Results 61 to 70 of about 47,614 (155)
BANNER: AN EXECUTABLE SURVEY OF ADVANCES IN BIOMEDICAL NAMED ENTITY RECOGNITION [PDF]
Biocomputing 2008, 2007 There has been an increasing amount of research on biomedical named entity recognition, the most basic text extraction problem, resulting in significant progress by different research teams around the world. This has created a need for a freely-available, open source system implementing the advances described in the literature. In this paper we present
Robert Leaman, Graciela Gonzalez 0001
openaire +2 more sources
NAMED ENTITY RECOGNITION FROM BIOMEDICAL TEXT -AN INFORMATION EXTRACTION TASK [PDF]
ICTACT Journal on Soft Computing, 2016 Biomedical Text Mining targets the Extraction of significant information from biomedical archives. Bio TM encompasses Information Retrieval (IR) and Information Extraction (IE).
N. Kanya, T. Ravi
doaj
A hybrid deep learning framework for bacterial named entity recognition with domain features
BMC Bioinformatics, 2019 Background Microbes have been shown to play a crucial role in various ecosystems. Many human diseases have been proved to be associated with bacteria, so it is essential to extract the interaction between bacteria for medical research and application. At
Xusheng Li +5 more
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Transfer Learning for Named Entity Recognition in Financial and Biomedical Documents
Information, 2019 Recent deep learning approaches have shown promising results for named entity recognition (NER). A reasonable assumption for training robust deep learning models is that a sufficient amount of high-quality annotated training data is available.
Sumam Francis +2 more
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Named Entity Recognition Using Web Document Corpus
, 2011 This paper introduces a named entity recognition approach in textual corpus. This Named Entity (NE) can be a named: location, person, organization, date, time, etc., characterized by instances.
Karaa, Wahiba Ben Abdessalem
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Neural Reranking for Named Entity Recognition
, 2017 We propose a neural reranking system for named entity recognition (NER). The basic idea is to leverage recurrent neural network models to learn sentence-level patterns that involve named entity mentions.
Dong, Fei, Yang, Jie, Zhang, Yue
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Named Entity Recognition From Biomedical Texts Using a Fusion Attention-Based BiLSTM-CRF
IEEE Access, 2019 Biomedical named entity recognition (BNER) is the basis of biomedical text mining and one of the core sub-tasks of information extraction. Previous BNER models based on conventional machine learning rely on time-consuming feature engineering. Though most
Hao Wei +6 more
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A systematic review of named entity recognition in biomedical texts
Journal of the Brazilian Computer Society, 2011 Abstract Biomedical Named Entities (NEs) are phrases or combinations of phrases that denote specific objects or groups of objects in the biomedical literature. Research on Named Entity Recognition (NER) is one of the most disseminated activities in the automatic processing of biomedical scientific articles.
Rodrigo Rafael Villarreal Goulart +2 more
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Grounding Gene Mentions with Respect to Gene Database Identifiers [PDF]
, 2004 We describe our submission for task 1B of the BioCreAtIvE competition which is concerned with grounding gene mentions with respect to databases of organism gene identifiers.
Alex, Beatrice +4 more
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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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