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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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Published in:Language Resources & Evaluation Vol. 58; no. 2; pp. 659 - 695
Main Authors: Bencke, Luciana, Moreira, Viviane Pereira
Format: Article
Published: Springer Nature Jun2024
Subjects:
Data augmentation
Smart cities
Natural language processing
Language models
Classification algorithms
Online Access:View this record in EBSCOhost