Data augmentation strategies to improve text classification: a use case in smart cities.

Text classification is a very common and important task in Natural Language Processing. In many domains and real-world settings, a few labeled instances are the only resource available to train classifiers. Models trained on small datasets tend to overfit and produce inaccurate results – Data augmen...

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Detalles Bibliográficos

Publicado en:	Language Resources & Evaluation Vol. 58; no. 2; pp. 659 - 695
Autores principales:	Bencke, Luciana, Moreira, Viviane Pereira
Formato:	Artículo
Publicado:	Springer Nature Jun2024
Materias:	Data augmentation Smart cities Natural language processing Language models Classification algorithms
Acceso en línea:	Ver este registro en EBSCOhost