Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Automated Spelling Correction for Clinical Text Mining in Russian   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.

9
The categories of this paper are: nlin
6
The categories of this paper are: astro-ph
36
The categories of this paper are: cmp-lg
8
The categories of this paper are: hep-ex
5
The categories of this paper are: gr-qc
29
The categories of this paper are: funct-an
25
The categories of this paper are: patt-sol
35
The categories of this paper are: mtrl-th
21
The categories of this paper are: adap-org
31
The categories of this paper are: ao-sci
27
The categories of this paper are: comp-gas
10
The categories of this paper are: q-bio
34
The categories of this paper are: chem-ph
4
The categories of this paper are: cond-mat
26
The categories of this paper are: bayes-an
30
The categories of this paper are: q-alg