Elaborating Russian spelling-correction algorithms with custom n-gram models
DOI:
https://doi.org/10.36505/ExLing-2023/14/0018/000612Keywords:
Russian corpora, Spelling correction, N-gram modelsAbstract
The aim of the paper is to compare and improve the effectiveness of different approaches to the task of automatic spelling correction of Russian social media texts in terms of qualitative evaluation of results and algorithm complexity.
References
Korobov, M. 2015. Morphological Analyzer and Generator for Russian and Ukrainian Languages. In International Conference on Analysis of Images, Social Networks and Texts (AIST 2015), CCIS, volume 542, 320-332.
Levenshtein, V. I. 1965. Binary codes with correction of dropouts, insertions and substitutions of characters. In Reports of the USSR Academy of Sciences, 163(4), 845-848.
Panina, M. F., Baytin, A. V., Galinskaya, I. E. 2013. Context-independent autocorrection of query spelling errors. In Computational Linguistics and Intellectual Technologies: Papers from the Annual Conference “Dialogue” (Bekasovo, May 29-June 2, 2013), 12(19), volume 1, 556-567.
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Articles are published under the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
