Natural Language Processing Models for Robust Document Categorization

Ali Nemati4 days ago22 sec read9 views

The article evaluates three machine learning models—Naive Bayes, BiLSTM, and BERT—for document categorization, finding that while BERT offers the highest accuracy, BiLSTM provides a practical balance between performance and computational efficiency. Content creators should consider BiLSTM for applications requiring high accuracy with moderate resource constraints.

Read the full article at arXiv cs.CL (NLP)

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