Results 11 to 20 of about 318,360 (330)

Named Entity Recognition in Bengali

Northern European Journal of Language Technology, 2010
This paper reports about a multi-engine approach for the development of a Named Entity Recognition (NER) system in Bengali by combining the classifiers such as Maximum Entropy (ME), Conditional Random Field (CRF) and Support Vector Machine (SVM) with ...
Asif Ekbal, Sivaji Bandyopadhyay
doaj   +3 more sources

Named Entity Recognition and Named Entity Linking on Esports Contents [PDF]

Annals of computer science and information systems, 2020
Ziyu Liu, Yifan Leng, Meiqi Wang, Congzhu Lin   +3 more
doaj   +3 more sources

Named entity recognition [PDF]

Proceedings of the 19th international conference on Computational linguistics -, 2002
This paper presents a maximum entropy-based named entity recognizer (NER). It differs from previous machine learning-based NERs in that it uses information from the whole document to classify each word, with just one classifier. Previous work that involves the gathering of information from the whole document often uses a secondary classifier, which ...
Hai Leong Chieu, Hwee Tou Ng
openaire   +1 more source

Named Entity Recognition - Is There a Glass Ceiling? [PDF]

Proceedings of the 23rd Conference on Computational Natural Language Learning (CoNLL), 2019
Accepted to CoNLL ...
Stanislawek, Tomasz, Wróblewska, Anna, Wójcicka, Alicja, Ziembicki, Daniel, Biecek, Przemyslaw   +4 more
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Concept recognition as a machine translation problem

BMC Bioinformatics, 2021
Background Automated assignment of specific ontology concepts to mentions in text is a critical task in biomedical natural language processing, and the subject of many open shared tasks.
Mayla R. Boguslav, Negacy D. Hailu, Michael Bada, William A. Baumgartner, Lawrence E. Hunter   +4 more
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Named Entity Recognition Using Conditional Random Fields

Applied Sciences, 2022
Named entity recognition (NER) is an important task in natural language processing, as it is widely featured as a key information extraction sub-task with numerous application areas.
Wahab Khan, Ali Daud, Khurram Shahzad, Tehmina Amjad, Ameen Banjar, Heba Fasihuddin   +5 more
doaj   +1 more source

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, Ballesteros, Miguel, Subramanian, Sandeep, Kawakami, Kazuya, Dyer, Chris   +4 more
openaire   +3 more sources

Multi-grained Named Entity Recognition [PDF]

Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, 2019
In ACL 2019 as a long ...
Xia, Congying, Zhang, Chenwei, Yang, Tao, Li, Yaliang, Du, Nan, Wu, Xian, Fan, Wei, Ma, Fenglong, Yu, Philip   +8 more
openaire   +2 more sources

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
doaj   +1 more source

Spanish named entity recognition in the biomedical domain [PDF]

, 2018
Named Entity Recognition in the clinical domain and in languages different from English has the difficulty of the absence of complete dictionaries, the informality of texts, the polysemy of terms, the lack of accordance in the boundaries of an entity ...
Cotik, Viviana, Rodríguez Hontoria, Horacio, Vivaldi Palatresi, Jorge   +2 more
core   +1 more source