuanyuan Wang, Liuchang Xu, Fei Li   +7 more
doaj   +1 more source

MNER-QG: An End-to-End MRC framework for Multimodal Named Entity Recognition with Query Grounding [PDF]

AAAI Conference on Artificial Intelligence, 2022
Multimodal named entity recognition (MNER) is a critical step in information extraction, which aims to detect entity spans and classify them to corresponding entity types given a sentence-image pair. Existing methods either (1) obtain named entities with
Meihuizi Jia, Lei Shen, X. Shen, L. Liao, Meng Chen, Xiaodong He, Zhen-Heng Chen, Jiaqi Li   +7 more
semanticscholar   +1 more source

CONTaiNER: Few-Shot Named Entity Recognition via Contrastive Learning [PDF]

Annual Meeting of the Association for Computational Linguistics, 2021
Named Entity Recognition (NER) in Few-Shot setting is imperative for entity tagging in low resource domains. Existing approaches only learn class-specific semantic features and intermediate representations from source domains.
Sarkar Snigdha Sarathi Das, Arzoo Katiyar, R. Passonneau, Rui Zhang   +3 more
semanticscholar   +1 more source

Perioperative optimization of Crohn's disease

Annals of Gastroenterological Surgery, Volume 7, Issue 1, Page 10-26, January 2023., 2023
Most Crohn's disease patients require surgery during the course of their illness, especially those who experience complications. The management of perioperative medications and surgery‐related decision‐making should be individualized and patient‐centered based on a multidisciplinary approach.
Chun‐Chi Lin, Hung‐Hsin Lin, Hui‐Chuen Chen, Nai‐Chia Chen, I‐Lun Shih, Ji‐Shiang Hung, Te‐Cheng Yueh, Feng‐Fan Chiang, Ping‐Wei Lin, Yuan‐Yao Tsai, Shu‐Chen Wei   +10 more
wiley   +1 more source

CMNEROne at SemEval-2022 Task 11: Code-Mixed Named Entity Recognition by leveraging multilingual data [PDF]

arXiv, 2022
Identifying named entities is, in general, a practical and challenging task in the field of Natural Language Processing. Named Entity Recognition on the code-mixed text is further challenging due to the linguistic complexity resulting from the nature of the mixing.
arxiv  

Memory-based named entity recognition [PDF]

proceeding of the 6th conference on Natural language learning - COLING-02, 2002
We apply a memory-based learner to the CoNLL-2002 shared task: language-independent named entity recognition. We use three additional techniques for improving the base performance of the learner: cascading, feature selection and system combination.
openaire   +4 more sources

Named entity recognition in Wikipedia [PDF]

Proceedings of the 2009 Workshop on The People's Web Meets NLP Collaboratively Constructed Semantic Resources - People's Web '09, 2009
Named entity recognition (NER) is used in many domains beyond the newswire text that comprises current gold-standard corpora. Recent work has used Wikipedia's link structure to automatically generate near gold-standard annotations. Until now, these resources have only been evaluated on newswire corpora or themselves.
Joel Nothman, Nicky Ringland, Dominic Balasuriya, James Curran, Tara Murphy   +4 more
openaire   +2 more sources

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, Yanrong Liu, Jing Cui, Handong He   +3 more
doaj   +1 more source

Named Entity Inclusion in Abstractive Text Summarization [PDF]

In Proceedings of the Third Workshop on Scholarly Document Processing, 2022, 2023
We address the named entity omission - the drawback of many current abstractive text summarizers. We suggest a custom pretraining objective to enhance the model's attention on the named entities in a text. At first, the named entity recognition model RoBERTa is trained to determine named entities in the text.
arxiv  

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.
Kucuk, Dilek, Kucuk, Dogan, Arici, Nursal   +2 more
openaire   +4 more sources