Results 131 to 140 of about 408,758 (354)

Evaluation of Named Entity Recognition Algorithms in Short Texts

open access: yesCLEI Electronic Journal, 2017
: One of the major consequences of the growth of social networks has been the generation of huge volumes of content. The text that is generated in social networks constitutes a new type of content, that is short, informal, lacking grammar in some cases,
Edgar Casasola Murillo, Raquel Fonseca
doaj   +1 more source

A Research Toward Chinese Named Entity Recognition Based on Transfer Learning

open access: yesInternational Journal of Computational Intelligence Systems, 2023
To improve the performance of named entity recognition in the lack of well-annotated entity data, a transfer learning-based Chinese named entity recognition model is proposed in this paper.
Hui Kang   +5 more
doaj   +1 more source

Boosting Named Entity Recognition with Neural Character Embeddings

open access: yes, 2015
Most state-of-the-art named entity recognition (NER) systems rely on handcrafted features and on the output of other NLP tasks such as part-of-speech (POS) tagging and text chunking.
Guimarães, Victor   +1 more
core   +1 more source

State‐of‐the‐Art, Insights, and Perspectives for MOFs‐Nanocomposites and MOF‐Derived (Nano)Materials

open access: yesAdvanced Materials, EarlyView.
Different approaches to MOF‐NP composite formation, such as ship‐in‐a‐bottle, bottle‐around‐the‐ship and in situ one‐step synthesis, are used. Owing to synergistic effects, the advantageous features of the components of the composites are beneficially combined, and their individual drawbacks are mitigated.
Stefanos Mourdikoudis   +6 more
wiley   +1 more source

Optimising Selective Sampling for Bootstrapping Named Entity Recognition [PDF]

open access: yes, 2005
Training a statistical named entity recognition system in a new domain requires costly manual annotation of large quantities of in-domain data. Active learning promises to reduce the annotation cost by selecting only highly informative data points.
Alex, Beatrice   +3 more
core   +1 more source

Light‐Harvesting Nanomaterials Based on Dyes for Energy Transfer and Amplified Biosensing

open access: yesAdvanced Materials, EarlyView.
Light harvesting (LH) in plants inspires researchers to develop artificial LH nanomaterials. Here, LH nanomaterials based on organic dyes are reviewed, considering fundamental challenges on aggregation‐caused quenching, excitation energy transfer, and exciton migration length.
Andrey S. Klymchenko   +2 more
wiley   +1 more source

Malay Named Entity Recognition: A Review

open access: yesJournal of ICT in Education, 2015
The Named Entity Recognition (NER) field had been thriving for more than 15 years. NER could be defined as a process that recognizes named entities, such as the names of persons, organizations, locations, times, and quantities.
Farid Morsidi   +4 more
doaj  

Neural Named Entity Recognition for Kazakh

open access: yes, 2023
We present several neural networks to address the task of named entity recognition for morphologically complex languages (MCL). Kazakh is a morphologically complex language in which each root/stem can produce hundreds or thousands of variant word forms.
Tolegen, Gulmira   +3 more
openaire   +2 more sources

Designing the Next Generation of Biomaterials through Nanoengineering

open access: yesAdvanced Materials, EarlyView.
Nanoengineering enables precise control over biomaterial interactions with living systems by tuning surface energy, defects, porosity, and crystallinity. This review highlights how these nanoscale design parameters drive advances in regenerative medicine, drug delivery, bioprinting, biosensing, and bioimaging, while outlining key translational ...
Ryan Davis Jr.   +3 more
wiley   +1 more source

Precursor-induced conditional random fields: connecting separate entities by induction for improved clinical named entity recognition

open access: yesBMC Medical Informatics and Decision Making, 2019
Background This paper presents a conditional random fields (CRF) method that enables the capture of specific high-order label transition factors to improve clinical named entity recognition performance.
Wangjin Lee, Jinwook Choi
doaj   +1 more source

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