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Abbreviation is a method of word formation that aims to construct theshortened term from the first letters of the initial phrase. Implicitabbreviations frequently cause the comprehension difficulties for unpreparedreaders. In this paper, we propose an efficient ML-based algorithm which allowsto identify the abbreviations in Russian texts. The method achieves ROC AUCscore 0.926 and F1 score 0.706 which are confirmed as competitive in comparisonwith the baselines. Along with the pipeline, we also establish first to ourknowledge Russian dataset that is relevant for the desired task.

Atypical lexical abbreviations identification in Russian medical texts