BoW-based neural networks vs. cutting-edge models for single-label text classification
BoW-based neural networks vs. cutting-edge models for single-label text classification
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Publisher
London: Springer London
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Language
English
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Publisher
London: Springer London
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Scope and Contents
Contents
To reliably and accurately classify complicated "big" datasets, machine learning models must be continually improved. This research proposes straightforward yet competitive neural networks for text classification, even though graph neural networks (GNN) have reignited interest in graph-based text classification models. Convolutional neural networks...
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Full title
BoW-based neural networks vs. cutting-edge models for single-label text classification
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TN_cdi_proquest_journals_2858503426
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2858503426
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ISSN
0941-0643
E-ISSN
1433-3058
DOI
10.1007/s00521-023-08754-z
