Results 51 to 60 of about 314,969 (284)
CRFVoter: gene and protein related object recognition using a conglomerate of CRF-based tools
Journal of Cheminformatics, 2019 Background Gene and protein related objects are an important class of entities in biomedical research, whose identification and extraction from scientific articles is attracting increasing interest.
Wahed Hemati, Alexander Mehler
doaj +1 more source
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
doaj +1 more source
Few-shot classification in Named Entity Recognition Task
, 2018 For many natural language processing (NLP) tasks the amount of annotated data is limited. This urges a need to apply semi-supervised learning techniques, such as transfer learning or meta-learning.
Akhundov Adnan +5 more
core +1 more source
Retractions in Rheumatology: Trends, Causes, and Implications for Research Integrity
Arthritis Care &Research, EarlyView.Objective We aimed to describe the trends and main reasons for study retraction in rheumatology literature. Methods We reviewed the Retraction Watch database to identify retracted articles in rheumatology. We recorded the main study characteristics, authors’ countries, reasons for retraction, time from publication to retraction, and trends over time ...
Anna Maria Vettori, Michele Iudici
wiley +1 more source
Deep Active Learning for Named Entity Recognition [PDF]
, 2018 Deep learning has yielded state-of-the-art performance on many natural language processing tasks including named entity recognition (NER). However, this typically requires large amounts of labeled data.
Anandkumar, Animashree +4 more
core +1 more source
Innovating Aircraft Repair Processes: The Role of Digitalization in Sustainability
Advanced Engineering Materials, EarlyView.This research explores how digitalization—by storing detailed non‐destructive testing data in structured DICONDE databases and creating a standard data model of the component—innovates aviation maintenance and repair processes. Coupled with a developed state‐based simulation model, it enables data‐driven, sustainable repair strategies that reduce waste,
Johanna Aigner +3 more
wiley +1 more source
Advanced Engineering Materials, EarlyView.The documentation of component manufacture has become an essential part of today's production processes, especially for the analysis and optimization of production or component design with regard to structural performance, economic efficiency, and sustainability.
Björn Denker +4 more
wiley +1 more source
Improving Multilingual Named Entity Recognition with Wikipedia Entity Type Mapping
, 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
core +1 more source
Advanced Engineering Materials, EarlyView.This article presents a solver‐agnostic domain‐specific language (DSL) for computational structural mechanics that strengthens interoperability in virtual product development. Using a hierarchical data model, the DSL enables seamless exchange between diverse simulation tools and numerical methods.
Martin Rädel +3 more
wiley +1 more source
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