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