A hybrid model integrating RoBERTa, TF-IDF, and attention mechanism for medical query intent classification

Abstract In medical retrieval scenarios, accurate identification of user query intent is pivotal for enhancing retrieval relevance and knowledge augmentation effectiveness. However, existing approaches exhibit polarized performance: traditional shallow models (e.g., TF-IDF, Bag-of-Words) struggle to...

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Autores principales:	Zejian Liang, Yunxiang Zhao, Haiwen Xu, Hong Huang, Luning Chen
Formato:	Artigo
Lenguaje:	Inglês
Publicado:	Nature Portfolio 2025-11-01
Colección:	Scientific Reports
Materias:	Medial intent classification RoBERTa TF-IDF Attention mechanism Knowledge-enhanced retrieval
Acceso en línea:	https://doi.org/10.1038/s41598-025-25783-x
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