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Automated Spelling Correction for Clinical Text Mining in Russian

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arxiv 2004.04987 v1 pith:SODOI2JS submitted 2020-04-10 cs.CL

Ksenia Balabaeva , Anastasia Funkner , Sergey Kovalchuk This is my paper · ORCID
classification cs.CL
keywords precisiontextcheckerclinicaldevelopminingrussianspell
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The main goal of this paper is to develop a spell checker module for clinical text in Russian. The described approach combines string distance measure algorithms with technics of machine learning embedding methods. Our overall precision is 0.86, lexical precision - 0.975 and error precision is 0.74. We develop spell checker as a part of medical text mining tool regarding the problems of misspelling, negation, experiencer and temporality detection.

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