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The research aims to enhance the accuracy of metaphor recognition using gloss information and data augmentation techniques.

January 18, 2026ElectronicsOpen Access

Data Augmentation and Gloss-Based Siamese Network for Metaphor Recognition

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This model improves metaphor recognition accuracy in natural language processing, indicating better comprehension of language nuances.

The research aims to enhance the accuracy of metaphor recognition using gloss information and data augmentation techniques.
Introduced EGSNet for metaphor recognition.
Incorporated gloss annotations of metaphor words into the model.
Utilized data augmentation to highlight context relevance of target words.
Combined MIP linguistic rules to analyze semantic conflicts.
EGSNet achieved higher accuracy in metaphor recognition compared to previous models.
Effectively captured subtle semantic differences in contextual sentences.
Significant improvement noted in understanding metaphorical language.

Tang et al. (2026) studied this question.

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