Results 91 to 100 of about 379,251 (377)
Nested Named Entity Recognition with Span-level Graphs
Annual Meeting of the Association for Computational Linguistics, 2022 Span-based methods with the neural networks backbone have great potential for the nested named entity recognition (NER) problem. However, they face problems such as degenerating when positive instances and negative instances largely overlap. Besides, the
Juncheng Wan +3 more
semanticscholar +1 more source
A Boundary Offset Prediction Network for Named Entity Recognition [PDF]
arXiv, 2023 Named entity recognition (NER) is a fundamental task in natural language processing that aims to identify and classify named entities in text. However, span-based methods for NER typically assign entity types to text spans, resulting in an imbalanced sample space and neglecting the connections between non-entity and entity spans.
arxiv
Partially Supervised Named Entity Recognition via the Expected Entity Ratio Loss
Transactions of the Association for Computational Linguistics, 2021 We study learning named entity recognizers in the presence of missing entity annotations. We approach this setting as tagging with latent variables and propose a novel loss, the Expected Entity Ratio, to learn models in the presence of systematically ...
Thomas Effland, Michael Collins
doaj +1 more source
Named entity recognition in resumes
, 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 ...
Kesim, Ege, Deliahmetoglu, Aysu
openaire +2 more sources
An Analysis of Simple Data Augmentation for Named Entity Recognition [PDF]
International Conference on Computational Linguistics, 2020 Simple yet effective data augmentation techniques have been proposed for sentence-level and sentence-pair natural language processing tasks. Inspired by these efforts, we design and compare data augmentation for named entity recognition, which is usually
Xiang Dai, Heike Adel
semanticscholar +1 more source
HMM based Korean Named Entity Recognition [PDF]
Journal of Systemics, Cybernetics and Informatics, 2003 In this paper, we present a named entity recognition model for Korean Language. Named entity recognition is an essential and important process of Question Answering and Information Extraction system.
Yi-Gyu Hwang +2 more
doaj
Iterative Named Entity Recognition with Conditional Random Fields
Applied Sciences, 2021 Named entity recognition (NER) constitutes an important step in the processing of unstructured text content for the extraction of information as well as for the computer-supported analysis of large amounts of digital data via machine learning methods ...
Ana Alves-Pinto +4 more
doaj +1 more source
FEBS Letters, EarlyView.α2 → 8 polysialic acid elicits poor immunogenicity. Small‐angle scattering shows a supramolecular structure with parallel‐chain binding, although in different forms at μm and mm calcium. The major histocompatibility complex requires molecular weights around 2000 Da to produce antibodies, and 2000 Da polysialic oligomers will bind in these structures ...
Kenneth A. Rubinson
wiley +1 more source
Boosting for named entity recognition [PDF]
proceeding of the 6th conference on Natural language learning - COLING-02, 2002 This paper presents a system that applies boosting to the task of named-entity identification. The CoNLL-2002 shared task, for which the system is designed, is language-independent named-entity recognition. Using a set of features which are easily obtainable for almost any language, the presented system uses boosting to combine a set of weak ...
Grace Ngai +4 more
openaire +2 more sources
Molecular Oncology, EarlyView.Circulating tumor DNA (ctDNA) offers a possibility for different applications in early and late stage breast cancer management. In early breast cancer tumor informed approaches are increasingly used for detecting molecular residual disease (MRD) and early recurrence. In advanced stage, ctDNA provides a possibility for monitoring disease progression and
Eva Valentina Klocker +14 more
wiley +1 more source