Sentence Compression Using BERT and Graph Convolutional Networks

Sentence Compression Using BERT and Graph Convolutional Networks

Sentence compression is a natural language-processing task that produces a short paraphrase of an input sentence by deleting words from the input sentence while ensuring grammatical correctness and preserving meaningful core information. This study introduces a graph convolutional network (GCN) into...

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Detalles Bibliográficos
Autores principales: Yo-Han Park, Gyong-Ho Lee, Yong-Seok Choi, Kong-Joo Lee
Formato: article
Lenguaje:EN
Publicado: MDPI AG 2021
Materias:
dependency tree
graph convolutional network
graph neural networks
pre-trained model
sentence compression
Technology
T
Engineering (General). Civil engineering (General)
TA1-2040
Biology (General)
QH301-705.5
Physics
QC1-999
Chemistry
QD1-999
Acceso en línea:https://doaj.org/article/f662c617032640ec80e68ff4dde1c624
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Internet

https://doaj.org/article/f662c617032640ec80e68ff4dde1c624

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