Results 11 to 20 of about 709,306 (283)
OGER++: hybrid multi-type entity recognition
Journal of Cheminformatics, 2019 Background We present a text-mining tool for recognizing biomedical entities in scientific literature. OGER++ is a hybrid system for named entity recognition and concept recognition (linking), which combines a dictionary-based annotator with a corpus ...
Lenz Furrer +3 more
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Improving Multilingual Named Entity Recognition with Wikipedia Entity Type Mapping [PDF]
Proceedings of the 2016 Conference on Empirical Methods in Natural
Language Processing, 2016 The state-of-the-art named entity recognition (NER) systems are statistical machine learning models that have strong generalization capability (i.e., can recognize unseen entities that do not appear in training data) based on lexical and contextual ...
Florian, Radu, Ni, Jian
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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
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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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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 +8 more
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Cross-Lingual Named Entity Recognition Based on Attention and Adversarial Training
Applied Sciences, 2023 Named entity recognition aims to extract entities with specific meaning from unstructured text. Currently, deep learning methods have been widely used for this task and have achieved remarkable results, but it is often difficult to achieve better results
Hao Wang +3 more
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Indirectly Named Entity Recognition
Journal of Computer-Assisted Linguistic Research, 2021 We define here indirectly named entities, as a term to denote multiword expressions referring to known named entities by means of periphrasis. While named entity recognition is a classical task in natural language processing, little attention has been paid to indirectly named entities and their treatment.
Kauffmann, Alexis +6 more
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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 +2 more
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Power entity recognition based on bidirectional long short-term memory and conditional random fields
Global Energy Interconnection, 2020 With the application of artificial intelligence technology in the power industry, the knowledge graph is expected to play a key role in power grid dispatch processes, intelligent maintenance, and customer service response provision.
Zhixiang Ji +3 more
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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 +3 more
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