An unsupervised and customizable misspelling generator for mining noisy health-related text sources.

Background: Data collection and extraction from noisy text sources such as social media typically rely on keyword-based searching/listening. However, health-related terms are often misspelled in such noisy text sources due to their complex morphology, resulting in the exclusion of relevant data for...

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Detalles Bibliográficos
Publicado en:Journal of Biomedical Informatics Vol. 88; pp. 98 - 108
Autores principales: Sarker, Abeed, Gonzalez-Hernandez, Graciela
Formato: research tables/charts Journal Article
Publicado: Academic Press Inc. Dec2018
Acceso en línea:Ver este registro en EBSCOhost