Using WordNet to Complement Training Information in Text Categorization

Dev.to / 4/28/2026

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Key Points

The article explains how WordNet can be used to complement training information for text categorization tasks.
It proposes leveraging semantic relationships from WordNet (e.g., synonymy and lexical connections) to enrich or expand the training signals beyond surface-level text features.
The approach is intended to improve model performance by providing additional context and reducing ambiguity in classification.
It frames WordNet as an external knowledge resource that can be integrated into the data preparation or feature augmentation stage of a classifier pipeline.

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