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

ConclusionThe performance and relative simplicity of our proposed approach make it a much-needed spelling variant generation resource for health-related text mining from noisy sources. The source code for the system has been made publicly available for research.Graphical abstract
Source: Journal of Biomedical Informatics - Category: Information Technology Source Type: research